JAK/STAT in human diseases: a common axis in immunodeficiencies and hematological disorders

The JAK-STAT signaling pathway (Janus Kinase-Signal Transducer and Activator of Transcription) is a crucial molecular cascade that regulates immune responses, cell proliferation, and hematopoiesis. Germline or somatic mutations affecting this pathway leads to a wide range of pathologies, from severe immunodeficiencies to inflammatory and autoimmune diseases, as well as hematologic malignancies. Loss-of-function mutations impair cytokine signaling and primarily result in immunodeficiency, while gain-of-function mutations cause excessive pathway activation, promoting autoimmune diseases and myeloproliferative syndromes. Advances in our understanding of the JAK-STAT pathway and its involvement in various diseases have opened new perspectives in precision medicine and targeted therapies including JAK inhibitors (JAKi), gene therapy, and hematopoietic stem cell transplantation (HSCT). A detailed understanding of specific mutations and their effects on intracellular signaling allows for the refinement of therapeutic strategies and optimization of patient management. In this review, we examined the biology of the JAK-STAT pathway, highlighted the key pathogenic mutations and their clinical consequences, and described the laboratory and diagnostic approaches used to investigate this pathway.

1 Introduction

The Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway plays a pivotal role in mediating signals from a broad range of cytokines and growth factors. Through this activation, it orchestrates essential biological processes such as cell proliferation, differentiation, survival, and apoptosis (Table 1), thereby maintaining immune homeostasis and enabling effective responses to pathogenic threats (1–9).

Table 1

Table 1. Canonical Cytokine–JAK–STAT interactions and their physiologic effects.

Tight regulation of the JAK-STAT pathway is crucial for ensuring a delicate balance between immune activation and the maintenance of self-tolerance. Disruption of this equilibrium by germline or somatic mutations in JAK or STAT genes gives rise to a broad spectrum of clinical phenotypes. Notably, recent findings have challenged the traditional view that loss-of-function (LOF) variants cause only immunodeficiency while gain-of-function (GOF) variants lead solely to inflammation and/or autoimmunity and/or malignancy (10, 11). Instead, both types of mutations can manifest with overlapping and sometimes paradoxical combinations of infection susceptibility and immune dysregulation (12, 13).

The identification and characterization of inborn errors of immunity (IEIs) affecting the JAK-STAT pathway have significantly advanced both patient care and our understanding of fundamental human immunobiology. While most germline IEIs are either inherited or result from de novo mutations, emerging evidence shows that post-zygotic somatic mutations restricted to a subset of cells can phenotypically mimic germline IEIs. These so-called “phenocopies” challenge traditional classifications and highlight the importance of somatic mosaicism in immune disorders (14, 15).

In parallel, mutations affecting the JAK-STAT pathway play a key role in the development of hematologic malignancies by driving persistent cytokine signaling that promotes proliferation and survival. GOF mutations in JAKs (JAK1, JAK2, JAK3) and STATs (particularly STAT3 and STAT5B), as well as alterations in cytokine receptors (IL7R, CRLF2) and negative regulators (SOCS1, PTPN2), are recurrent in myeloproliferative neoplasms and certain lymphoid cancers. These mutations not only contribute to oncogenesis but also influence prognosis (16–18).

These molecular insights have direct clinical implications. Recent progress in next-generation sequencing has greatly improved the detection of pathogenic mutations in the JAK-STAT pathway, enabling precise molecular diagnosis. This advancement facilitates the implementation of personalized and targeted therapeutic strategies, including the use of JAK inhibitors (JAKi), which have shown efficacy in attenuating aberrant signaling and are already used in the management of certain autoimmune diseases, as well as myelofibrosis and polycythemia vera. Other promising approaches include gene therapy and hematopoietic stem cell transplantation, which offer curative potential for patients with severe immunodeficiencies or LOF-associated syndromes (19, 20).

Given the rapidly evolving landscape of JAK-STAT-related research, an updated synthesis is essential. In this review, we provide a comprehensive overview of key germline and somatic mutations affecting this pathway, covering both IEIs and hematologic malignancies, two fields that are usually addressed separately, and discuss them within a unified JAK-STAT framework. To enrich the clinical relevance of this review, we have included a dedicated section on diagnostic strategies and tools, outlining current laboratory approaches and their direct clinical applications, bridging the gap between molecular insights and real-world practice.

2 JAK/STAT pathway

2.1 JAK/STAT biology

The JAK family, which includes JAK1, JAK2, JAK3, and TYK2, consists of cytoplasmic tyrosine kinases that associate with various membrane receptors to mediate intracellular signal transmission (21, 22). JAK1, JAK2, and TYK2 are expressed throughout all tissues, while JAK3 is primarily found in hematopoietic cells, where it regulates immune cell growth, survival, and differentiation (23–25).

JAK proteins contain seven homology domains known as Janus Homology (JH) domains (Figure 1). The JH1 domain, located at the C-terminal end, corresponds to the tyrosine kinase domain, which serves as the main site of autophosphorylation. In JAK3, phosphorylation of tyrosine Y980 activates the enzyme, whereas Y981 has an inhibitory effect (26). In JAK2, the mutation of Y1007 to phenylalanine blocks activation, whereas substitution of Y1008 does not affect its function (27). Tyrosines Y1054 and Y1055 in TYK2 are also essential for ligand-induced activation (28). In JAK1, Y1023 is more highly phosphorylated than Y1022, although the precise roles of these tyrosines remain unclear (29). Additional phosphorylation sites have also been identified in JAK3, such as Y904 and Y939, which enhance its activity during cytokine-induced activation (30). In JAK2, Y868, Y966, and Y972 are required for optimal activation, whereas phosphorylation of Y913 negatively regulates its activity (31, 32). Phosphorylation of Y813, located between the JH1 and JH2 domains in JAK2, promotes binding to the adaptor SH2-Bb, further enhancing enzymatic activity (33). The equivalent tyrosine in JAK3, Y785, is also phosphorylated in response to IL-2 and is essential for this interaction (34). The JH2 domain, known as the pseudokinase domain, is catalytically inactive but regulates the enzyme’s activity. In JAK3, Y570 and Y637 are autophosphorylation sites that differentially modulate catalytic function (34, 35). The SH2 domain (JH3–JH4) has an unclear function, but phosphorylation of JAK2 at S523 within this region has been shown to act as a negative regulatory mechanism (36). Furthermore, JAK3 is also phosphorylated on serine after IL-2 stimulation (37). Finally, the N-terminal region (JH4–JH7) contains a FERM domain (band 4.1, ezrin, radixin, moesin), which is essential for interaction with cytokine receptors and regulation of kinase activity (38, 39). In JAK2, tyrosines Y119 and Y221 within the FERM domain are autophosphorylation sites with inhibitory effects (34, 40). Other sites, such as Y317(in JH5) and Y372 (in JH4), also modulate catalytic activity differently (35, 41).

Figure 1

Figure 1. Functional domains and phosphorylation sites of JAK and STAT proteins in the JAK/STAT pathway. (a) Linear structure of the four Janus kinases (JAK1, JAK2, JAK3, TYK2), showing the different functional domains: FERM domain (JH7–JH4), SH2 domain (JH3–JH4), pseudokinase domain (JH2), and catalytic kinase domain (JH1). The main phosphorylation residues identified are indicated in red, including tyrosines (Tyr) and serines (Ser) critical for activation and regulation of enzymatic activity. (b) Schematic representation of the structures of STAT transcription factors (STAT1 to STAT6), including the N-terminal, coiled-coil, DNA-binding, linker, SH2, and C-terminal domains. Key phosphorylation sites (Tyr and Ser) are also annotated in red, as these post-translational modifications are essential for dimerization, nuclear translocation, and transcriptional activation. Created in BioRender. djidjik, r (2025). https://BioRender.com/s9fko80.

The STAT protein family includes seven members (STAT1, STAT2, STAT3, STAT4, STAT5A, STAT5B, STAT6) (42, 43), each comprising approximately 750–900 amino acids (44) and sharing six conserved domains essential for their functions (45). The N-terminal domain (NTD) promotes dimerization by mediating STAT-STAT interactions, even without phosphorylation (46, 47). The coiled-coil domain (CCD) enables interaction with coactivators (e.g., IRF9, Nmi) and corepressors (e.g., SMRT/N-CoR) and plays a role in nuclear import via an NLS motif (48–50). The DNA-binding domain (DBD), characterized by an immunoglobulin-like fold, binds specific DNA motifs, such as GAS (TTCN₃–₄GAA) in STAT-responsive gene promoters (45, 51–53). The linker domain (LD) supports STAT structure during activation and DNA binding and aids in the formation of transcriptional complexes (45, 54). Lastly, the highly conserved SH2 domain mediates phospho-dependent protein-protein interactions essential for STAT signaling.

2.2 JAK/STAT signaling pathway

The JAK/STAT canonical signaling pathway is initiated when a cytokine or hormone binds to its specific transmembrane receptor expressed on the surface of a target cell (Figure 2). This interaction induces receptor dimerization or conformational rearrangement, facilitating the juxtaposition and activation of receptor-associated Janus kinases (JAKs). The four members of the JAK family JAK1, JAK2, JAK3, and TYK2 become activated through transphosphorylation and subsequently phosphorylate specific tyrosine residues within the cytoplasmic domains of the receptor. These phosphotyrosine motifs serve as docking sites for cytoplasmic proteins of the STAT family, specifically STAT1 through STAT6, which are recruited via their SH2 domains (13, 55–57).

Figure 2

Figure 2. Activation and regulation of the JAK-STAT signaling pathway. The JAK-STAT signaling pathway is a key mechanism of cellular communication, activated by a variety of proteins, including hematopoietic and immune cytokines, metabolic and growth hormones, and hematopoietic growth factors. When a cytokine binds to its specific membrane receptor, (1) it triggers the activation of associated JAK proteins (JAK1, JAK2, JAK3, TYK2) through a transphosphorylation mechanism. These activated JAKs then phosphorylate tyrosine residues in the cytoplasmic domains of the receptors, (2) thereby promoting the recruitment of STAT proteins (STAT1 to STAT6). (3) These proteins, once phosphorylated, form dimers (homodimers or heterodimers) through their SH2 domains (4) and then migrate to the nucleus, where they regulate the transcription of target genes involved in various biological processes (5), such as the immune response or cell proliferation. The JAK/STAT pathway is tightly controlled by several negative regulators to prevent excessive activation. (A) Suppressors of Cytokine Signaling (SOCS) proteins bind, via their SH2 domain, to phosphorylated tyrosine residues of JAKs, thereby inhibiting their kinase activity and STAT recruitment. (B) The LNK (SH2B3) protein binds directly to phosphorylated JAK via its SH2 domain, inhibiting STAT phosphorylation. (C) Protein tyrosine phosphatases (PTPs) dephosphorylate JAKs and STATs at various cellular levels, while protein inhibitors of activated STATs (PIASs) (D) prevent the binding of dimerized STATs to DNA, thereby modulating their transcriptional effect. Created in BioRender. djidjik, r (2025). https://BioRender.com/ygo2b82.

Following recruitment, STAT proteins are phosphorylated by the activated JAKs, leading to their dimerization into homo- or heterodimers. These dimers translocate into the nucleus, where they bind to specific DNA response elements in the promoters of target genes, ultimately modulating their transcription. The nature of the transcriptional response is determined by the specific STAT isoforms involved and the cellular context (56).

A wide variety of extracellular signals converge on this pathway. Cytokines of the common gamma-chain family, such as IL-2, IL-4, IL-7, IL-9, IL-15, and IL-21, typically activate JAK1 in association with JAK3 and primarily signal through STAT5 and STAT3, orchestrating key events in lymphocyte development, proliferation, and survival. The IL-6 family of cytokines, including IL-6 and IL-11, generally signal through JAK1 in combination with either JAK2 or TYK2 and engage STAT3, playing critical roles in inflammation and acute-phase responses (6).

Type I interferons (IFN-α, IFN-β) signal through receptors associated with JAK1 and TYK2, leading to the activation of STAT1 and STAT2, and promoting antiviral responses and immune surveillance. In contrast, Type II interferon (IFN-γ) signals through JAK1 and JAK2, primarily activating STAT1 to induce macrophage activation, antigen presentation, and pro-inflammatory gene expression (58).

Interleukins such as IL-10, IL-19, IL-20, IL-22, and IL-24 also use JAK1 and TYK2 to engage STAT3, thereby exerting anti-inflammatory and barrier-protective functions, particularly at mucosal surfaces. The IL-12 and IL-23 families activate JAK2 and TYK2, triggering STAT4 and STAT3, respectively, which are essential for the differentiation of Th1 and Th17 cells. Finally, a group of hematopoietic growth factors and metabolic hormones, including erythropoietin (EPO), thrombopoietin (TPO), GM-CSF, growth hormone (GH), leptin, IL-3, and IL-5, utilize JAK2 homodimers to signal primarily via STAT5, regulating erythropoiesis, granulopoiesis, and systemic growth and metabolism (3, 6).

Despite the diversity of ligands and biological effects, the JAK/STAT pathway operates through a common signaling architecture, allowing for a rapid and transcriptionally efficient response to extracellular cues. However, this potency also requires stringent regulatory control mechanisms to prevent aberrant or prolonged activation, which could otherwise result in immunopathology or oncogenesis.

The regulation of the JAK/STAT pathway involves multiple negative feedback loops that act at various levels of the signaling cascade. One key regulatory system is mediated by SOCS (Suppressor of Cytokine Signaling) proteins, which are themselves transcriptionally induced by STATs. SOCS proteins bind directly to phosphorylated JAKs or cytokine receptors via their SH2 domains and block further signal propagation by inhibiting kinase activity or competing with STAT recruitment. This classical negative feedback loop is essential for curtailing excessive cytokine responses and restoring homeostasis after immune stimulation (19, 59).

Another layer of control is provided by protein tyrosine phosphatases (PTPs), such as SHP1, SHP2, and TC-PTP, which can dephosphorylate JAKs and STATs at multiple steps of the signaling pathway. By reversing phosphorylation events, PTPs effectively shut down active signaling complexes, ensuring that the duration of the response is appropriately limited (59, 60).

A third class of negative regulators is the PIAS (Protein Inhibitors of Activated STATs) family, which functions in the nucleus to inhibit the transcriptional activity of STAT dimers. PIAS proteins prevent STATs from binding to DNA or promote the recruitment of co-repressors, thereby modulating gene expression without altering the phosphorylation status of STATs (61).

3 Impact of JAK/STAT mutations on human diseases

As mentioned, the JAK/STAT signaling pathway serves as a crucial regulatory network for various cellular processes. Disruption of normal JAK/STAT protein function, particularly through mutations, is linked to a wide range of human diseases, especially inborn errors of immunity (IEIs) and hematologic malignancies.

3.1 JAK/STAT pathway and IEIs

According to the latest International Union of Immunological Societies (IUIS) classification in 2024 (62), nineteen IEIs have been associated with mutations in the JAK-STAT pathway (Figure 3, Table 2). Reported disorders are linked to distinct inheritance patterns (autosomal recessive (AR) or autosomal dominant (AD)) and distinct mutation types (germline or somatic, LOF or GOF).

Figure 3

Figure 3. JAK-STAT mutations in inborn errors of immunity. At the molecular level, diverse dysregulations can disrupt the JAK-STAT pathway, leading to a various type of inborn errors of immunity (IEIs) including (a) Immunodeficiencies affecting cellular and humoral immunity, (b) Combined immunodeficiencies with associated or syndromic features, (c) Diseases of immune dysregulation, (d) Defects in intrinsic and innate immunity, (e) Autoinflammatory disorders and (f) Phenocopies of inborn errors of immunity. Mutations in proteins associated with the JAK-STAT pathway are presented along with the clinical manifestations of the resulting IEIs. Germline LOF defects and their principal clinical symptoms are displayed in bleu, germline GOF defects in red and somatic GOF defects in green. AD, autosomal dominant; AR, autosomal recessive; CMC, chronic mucocutaneous candidiasis; GOF, gain of function; HIES, hyper-IgE syndrome; LOF, loss of function; MSMD, Mendelian susceptibility to mycobacterial disease; SCID, severe combined immunodeficiency. Created in BioRender. djidjik, r (2025). https://BioRender.com/4jpwstk.

Table 2

Table 2. Overview of IEIs in JAK-STAT signaling pathway (12, 13).

These mutations give rise to a broad spectrum of overlapping clinical phenotypes (14), spanning from infection susceptibility to autoimmune and inflammatory manifestations (Figure 4, supplementary Tables S1 to S10). The clinical picture is largely shaped by the nature of the variant: LOF and dominant negative (DN) mutations both impair cytokine signaling and compromise immune responses, resulting in severe or atypical immunodeficiencies. While LOF mutations result in a non-functional or absent protein, DN mutations produce aberrant proteins that interfere with the function of the wild-type counterpart, often leading to even more profound signaling defects. In contrast, GOF mutations promote hyperactivation of the pathway and are associated with chronic inflammatory diseases, autoimmune disorders, and hematologic malignancies (10, 11). However, this simple dichotomy no longer captures the clinical reality of JAK-STAT disorders. Patient cohorts and recent mechanistic studies have revealed that both LOF and GOF mutations can generate phenotypes that blur the classical boundaries between immunodeficiency and inflammation/autoimmunity. In practice, patients with activating mutations may also suffer from recurrent or opportunistic infections, while some with inactivating variants develop autoimmune or autoinflammatory features (12, 13). These apparently contradictory presentations highlight that impaired signaling does not operate in a single direction but rather perturbs a wider immunological network.

Figure 4

Figure 4. Clinical overlap of JAK-STAT pathway associated IEIs. Some IEIs are characterized by predominant manifestations within one of four distinct pathological axes: infections (light blue), autoimmunity (purple), inflammation (pink), or allergy (green), while others exhibit overlapping symptoms. AD, autosomal dominant; AR, autosomal recessive; GOF, gain of function; LOF, loss of function. Created in BioRender. djidjik, r (2025). https://BioRender.com/72xxu1g.

To enhance the understanding of these immunodeficiencies, they will be presented in the following sections according to the most recent IUIS classification.

3.1.1 Immunodeficiencies affecting cellular and humoral immunity

• AR JAK3 LOF

Biallelic null mutations (homozygous/compound) in the JAK3 gene cause SCID (63, 64). These mutations result in a total or near-total loss of JAK3 expression and function, preventing the signaling of all cytokines that rely on the common γ chain (CD132). At the molecular level, JAK3 associates with the common γ chain and is essential for signal transduction by γc-containing receptors, including IL7 and IL15, which are required for the development of T and NK cells, respectively (65). Consequently, mutations in human JAK3 lead to a complete absence of circulating T and NK cells, with a normal number of nonfunctional B cells (T^-B⁺NK^- SCID). The clinical phenotype of JAK3-SCID is nearly identical to that of X-linked SCID (IL2Rγ deficiency). Affected patients typically present within the first few months of age with oral candidiasis (thrush), intractable diarrhea with failure to thrive, and life-threatening bacterial, viral, and fungal infections, often caused by Pneumocystis jirovecii (66–74).

Hypomorphic forms of JAK3 have been identified in patients with late-onset combined immune deficiency (75, 76). Some hypomorphic mutations result in residual protein function allowing partial cytokine signaling and enabling some production of T and NK cells. These patients exhibit a milder clinical phenotype, characterized by less severe infections and the presence of autoimmune features (type 1 diabetes, autoimmune cytopenia).

3.1.2 Combined immunodeficiencies with associated or syndromic features

• AD STAT3 LOF (dominant negative)

Dominant negative mutations in STAT3 are the most common cause of hyper IgE syndrome (HIES), previously known as Job’s syndrome (77). This multisystem disorder is characterized by eczematoid dermatitis, recurrent skin and lung infections, retained primary teeth, skeletal and joint abnormalities, and vascular anomalies (78). The multisystemic manifestations of the disease are consistent with the ubiquitous expression of STAT3 and its crucial role in mediating responses to various cytokines and growth factors, including the IL-6 family, IL-10 family, IL-21, and IL-23 (79). The infectious spectrum is predominantly characterized by bacterial and fungal infections, primarily involving Staphylococcus aureus (80), Candida albicans (81), and Aspergillus (82, 83), likely related to defective STAT3/Th17 immunity (84).

• AD STAT6 GOF

Recently, several research groups reported a new primary atopic disease caused by germline heterozygous STAT6 GOF variants (85–89). These mutations are primarily located in the DNA-binding domain, enhancing the transcriptional activity of STAT6. An increase in STAT6 phosphorylation was observed before and after IL-4 stimulation (86, 87), along with the overactivation of STAT6 target genes and excessive expression of IL4R (87, 89), CCL24 (85), and IL-5, leading to elevated production of Th2 cytokines (IL-4, IL-5, IL-13) (87). Consistent with STAT6’s physiological role, elevated serum IgE levels and marked hypereosinophilia were prominent characteristics observed in STAT6 GOF patients.

Clinically, this condition is a multisystem disorder characterized by severe early-onset treatment-resistant atopic dermatitis, multiple food and drug allergies, eosinophilic gastrointestinal disease, lymphoproliferation, and some syndromic features (85–89). Moreover, recurrent skin and respiratory infections of bacterial, fungal, and viral origin have been reported (87, 88). In one case, B-cell lymphoma was described (89). Several features of STAT6 GOF overlap with those of autosomal dominant HIES, justifying its classification as another cause of HIES (62).

• AR STAT5b LOF

Patients with homozygous LOF STAT5B mutations (90–98) exhibit a combination of severe growth hormone insensitivity and significant immunodeficiency.

As the primary downstream mediator of the IL-2 cytokine family (including IL-2, IL-4, IL- 7, IL-9, and IL-15), STAT5B plays a crucial role in lymphocyte development, function, and survival (99). Consequently, STAT5B mutations can lead to T and NK lymphopenia (93, 95, 97), potentially explaining the increased susceptibility to severe viral and bacterial infections. Additionally, STAT5B is also crucial for the differentiation of regulatory T cells (100). Indeed, Treg count was found to be reduced in a significant proportion of patients with homozygous STAT5B mutations, who presented with autoimmune manifestations (e.g., Hashimoto’s thyroiditis, autoimmune cytopenia) (101).

These mutations disrupt growth hormone signaling, which is associated with post-natal growth failure resulting in severe short stature (90–98). Facial dysmorphism (95), delayed bone age (93, 97), and delayed puberty (92) were also noted in some cases.

• AD STAT5b LOF (dominant negative)

Heterozygous dominant negative LOF STAT5B mutations are extremely rare. Patients present with a milder clinical phenotype characterized by partial growth hormone insensitivity, impaired post-natal growth, eczema and elevated serum IgE without the profound immunologic abnormalities seen in AR STAT5B LOF variants (102). At the molecular level, mutant proteins exhibit normal mobilization to the nucleus, but their DNA-binding capacity is impaired. Moreover, these variants can dimerize with wild-type STAT5B, disrupting its normal function and explaining the pathogenicity in heterozygous carriers.

3.1.3 Diseases of immune dysregulation

• AD STAT3 GOF

GOF mutations in STAT3 lead to excessive activation of STAT3 signaling, promoting hyperinflammation and severe autoimmunity.

Patients with STAT3 GOF mutations exhibit a dysregulation in the balance between Th17 and Treg cells, characterized by an expansion of Th17 cells and a decreased number of Treg cells with impaired function. This imbalance results in autoimmune manifestations, with more than half of the patients presenting with autoimmune cytopenia (103, 104). Affected individuals frequently develop hypogammaglobulinemia and lymphopenia, making them susceptible to sinopulmonary bacterial infections (103, 104).

Patients with this disorder also exhibit massive lymphoproliferation, with lymphadenopathy, and hepatosplenomegaly (103, 104). Some patients may experience growth delays likely due to enhanced STAT3 signaling disrupting STAT5B-dependent growth hormone signaling (105–107).

• AD JAK1 GOF

The first germline GOF mutation in JAK1 was reported in 2017 by Del Bel et al. (108). Since then, several patients with JAK1 GOF variants have been identified (109–111). These mutations are primarily located in the inhibitory pseudo-kinase domain of JAK1, resulting in persistent overactivation of the JAK-STAT signaling pathways. Pronounced hyperphosphorylation of STAT1 and STAT3 has been reported both at baseline and after stimulation with IFN-γ and IL-6 (108, 111). Although less consistently observed, this dysregulation can extend to other STAT proteins, including STAT2, STAT4, STAT5B, and STAT6, leading to an overlapping clinical phenotype. Affected individuals typically present in infancy and experience a lifelong multisystem disorder with heterogeneous features, including atopic diseases (severe atopic dermatitis, allergies, asthma), hyper-eosinophilic syndrome (profound eosinophilia with eosinophilic infiltration of the liver and gastrointestinal tract), autoimmunity (autoimmune thrombocytopenia, autoimmune hepatitis, type I diabetes), inflammatory bowel disease, recurrent infections, and growth defects (108–111).

• SOCS1 haploinsufficiency

Heterozygous LOF mutations in SOCS1 were first reported in 2020 (112–114). Since then, several patients have been identified. The evolving disease phenotype includes a wide range of immune dysregulatory manifestations, such as allergy, inflammatory bowel diseases, autoimmune cytopenia, lymphoproliferation, and rheumatological manifestations (115). Patients also show increased susceptibility to bacterial and viral infections. Notably, these mutations exhibit incomplete penetrance, with some carriers remaining asymptomatic. Immunological investigations revealed a low proportion of switched memory B cells while the proportion of CD21^low B cells was elevated (115). The patients’ PBMC showed increased STAT1 phosphorylation and enhanced IFN I and II signaling consistent with reduced SOCS1 activity (114).

• PTPN2 Haploinsufficiency

Recent studies have identified both heterozygous and homozygous LOF mutations in PTPN2 associated with a spectrum of clinical manifestations, including autoimmune enteropathy (116, 117), recurrent infections (112), and systemic autoimmunity, including systemic lupus erythematosus and cytopenia (118). Mutations in PTPN2 also result in incomplete penetrance, similar to that observed with SOCS1 haploinsufficiency. At the molecular level, increased phosphorylation of STAT1 and STAT5 after stimulation with IFN-γ and IL-2 has been reported, reflecting hyperactivation of the JAK–STAT pathway (118). Additionally, elevated levels of inflammatory cytokines have been detected in the patients’ sera, further underscoring the inflammatory immune dysregulation associated with PTPN2 deficiency.

3.1.4 Defects in intrinsic and innate immunity

• Mendelian Susceptibility To Mycobacterial Disease (MSMD)

• AD STAT1 LOF

Heterozygous LOF mutations in STAT1 are rare and lead to increased susceptibility to mycobacterial infections without predisposing to viral infections (119–129), this can be explained by an impaired response to IFN-γ, while IFN-α/β signaling remains preserved. This likely stems from the distinct signaling mechanisms of interferons: IFN-γ relies on STAT1-STAT1 homodimers, whereas IFN-α/β signaling occurs through STAT1-STAT2 heterodimers (130).

• AR TYK2 LOF

TYK2 deficiency is a rare disorder inherited as an AR trait, initially described as a cause of HIES (131). However, further investigation revealed that the majority of TYK2-deficient patients do not exhibit the HIES features. Instead, they demonstrate increased susceptibility to intracellular bacterial and/or viral infections, with mycobacterial disease being the most consistent infection (132). Therefore, it was proposed that human TYK2 deficiency represents a distinct IEIs entity, clinically different from the previously identified patients with AR-HIES. According to the categorization reported by IUIS, TYK2 deficiency was classified under MSMD (133).

There are three forms of TYK2 inherited deficiency (134):

- AR complete TYK2 deficiency (with or without TYK2 expression) (131, 132, 134–136): Characterized by MSMD (and more rarely tuberculosis) and/or viral diseases due to an impaired response to IL-12, IL-23 (poor IFN-γ underlies mycobacterial diseases), IFN-α (viral diseases), and IL-10 signaling.

- Homozygosity for the missense variant P1104A (137): Described as a rare genetic etiology of MSMD and a common genetic cause of primary tuberculosis. Patients mainly present tuberculosis, and more rarely MSMD, without viral diseases. This variant affects the enzymatic activity of TYK2 but not its expression leading to selectively impaired responses to IL-23.

- AR partial TYK2 deficiency (134): Caused by hypomorphic variants. Individuals with partial TYK2 deficiency have normal TYK2 expression but exhibit either impaired responses to several cytokines (similar to complete TYK2 deficiency) or selectively impaired responses to IL-23 (as seen in P1104A).

The impairment of IL-23–dependent induction of IFN-γ is the only mechanism of mycobacterial disease common to all molecular forms of TYK2 deficiency.

• AR JAK1 LOF

So far, only one patient with JAK1 germline [LOF] mutations has been identified (138), where JAK1 was reduced but not completely absent. Exome sequencing revealed two homozygous hypomorphic mutations affecting the pseudo-kinase domain of JAK1 leading to impaired phosphorylation of several STAT proteins (STAT1, STAT3, STAT4, STAT5, and STAT6), which contributed to the immunodeficiency manifested by the patient. He presented with recurrent atypical mycobacterial infections, cardiomyopathy, developmental delay, and early-onset metastatic bladder carcinoma. Susceptibility to atypical mycobacterial infections could be related to T cell lymphopenia, reduced IFN-γ production, and an impaired JAK1-STAT1 signaling pathway.

• Predisposition to Severe Viral Infection

• AR STAT1 LOF

STAT1 deficiency, in its autosomal recessive inheritance pattern, can occur in two forms: complete and partial.

Complete LOF leads to early-onset, life-threatening infections caused by intracellular pathogens (nontuberculous mycobacteria, BCG) and viruses (typically herpesviruses), reflecting the lack of a STAT1-mediated response to IFN-γ, IFN-α/β, IFN-λ, and IL-27 (139–144). HSCT remains the only curative option for this disease. Notably, some cases suffer from a secondary hemophagocytic syndrome (143).

A milder form of the disease (partial AR STAT1 LOF) has been reported in patients with biallelic hypomorphic mutations, who exhibit an impaired but not abolished STAT1 response to interferons (144–147).

• AR STAT2 LOF

As part of the ISGF3 (STAT1-STAT2-IRF9) transcription factor complex, STAT2 is essential for cellular responses to type I and type III interferons downstream of their respective receptors (148). Consequently, biallelic LOF mutations in STAT2 impair the formation of the ISGF3 complex, disrupting the induction of interferon-stimulated antiviral genes (ISGs), resulting in defective IFN-α and IFN-β signaling and an inadequate ability to control viral infections.

Patients with a complete STAT2 deficiency suffer from severe adverse reactions to live attenuated viral vaccines (especially the measles-mumps-rubella vaccine) and severe viral infections, particularly critical influenza pneumonia, critical COVID-19 pneumonia, and herpes simplex virus type 1 (HSV-1) encephalitis (149). Furthermore, some patients experience hemophagocytic lymphohistiocytosis (HLH) and other inflammatory complications, including myocarditis and atypical Kawasaki disease.

• Predisposition To Mucocutaneous Candidiasis

• AD STAT1 GOF

Germline-activating STAT1 mutations are the most common cause of STAT1-related IEIs. This disease is inherited in an autosomal dominant manner. Dysregulation of STAT1 due to GOF mutations leads to a disorder associated with IEIs that presents with a wide spectrum of phenotypes. These range from mild cases of recurrent thrush, which meet the definition of chronic mucocutaneous candidiasis (CMC), to severe cases that may hinder the diagnosis. In the largest multicenter study of 274 patients with STAT1-GOF mutations (150), it was found that 98% of the cases developed CMC. This prevalence can be partially explained by a deficiency of TH17 cells observed in 87% of these patients, which is associated with negative effect of STAT1 GOF on STAT3-driven induction of TH17 cells crucial for preventing CMC (151). Additionally, patients were susceptible to recurrent lower respiratory tract bacterial infections, primarily caused by Staphylococcus aureus. Aside from infectious phenotypes, autoimmune diseases are common complications, affecting 40% of patients, along with conditions such as hypothyroidism, type I diabetes, Addison’s disease, and autoimmune thrombocytopenia. A small proportion (5%) of patients develop squamous cell cancers, particularly cutaneous carcinomas.

3.1.5 Autoinflammatory Disorders

• AR STAT2 Loss of Negative Regulation

In the later stages of IFN-I signaling, STAT 2 contributes to negative regulation by recruiting USP18 to the IFNAR2 subunit of the IFN-I receptor (58). To date, three homozygous STAT2 variants (R148W, R148Q, and A219V) have been reported to impair this regulatory function. These variants disrupt USP18 binding (R148W and A219V) (152, 153) or hinder proper trafficking of the STAT2-USP18 complex to the receptor (R148Q) (154), leading to prolonged IFN-I signaling and contributing to interferonopathies.

Notably some previous reports referred to the R148W and R148Q variants as conferring a “GOF”. Nevertheless, in this context, the term “GOF” describes the resulting biochemical and clinical phenotype rather than the underlying molecular mechanism related to the loss of the negative regulatory function of STAT2 on IFN-I signaling.

Patients with homozygous loss-of-inhibitory function mutations in STAT2 mainly present with severe inflammatory encephalopathy (including seizures, brain calcifications, and developmental delay) and inflammatory interstitial lung disease (152–154).

• AD STAT4 GOF

Baghdassarian et al. identified the first monogenic disorder caused by a heterozygous germline GOF variant in STAT4 in 2023 (155). Affected patients presented with disabling pansclerotic morphea, a severe childhood-onset systemic inflammatory disorder characterized by skin sclerosis and mucosal ulcerations. Laboratory evaluations showed mild neutropenia and lymphopenia with hypogammaglobulinemia. Inhibition of JAK signaling with ruxolitinib led to the normalization of most immunologic variables and resolution of systemic symptoms.

3.1.6 Phenocopies of inborn errors of immunity

• Non-Clonal Hypereosinophilic Syndrome Due to Somatic Mutation in STAT5b GOF

Somatic GOF mutations in STAT5B, particularly the N642H variant, were initially identified only in association with hematologic malignancies (156). Nevertheless, in 2016, Ma et al. described two patients with an identical somatic mutation in the STAT5B gene presenting with a non-neoplastic phenotype of early-onset, severe non-clonal hypereosinophilia, accompanied by urticaria, dermatitis, and diarrhea (157). Since then, this disorder has been included in the IUIS classification as a phenocopy of IEIs due to somatic variants (158). Lymphocytes from affected patients showed a significant increase in STAT5B phosphorylation in response to several cytokines, with only a minimal elevation at the basal state (157).

• Somatic JAK1 GOF (S703I)

In 2020, Gruber et al. identified a de novo mutation in the JAK1 gene (c.2108G >T, S703I) in a patient presenting with a complex autoinflammatory and atopic syndrome (159). From an early age, the patient suffered from an asymmetric pustular rash and chronic gastrointestinal tract inflammation. Later, he developed a membranous glomerulonephritis and multiple allergies. Elevated phosphorylation of STAT1, STAT3, STAT4, STAT5, and STAT6 was observed selectively, depending on the immune cell type. Treatment with tofacitinib reduced STAT hyperphosphorylation and improved disease outcomes.

3.2 JAK/STAT pathway in hematologic malignancies

Hematologic malignancies involve the abnormal proliferation and accumulation of blood cells and represent a heterogeneous group of diseases with complex molecular mechanisms. A key driver in the development and progression of these diseases is the dysregulation of the JAK-STAT signaling pathway. Aberrant activation of JAK-STAT signaling, often driven by genetic mutations (supplementary tables) that occur upstream or within core components of the pathway, plays a pivotal role in the pathogenesis of various hematologic malignancies, including myeloproliferative neoplasms, acute leukemias, and mature lymphoid neoplasms (160). These diseases will be reviewed in decreasing order of reported mutation frequency to enable a structured analysis of the most commonly affected conditions. (Figure 5).

Figure 5

Figure 5. JAK-STAT pathway gene alterations in hematologic malignancies. Common pathogenic mutations are grouped by disease type: (a) myeloproliferative neoplasms, (b) acute leukemias, and (c) mature lymphoid neoplasms. Subtypes are indicated in blue boxes. ALL, Acute Lymphoblastic Leukemia; AML, Acute Myeloid Leukemia; cHL, Classical Hodgkin Lymphoma; CTCL, Cutaneous T-Cell Lymphoma; ET, Essential Thrombocythemia; LGLL, Large Granular Lymphocyte Leukemia; MCL, Mantle Cell Lymphoma; MLNs, Mature lymphoid neoplasms; NKTCL, Natural Killer/T-Cell Lymphoma; PMF, Primary Myelofibrosis; PTCL, Peripheral T-Cell Lymphoma; PV, Polycythemia Vera; sAML, Secondary Acute Myeloid Leukemia. Created in BioRender. djidjik, r (2025). https://BioRender.com/grqjm63.

3.2.1 Myeloproliferative neoplasms

Myeloproliferative neoplasms (MPNs) are a group of clonal hematologic malignancies originating from hematopoietic stem cells. They are characterized by the excessive proliferation of one or more blood cell lineages, typically leukocytes, erythrocytes, or platelets, depending on the specific disease subtype. These disorders are associated with an elevated risk of thrombosis, progressive myelofibrosis, and leukemic transformation. Mutations affecting key components of the JAK-STAT pathway, including the driver mutations JAK2, Calreticulin (CALR), and the myeloproliferative leukemia virus oncogene (MPL), are commonly observed in MPN patients (161, 162).

• JAK2

As discussed in the first section, the JAK2 protein, a member of the tyrosine kinase family, is involved in the signal transduction of several cytokine receptors, including erythropoietin (EPO), thrombopoietin (TPO), and granulocyte-colony stimulating factor (G-CSF).

The JAK2 V617F mutation is a hallmark driver mutation and the most frequent mutation in Philadelphia chromosome (Ph)-negative MPNs. It is found in over 90% of patients with polycythemia vera (PV), approximately 50%-60% of patients with essential thrombocythemia (ET), and primary myelofibrosis (PMF) (16, 163, 164). This mutation is one of the major diagnostic criteria for Ph-negative MPNs. It results from a guanine-to-thymine substitution at nucleotide 1849 in exon 14 of the JAK2 gene, leading to a valine-to-phenylalanine substitution at position 617 in the pseudokinase domain (JH2). The mutation disrupts the inhibitory function of this domain, resulting in the constitutive activation of the kinase’s catalytic (JH1) domain and persistent stimulation of downstream STAT transcription factors, notably STAT3, STAT5, and STAT6. This leads to cytokine hypersensitivity and cytokine-independent growth of myeloid cells, contributing to oncogenic processes in hematologic malignancies. Additionally, the mutation activates the PI3K-AKT and Ras-Raf-MAPK-ERK signaling pathways, making it a significant oncogenic driver (165).

Mutations within exon 12 of the JAK2 gene also contribute significantly to the pathogenesis of Ph-negative MPNs. Similar to JAK2 V617F, these mutations impair the autoinhibition of the JAK2 kinase, resulting in its constitutive activation. Most exon 12 mutations affect residues between residues 537 and 547 (substitutions, deletions, and deletions-insertions). Unlike JAK2 V617F, exon 12 mutations are almost exclusively found in patients with PV, accounting for approximately 2-5% of cases (166, 167).

• CALR

Calreticulin is an endoplasmic reticulum chaperone protein involved in protein folding and is the second most commonly mutated protein in MPNs, following JAK2. Mutations in CALR Exon 9, which are a major diagnostic criterion for Ph-negative MPNs, are found in 67% to 88% of patients with ET or PMF who lack JAK2 mutations (18, 168). The most frequent mutations, L367fs*46 (Type I) and K385fs*47 (Type II), generate a novel C-terminal peptide that aberrantly activates the TPO receptor or MPL through homomultimerization. This interaction results in the constitutive activation of MPL-associated JAK2, driving cytokine-independent signaling (18). CALR mutations are mutually exclusive with other MPNs driver mutations, including JAK2 V617F and MPL mutations (18). Recent findings have demonstrated that mutant CALR induces cytokine-independent activation of MPL through a specific interaction mechanism. This involves the binding of mutant CALR to immature MPL via asparagine-linked glycans within the endoplasmic reticulum, facilitating the formation of a CALR-MPL complex. This complex is subsequently trafficked to the cell surface, where it promotes constitutive activation of the downstream kinase JAK2 associated with MPL (169). Patients with CALR-mutated PMF typically experience better outcomes, including higher platelet and hemoglobin levels, lower thrombosis risk, and longer survival (18).

• MPL

The TPO receptor or MPL is a key component of the TPO-JAK2-STAT signaling pathway, playing a crucial role in the JAK2-STAT signaling cascade. Mutations in MPL can aberrantly activate downstream signaling pathways, contributing to tumorigenesis and disease progression. Common MPL mutations include W515L, W515K, W515A, W515S, W515R, and S505N (169). These mutations are present in 3% to 5% of patients with ET and 8% to 10% of patients with PMF, representing one of the diagnostic criteria for Ph-negative MPNs (170). MPL mutations in ET patients are typically associated with elevated platelet counts, lower hemoglobin levels, increased arterial thrombosis risk, and poorer overall survival. A cohort study of MPN patients and analysis of bone marrow-derived DNA from different disease stages have consistently shown that MPL W515L and JAK2 V617F co-occur in MPNs, suggesting that these mutations may complement each other in driving MPN pathogenesis (171).

• LNK

LNK, a lymphocyte adaptor protein that negatively regulates the JAK-STAT signaling pathway, plays a crucial role in MPNs. Loss-of-function mutations in the LNK gene (SH2B3), mostly missense or frameshift mutations, lead to activation of the JAK-STAT pathway, promoting hematopoietic stem cell proliferation (172, 173).

3.2.2 Acute lymphoblastic leukemias

Acute lymphoblastic leukemia (ALL) is an aggressive hematologic malignancy characterized by the malignant transformation of developing lymphoid precursor cells, driven by the accumulation of genetic alterations. The pathogenesis of ALL involves multiple signaling pathways, with recent studies highlighting the significant role of the JAK-STAT pathway. Dysregulated activation of this pathway promotes abnormal cell proliferation and inhibits apoptosis, contributing to the onset of ALL (19).

• JAK2

Gain-of-function mutations in JAK2, frequently observed in ALL, are primarily located in exon 16, notably affecting arginine at position 683 (R683), which is most commonly substituted with glycine (R683G) or serine (R683S). A rare JAK2 ΔIREED mutation, involving a five–amino acid deletion within the JH2 pseudokinase domain, has also been reported (19, 174). In addition, JAK2 fusion genes resulting in constitutive kinase activity have been described, although rarely in ALL, including ETV6-JAK2 (175) and PCM1-JAK2 fusions (19, 176), all of which are associated with poor prognosis. Nonetheless, JAK2 mutations often require cooperating genetic alterations, particularly cytokine receptor-like factor 2 (CRLF2) rearrangements or additional mutations in JAK family members (177).

• CRLF2

Thymic stromal lymphopoietin (TSLP) signals through a receptor composed of CRLF2 (on X/Y chromosomes) and IL-7Rα, which are constitutively associated with JAK2 and JAK1, respectively (178, 179). CRLF2 alterations, frequently co-occurring with JAK2 mutations, contribute to the constitutive activation of STAT5. These changes promote cytokine-independent proliferation and survival of early hematopoietic cells, thereby facilitating the development of B-cell precursor acute lymphoblastic leukemia (BCP-ALL) (178).

CRLF2 overexpression is primarily driven by chromosomal rearrangements involving IGH or P2RY8 (179).

• IL-7R

A key upstream mutation associated with the abnormal activation of the JAK-STAT pathway in T-ALL is the dysregulated expression of the interleukin 7 receptor (IL-7R). Aberrant IL-7R expression drives oncogenic programs in over 70% of T-ALL cases. IL-7R, predominantly expressed in lymphoid cells, is crucial for T cell development and maintaining homeostasis in mature T cells. Activating mutations in IL7R, notably those causing homodimerization of IL-7Rα, such as the S185C substitution in the extracellular domain or insertions or deletions in the transmembrane domain of IL-7R, enhance JAK–STAT5 signaling and are found in approximately 12% of Ph-like ALL and 2–3% of B-ALL cases (180, 181).

• JAK1 and JAK3

Sustained activation of the JAK-STAT signaling pathway is a key driver in the initiation and progression of T-cell acute lymphoblastic leukemia (T-ALL), with activating mutations in JAK1 (e.g., V658F) and JAK3 (e.g., M511I) commonly reported in T-ALL cases. Recent studies suggest that T-ALL arises through a multistep transformation process involving the accumulation of various genetic defects, such as activating mutations in the JAK-STAT pathway (182).

• PTPN2

Enhanced activation of the JAK-STAT pathway in T-ALL can result from mutations and deletions in protein tyrosine phosphatase non-receptor type 2 (PTPN2). Loss of PTPN2 function increases IL-7R signaling responsiveness, thereby amplifying downstream JAK-STAT activation (17).

• STAT5

The STAT5B N642H hotspot mutation has been commonly found in pediatric T-cell acute lymphoblastic leukemia (T-ALL) and is associated with poor prognosis and an increased risk of relapse (183). In addition, the less frequent STAT5B Y665F mutation, as well as other rare missense mutations in STAT5A or STAT5B affecting the SH2 or transactivation domains, have been reported (184). These gain-of-function mutations result in constitutive activation of the JAK-STAT pathway, promoting leukemic cell proliferation and survival.

3.2.3 Mature lymphoid neoplasms

Studies have shown that aberrant activation and mutations of the JAK-STAT signaling pathway are frequently detected in various mature B-cell, T-cell, natural killer (NK) cell neoplasms, and Hodgkin lymphomas (185).

• STAT3, STAT5, STAT6, and SOCS1

Aberrations in the JAK-STAT pathway are critical features of classical Hodgkin lymphoma (cHL), with frequent mutations in STAT6 (32%) and SOCS1 (59%). In cHL, Pleiotrophin activates JAK2/STAT6, contributing to immune evasion and tumor plasticity. Elevated cytokines, such as IL-21, further stimulate STAT5, enhancing tumor growth (186).

In mantle cell lymphoma (MCL), STAT3 mutations, although rare, can lead to constitutive activation of the JAK/STAT pathway, promoting tumor cell survival, proliferation, and immune evasion (186).

Elevated expression of STAT5A/B has also been detected in human PTCL samples. Both factors have been confirmed as oncogenes in PTCL, with STAT5B being more transforming (187).

Moreover, mutations in STAT3 and STAT5B genes have been detected in patients with large granular lymphocytic leukemia (LGLL), with the STAT5B N642H mutation linked to unfavorable disease progression (156, 188).

• JAK1 and JAK3

Recent studies have identified JAK1 as an oncogenic driver in various lymphomas, particularly in relapsed or refractory peripheral T-cell lymphoma (PTCL), where its sustained activation is associated with enhanced tumor proliferation, survival, migration, and suppression of anti-tumor immunity (189).

Deregulated JAK/STAT signaling due to JAK1 and JAK3 somatic mutations has also been observed in Cutaneous T-Cell Lymphoma (CTCL), supporting malignant proliferation (190).

In natural killer T-cell lymphoma (NKTCL), JAK3 mutations (A572V/A573V) occur in approximately 35% of cases and drive constitutive JAK3/STAT5 activation, promoting proliferation (190).

3.2.4 Acute myeloid leukemia

Acute myeloid leukemia (AML) is a genetically heterogeneous malignancy characterized by the clonal expansion of hematopoietic stem and progenitor cells (HSPCs), leading to the accumulation of immature myeloid precursors in the bone marrow and peripheral blood. This proliferation disrupts normal hematopoiesis, resulting in cytopenia such as anemia, leukopenia, and thrombocytopenia (19).

The development of AML is considered a multistep and multifactorial process (191). Mutations within the JAK/STAT signaling pathway have been implicated not only in secondary acute leukemias (sAML) arising from MPNs but also in de novo acute leukemias (192, 193). This aberrant signaling is associated with poor prognosis and serves as a predictive biomarker for disease progression.

• JAK2

High expression levels of JAK2 V617F promote the transformation from MPN to sAML by enabling cytokine-independent survival and proliferation of myeloid progenitor cells (194, 195). JAK2 exon 12 mutations can also occur in sAML derived from PV (167).

Fusion genes such as PCM1–JAK2 (174, 177), BCR–JAK2 (174, 196), and ETV6–JAK2 have been identified in de novo AML, leading to constitutive kinase activation (175). This results in persistent activation of downstream signaling, which can lead to unregulated cell division and evasion of apoptotic signals, key hallmarks of AML.

• STAT 3 and STAT 5

Although direct STAT3 and STAT5 mutations are rare in AML, constitutive activation of these transcription factors is frequently observed, with studies reporting activation in 44–76% of patients. This persistent activation is often driven by upstream mutations or cytokine signaling and is associated with chemoresistance and poor prognosis (197, 198).

3.2.5 Indirect genetic activation of JAK-STAT in hematologic malignancies

In addition to canonical cytokine stimulation, various genetic alterations modulate the JAK-STAT pathway in hematologic malignancies, reinforcing disease progression. Lysine (K)-methyltransferase 2A (KMT2A) rearrangements, common in ALL and AML, enhance JAK-STAT signaling by downregulating IL-7R/IL-4R and suppressing KMT2A expression (199). Similarly, the BCR-ABL1 fusion, particularly the p190 isoform in Ph-positive B-ALL, directly activates STAT5, either independently or via JAK2, driving proliferation and correlating with poor prognosis (200). In lymphoplasmacytic lymphoma, the MYD88 L265P mutation leads to constitutive STAT3 activation, promoting B-cell survival and immune evasion (201). In Hodgkin lymphoma, PD-L1/PD-L2: 9p24.1 alterations and PD-L1/PD-L2 mutations drive JAK-dependent overexpression of PD-L1/PD-L2, facilitating immune escape via PD-1 signaling (4). In AML, mutations in kinases such as FMS-like tyrosine kinase 3 (FLT3) can activate STAT5 independently of JAK2, particularly in the presence of co-occurring nucleophosmin (NPM1) or DNA methyltransferase 3A (DNMT3A) mutations, which further upregulate MYC and BCL2 (202–204). Additionally, gain-of-function KIT mutations (e.g., D816V), along with alterations in CCAAT/enhancer-binding protein alpha (CEBPA) and colony-stimulating factor 3 receptor (CSF3R), increase JAK-STAT pathway sensitivity in AML (205). The JAK-STAT pathway also interacts with p53 signaling in hematologic malignancies: JAK2 V617F promotes p53 degradation via murine double minute 2 (MDM2) and La protein through the PI3K/Akt/mTOR pathway, while STAT1 counters this by stabilizing p53. Conversely, STAT3 represses TP53 transcription, and STAT5 disrupts NPM1-mediated p53 stabilization. Additionally, the protein inhibitor of activated STAT Y (PIASy), a STAT inhibitor, further suppresses p53 activity (206).

Collectively, these findings underscore the central role of the JAK-STAT pathway in the pathogenesis of various hematologic malignancies, including MPNs, acute leukemias, and mature lymphoid neoplasms. Aberrant activation of this pathway, driven by somatic mutations, chromosomal rearrangements, or dysregulated cytokine signaling, promotes malignant cell proliferation, survival, and immune evasion. Recurrent alterations in core components such as JAK1, JAK2, JAK3, STAT3, STAT5, and STAT6 not only contribute to oncogenesis but also represent actionable therapeutic targets. The development of JAK inhibitors, particularly in combination with immune checkpoint blockade, has opened promising therapeutic avenues. Ongoing elucidation of the molecular mechanisms governing JAK-STAT dysregulation will be critical to advancing precision medicine approaches in hematologic cancers.

4 Laboratory-based investigation of the JAK/STAT pathway

4.1 Initial assessment of JAK/STAT pathway activity

4.1.1 Analysis of JAK-STAT pathway phosphorylation

JAK-STAT phosphorylation can be studied using various approaches, each providing specific types of information. The most common method is Western blotting following immunoprecipitation from activated cell extracts using anti-phosphotyrosine (a-pY) antibodies. Cells are first lysed in an appropriate buffer, and the targeted JAK or STAT protein is immunoprecipitated, separated by SDS-PAGE, transferred to a membrane, and detected by Western blot. The identity of the phosphorylated protein is then confirmed using JAK- or STAT-specific antibodies. However, Western blot analyses performed on heterogeneous cell populations yield results that are difficult to interpret, making it necessary to use pre-sorted cells. In contrast, a flow cytometry-based method for detecting phosphorylated proteins provides clearer results, and cell populations can be identified simultaneously. After cytokine stimulation, the cells are fixed with paraformaldehyde and then permeabilized using a cold methanol/acetone mixture. The cells are then washed and stained with a phospho-specific antibody that is either directly conjugated to a fluorochrome or followed by a fluorescent secondary antibody if the primary antibody is unlabeled. Surface staining must also be performed to target the cellular subpopulations of interest. After several washes, the cells are analyzed by flow cytometry (207).

4.1.2 Analysis of STAT-induced transcriptional activity

While tyrosine phosphorylation of STAT proteins is crucial for their activation, the primary biological outcome of JAK-STAT pathway stimulation is the altered expression of its target genes (208, 209).

The transcriptional activity of STAT proteins can be assessed by measuring the expression levels of well-characterized target genes such as GBP1, SOCS1, SOCS2, SOCS3, ABCB2, CCND1, c-Myc, Bcl-xL, and Cyclin D1 (210). Total RNA is extracted from cells using a suitable reagent, such as TRIzol or an equivalent kit, followed by DNase I treatment to eliminate any genomic DNA contamination. RNA concentration and purity are evaluated by spectrophotometry, and RNA integrity is assessed by agarose gel electrophoresis or using a bioanalyzer. For quantitative PCR (qPCR), total RNA is first reverse transcribed using random hexamer primers and a reverse transcriptase. qPCR is then carried out using gene-specific primers and a SYBR Green or TaqMan detection system on a real-time thermocycler (211). Gene expression levels are normalized to reference genes such as GAPDH or ACTB.

As a complement or alternative, high-throughput RNA sequencing (RNA-seq) can be used to globally analyze the transcriptome. RNA libraries are prepared from enriched mRNA (by polyA tail selection) or after rRNA depletion, followed by fragmentation, cDNA synthesis, and adaptor ligation. Sequencing is performed using single-end or paired-end reads. Raw reads are then aligned to the reference genome, and transcript abundance is quantified. Differential gene expression analysis is conducted using bioinformatics tools such as DESeq2 or EdgeR. This approach enables accurate and comprehensive evaluation of STAT-dependent transcriptional regulation in response to specific stimuli or conditions (212).

4.1.3 Measurement of cytokines

Quantification of cytokines is essential for evaluating the activation status of the JAK/STAT signaling pathway. Enzyme-linked immunosorbent assays (ELISA) remain the gold standard for the quantification of individual cytokines, offering high sensitivity and specificity. However, ELISA is generally limited to the detection of one analyte per sample. In contrast, multiplex assays such as Luminex xMAP technology or Meso Scale Discovery (MSD) electrochemiluminescence platforms enable the simultaneous detection and quantification of multiple cytokines in small sample volumes. These bead- or spot-based technologies employ fluorescent or electro-chemiluminescent tags bound to capture antibodies specific to the target cytokines, enabling parallel profiling of complex cytokine networks (213–218). Multiplexing is especially valuable when analyzing cytokine panels in inflammatory or immune signaling contexts, where multiple STAT activators may be present. Sample preparation typically involves collection of conditioned media from cultured cells or plasma/serum from in vivo studies, followed by centrifugation and dilution according to assay requirements. Controls and standards must be included for accurate quantification, and results are usually reported in pg/mL or ng/mL. Assay sensitivity, cross-reactivity, and dynamic range should be carefully considered during assay selection and data interpretation.

Quantitative cytokine measurements serve not only to confirm the presence of signaling molecules but also to correlate cytokine abundance with downstream STAT phosphorylation and transcriptional output, thereby providing a comprehensive picture of pathway activation.

4.2 Genetic and epigenetic analysis of the JAK/STAT pathway

Genetic mutations and epigenetic alterations are key drivers of JAK/STAT pathway dysregulation in human disease. Integrating mutation analysis, CNV profiling, and epigenetic mapping provides critical insights for disease classification, prognosis, and the tailored use of targeted therapies such as JAK inhibitors.

4.2.1 Mutation analysis

• Quantitative PCR (qPCR) Diagnosis: Targeted and Rapid Detection

qPCR is widely used for detecting known point mutations in key genes of the JAK/STAT pathway, such as JAK2, STAT3, and STAT5B. This method uses specific probes or allele-discriminating primers capable of distinguishing wild-type from mutant alleles. A classic example is the JAK2 V617F mutation, found in over 90% of patients with polycythemia vera and in a significant proportion of those with essential thrombocythemia or primary myelofibrosis (219–222). Commercial qPCR kits offer rapid and sensitive detection of these mutations. However, qPCR is limited to the detection of predefined mutations and is therefore not suitable for identifying rare or novel mutations, nor for comprehensively analyzing entire gene regions. Nevertheless, it remains a preferred technique for targeted screening in clinical diagnostics or for monitoring mutation burden over time (223, 224).

• Sanger Sequencing: Validation and Point Mutation Detection

Sanger sequencing remains the gold standard for identifying point mutations, small insertions, or deletions in JAK/STAT pathway genes. It enables direct reading of nucleotide sequences, typically focusing on the coding exons of genes (164, 225, 226). This technique is often used to validate results from other approaches (qPCR or NGS), or in translational research settings. While highly accurate, Sanger sequencing has certain limitations: it lacks sensitivity for detecting low-frequency mutations (allelic frequency <15–20%) and is less efficient for large gene panels. Thus, it is less suitable for complex diagnostic needs requiring broader coverage or high sensitivity (227).

• Next-Generation Sequencing (NGS): Comprehensive Analysis of the JAK/STAT Pathway

NGS has revolutionized molecular diagnostics by enabling massively parallel analysis of numerous genes, entire exomes, or even whole genomes. Three main strategies are commonly used:

- Targeted Gene Panels (TGP): TGPs are NGS-based assays designed to selectively analyze a predefined set of genes associated with specific diseases or biological pathways. They focus on capturing and sequencing only the exons or relevant regions of selected genes, enabling high coverage and sensitivity for detecting pathogenic variants, including single nucleotide variants (SNVs), insertions/deletions (indels), and copy number variations (CNVs) (228, 229). TGPs targeted hematological diseases, IEIs, or signaling pathways often include core JAK/STAT pathway genes. These panels can detect somatic or germline mutations, as well as GOF or LOF mutations (62, 230–232). In oncology, TGPs are also used to identify actionable mutations in the JAK/STAT axis, helping to inform therapeutic decisions and guide personalized medicine strategies (e.g., JAK inhibitor sensitivity) (233–236).

- Whole Exome Sequencing (WES): WES focuses on analyzing the protein-coding regions of the genome, which represent approximately 1–2% of the entire genome but harbor around 85% of disease-causing mutations (237). By targeting exons, WES enables the identification of both known and novel mutations that can lead to various monogenic diseases. It is particularly valuable in atypical clinical presentations or when routine targeted sequencing fails to detect pathogenic variants. In the context of the JAK/STAT pathway, WES allows for the discovery of rare or de novo mutations in coding regions of genes such as JAK1-3, TYK2, and STAT1-6, which may be implicated in immunodeficiencies, autoimmune syndromes, or hematological disorders. Furthermore, WES can detect mutations in regulatory genes or genetic modifiers that influence the function of the JAK/STAT pathway, often overlooked by standard gene panels limited to core pathway genes (238–240).

- Whole Genome Sequencing (WGS): WGS provides comprehensive coverage of the entire genome, including coding, non-coding, regulatory, intronic, and intergenic regions. This broader scope enables the detection of deep intronic mutations, enhancer or promoter alterations, structural variants (e.g., insertions, deletions, inversions), and CNVs that may dysregulate gene expression or disrupt chromosomal architecture (241–244). Such genomic events can influence the expression and regulation of JAK/STAT components or their upstream/downstream effectors, contributing to complex or cryptic disease phenotypes. Although WGS is more expensive and computationally demanding than WES, it is increasingly used in both research and clinical settings for patients with undiagnosed genetic conditions or for those with inconclusive prior testing (245). In particular, WGS can uncover regulatory elements or structural anomalies that modulate the JAK/STAT pathway and are critical for comprehensive diagnosis and precision medicine approaches.

4.2.2 Copy number variations

In cancers, CNVs, including deletions or amplifications, frequently lead to JAK-STAT pathway dysregulation. For example, amplification of STAT3 or STAT5B has been reported in T-cell large granular lymphocytic leukemia and other malignancies (156). Detection of CNVs can be achieved via fluorescence in situ hybridization (FISH), qPCR, or more comprehensively through NGS-based copy number profiling and comparative genomic hybridization (CGH) arrays (246). These methods provide insight into dosage alterations that may influence pathway output and therapeutic resistance.

4.2.3 Epigenetic modifications

The epigenetic landscape also contributes to the regulation of JAK/STAT signaling. Promoter hypermethylation of STAT5A, STAT5B, or SOCS1/3 genes has been implicated in the silencing of pathway modulators in various cancers and immune disorders (247, 248). DNA methylation patterns are typically assessed by bisulfite sequencing, methylation-specific PCR, or methylation arrays. Additionally, histone modifications, such as H3K27ac and H3K4me3 at cytokine-responsive promoters, can be evaluated using chromatin immunoprecipitation followed by sequencing (ChIP-seq). These epigenetic signatures provide insights into the transcriptional regulation of STAT target genes and are often integrated with transcriptomic analyses (e.g., RNA-seq) to elucidate downstream effects (249).

4.3 Functional assays

4.3.1 Luciferase reporter assays

Luciferase reporter assays are widely used to monitor the transcriptional activity of STAT proteins in living cells. In this approach, cells are transfected with plasmids containing STAT-responsive elements upstream of a luciferase reporter gene (250). Commonly used constructs include pSTAT3-TA-Luc and GAS-Luc, which incorporate tandem repeats of gamma-activated sequences (GAS) that are specifically recognized by activated STATs such as STAT1 or STAT3. Upon cytokine stimulation (e.g., IL-6, IFN-γ), activated STATs translocate to the nucleus and bind to these elements, promoting luciferase expression. The resulting luminescent signal, measured with a luminometer, reflects the degree of STAT-dependent transcriptional activation. This method provides a sensitive, quantitative, and rapid readout of STAT signaling dynamics in response to genetic manipulation or pharmacological inhibition (251, 252).

4.3.2 siRNA/shRNA knockdown of JAK/STAT components to see effects on signaling

To investigate the functional role of JAK/STAT pathway components in signal transduction, gene silencing is performed using small interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs) targeting JAK1, JAK2, STAT1, STAT3, or STAT5.

In brief, siRNA duplexes are transfected into cultured cells using Lipofectamine™ RNAiMAX (Thermos Fisher Scientific) a lipid-based transfection reagent optimized for high-efficiency siRNA delivery with minimal cytotoxicity. Knockdown efficiency is evaluated by quantitative reverse transcription PCR (qRT-PCR) or immunoblotting 2–3 days post-transfection. Non-targeting and positive control siRNAs are included respectively as a negative control and to monitor transfection efficiency. This approach enables efficient and reproducible silencing of target genes involved in critical cellular signaling pathways. For example, it has been employed to dissect the roles of individual components of the JAK/STAT pathway, such as STAT1, STAT3, JAK1, and JAK2, in cytokine signaling and immune regulation (253).

For shRNA-mediated knockdown, lentiviral vectors expressing shRNA sequences under the control of the U6 promoter, were generated by co-transfection into HEK293T cells along with plasmids, as described by Campeau et al. (254). Viral supernatants are harvested and used to infect target cells in the presence of polybrene followed by puromycin selection for 48–72 hours to enrich for transduced populations. Knockdown efficiency can be assessed by RT-qPCR and confirmed at the protein level via Western blot using antibodies against total and phosphorylated forms of the targeted JAK and STAT proteins. To evaluate the functional consequences of the knockdown, cells are stimulated with cytokines known to activate the pathway, followed by assessment of STAT phosphorylation using phospho-specific antibodies and quantification of downstream target gene expression (SOCS1, SOCS3, Bcl-xL, c-Myc) by qPCR (255, 256). This strategy enables a mechanistic dissection of individual JAK/STAT components and their specific contributions to signal transduction and transcriptional regulation.

4.3.3 Overexpression of constitutively active STAT mutants

Overexpression of constitutively active (CA) STAT mutants is a widely used strategy to study GOF effects of STAT signaling in various cellular contexts (257). These CA mutants are designed to mimic the active, phosphorylated state of STAT proteins, thereby bypassing the need for upstream cytokine or growth factor stimulation. This approach allows researchers to dissect the direct transcriptional and phenotypic consequences of sustained STAT activation under controlled experimental conditions.

A well-known example is the STAT3-C mutant, in which two cysteine residues are introduced into the SH2 domain (at positions A661C and N663C). This modification promotes the formation of stable disulfide-linked dimers, enabling cytokine-independent nuclear localization and DNA binding (257). Similarly, other mutations such as Y640F in STAT1 or D661V in STAT3, which occur in the SH2 domain or in regions that regulate dimerization, have been reported to enhance STAT activity and are sometimes found in hematologic malignancies and immune disorders (258, 259).

The functional impact of CA-STATs can be assessed by introducing these mutants into cells via plasmid transfection, viral transduction, or genome editing. Downstream effects are typically evaluated using luciferase reporter assays to measure transcriptional activity, or qPCR/RNA-seq to quantify the expression of well-established STAT target genes such as SOCS1, SOCS3, Bcl-xL, Cyclin D1, and c-Myc (260). Moreover, CA-STATs often induce biological changes such as enhanced cell proliferation, increased survival, or even cellular transformation, reflecting the oncogenic potential of deregulated STAT signaling (261).

4.3.4 CRISPR-Cas9 knockout

CRISPR-Cas9 Knockout technology offers a precise and efficient method for disrupting specific genes to investigate their functional roles in signaling pathways such as JAK/STAT. By designing guide RNAs targeting exons of genes encoding pathway components (e.g., JAK1, JAK2, STAT1, STAT3), researchers can introduce targeted double-strand breaks, which are repaired through non-homologous end joining (NHEJ), often resulting in frameshift mutations and gene knockout (262, 263).

Establishing STAT or JAK knockout (KO) cell lines using CRISPR-Cas9 allows for a direct evaluation of the dependence of downstream responses, such as cytokine-induced gene expression, transcriptional activity, and phenotypic outcomes, on specific pathway components. These KO models are especially useful for distinguishing between canonical and non-canonical STAT functions and for confirming the specificity of small-molecule inhibitors or siRNA effects (264–267). For example, Zhou et al. used CRISPR-mediated STAT3 knockout in A549 cells to show the essential role of STAT3 in IL-6-induced gene expression and tumorigenesis (268). Similarly, Zhang et al. demonstrated that knocking out JAK1 or JAK2 abrogated interferon signaling, validating pathway specificity (269).

4.3.5 Receptor blocking strategies to inhibit JAK/STAT activation

To inhibit cytokine-induced activation of the JAK/STAT pathway, receptor blocking approaches can be employed. This involves using neutralizing antibodies against cytokine receptors or applying small-molecule inhibitors targeting associated kinases. For instance, anti-IL-6R antibodies (such as Tocilizumab) effectively block IL-6 binding to its receptor, thereby preventing downstream STAT3 phosphorylation and activation (270). Similarly, JAK inhibitors such as Ruxolitinib, a selective JAK1/2 inhibitor, suppress cytokine signaling by preventing the phosphorylation of STAT proteins downstream of receptor engagement (271). These interventions allow for the functional analysis of cytokine pathways and are instrumental in both mechanistic studies and therapeutic applications.

4.4 Diagnostic Approaches in Diseases Involving the JAK/STAT Pathway

As mentioned before, aberrations in the JAK/STAT signaling pathway have been implicated in a wide spectrum of human diseases, including malignancies, autoimmune disorders, and primary immunodeficiencies. Laboratory investigations of these conditions involve the integration of the different tests mentioned above to accurately assess pathway dysregulation (Supplementary Figure).

A prime example can be found in hematological malignancies, such as ALL, lymphoma, and MPNs, genetic alterations affecting JAK2 are frequently observed. Among these, fusion events such as TEL-JAK2 (ETV6-JAK2) and PCM1-JAK2 result in constitutive activation of the JAK2 kinase, leading to persistent STAT phosphorylation and oncogenic transcriptional programs (272, 273). Detection of such fusions can be performed by reverse transcription PCR (RT-PCR) targeting the fusion junctions or by fluorescence in situ hybridization (FISH) to detect the underlying chromosomal translocations. Additionally, the JAK2 V617F point mutation, a hallmark of classical MPNs, is routinely screened using allele-specific PCR, high-resolution melting (HRM) analysis, or Sanger sequencing (274). Downstream activation of STATs, particularly STAT5, can be assessed using phospho-flow cytometry or Western blotting, providing functional evidence of pathway activation.

In autoimmune disorders such as rheumatoid arthritis, systemic lupus erythematosus, and psoriasis, aberrant activation of the JAK/STAT pathway, especially involving STAT3 and STAT5, is commonly observed. This hyperactivation is primarily driven by elevated levels of cytokines such as IL-6, IL-21, and IL-23, which enhance Th17 differentiation and promote chronic inflammation. Laboratory evaluation typically involves stimulation of peripheral blood mononuclear cells (PBMCs) with relevant cytokines, followed by assessment of STAT phosphorylation using specific antibodies in flow cytometry or immunoblotting formats (264). Transcriptional activation of downstream targets (e.g., SOCS3, IL17A, BCL-XL) is measured using quantitative PCR (qPCR). Concurrently, serum or plasma levels of inflammatory cytokines can be quantified using ELISA or multiplex bead-based assays, providing a broader picture of the inflammatory milieu.

For IEIs, as previously discussed, several monogenic disorders involving mutations in JAKs or STATs lead to inborn errors of immunity. LOF mutations in STAT3 underlie AD-HIES, characterized by eczema, recurrent infections, and impaired Th17 differentiation. Diagnosis involves STAT3 gene sequencing, typically by Sanger or whole exome sequencing (WES), and functional assays such as IL-6-induced STAT3 phosphorylation (by phospho-flow cytometry or Western blot) and Th17 differentiation assays with IL-17A measurement by ELISA or intracellular cytokine staining (275, 276). Conversely, GOF mutations in STAT3 lead to early-onset autoimmunity and lymphoproliferation. Affected individuals show elevated basal STAT3 phosphorylation and increased transcription of proinflammatory target genes, which can be assessed similarly via flow cytometry and qPCR. STAT1 GOF mutations, associated with chronic mucocutaneous candidiasis and autoimmunity, are diagnosed via STAT1 gene sequencing and functional demonstration of exaggerated STAT1 phosphorylation in response to IFN-α or IFN-γ. In contrast, STAT1 LOF mutations often associated with MSMD result in impaired interferon signaling and are confirmed by reduced STAT1 phosphorylation and target gene expression following stimulation (122). JAK3 deficiency, a well-established AR-SCID cause, results in defective signaling through the common γ-chain (γc) of several interleukin receptors. Immunophenotyping typically reveals a T−B+NK− phenotype, while JAK3 mutations are detected by sequencing (63, 277). Functional assays show absent phosphorylation of STAT5 upon stimulation with γc-dependent cytokines (e.g., IL-2, IL-7). Similarly, STAT5b deficiency impairs growth hormone signaling and immune regulation, with diagnosis relying on genetic testing and evaluation of STAT5 phosphorylation in response to IL-2 (278–280). STAT6 GOF are identified through sequencing and functional assays showing enhanced IL-4 induced STAT6 phosphorylation and elevated IgE production (87–89).

Taken together, these diverse disease entities underscore the critical role of precise molecular and functional assays in characterizing JAK/STAT pathway dysfunction. Integrating genomic sequencing, phospho-protein analysis, cytokine profiling, and cellular immune function assays provides a comprehensive framework for diagnosing and stratifying patients with JAK/STAT-related pathologies.

5 Advanced strategies for targeting the JAK/STAT pathway

The concept of inhibiting cytokines by targeting their signaling pathways with small molecules was introduced in 1995. The success of this approach stemmed from the discovery that these molecules could be specifically designed to inhibit protein kinases by targeting the ATP binding site. Several classes of therapeutics have been developed, with the majority focusing on inhibiting JAKs (Jakinibs), alongside growing interest in downstream STAT proteins and regulatory components. Some therapies have been approved, while many others remain in clinical trials (4).

JAK inhibitors (JAKi) represent an emerging class of small molecules that selectively target one or more members of the JAK family signaling pathway. This selectivity prevents STAT phosphorylation, activation, and subsequent gene transcription. Several JAK inhibitors have been developed and approved for clinical use in various IEI, immune-mediated inflammatory diseases and hematologic disorders (Table 3). While the first-generation inhibitors, which act as non-selective inhibitors, have demonstrated significant efficacy, they are associated with adverse events such as an increased risk of viral infections and hematological abnormalities. The development of second-generation molecules with selective inhibitory activity against JAKs aims to enhance safety profiles while preserving therapeutic benefits.

Table 3

Table 3. Therapeutic Strategies Targeting the JAK-STAT Pathway.

The molecular mechanism of JAK inhibitors involves their binding mode and the type of interactions with amino acids in JAKs proteins, categorized as reversible (competitive) or irreversible (covalent) (4).

5.1 First generation janus kinase inhibitors

The first approved JAKi were tofacitinib and baricitinib for the oral treatment of rheumatoid arthritis and other autoimmune disorders. Numerous JAKi are currently under preclinical and clinical investigation. The first generation JAKi (tofacitinib, baricitinib, ruxolitinib) are ATP-competitive molecules, leading to the inhibition of multiple JAK family members and, consequently, the restricted release of various cytokines and growth factor (281).

• Ruxolitinib

Ruxolitinib is a selective JAK1/2 inhibitor that blocks the ATP-binding catalytic site of these kinases, inhibiting their activation and thus the disruption of molecules and growth factors signaling pathways, reducing pro inflammatory cytokines and chemokine production.

Ruxolitinib received FDA approval for myelofibrosis in 2011, becoming the first JAK inhibitor. It was later approved for polycythemia vera in 2014 and for graft-versus-host disease in 2019. Ten years after its approval, ruxolitinib has demonstrated sustained efficacy and safety in treating polycythemia vera, especially in patients who are resistant or intolerant to hydroxyurea. Additionally, in 2021, the FDA approved ruxolitinib cream as the first topical JAKi for treating mild to moderate atopic dermatitis, which is generally considered safe even for young children. Ruxolitinib is also being explored for new therapeutic uses, particularly in alopecia areata, psoriasis, peripheral T-cell lymphoma, and relapsed diffuse large T-cell lymphoma. For the JAK/STAT gain-of-function IEI, the JAKi are increasingly recognized as promising therapeutic options. Since the first reported success of ruxolitinib in a STAT1-GOF patient in 2015, its efficacy has been documented in over 30 STAT1-GOF cases, more than 50 STAT3-GOF cases, and isolated cases of other JAK/STAT IEIs (SOCS1 haploinsufficiency, and GOF mutations in JAK1, STAT4, STAT5B, STAT6, as well as STAT1 loss of function) (282, 283).

Ruxolitinib dosing varies depending on the disease: for polycythemia vera and acute graft-versus-host disease, the starting dose is 10 mg twice daily; for myelofibrosis, it is 5–20 mg twice daily; and for acute and chronic graft-versus-host disease, it is 10 mg twice daily. Doses are adjusted during treatment based on patient tolerance and safety. The main side effects reported are hematological events, including anemia and thrombocytopenia, linked to JAK2 inhibition, which plays an important role in erythropoietin and thrombopoietin signaling. Other serious effects may include neutropenia and viral infections (284).

• Tofacitinib

Tofacitinib was the first JAK inhibitor studied and approved by the FDA for rheumatoid arthritis, demonstrating efficacy in diverse patient groups, including those unresponsive to conventional DMARDs and methotrexate-naïve patients. This therapy has also been approved for several auto inflammatory and autoimmune disorders, such as psoriatic arthritis, ulcerative colitis, and polyarticular course juvenile idiopathic arthritis (285).

Pharmacological studies showed that JAK3 and JAK1 were primarily inhibited, with weaker effects on JAK2 and TYK2, further diminishing their inflammatory effects through the greatest effect on IL-6, IFNγ, and common γc cytokines.

Tofacitinib is available as 5 mg and 10 mg dosages, as well as an 11 mg extended-release tablet for adults, while a1 mg/mL oral solution is available for children aged 2 years and older. Adverse effects include a small percentage of patients developing nasopharyngitis, headache, and increased blood creatine phosphokinase and cholesterol levels. Severe adverse effects may include viral and bacterial infections such as cytomegalovirus, Epstein Barr Virus, BK virus, tuberculosis, malignancy, lymphoproliferative disorder, and hematological abnormalities (anemia and leukopenia) (286).

• Baricitinib

This medication is FDA-approved for treating adults with moderate to severe rheumatoid arthritis who have not responded well to other DMARDs, including TNF inhibitor therapies. Additionally, clinical trials have reported that baricitinib effectively improves symptoms of severe atopic dermatitis, psoriatic arthritis, and vitiligo. The FDA granted emergency use authorization for the combination of baricitinib and remdesivir to treat severe hospitalized Covid-19 patients (287).

Baricitinib is an orally active small-molecule inhibitor of JAK1/2, preventing the phosphorylation and activation of STATs. This molecule can modulate the signaling pathways of various interleukins and growth factors (IFNγ, IL-6, IL12/23, EPO, and GM-CSF) and induces cell apoptosis. In patients with rheumatoid arthritis, baricitinib treatment significantly induced an accelerated decrease of serum inflammatory proteins.

The therapy is available in two different strengths: 2 mg and 4 mg. The recommended dosage for rheumatoid arthritis is 2 mg once-daily oral, as monotherapy or in combination. Baricitinib is generally considered a safe and well-tolerated therapy. However, some side effects including severe infections (such as upper respiratory tract infections, urinary tract infections, and herpes zoster infections) have been reported, likely due to its immunosuppressive properties. Moreover, like the other JAKi, baricitinib is associated with bone marrow suppression and hematological abnormalities, including anemia, neutropenia, and lymphopenia. Other frequently observed adverse effects include acne vulgaris and headaches (288).

5.2 Second Generation Janus Kinase Inhibitors

Second-generation JAKi, such as filgotinib, itacitinib, and upadacitinib (anti JAK1), fedratinib (anti JAK2), and deucravacitinib (anti TYK2) offer greater target specificity and may provide a lower risk for hematological abnormalities and viral infections. These molecules are generally well-tolerated, with safety and efficacy currently under investigation.

• Upadacitinib

Upadacitinib, taken at 15 mg once daily, is a JAK1 inhibitor approved to treat rheumatoid arthritis, psoriatic arthritis, atopic dermatitis and moderate-to-severe active ulcerative colitis (289).

• Filgotinib

Filgotinib, administred at 200 mg once daily, is a selective, ATP-competitive JAK1 inhibitor approved in September 2020 by the EMA and in Japan for treating moderate to severe rheumatoid arthritis in adults. It is also being evaluated for the treatment of Crohn’s disease, ulcerative colitis, and psoriatic arthritis (290).

• Fedratinib

Fedratinib is a competitive inhibitor of JAK2, BRD4, and FLT3, approved by the FDA in 2019 for treating intermediate or high-risk primary or secondary myelofibrosis (291).

• Deucravacitinib

Deucravacitinib is the first selective allosteric inhibitor targeting the TYK2 pseudokinase domain, effectively blocking IL-12, IL-23, and IFN signaling pathways. The FDA approved its use for treating patients with moderate-to-severe psoriasis (292).

5.3 Safety and monitoring strategies for JAK inhibitors

Although JAKi have demonstrated significant clinical efficacy across a range of immune-mediated disorders and hematologic malignancies, several limitations remain. Resistance to therapy can emerge through secondary mutations or compensatory signaling pathways, reducing long-term effectiveness. In addition, incomplete selectivity may lead to off-target effects, raising concerns about safety profiles. The long-term use of JAK inhibitors is also associated with potential adverse events, including malignancies and cardiovascular complications, underscoring the importance of careful monitoring.

Given the risk of hematologic, hepatic, metabolic, and infectious adverse events, patients treated with JAKi should undergo systematic laboratory monitoring before and periodically after the treatment (293, 294). Baseline assessments should include a complete blood count with differential to identify pre-existing cytopenia (anemia, neutropenia, lymphopenia), as JAKi can exacerbate these abnormalities. Also, liver enzymes (transaminases) should be checked prior to initiation due to the risk of hepatotoxicity, particularly in patients receiving concomitant hepatotoxic medications. Renal function (estimated glomerular filtration rate (eGFR)) is also recommended at baseline, as certain JAKi require dose reduction in patients with moderate to severe renal impairment. A fasting lipid profile (low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglycerides (TG)) should be evaluated, as certain JAKi are associated with increases in both LDL and HDL cholesterol, typically within the first 12 weeks of treatment initiation. Screening for latent tuberculosis is essential before starting therapy, given the increased risk of reactivation. Additional baseline infectious work-up may include hepatitis B and C serologies, and HIV testing where clinically indicated.

Follow-up monitoring (4–12 weeks after initiation, then every 3–6 months) should include repeat assessments of complete blood count, liver enzymes, lipid profile, and renal function. These evaluations should be conducted regularly throughout treatment, with increased frequency in the presence of laboratory abnormalities or clinical symptoms. Particular attention should be given to elderly patients and those with baseline organ dysfunction.

These challenges underscore the need for ongoing optimization of JAKi design, patient stratification strategies, and combination approaches to maximize therapeutic benefit while minimizing risks.

6 Translational and interdisciplinary perspectives on JAK-STAT dysregulation

Building on knowledge from JAK-STAT dysregulation in IEIs, hematologic malignancies, and therapeutic applications, it becomes important to explore their relevance in broader disease settings.

Beyond their role in driving monogenic immune disorders, insights from JAK–STAT pathway dysregulation in IEIs offer valuable perspectives on broader immune conditions including hyperinflammatory states. As outlined above, LOF mutations typically impair host defense and increase susceptibility to infections, whereas GOF mutations, particularly in STAT1 and STAT3, are linked to immune dysregulation and hyperinflammation. These clinical observations mirror the pathophysiological mechanisms underlying acquired hyperinflammatory disorders thereby supporting the potential use of JAK inhibitors (such as ruxolitinib or baricitinib) in hyperinflammatory syndromes like HLH or the cytokine storm associated with COVID-19 (295, 296). Such examples illustrate how mechanistic insights from IEIs can be applied to develop targeted therapies that extend well beyond their original scope.

Similar translational lessons emerge from oncology, where dysregulated JAK-STAT signaling, first characterized in hematologic malignancies, provides a framework for understanding and targeting solid tumors. Indeed, aberrant JAK-STAT signaling also contributes to the pathogenesis of several solid tumors (including breast, colorectal, prostate, and pancreatic cancers) by driving proliferation, survival, angiogenesis, and immune evasion (297, 298). Notably, STAT3 and STAT5 are frequently overactivated in solid tumors, acting as potent oncogenic drivers by inducing pro-survival genes (BCL-2, BCL-XL, Survivin), promoting angiogenesis, and facilitating epithelial–mesenchymal transition. In contrast, STAT1 and STAT2 often play tumor-suppressive and immunoprotective roles. In parallel, JAK1 and JAK2 hyperactivation is commonly linked to cytokine-driven signaling that sustains tumor growth, while TYK2 shows dual behavior: supporting immune surveillance in some contexts but fostering immune evasion in others. Such mechanistic insights are increasingly being translated into therapeutic strategies tailored to solid tumors. For example, the rationale for targeting the JAK/STAT3 signaling axis in colorectal and pancreatic cancers builds on its established oncogenic role in hematologic settings, while the immunomodulatory functions of STAT1-STAT2 could inspire combination approaches with immune checkpoint inhibitors in solid tumors (297, 298).

Taken together, these interdisciplinary perspectives emphasize that unraveling JAK–STAT dysregulation in one disease context can inform therapeutic innovation across others, reinforcing the pathway’s central role as both a mechanistic driver and a therapeutic target in human pathology. Beyond their current applications, the JAK–STAT axis carries broad implications for precision medicine, serving as a cross-disciplinary platform for patient stratification, risk prediction, and treatment monitoring.

7 Conclusion

Over the past two decades, our understanding of JAK/STAT dysfunction has expanded significantly, primarily through the study of inborn errors of immunity and hematologic malignancies. Mutations within this pathway, whether germline or somatic, LOF or GOF, lead to a strikingly diverse range of clinical phenotypes: from severe combined immunodeficiencies to systemic autoimmunity, severe atopy, lymphoproliferation, and hematologic cancers. These conditions underscore the pleiotropic roles of JAK/STAT components in both innate and adaptive immunity.

Advances in molecular diagnostics, notably next-generation sequencing and flow cytometry, have allowed clinicians and researchers to delineate the functional consequences of specific mutations and to guide diagnosis and therapy. In parallel, therapeutic innovation has shifted from empirical immune suppression to rational, targeted modulation of signaling pathways. The clinical deployment of JAK inhibitors has validated the therapeutic potential of intervening in this pathway, particularly in myeloproliferative neoplasms, autoimmune diseases, and interferonopathies.

This review brings a unified perspective on these complex challenges by addressing both IEIs and hematologic malignancies within a shared JAK/STAT framework, a connection that is rarely emphasized in previous reviews. In addition, the inclusion of a dedicated section on diagnostic approaches offers practical guidance for clinicians, linking molecular understanding to real-world application. By integrating the latest insights into germline and somatic mutations, updated disease classifications, and currently available therapeutic options, we also provide a timely update in a rapidly evolving field.

Nonetheless, challenges remain. The overlapping phenotypes, variable penetrance, and mosaic presentations demand improved diagnostic algorithms and international registries. Long-term safety data on JAK inhibitors and other pathway modulators are needed, especially in pediatric populations and chronic disease settings. Furthermore, while precision medicine has taken root in hematology, its expansion into immune dysregulation disorders and rare IEIs requires coordinated multidisciplinary efforts.

Looking ahead, integrative approaches combining clinical, immunologic, and genomic profiling with artificial intelligence will likely redefine how JAK/STAT-related disorders are diagnosed and managed. The emergence of gene and RNA-based therapies opens new horizons for curative interventions, while a better understanding of cytokine biology will enable more refined immunomodulation.

In conclusion, the JAK/STAT pathway exemplifies the fusion of basic immunology, clinical medicine, and translational science. By bridging these domains and highlighting both recent discoveries and practical tools for diagnosis and treatment, our review aims to support ongoing efforts to advance precision immunology and improve patient outcomes across a wide disease spectrum.

Author contributions

RD: Writing – original draft, Conceptualization, Visualization, Supervision. LLM: Writing – original draft, Investigation, Visualization. LMB: Writing – original draft, Investigation, Visualization. IA: Writing – original draft, Investigation. AHB: Writing – review & editing, Visualization. MG: Writing – review & editing. BB: Writing – original draft, Investigation.

Funding

The author(s) declare that no financial support was received for the research and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declare that no Generative AI was used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2025.1669688/full#supplementary-material

Glossary

BCP-ALL: B-cell Precursor Acute Lymphoblastic Leukemia

CCD: Coiled-Coil Domain

ChIP-seq: Chromatin Immunoprecipitation Sequencing

CMC: Chronic Mucocutaneous Candidiasis

CNV: Copy Number Variation

CRLF2: Cytokine Receptor-Like Factor 2

CSF3R: Colony-Stimulating Factor 3 Receptor

DBD: DNA-Binding Domain

DN: Dominant Negative

DNMT3A: DNA Methyltransferase 3A

ELISA: Enzyme-Linked Immunosorbent Assay

EPO: Erythropoietin

FERM: Four-point-one Ezrin Radixin Moesin

FLT3: FMS-like Tyrosine Kinase 3

GAS: Gamma-Activated Sequence

GH: Growth Hormone

GM-CSF: Granulocyte-Macrophage Colony-Stimulating Factor

HIES: Hyper IgE Syndrome

HLH: Hemophagocytic Lymphohistiocytosis

IEI: Inborn Error of Immunity

IFN: Interferon

IRF9: Interferon Regulatory Factor 9

IL: Interleukin

ISG: Interferon-Stimulated Gene

ISGF3: Interferon-Stimulated Gene Factor 3

JAK: Janus kinase

JAKi: JAK inhibitor

KMT2A: Lysine Methyltransferase 2A

KO: Knockout

LD: Linker Domain

MLNs: Mature Lymphoid Neoplasms

MPN: Myeloproliferative Neoplasm

MSMD: Mendelian Susceptibility to Mycobacterial Disease

Nmi: N-Myc interactor

NTD: N-terminal domain

PIAS: Protein Inhibitors of Activated STATs

PTP: Protein Tyrosine Phosphatase

PTPN2: Protein Tyrosine Phosphatase Non-receptor Type 2

qPCR: Quantitative PCR

RNA-seq: RNA sequencing

RT-PCR: Reverse Transcription PCR

SCID: Severe Combined Immunodeficiency

SH2: Src Homology 2

SHP1/2: Src Homology Phosphatase 1/2

shRNA: Short Hairpin RNA

siRNA: Small Interfering RNA

SMRT/N-CoR: Silencing Mediator of Retinoid and Thyroid hormone receptor/Nuclear Co-Repressor

SOCS: Suppressor of Cytokine Signaling

STAT: Signal Transducer and Activator of Transcription

T-ALL: T-cell Acute Lymphoblastic Leukemia

TC-PTP: T-cell Protein Tyrosine Phosphatase

TGP: Targeted Gene Panel

TPO: Thrombopoietin

TYK2: Tyrosine kinase 2

USP18: Ubiquitin-Specific Peptidase 18

WES: Whole Exome Sequencing

WGS: Whole Genome Sequencing;

References

1. Darnell JE. STATs and gene regulation. Science. (1997) 277:16305. doi: 10.1126/science.277.5332.1630

PubMed Abstract | Crossref Full Text | Google Scholar

2. Ihle JN. Cytokine receptor signalling. Nature. (1995) 377:5914. doi: 10.1038/377591a0

PubMed Abstract | Crossref Full Text | Google Scholar

3. O’Shea JJ, Gadina M, and Kanno Y. Cytokine signaling: birth of a pathway. J Immunol Baltim Md 1950. (2011) 187:54758. doi: 10.4049/jimmunol.1102913

PubMed Abstract | Crossref Full Text | Google Scholar

4. Hu X, Li J, Fu M, Zhao X, and Wang W. The JAK/STAT signaling pathway: from bench to clinic. Signal Transduct Target Ther. (2021) 6:402. doi: 10.1038/s41392-021-00791-1

PubMed Abstract | Crossref Full Text | Google Scholar

5. Owen KL, Brockwell NK, and Parker BS. JAK-STAT signaling: A double-edged sword of immune regulation and cancer progression. Cancers. (2019) 11:2002. doi: 10.3390/cancers11122002

PubMed Abstract | Crossref Full Text | Google Scholar

6. Morris R, Kershaw NJ, and Babon JJ. The molecular details of cytokine signaling via the JAK/STAT pathway. Protein Sci Publ Protein Soc. (2018) 27:19842009. doi: 10.1002/pro.3519

PubMed Abstract | Crossref Full Text | Google Scholar

7. Velazquez L, Fellous M, Stark GR, and Pellegrini S. A protein tyrosine kinase in the interferon alpha/beta signaling pathway. Cell. (1992) 70:31322. doi: 10.1016/0092-8674(92)90105-L

PubMed Abstract | Crossref Full Text | Google Scholar

8. Reilley MJ, McCoon P, Cook C, Lyne P, Kurzrock R, Kim Y, et al. STAT3 antisense oligonucleotide AZD9150 in a subset of patients with heavily pretreated lymphoma: results of a phase 1b trial. J Immunother Cancer. (2018) 6:119. doi: 10.1186/s40425-018-0436-5

PubMed Abstract | Crossref Full Text | Google Scholar

9. Awasthi N, Liongue C, and Ward AC. STAT proteins: a kaleidoscope of canonical and non-canonical functions in immunity and cancer. J Hematol OncolJ Hematol Oncol. (2021) 14:198. doi: 10.1186/s13045-021-01214-y

PubMed Abstract | Crossref Full Text | Google Scholar

10. Sevim Bayrak C, Stein D, Jain A, Chaudhary K, Nadkarni GN, Van Vleck TT, et al. Identification of discriminative gene-level and protein-level features associated with pathogenic gain-of-function and loss-of-function variants. Am J Hum Genet. (2021) 108:2301−18. doi: 10.1016/j.ajhg.2021.10.007

PubMed Abstract | Crossref Full Text | Google Scholar

11. Gerasimavicius L, Livesey BJ, and Marsh JA. Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure. Nat Commun. (2022) 13:3895. doi: 10.1038/s41467-022-31686-6

PubMed Abstract | Crossref Full Text | Google Scholar

12. Samra S, Bergerson JRE, Freeman AF, and Turvey SE. JAK-STAT signaling pathway, immunodeficiency, inflammation, immune dysregulation, and inborn errors of immunity. J Allergy Clin Immunol. (2025) 155:35767. doi: 10.1016/j.jaci.2024.09.020

PubMed Abstract | Crossref Full Text | Google Scholar

13. Ott N, Faletti L, Heeg M, Andreani V, and Grimbacher B. JAKs and STATs from a clinical perspective: loss-of-function mutations, gain-of-function mutations, and their multidimensional consequences. J Clin Immunol. (2023) 43:132659. doi: 10.1007/s10875-023-01483-x

PubMed Abstract | Crossref Full Text | Google Scholar

14. Bousfiha AA, Jeddane L, Moundir A, Poli MC, Aksentijevich I, Cunningham-Rundles C, et al. The 2024 update of IUIS phenotypic classification of human inborn errors of immunity. J Hum Immun. (2025) 1(1):e20250002. doi: 10.70962/jhi.20250002

PubMed Abstract | Crossref Full Text | Google Scholar

15. Villarino AV, Kanno Y, and O’Shea JJ. Mechanisms of Jak/STAT signaling in immunity and disease. J Immunol Baltim Md 1950. (2015) 194:217. doi: 10.4049/jimmunol.1401867

PubMed Abstract | Crossref Full Text | Google Scholar

16. Kralovics R, Passamonti F, Buser AS, Teo SS, Tiedt R, Passweg JR, et al. A gain-of-function mutation of JAK2 in myeloproliferative disorders. N Engl J Med. (2005) 352:177990. doi: 10.1056/NEJMoa051113

PubMed Abstract | Crossref Full Text | Google Scholar

17. Silva A, Almeida ARM, Cachucho A, Neto JL, Demeyer S, de Matos M, et al. Overexpression of wild-type IL-7Rα promotes T-cell acute lymphoblastic leukemia/lymphoma. Blood. (2021) 138:104052. doi: 10.1182/blood.2019000553

PubMed Abstract | Crossref Full Text | Google Scholar

18. Bellani V, Mora B, Iurlo A, and Passamonti F. CALR-mutated myeloproliferative neoplasms. Leuk Lymphoma. (2025) 66(7):1198–210. doi: 10.1080/10428194.2025.2465551

PubMed Abstract | Crossref Full Text | Google Scholar

19. Liang D, Wang Q, Zhang W, Tang H, Song C, Yan Z, et al. JAK/STAT in leukemia: a clinical update. Mol Cancer. (2024) 23:25. doi: 10.1186/s12943-023-01929-1

PubMed Abstract | Crossref Full Text | Google Scholar

20. Luo Y, Alexander M, Gadina M, O’Shea JJ, Meylan F, and Schwartz DM. JAK-STAT signaling in human disease: From genetic syndromes to clinical inhibition. J Allergy Clin Immunol. (2021) 148:91125. doi: 10.1016/j.jaci.2021.08.004

PubMed Abstract | Crossref Full Text | Google Scholar

21. Ghoreschi K, Laurence A, and O’Shea JJ. Janus kinases in immune cell signaling. Immunol Rev. (2009) 228:27387. doi: 10.1111/j.1600-065X.2008.00754.x

PubMed Abstract | Crossref Full Text | Google Scholar

22. Ihle JN, Witthuhn BA, Quelle FW, Yamamoto K, and Silvennoinen O. Signaling through the hematopoietic cytokine receptors. Annu Rev Immunol. (1995) 13:36998. doi: 10.1146/annurev.iy.13.040195.002101

PubMed Abstract | Crossref Full Text | Google Scholar

23. Kawamura M, McVicar DW, Johnston JA, Blake TB, Chen YQ, Lal BK, et al. Molecular cloning of L-JAK, a Janus family protein-tyrosine kinase expressed in natural killer cells and activated leukocytes. Proc Natl Acad Sci U.S.A. (1994) 91:63748. doi: 10.1073/pnas.91.14.6374

PubMed Abstract | Crossref Full Text | Google Scholar

24. Ross JA, Nagy ZS, Cheng H, Stepkowski SM, and Kirken RA. Regulation of T cell homeostasis by JAKs and STATs. Arch Immunol Ther Exp (Warsz). (2007) 55:23145. doi: 10.1007/s00005-007-0030-x

PubMed Abstract | Crossref Full Text | Google Scholar

25. Musso T, Johnston JA, Linnekin D, Varesio L, Rowe TK, O’Shea JJ, et al. Regulation of JAK3 expression in human monocytes: phosphorylation in response to interleukins 2, 4, and 7. J Exp Med. (1995) 181:142531. doi: 10.1084/jem.181.4.1425

PubMed Abstract | Crossref Full Text | Google Scholar

26. Zhou YJ, Hanson EP, Chen YQ, Magnuson K, Chen M, Swann PG, et al. Distinct tyrosine phosphorylation sites in JAK3 kinase domain positively and negatively regulate its enzymatic activity. Proc Natl Acad Sci. (1997) 94:138505. doi: 10.1073/pnas.94.25.13850

PubMed Abstract | Crossref Full Text | Google Scholar

27. Feng J, Witthuhn BA, Matsuda T, Kohlhuber F, Kerr IM, and Ihle JN. Activation of Jak2 catalytic activity requires phosphorylation of Y1007 in the kinase activation loop. Mol Cell Biol. (1997) 17:2497501. doi: 10.1128/MCB.17.5.2497

PubMed Abstract | Crossref Full Text | Google Scholar

28. Gauzzi MC, Velazquez L, McKendry R, Mogensen KE, Fellous M, and Pellegrini S. Interferon-alpha-dependent activation of Tyk2 requires phosphorylation of positive regulatory tyrosines by another kinase. J Biol Chem. (1996) 271:20494500. doi: 10.1074/jbc.271.34.20494

PubMed Abstract | Crossref Full Text | Google Scholar

29. Wang R, Griffin PR, Small EC, and Thompson JE. Mechanism of Janus kinase 3-catalyzed phosphorylation of a Janus kinase 1 activation loop peptide. Arch Biochem Biophys. (2003) 410:715. doi: 10.1016/S0003-9861(02)00637-9

PubMed Abstract | Crossref Full Text | Google Scholar

30. Cheng H, Ross JA, Frost JA, and Kirken RA. Phosphorylation of human Jak3 at tyrosines 904 and 939 positively regulates its activity. Mol Cell Biol. (2008) 28:227182. doi: 10.1128/MCB.01789-07

PubMed Abstract | Crossref Full Text | Google Scholar

31. Argetsinger LS, Stuckey JA, Robertson SA, Koleva RI, Cline JM, Marto JA, et al. Tyrosines 868, 966, and 972 in the kinase domain of JAK2 are autophosphorylated and required for maximal JAK2 kinase activity. Mol Endocrinol. (2010) 24:106276. doi: 10.1210/me.2009-0355

PubMed Abstract | Crossref Full Text | Google Scholar

32. Funakoshi-Tago M, Tago K, Kasahara T, Parganas E, and Ihle JN. Negative regulation of Jak2 by its auto-phosphorylation at tyrosine 913 via the Epo signaling pathway. Cell Signal. (2008) 20:19952001. doi: 10.1016/j.cellsig.2008.07.008

PubMed Abstract | Crossref Full Text | Google Scholar

33. Li Z, Zhou Y, Carter-Su C, Myers MG, and Rui L. SH2B1 enhances leptin signaling by both janus kinase 2 tyr813 phosphorylation-dependent and -independent mechanisms. Mol Endocrinol. (2007) 21:227081. doi: 10.1210/me.2007-0111

PubMed Abstract | Crossref Full Text | Google Scholar

34. Kurzer JH, Argetsinger LS, Zhou YJ, Kouadio JLK, O’Shea JJ, and Carter-Su C. Tyrosine 813 is a site of JAK2 autophosphorylation critical for activation of JAK2 by SH2-B beta. Mol Cell Biol. (2004) 24:455770. doi: 10.1128/MCB.24.10.4557-4570.2004

PubMed Abstract | Crossref Full Text | Google Scholar

35. Robertson SA, Koleva RI, Argetsinger LS, Carter-Su C, Marto JA, Feener EP, et al. Regulation of jak2 function by phosphorylation of tyr₃₁₇ and tyr₆₃₇ during cytokine signaling. Mol Cell Biol. (2009) 29:336778. doi: 10.1128/MCB.00278-09

PubMed Abstract | Crossref Full Text | Google Scholar

36. Mazurkiewicz-Munoz AM, Argetsinger LS, Kouadio JLK, Stensballe A, Jensen ON, Cline JM, et al. Phosphorylation of JAK2 at serine 523: a negative regulator of JAK2 that is stimulated by growthHormone and epidermal growth factor. Mol Cell Biol. (2006) 26:405262. doi: 10.1128/MCB.01591-05

PubMed Abstract | Crossref Full Text | Google Scholar

37. Ross JA, Cheng H, Nagy ZS, Frost JA, and Kirken RA. Protein phosphatase 2A regulates interleukin-2 receptor complex formation and JAK3/STAT5 activation. J Biol Chem. (2010) 285:358291. doi: 10.1074/jbc.M109.053843

PubMed Abstract | Crossref Full Text | Google Scholar

38. Zhou YJ, Chen M, Cusack NA, Kimmel LH, Magnuson KS, Boyd JG, et al. Unexpected effects of FERM domain mutations on catalytic activity of Jak3: structural implication for Janus kinases. Mol Cell. (2001) 8:95969. doi: 10.1016/S1097-2765(01)00398-7

PubMed Abstract | Crossref Full Text | Google Scholar

39. Cacalano NA, Migone TS, Bazan F, Hanson EP, Chen M, Candotti F, et al. Autosomal SCID caused by a point mutation in the N-terminus of Jak3: mapping of the Jak3-receptor interaction domain. EMBO J. (1999) 18:154958. doi: 10.1093/emboj/18.6.1549

PubMed Abstract | Crossref Full Text | Google Scholar

40. Funakoshi-Tago M, Pelletier S, Matsuda T, Parganas E, and Ihle JN. Receptor specific downregulation of cytokine signaling by autophosphorylation in the FERM domain of Jak2. EMBO J. (2006) 25:476372. doi: 10.1038/sj.emboj.7601365

PubMed Abstract | Crossref Full Text | Google Scholar

41. Sayyah J, Gnanasambandan K, Kamarajugadda S, Tsuda S, Caldwell-Busby J, and Sayeski PP. Phosphorylation of Y372 is critical for Jak2 tyrosine kinase activation. Cell Signal. (2011) 23:180615. doi: 10.1016/j.cellsig.2011.06.015

PubMed Abstract | Crossref Full Text | Google Scholar

42. Copeland NG, Gilbert DJ, Schindler C, Zhong Z, Wen Z, Darnell JE, et al. Distribution of the mammalian Stat gene family in mouse chromosomes. Genomics. (1995) 29:2258. doi: 10.1006/geno.1995.1235

PubMed Abstract | Crossref Full Text | Google Scholar

43. Heim MH. The STAT protein family. In: Sehgal PB, Levy DE, and Hirano T, editors. Signal transducers and activators of transcription (STATs): activation and biology. Springer Netherlands, Dordrecht (2003). p. 1126. doi: 10.1007/978-94-017-3000-6_2

Crossref Full Text | Google Scholar

44. Kisseleva T, Bhattacharya S, Braunstein J, and Schindler CW. Signaling through the JAK/STAT pathway, recent advances and future challenges. Gene. (2002) 285:124. doi: 10.1016/S0378-1119(02)00398-0

PubMed Abstract | Crossref Full Text | Google Scholar

45. Lim CP and Cao X. Structure, function, and regulation of STAT proteins. Mol Biosyst. (2006) 2:53650. doi: 10.1039/b606246f

PubMed Abstract | Crossref Full Text | Google Scholar

46. Vinkemeier U, Moarefi I, Darnell JE, and Kuriyan J. Structure of the amino-terminal protein interaction domain of STAT-4. Science. (1998) 279:104852. doi: 10.1126/science.279.5353.1048

PubMed Abstract | Crossref Full Text | Google Scholar

47. Strehlow I and Schindler C. Amino-terminal signal transducer and activator of transcription (STAT) domains regulate nuclear translocation and STAT deactivation. J Biol Chem. (1998) 273:2804956. doi: 10.1074/jbc.273.43.28049

PubMed Abstract | Crossref Full Text | Google Scholar

48. Brown S, Hu N, and Hombría JCG. Novel level of signalling control in the JAK/STAT pathway revealed by in situ visualisation of protein-protein interaction during Drosophila development. Dev Camb Engl. (2003) 130:307784. doi: 10.1242/dev.00535

PubMed Abstract | Crossref Full Text | Google Scholar

49. Nakajima H, Brindle PK, Handa M, and Ihle JN. Functional interaction of STAT5 and nuclear receptor co-repressor SMRT: implications in negative regulation of STAT5-dependent transcription. EMBO J. (2001) 20:683644. doi: 10.1093/emboj/20.23.6836

PubMed Abstract | Crossref Full Text | Google Scholar

50. Zhu M, John S, Berg M, and Leonard WJ. Functional association of Nmi with Stat5 and Stat1 in IL-2- and IFNgamma-mediated signaling. Cell. (1999) 96:12130. doi: 10.1016/S0092-8674(00)80965-4

PubMed Abstract | Crossref Full Text | Google Scholar

51. Levy DE and Darnell JE. Stats: transcriptional control and biological impact. Nat Rev Mol Cell Biol. (2002) 3:65162. doi: 10.1038/nrm909

PubMed Abstract | Crossref Full Text | Google Scholar

52. Horvath CM, Wen Z, and Darnell JE. A STAT protein domain that determines DNA sequence recognition suggests a novel DNA-binding domain. Genes Dev. (1995) 9:98494. doi: 10.1101/gad.9.8.984

PubMed Abstract | Crossref Full Text | Google Scholar

53. Decker T, Kovarik P, and Meinke A. GAS elements: a few nucleotides with a major impact on cytokine-induced gene expression. J Interferon Cytokine Res Off J Int Soc Interferon Cytokine Res. (1997) 17:12134. doi: 10.1089/jir.1997.17.121

PubMed Abstract | Crossref Full Text | Google Scholar

54. Yang E, Wen Z, Haspel RL, Zhang JJ, and Darnell JE. The linker domain of stat1 is required for gamma interferon-driven transcription. Mol Cell Biol. (1999) 19:510612. doi: 10.1128/MCB.19.7.5106

PubMed Abstract | Crossref Full Text | Google Scholar

55. Kretzschmar AK, Dinger MC, Henze C, Brocke-Heidrich K, and Horn F. Analysis of Stat3 (signal transducer and activator of transcription 3) dimerization by fluorescence resonance energy transfer in living cells. Biochem J. (2004) 377:28997. doi: 10.1042/bj20030708

PubMed Abstract | Crossref Full Text | Google Scholar

56. Zhang HX, Yang PL, Li EM, and Xu LY. STAT3beta, a distinct isoform from STAT3. Int J Biochem Cell Biol. (2019) 110:1309. doi: 10.1016/j.biocel.2019.02.006

PubMed Abstract | Crossref Full Text | Google Scholar

57. Endo TA, Masuhara M, Yokouchi M, Suzuki R, Sakamoto H, Mitsui K, et al. A new protein containing an SH2 domain that inhibits JAK kinases. Nature. (1997) 387:9214. doi: 10.1038/43213

PubMed Abstract | Crossref Full Text | Google Scholar

58. Arimoto KI, Löchte S, Stoner SA, Burkart C, Zhang Y, Miyauchi S, et al. STAT2 is an essential adaptor in USP18-mediated suppression of type I interferon signaling. Nat Struct Mol Biol. (2017) 24:27989. doi: 10.1038/nsmb.3378

PubMed Abstract | Crossref Full Text | Google Scholar

59. Yoshimura A and Yasukawa H. JAK’s SOCS: a mechanism of inhibition. Immunity. (2012) 36:1579. doi: 10.1016/j.immuni.2012.01.010

PubMed Abstract | Crossref Full Text | Google Scholar

60. Xue C, Yao Q, Gu X, Shi Q, Yuan X, Chu Q, et al. Evolving cognition of the JAK-STAT signaling pathway: autoimmune disorders and cancer. Signal Transduct Target Ther. (2023) 8:204. doi: 10.1038/s41392-023-01468-7

PubMed Abstract | Crossref Full Text | Google Scholar

61. Seif F, Khoshmirsafa M, Aazami H, Mohsenzadegan M, Sedighi G, and Bahar M. The role of JAK-STAT signaling pathway and its regulators in the fate of T helper cells. Cell Commun Signal. (2017) 15:23. doi: 10.1186/s12964-017-0177-y

PubMed Abstract | Crossref Full Text | Google Scholar

62. Poli MC, Aksentijevich I, Bousfiha AA, Cunningham-Rundles C, Hambleton S, Klein C, et al. Human inborn errors of immunity: 2024 update on the classification from the International Union of Immunological Societies Expert Committee. J Hum Immun. (2025) 1:e20250003. doi: 10.70962/jhi.20250003

PubMed Abstract | Crossref Full Text | Google Scholar

63. Macchi P, Villa A, Giliani S, Sacco MG, Frattini A, Porta F, et al. Mutations of Jak-3 gene in patients with autosomal severe combined immune deficiency (SCID). Nature. (1995) 377:658. doi: 10.1038/377065a0

PubMed Abstract | Crossref Full Text | Google Scholar

64. Russell SM, Tayebi N, Nakajima H, Riedy MC, Roberts JL, Aman MJ, et al. Mutation of Jak3 in a patient with SCID: essential role of Jak3 in lymphoid development. Science. (1995) 270:797800. doi: 10.1126/science.270.5237.797

PubMed Abstract | Crossref Full Text | Google Scholar

65. Lv Y, Qi J, Babon JJ, Cao L, Fan G, Lang J, et al. The JAK-STAT pathway: from structural biology to cytokine engineering. Signal Transduct Target Ther. (2024) 9:221. doi: 10.1038/s41392-024-01934-w

PubMed Abstract | Crossref Full Text | Google Scholar

66. Lee PPW, Chan KW, Chen TX, Jiang LP, Wang XC, Zeng HS, et al. Molecular diagnosis of severe combined immunodeficiency–identification of IL2RG, JAK3, IL7R, DCLRE1C, RAG1, and RAG2 mutations in a cohort of Chinese and Southeast Asian children. J Clin Immunol. (2011) 31:28196. doi: 10.1007/s10875-010-9489-z

PubMed Abstract | Crossref Full Text | Google Scholar

67. Michos A, Tzanoudaki M, Villa A, Giliani S, Chrousos G, and Kanariou M. Severe combined immunodeficiency in Greek children over a 20-year period: rarity of γc-chain deficiency (X-linked) type. J Clin Immunol. (2011) 31:77883. doi: 10.1007/s10875-011-9564-0

PubMed Abstract | Crossref Full Text | Google Scholar

68. Pasic S, Vujic D, Veljković D, Slavkovic B, Mostarica-Stojkovic M, Minic P, et al. Severe combined immunodeficiency in Serbia and Montenegro between years 1986 and 2010: a single-center experience. J Clin Immunol. (2014) 34:3048. doi: 10.1007/s10875-014-9991-9

PubMed Abstract | Crossref Full Text | Google Scholar

69. Abolhassani H, Chou J, Bainter W, Platt CD, Tavassoli M, Momen T, et al. Clinical, immunologic, and genetic spectrum of 696 patients with combined immunodeficiency. J Allergy Clin Immunol. (2018) 141:14508. doi: 10.1016/j.jaci.2017.06.049

PubMed Abstract | Crossref Full Text | Google Scholar

70. Haddad E, Logan BR, Griffith LM, Buckley RH, Parrott RE, Prockop SE, et al. SCID genotype and 6-month posttransplant CD4 count predict survival and immune recovery. Blood. (2018) 132:173749. doi: 10.1182/blood-2018-03-840702

PubMed Abstract | Crossref Full Text | Google Scholar

71. Aluri J, Desai M, Gupta M, Dalvi A, Terance A, Rosenzweig SD, et al. Clinical, immunological, and molecular findings in 57 patients with severe combined immunodeficiency (SCID) from India. Front Immunol. (2019) 10:23. doi: 10.3389/fimmu.2019.00023

PubMed Abstract | Crossref Full Text | Google Scholar

72. Ikinciogullari A, Cagdas D, Dogu F, Tugrul T, Karasu G, Haskologlu S, et al. Clinical features and HSCT outcome for SCID in Turkey. J Clin Immunol. (2019) 39:31623. doi: 10.1007/s10875-019-00610-x

PubMed Abstract | Crossref Full Text | Google Scholar

73. Vignesh P, Rawat A, Kumrah R, Singh A, Gummadi A, Sharma M, et al. Clinical, immunological, and molecular features of severe combined immune deficiency: A multi-institutional experience from India. Front Immunol. (2020) 11:619146. doi: 10.3389/fimmu.2020.619146

PubMed Abstract | Crossref Full Text | Google Scholar

74. Aykut A, Durmaz A, Karaca N, Gulez N, Genel F, Celmeli F, et al. Severe combined immunodeficiencies: Expanding the mutation spectrum in Turkey and identification of 12 novel variants. Scand J Immunol. (2022) 95:e13163. doi: 10.1111/sji.13163

PubMed Abstract | Crossref Full Text | Google Scholar

75. Cattaneo F, Recher M, Masneri S, Baxi SN, Fiorini C, Antonelli F, et al. Hypomorphic Janus kinase 3 mutations result in a spectrum of immune defects, including partial maternal T-cell engraftment. J Allergy Clin Immunol. (2013) 131:113645. doi: 10.1016/j.jaci.2012.12.667

PubMed Abstract | Crossref Full Text | Google Scholar

76. Abolhassani H, Cheraghi T, Rezaei N, Aghamohammadi A, and Hammarström L. Common variable immunodeficiency or late-onset combined immunodeficiency: A new hypomorphic JAK3 patient and review of the literature. J Investig Allergol Clin Immunol. (2015) 25:21820.

Google Scholar

77. Davis SD, Schaller J, and Wedgwood RJ. Job’s Syndrome. Recurrent, « cold », staphylococcal abscesses. Lancet Lond Engl. (1966) 1:10135. doi: 10.1016/s0140-6736(66)90119-x

PubMed Abstract | Crossref Full Text | Google Scholar

78. Chandesris MO, Melki I, Natividad A, Puel A, Fieschi C, Yun L, et al. Autosomal dominant STAT3 deficiency and hyper-IgE syndrome: molecular, cellular, and clinical features from a French national survey. Med (Baltimore). (2012) 91:e119. doi: 10.1097/MD.0b013e31825f95b9

PubMed Abstract | Crossref Full Text | Google Scholar

79. Kane A, Deenick EK, Ma CS, Cook MC, Uzel G, and Tangye SG. STAT3 is a central regulator of lymphocyte differentiation and function. Curr Opin Immunol. (2014) 28:4957. doi: 10.1016/j.coi.2014.01.015

PubMed Abstract | Crossref Full Text | Google Scholar

80. Park B and Liu GY. Staphylococcus aureus and hyper-igE syndrome. Int J Mol Sci. (2020) 21:9152. doi: 10.3390/ijms21239152

PubMed Abstract | Crossref Full Text | Google Scholar

81. Conti HR, Baker O, Freeman AF, Jang WS, Holland SM, Li RA, et al. New mechanism of oral immunity to mucosal candidiasis in hyper-IgE syndrome. Mucosal Immunol. (2011) 4:44855. doi: 10.1038/mi.2011.5

PubMed Abstract | Crossref Full Text | Google Scholar

82. Vinh DC, Sugui JA, Hsu AP, Freeman AF, and Holland SM. Invasive fungal disease in autosomal-dominant hyper-IgE syndrome. J Allergy Clin Immunol. (2010) 125:138990. doi: 10.1016/j.jaci.2010.01.047

PubMed Abstract | Crossref Full Text | Google Scholar

83. Duréault A, Tcherakian C, Poiree S, Catherinot E, Danion F, Jouvion G, et al. Spectrum of pulmonary aspergillosis in hyper-igE syndrome with autosomal-dominant STAT3 deficiency. J Allergy Clin Immunol Pract. (2019) 7:1986–1995.e3. doi: 10.1016/j.jaip.2019.02.041

PubMed Abstract | Crossref Full Text | Google Scholar

84. Ma CS, Chew GYJ, Simpson N, Priyadarshi A, Wong M, Grimbacher B, et al. Deficiency of Th17 cells in hyper IgE syndrome due to mutations in STAT3. J Exp Med. (2008) 205:15517. doi: 10.1084/jem.20080218

PubMed Abstract | Crossref Full Text | Google Scholar

85. Suratannon N, Ittiwut C, Dik WA, Ittiwut R, Meesilpavikkai K, Israsena N, et al. A germline STAT6 gain-of-function variant is associated with early-onset allergies. J Allergy Clin Immunol. (2023) 151:565–571.e9. doi: 10.1016/j.jaci.2022.09.028

PubMed Abstract | Crossref Full Text | Google Scholar

86. Takeuchi I, Yanagi K, Takada S, Uchiyama T, Igarashi A, Motomura K, et al. STAT6 gain-of-function variant exacerbates multiple allergic symptoms. J Allergy Clin Immunol. (2023) 151:1402–1409.e6. doi: 10.1016/j.jaci.2022.12.802

PubMed Abstract | Crossref Full Text | Google Scholar

87. Sharma M, Leung D, Momenilandi M, Jones LCW, Pacillo L, James AE, et al. Human germline heterozygous gain-of-function STAT6 variants cause severe allergic disease. J Exp Med. (2023) 220:e20221755. doi: 10.1016/j.clim.2023.109364

Crossref Full Text | Google Scholar

88. Baris S, Benamar M, Chen Q, Catak MC, Martínez-Blanco M, Wang M, et al. Severe allergic dysregulation due to a gain of function mutation in the transcription factor STAT6. J Allergy Clin Immunol. (2023) 152:182–194.e7. doi: 10.1016/j.jaci.2023.01.023

PubMed Abstract | Crossref Full Text | Google Scholar

89. Minskaia E, Maimaris J, Jenkins P, Albuquerque AS, Hong Y, Eleftheriou D, et al. Autosomal dominant STAT6 gain of function causes severe atopy associated with lymphoma. J Clin Immunol. (2023) 43:161122. doi: 10.1007/s10875-023-01530-7

PubMed Abstract | Crossref Full Text | Google Scholar

90. Kofoed EM, Hwa V, Little B, Woods KA, Buckway CK, Tsubaki J, et al. Growth hormone insensitivity associated with a STAT5b mutation. N Engl J Med. (2003) 349:113947. doi: 10.1056/NEJMoa022926

PubMed Abstract | Crossref Full Text | Google Scholar

91. Hwa V, Little B, Adiyaman P, Kofoed EM, Pratt KL, Ocal G, et al. Severe growth hormone insensitivity resulting from total absence of signal transducer and activator of transcription 5b. J Clin Endocrinol Metab. (2005) 90:42606. doi: 10.1210/jc.2005-0515

PubMed Abstract | Crossref Full Text | Google Scholar

92. Vidarsdottir S, Walenkamp MJE, Pereira AM, Karperien M, van Doorn J, van Duyvenvoorde HA, et al. Clinical and biochemical characteristics of a male patient with a novel homozygous STAT5b mutation. J Clin Endocrinol Metab. (2006) 91:34825. doi: 10.1210/jc.2006-0368

PubMed Abstract | Crossref Full Text | Google Scholar

93. Bernasconi A, Marino R, Ribas A, Rossi J, Ciaccio M, Oleastro M, et al. Characterization of immunodeficiency in a patient with growth hormone insensitivity secondary to a novel STAT5b gene mutation. Pediatrics. (2006) 118:e1584–1592. doi: 10.1542/peds.2005-2882

PubMed Abstract | Crossref Full Text | Google Scholar

94. Hwa V, Camacho-Hübner C, Little BM, David A, Metherell LA, El-Khatib N, et al. Growth hormone insensitivity and severe short stature in siblings: a novel mutation at the exon 13-intron 13 junction of the STAT5b gene. Horm Res. (2007) 68:21824. doi: 10.1159/000101334

PubMed Abstract | Crossref Full Text | Google Scholar

95. Pugliese-Pires PN, Tonelli CA, Dora JM, Silva PCA, Czepielewski M, Simoni G, et al. A novel STAT5B mutation causing GH insensitivity syndrome associated with hyperprolactinemia and immune dysfunction in two male siblings. Eur J Endocrinol. (2010) 163:34955. doi: 10.1530/EJE-10-0272

PubMed Abstract | Crossref Full Text | Google Scholar

96. Scaglia PA, Martínez AS, Feigerlová E, Bezrodnik L, Gaillard MI, Di Giovanni D, et al. A novel missense mutation in the SH2 domain of the STAT5B gene results in a transcriptionally inactive STAT5b associated with severe IGF-I deficiency, immune dysfunction, and lack of pulmonary disease. J Clin Endocrinol Metab. (2012) 97:E830–839. doi: 10.1210/jc.2011-2554

PubMed Abstract | Crossref Full Text | Google Scholar

97. Acres MJ, Gothe F, Grainger A, Skelton AJ, Swan DJ, Willet JDP, et al. Signal transducer and activator of transcription 5B deficiency due to a novel missense mutation in the coiled-coil domain. J Allergy Clin Immunol. (2019) 143:413–416.e4. doi: 10.1016/j.jaci.2018.08.032

PubMed Abstract | Crossref Full Text | Google Scholar

98. Catli G, Gao W, Foley C, Özyilmaz B, Edeer N, Diniz G, et al. Atypical STAT5B deficiency, severe short stature and mild immunodeficiency associated with a novel homozygous STAT5B Variant. Mol Cell Endocrinol. (2023) 559:111799. doi: 10.1016/j.mce.2022.111799

PubMed Abstract | Crossref Full Text | Google Scholar

99. Smith MR, Satter LRF, and Vargas-Hernández A. STAT5b: A master regulator of key biological pathways. Front Immunol. (2022) 13:1025373. doi: 10.3389/fimmu.2022.1025373

PubMed Abstract | Crossref Full Text | Google Scholar

100. Yao Z, Kanno Y, Kerenyi M, Stephens G, Durant L, Watford WT, et al. Nonredundant roles for Stat5a/b in directly regulating Foxp3. Blood. (2007) 109:436875. doi: 10.1182/blood-2006-11-055756

PubMed Abstract | Crossref Full Text | Google Scholar

101. Kanai T, Jenks J, and Nadeau KC. The STAT5b pathway defect and autoimmunity. Front Immunol. (2012) 3:234. doi: 10.3389/fimmu.2012.00234

PubMed Abstract | Crossref Full Text | Google Scholar

102. Klammt J, Neumann D, Gevers EF, Andrew SF, Schwartz ID, Rockstroh D, et al. Dominant-negative STAT5B mutations cause growth hormone insensitivity with short stature and mild immune dysregulation. Nat Commun. (2018) 9:2105. doi: 10.1038/s41467-018-04521-0

PubMed Abstract | Crossref Full Text | Google Scholar

103. Fabre A, Marchal S, Barlogis V, Mari B, Barbry P, Rohrlich PS, et al. Clinical aspects of STAT3 gain-of-function germline mutations: A systematic review. J Allergy Clin Immunol Pract. (2019) 7:1958–1969.e9. doi: 10.1016/j.jaip.2019.02.018

PubMed Abstract | Crossref Full Text | Google Scholar

104. Faletti L, Ehl S, and Heeg M. Germline STAT3 gain-of-function mutations in primary immunodeficiency: Impact on the cellular and clinical phenotype. BioMed J. (2021) 44:41221. doi: 10.1016/j.bj.2021.03.003

PubMed Abstract | Crossref Full Text | Google Scholar

105. Milner JD, Vogel TP, Forbes L, Ma CA, Stray-Pedersen A, Niemela JE, et al. Early-onset lymphoproliferation and autoimmunity caused by germline STAT3 gain-of-function mutations. Blood. (2015) 125:5919. doi: 10.1182/blood-2014-09-602763

PubMed Abstract | Crossref Full Text | Google Scholar

106. Gutiérrez M, Scaglia P, Keselman A, Martucci L, Karabatas L, Domené S, et al. Partial growth hormone insensitivity and dysregulatory immune disease associated with de novo germline activating STAT3 mutations. Mol Cell Endocrinol. (2018) 473:16677. doi: 10.1016/j.mce.2018.01.016

PubMed Abstract | Crossref Full Text | Google Scholar

107. Mauracher AA, Eekels JJM, Woytschak J, van Drogen A, Bosch A, Prader S, et al. Erythropoiesis defect observed in STAT3 GOF patients with severe anemia. J Allergy Clin Immunol. (2020) 145:1297301. doi: 10.1016/j.jaci.2019.11.042

PubMed Abstract | Crossref Full Text | Google Scholar

108. Del Bel KL, Ragotte RJ, Saferali A, Lee S, Vercauteren SM, Mostafavi SA, et al. JAK1 gain-of-function causes an autosomal dominant immune dysregulatory and hypereosinophilic syndrome. J Allergy Clin Immunol. (2017) 139:2016–2020.e5. doi: 10.1016/j.jaci.2016.12.957

PubMed Abstract | Crossref Full Text | Google Scholar

109. Takeichi T, Lee JYW, Okuno Y, Miyasaka Y, Murase Y, Yoshikawa T, et al. Autoinflammatory keratinization disease with hepatitis and autism reveals roles for JAK1 kinase hyperactivity in autoinflammation. Front Immunol. (2021) 12:737747. doi: 10.3389/fimmu.2021.737747

PubMed Abstract | Crossref Full Text | Google Scholar

110. Fayand A, Hentgen V, Posseme C, Lacout C, Picard C, Moguelet P, et al. Successful treatment of JAK1-associated inflammatory disease. J Allergy Clin Immunol. (2023) 152:97283. doi: 10.1016/j.jaci.2023.06.004

PubMed Abstract | Crossref Full Text | Google Scholar

111. Horesh ME, Martin-Fernandez M, Gruber C, Buta S, Le Voyer T, Puzenat E, et al. Individuals with JAK1 variants are affected by syndromic features encompassing autoimmunity, atopy, colitis, and dermatitis. J Exp Med. (2024) 221:e20232387. doi: 10.1084/jem.20232387

PubMed Abstract | Crossref Full Text | Google Scholar

112. Thaventhiran JED, Lango Allen H, Burren OS, Rae W, Greene D, Staples E, et al. Whole-genome sequencing of a sporadic primary immunodeficiency cohort. Nature. (2020) 583:905. doi: 10.1038/s41586-020-2265-1

PubMed Abstract | Crossref Full Text | Google Scholar

113. Hadjadj J, Castro CN, Tusseau M, Stolzenberg MC, Mazerolles F, Aladjidi N, et al. Early-onset autoimmunity associated with SOCS1 haploinsufficiency. Nat Commun. (2020) 11:5341. doi: 10.1038/s41467-020-18925-4

PubMed Abstract | Crossref Full Text | Google Scholar

114. Lee PY, Platt CD, Weeks S, Grace RF, Maher G, Gauthier K, et al. Immune dysregulation and multisystem inflammatory syndrome in children (MIS-C) in individuals with haploinsufficiency of SOCS1. J Allergy Clin Immunol. (2020) 146:1194–1200.e1. doi: 10.1016/j.jaci.2020.07.033

PubMed Abstract | Crossref Full Text | Google Scholar

115. Hadjadj J, Wolfers A, Borisov O, Hazard D, Leahy R, Jeanpierre M, et al. Clinical manifestations, disease penetrance, and treatment in individuals with SOCS1 insufficiency: a registry-based and population-based study. Lancet Rheumatol. (2025) 7:e391402. doi: 10.1016/S2665-9913(24)00348-5

PubMed Abstract | Crossref Full Text | Google Scholar

116. Parlato M, Nian Q, Charbit-Henrion F, Ruemmele FM, Rodrigues-Lima F, Cerf-Bensussan N, et al. Loss-of-function mutation in PTPN2 causes aberrant activation of JAK signaling via STAT and very early onset intestinal inflammation. Gastroenterology. (2020) 159:1968–1971.e4. doi: 10.1053/j.gastro.2020.07.040

PubMed Abstract | Crossref Full Text | Google Scholar

117. Awwad J, Souaid M, Yammine T, Chebly A, Salem N, Esber R, et al. A homozygous missense variant in PTPN2 with early-onset Crohn’s disease, growth failure and dysmorphic features in an infant: a case report. J Genet. (2023) 102:37. doi: 10.1007/s12041-023-01433-x

PubMed Abstract | Crossref Full Text | Google Scholar

118. Jeanpierre M, Cognard J, Tusseau M, Riller Q, Bui LC, Berthelet J, et al. Haploinsufficiency in PTPN2 leads to early-onset systemic autoimmunity from Evans syndrome to lupus. J Exp Med. (2024) 221:e20232337. doi: 10.1084/jem.20232337

PubMed Abstract | Crossref Full Text | Google Scholar

119. Dupuis S, Dargemont C, Fieschi C, Thomassin N, Rosenzweig S, Harris J, et al. Impairment of mycobacterial but not viral immunity by a germline human STAT1 mutation. Science. (2001) 293:3003. doi: 10.1126/science.1061154

PubMed Abstract | Crossref Full Text | Google Scholar

120. Chapgier A, Boisson-Dupuis S, Jouanguy E, Vogt G, Feinberg J, Prochnicka-Chalufour A, et al. Novel STAT1 alleles in otherwise healthy patients with mycobacterial disease. PloS Genet. (2006) 2:e131. doi: 10.1371/journal.pgen.0020131

PubMed Abstract | Crossref Full Text | Google Scholar

121. Sampaio EP, Bax HI, Hsu AP, Kristosturyan E, Pechacek J, Chandrasekaran P, et al. A novel stat1 mutation associated with disseminated mycobacterial disease. J Clin Immunol. (2012) 32:6819. doi: 10.1007/s10875-012-9659-2

PubMed Abstract | Crossref Full Text | Google Scholar

122. Tsumura M, Okada S, Sakai H, Yasunaga S, Ohtsubo M, Murata T, et al. Dominant-negative STAT1 SH2 domain mutations in unrelated patients with Mendelian susceptibility to mycobacterial disease. Hum Mutat. (2012) 33:137787. doi: 10.1002/humu.22113

PubMed Abstract | Crossref Full Text | Google Scholar

123. Ueki M, Yamada M, Ito K, Tozawa Y, Morino S, Horikoshi Y, et al. A heterozygous dominant-negative mutation in the coiled-coil domain of STAT1 is the cause of autosomal-dominant Mendelian susceptibility to mycobacterial diseases. Clin Immunol Orlando Fla. (2017) 174:2431. doi: 10.1016/j.clim.2016.11.004

PubMed Abstract | Crossref Full Text | Google Scholar

124. Liu Z, Zhou M, Yuan C, Ni Z, Liu W, Tan Y, et al. Two novel STAT1 mutations cause Mendelian susceptibility to mycobacterial disease. Biochem Biophys Res Commun. (2022) 591:1249. doi: 10.1016/j.bbrc.2021.11.036

PubMed Abstract | Crossref Full Text | Google Scholar

125. Ye F, Zhang W, Dong J, Peng M, Fan C, Deng W, et al. A novel STAT1 loss-of-function mutation associated with Mendelian susceptibility to mycobacterial disease. Front Cell Infect Microbiol. (2022) 12:1002140. doi: 10.3389/fcimb.2022.1002140

PubMed Abstract | Crossref Full Text | Google Scholar

126. Chen X, Chen J, Chen R, Mou H, Sun G, Yang L, et al. Genetic and functional identifying of novel STAT1 loss-of-function mutations in patients with diverse clinical phenotypes. J Clin Immunol. (2022) 42:177894. doi: 10.1007/s10875-022-01339-w

PubMed Abstract | Crossref Full Text | Google Scholar

127. Greybe L, Leung D, Wieselthaler N, le Roux DM, Chan KW, Lau YL, et al. A rare mutation causing autosomal dominant STAT1 deficiency in a South African multiplex kindred with disseminated BCG infection. BMC Pediatr. (2023) 23:378. doi: 10.1186/s12887-023-04206-8

PubMed Abstract | Crossref Full Text | Google Scholar

128. Ono R, Tsumura M, Shima S, Matsuda Y, Gotoh K, Miyata Y, et al. Novel STAT1 variants in Japanese patients with isolated mendelian susceptibility to mycobacterial diseases. J Clin Immunol. (2023) 43:46678. doi: 10.1007/s10875-022-01396-1

PubMed Abstract | Crossref Full Text | Google Scholar

129. Lv K, Gong Z, Fu Y, Zhao S, Song Y, Wang H, et al. A novel loss-of-function variant in STAT1 causes Mendelian susceptibility to mycobacterial disease. Front Cell Infect Microbiol. (2025) 15:1595389. doi: 10.3389/fcimb.2025.1595389

PubMed Abstract | Crossref Full Text | Google Scholar

130. Lee AJ and Ashkar AA. The dual nature of type I and type II interferons. Front Immunol. (2018) 9:2061. doi: 10.3389/fimmu.2018.02061

PubMed Abstract | Crossref Full Text | Google Scholar

131. Minegishi Y, Saito M, Morio T, Watanabe K, Agematsu K, Tsuchiya S, et al. Human tyrosine kinase 2 deficiency reveals its requisite roles in multiple cytokine signals involved in innate and acquired immunity. Immunity. (2006) 25:74555. doi: 10.1016/j.immuni.2006.09.009

PubMed Abstract | Crossref Full Text | Google Scholar

132. Kreins AY, Ciancanelli MJ, Okada S, Kong XF, Ramírez-Alejo N, Kilic SS, et al. Human TYK2 deficiency: Mycobacterial and viral infections without hyper-IgE syndrome. J Exp Med. (2015) 212:164162. doi: 10.1084/jem.20140280

PubMed Abstract | Crossref Full Text | Google Scholar

133. Picard C, Al-Herz W, Bousfiha A, Casanova JL, Chatila T, Conley ME, et al. Primary immunodeficiency diseases: an update on the classification from the international union of immunological societies expert committee for primary immunodeficiency 2015. J Clin Immunol. (2015) 35:696726. doi: 10.1007/s10875-015-0201-1

PubMed Abstract | Crossref Full Text | Google Scholar

134. Ogishi M, Arias AA, Yang R, Han JE, Zhang P, Rinchai D, et al. Impaired IL-23-dependent induction of IFN-γ underlies mycobacterial disease in patients with inherited TYK2 deficiency. J Exp Med. (2022) 219:e20220094. doi: 10.1084/jem.20220094

PubMed Abstract | Crossref Full Text | Google Scholar

135. Wu P, Chen S, Wu B, Chen J, and Lv G. A TYK2 gene mutation c.2395G>A leads to TYK2 deficiency: A case report and literature review. Front Pediatr. (2020) 8:253. doi: 10.3389/fped.2020.00253

PubMed Abstract | Crossref Full Text | Google Scholar

136. Zhang Q, Matuozzo D, Le Pen J, Lee D, Moens L, Asano T, et al. Recessive inborn errors of type I IFN immunity in children with COVID-19 pneumonia. J Exp Med. (2022) 219:e20220131. doi: 10.1084/jem.20220131

PubMed Abstract | Crossref Full Text | Google Scholar

137. Boisson-Dupuis S, Ramirez-Alejo N, Li Z, Patin E, Rao G, Kerner G, et al. Tuberculosis and impaired IL-23-dependent IFN-γ immunity in humans homozygous for a common TYK2 missense variant. Sci Immunol. (2018) 3:eaau8714. doi: 10.1126/sciimmunol.aau8714

PubMed Abstract | Crossref Full Text | Google Scholar

138. Eletto D, Burns SO, Angulo I, Plagnol V, Gilmour KC, Henriquez F, et al. Biallelic JAK1 mutations in immunodeficient patient with mycobacterial infection. Nat Commun. (2016) 7:13992. doi: 10.1038/ncomms13992

PubMed Abstract | Crossref Full Text | Google Scholar

139. Dupuis S, Jouanguy E, Al-Hajjar S, Fieschi C, Al-Mohsen IZ, Al-Jumaah S, et al. Impaired response to interferon-alpha/beta and lethal viral disease in human STAT1 deficiency. Nat Genet. (2003) 33:38891. doi: 10.1038/ng1097

PubMed Abstract | Crossref Full Text | Google Scholar

140. Chapgier A, Wynn RF, Jouanguy E, Filipe-Santos O, Zhang S, Feinberg J, et al. Human complete Stat-1 deficiency is associated with defective type I and II IFN responses in vitro but immunity to some low virulence viruses in vivo. J Immunol Baltim Md 1950. (2006) 176:507883. doi: 10.4049/jimmunol.176.8.5078

PubMed Abstract | Crossref Full Text | Google Scholar

141. Vairo D, Tassone L, Tabellini G, Tamassia N, Gasperini S, Bazzoni F, et al. Severe impairment of IFN-γ and IFN-α responses in cells of a patient with a novel STAT1 splicing mutation. Blood. (2011) 118:180617. doi: 10.1182/blood-2011-01-330571

PubMed Abstract | Crossref Full Text | Google Scholar

142. Sakata S, Tsumura M, Matsubayashi T, Karakawa S, Kimura S, Tamaura M, et al. Autosomal recessive complete STAT1 deficiency caused by compound heterozygous intronic mutations. Int Immunol. (2020) 32:66371. doi: 10.1093/intimm/dxaa043

PubMed Abstract | Crossref Full Text | Google Scholar

143. Boehmer DFR, Koehler LM, Magg T, Metzger P, Rohlfs M, Ahlfeld J, et al. A novel complete autosomal-recessive STAT1 LOF variant causes immunodeficiency with hemophagocytic lymphohistiocytosis-like hyperinflammation. J Allergy Clin Immunol Pract. (2020) 8:310211. doi: 10.1016/j.jaip.2020.06.034

PubMed Abstract | Crossref Full Text | Google Scholar

144. Le Voyer T, Sakata S, Tsumura M, Khan T, Esteve-Sole A, Al-Saud BK, et al. Genetic, immunological, and clinical features of 32 patients with autosomal recessive STAT1 deficiency. J Immunol Baltim Md 1950. (2021) 207:13352. doi: 10.4049/jimmunol.2001451

PubMed Abstract | Crossref Full Text | Google Scholar

145. Chapgier A, Kong XF, Boisson-Dupuis S, Jouanguy E, Averbuch D, Feinberg J, et al. A partial form of recessive STAT1 deficiency in humans. J Clin Invest. (2009) 119:150214. doi: 10.1172/JCI37083

PubMed Abstract | Crossref Full Text | Google Scholar

146. Kong XF, Ciancanelli M, Al-Hajjar S, Alsina L, Zumwalt T, Bustamante J, et al. A novel form of human STAT1 deficiency impairing early but not late responses to interferons. Blood. (2010) 116:5895906. doi: 10.1182/blood-2010-04-280586

PubMed Abstract | Crossref Full Text | Google Scholar

147. Kristensen IA, Veirum JE, Møller BK, and Christiansen M. Novel STAT1 alleles in a patient with impaired resistance to mycobacteria. J Clin Immunol. (2011) 31:26571. doi: 10.1007/s10875-010-9480-8

PubMed Abstract | Crossref Full Text | Google Scholar

148. Blaszczyk K, Nowicka H, Kostyrko K, Antonczyk A, Wesoly J, and Bluyssen HAR. The unique role of STAT2 in constitutive and IFN-induced transcription and antiviral responses. Cytokine Growth Factor Rev. (2016) 29:7181. doi: 10.1016/j.cytogfr.2016.02.010

PubMed Abstract | Crossref Full Text | Google Scholar

149. Bucciol G, Moens L, Ogishi M, Rinchai D, Matuozzo D, Momenilandi M, et al. Human inherited complete STAT2 deficiency underlies inflammatory viral diseases. J Clin Invest. (2023) 133:e168321. doi: 10.1172/JCI168321

PubMed Abstract | Crossref Full Text | Google Scholar

150. Toubiana J, Okada S, Hiller J, Oleastro M, Lagos Gomez M, Aldave Becerra JC, et al. Heterozygous STAT1 gain-of-function mutations underlie an unexpectedly broad clinical phenotype. Blood. (2016) 127:315464. doi: 10.1182/blood-2015-11-679902

PubMed Abstract | Crossref Full Text | Google Scholar

151. Zheng J, van de Veerdonk FL, Crossland KL, Smeekens SP, Chan CM, Al Shehri T, et al. Gain-of-function STAT1 mutations impair STAT3 activity in patients with chronic mucocutaneous candidiasis (CMC). Eur J Immunol. (2015) 45:283446. doi: 10.1002/eji.201445344

PubMed Abstract | Crossref Full Text | Google Scholar

152. Duncan CJA, Thompson B, Chen R, Rice GI, Gothe F, Young DF, et al. Severe type I interferonopathy and unrestrained interferon signaling due to a homozygous germline mutation in STAT2. Sci Immunol. (2019) 4:eaav7501. doi: 10.1126/sciimmunol.aav7501

PubMed Abstract | Crossref Full Text | Google Scholar

153. Zhu G, Badonyi M, Franklin L, Seabra L, Rice GI, Anne-Boland-Auge, et al. Type I interferonopathy due to a homozygous loss-of-inhibitory function mutation in STAT2. J Clin Immunol. (2023) 43:80818. doi: 10.1007/s10875-023-01445-3

PubMed Abstract | Crossref Full Text | Google Scholar

154. Gruber C, Martin-Fernandez M, Ailal F, Qiu X, Taft J, Altman J, et al. Homozygous STAT2 gain-of-function mutation by loss of USP18 activity in a patient with type I interferonopathy. J Exp Med. (2020) 217:e20192319. doi: 10.1084/jem.20192319

PubMed Abstract | Crossref Full Text | Google Scholar

155. Baghdassarian H, Blackstone SA, Clay OS, Philips R, Matthiasardottir B, Nehrebecky M, et al. Variant STAT4 and response to ruxolitinib in an autoinflammatory syndrome. N Engl J Med. (2023) 388:224152. doi: 10.1056/NEJMoa2202318

PubMed Abstract | Crossref Full Text | Google Scholar

156. Rajala HLM, Eldfors S, Kuusanmäki H, van Adrichem AJ, Olson T, Lagström S, et al. Discovery of somatic STAT5b mutations in large granular lymphocytic leukemia. Blood. (2013) 121:454150. doi: 10.1182/blood-2012-12-474577

PubMed Abstract | Crossref Full Text | Google Scholar

157. Ma CA, Xi L, Cauff B, DeZure A, Freeman AF, Hambleton S, et al. Somatic STAT5b gain-of-function mutations in early onset nonclonal eosinophilia, urticaria, dermatitis, and diarrhea. Blood. (2017) 129:6503. doi: 10.1182/blood-2016-09-737817

PubMed Abstract | Crossref Full Text | Google Scholar

158. Tangye SG, Al-Herz W, Bousfiha A, Chatila T, Cunningham-Rundles C, Etzioni A, et al. Human inborn errors of immunity: 2019 update on the classification from the international union of immunological societies expert committee. J Clin Immunol. (2020) 40:2464. doi: 10.1007/s10875-019-00737-x

PubMed Abstract | Crossref Full Text | Google Scholar

159. Gruber CN, Calis JJA, Buta S, Evrony G, Martin JC, Uhl SA, et al. Complex autoinflammatory syndrome unveils fundamental principles of JAK1 kinase transcriptional and biochemical function. Immunity. (2020) 53:672–684.e11. doi: 10.1016/j.immuni.2020.07.006

PubMed Abstract | Crossref Full Text | Google Scholar

160. Leonard WJ and O’Shea JJ. Jaks and STATs: biological implications. Annu Rev Immunol. (1998) 16:293322. doi: 10.1146/annurev.immunol.16.1.293

PubMed Abstract | Crossref Full Text | Google Scholar

161. Haferlach T, Bacher U, Kern W, Schnittger S, and Haferlach C. The diagnosis of BCR/ABL-negative chronic myeloproliferative diseases (CMPD): a comprehensive approach based on morphology, cytogenetics, and molecular markers. Ann Hematol. (2008) 87:110. doi: 10.1007/s00277-007-0403-6

PubMed Abstract | Crossref Full Text | Google Scholar

162. Luque Paz D, Kralovics R, and Skoda RC. Genetic basis and molecular profiling in myeloproliferative neoplasms. Blood. (2023) 141:190921. doi: 10.1182/blood.2022017578

PubMed Abstract | Crossref Full Text | Google Scholar

163. Levine RL, Wadleigh M, Cools J, Ebert BL, Wernig G, Huntly BJP, et al. Activating mutation in the tyrosine kinase JAK2 in polycythemia vera, essential thrombocythemia, and myeloid metaplasia with myelofibrosis. Cancer Cell. (2005) 7:38797. doi: 10.1016/j.ccr.2005.03.023

PubMed Abstract | Crossref Full Text | Google Scholar

164. Baxter EJ, Scott LM, Campbell PJ, East C, Fourouclas N, Swanton S, et al. Acquired mutation of the tyrosine kinase JAK2 in human myeloproliferative disorders. Lancet Lond Engl. (2005) 365:105461. doi: 10.1016/S0140-6736(05)71142-9

PubMed Abstract | Crossref Full Text | Google Scholar

165. Lee JW, Kim YG, Soung YH, Han KJ, Kim SY, Rhim HS, et al. The JAK2 V617F mutation in de novo acute myelogenous leukemias. Oncogene. (2006) 25:14346. doi: 10.1038/sj.onc.1209163

PubMed Abstract | Crossref Full Text | Google Scholar

166. Passamonti F, Elena C, Schnittger S, Skoda RC, Green AR, Girodon F, et al. Molecular and clinical features of the myeloproliferative neoplasm associated with JAK2 exon 12 mutations. Blood. (2011) 117:28136. doi: 10.1182/blood-2010-11-316810

PubMed Abstract | Crossref Full Text | Google Scholar

167. Maddali M, Kulkarni UP, Ravindra N, Jajodia E, Arunachalam AK, Suresh H, et al. JAK2 exon 12 mutations in cases with JAK2V617F-negative polycythemia vera and primary myelofibrosis. Ann Hematol. (2020) 99:9839. doi: 10.1007/s00277-020-04004-7

PubMed Abstract | Crossref Full Text | Google Scholar

168. Luo W and Yu Z. Calreticulin (CALR) mutation in myeloproliferative neoplasms (MPNs). Stem Cell Investig. (2015) 2:16. doi: 10.3978/j.issn.2306-9759.2015.08.01

PubMed Abstract | Crossref Full Text | Google Scholar

169. Masubuchi N, Araki M, Yang Y, Hayashi E, Imai M, Edahiro Y, et al. Mutant calreticulin interacts with MPL in the secretion pathway for activation on the cell surface. Leukemia. (2020) 34:499509. doi: 10.1038/s41375-019-0564-z

PubMed Abstract | Crossref Full Text | Google Scholar

170. Szuber N, Hanson CA, Lasho TL, Finke C, Ketterling RP, Pardanani A, et al. MPL-mutated essential thrombocythemia: a morphologic reappraisal. Blood Cancer J. (2018) 8:121. doi: 10.1038/s41408-018-0159-3

PubMed Abstract | Crossref Full Text | Google Scholar

171. Akpınar TS, Hançer VS, Nalçacı M, and Diz-Küçükkaya R. MPL W515L/K mutations in chronic myeloproliferative neoplasms. Turk J Haematol Off J Turk Soc Haematol. (2013) 30:812. doi: 10.4274/tjh.65807

PubMed Abstract | Crossref Full Text | Google Scholar

172. Bersenev A, Wu C, Balcerek J, and Tong W. Lnk controls mouse hematopoietic stem cell self-renewal and quiescence through direct interactions with JAK2. J Clin Invest. (2008) 118:283244. doi: 10.1172/JCI35808

PubMed Abstract | Crossref Full Text | Google Scholar

173. McMullin MF and Cario H. LNK mutations and myeloproliferative disorders. Am J Hematol. (2016) 91:24851. doi: 10.1002/ajh.24259

PubMed Abstract | Crossref Full Text | Google Scholar

174. Li F, Guo HY, Wang M, Geng HL, Bian MR, Cao J, et al. The effects of R683S (G) genetic mutations on the JAK2 activity, structure and stability. Int J Biol Macromol. (2013) 60:18695. doi: 10.1016/j.ijbiomac.2013.05.029

PubMed Abstract | Crossref Full Text | Google Scholar

175. Lacronique V, Boureux A, Valle VD, Poirel H, Quang CT, Mauchauffé M, et al. A TEL-JAK2 fusion protein with constitutive kinase activity in human leukemia. Science. (1997) 278:130912. doi: 10.1126/science.278.5341.1309

PubMed Abstract | Crossref Full Text | Google Scholar

176. Patterer V, Schnittger S, Kern W, Haferlach T, and Haferlach C. Hematologic Malignancies with PCM1-JAK2 gene fusion share characteristics with myeloid and lymphoid neoplasms with eosinophilia and abnormalities of PDGFRA, PDGFRB, and FGFR1. Ann Hematol. (2013) 92:75969. doi: 10.1007/s00277-013-1695-3

PubMed Abstract | Crossref Full Text | Google Scholar

177. Downes CE, McClure BJ, McDougal DP, Heatley SL, Bruning JB, Thomas D, et al. JAK2 alterations in acute lymphoblastic leukemia: molecular insights for superior precision medicine strategies. Front Cell Dev Biol. (2022) 10:942053. doi: 10.3389/fcell.2022.942053

PubMed Abstract | Crossref Full Text | Google Scholar

178. Malin S, McManus S, and Busslinger M. STAT5 in B cell development and leukemia. Curr Opin Immunol. (2010) 22:16876. doi: 10.1016/j.coi.2010.02.004

PubMed Abstract | Crossref Full Text | Google Scholar

179. Dou H, Chen X, Huang Y, Su Y, Lu L, Yu J, et al. Prognostic significance of P2RY8-CRLF2 and CRLF2 overexpression may vary across risk subgroups of childhood B-cell acute lymphoblastic leukemia. Genes Chromosomes Cancer. (2017) 56:13546. doi: 10.1002/gcc.22421

PubMed Abstract | Crossref Full Text | Google Scholar

180. Campos LW, Pissinato LG, and Yunes JA. Deleterious and oncogenic mutations in the IL7RA. Cancers. (2019) 11:1952. doi: 10.3390/cancers11121952

PubMed Abstract | Crossref Full Text | Google Scholar

181. Shochat C, Tal N, Bandapalli OR, Palmi C, Ganmore I, te Kronnie G, et al. Gain-of-function mutations in interleukin-7 receptor-α (IL7R) in childhood acute lymphoblastic leukemias. J Exp Med. (2011) 208:9018. doi: 10.1084/jem.201105802011512c

Crossref Full Text | Google Scholar

182. Zhang J, Ding L, Holmfeldt L, Wu G, Heatley SL, Payne-Turner D, et al. The genetic basis of early T-cell precursor acute lymphoblastic leukaemia. Nature. (2012) 481:15763. doi: 10.1038/nature10725

PubMed Abstract | Crossref Full Text | Google Scholar

183. Bandapalli OR, Schuessele S, Kunz JB, Rausch T, Stütz AM, Tal N, et al. The activating STAT5B N642H mutation is a common abnormality in pediatric T-cell acute lymphoblastic leukemia and confers a higher risk of relapse. Haematologica. (2014) 99:e188–192. doi: 10.3324/haematol.2014.104992

PubMed Abstract | Crossref Full Text | Google Scholar

184. Kim U and Shin HY. Genomic mutations of the STAT5 transcription factor are associated with human cancer and immune diseases. Int J Mol Sci. (2022) 23:11297. doi: 10.3390/ijms231911297

PubMed Abstract | Crossref Full Text | Google Scholar

185. Yared MA, Khoury JD, Medeiros LJ, Rassidakis GZ, and Lai R. Activation status of the JAK/STAT3 pathway in mantle cell lymphoma. Arch Pathol Lab Med. (2005) 129:9906. doi: 10.5858/2005-129-990-ASOTSP

PubMed Abstract | Crossref Full Text | Google Scholar

186. Tiacci E, Ladewig E, Schiavoni G, Penson A, Fortini E, Pettirossi V, et al. Pervasive mutations of JAK-STAT pathway genes in classical Hodgkin lymphoma. Blood. (2018) 131:245465. doi: 10.1182/blood-2017-11-814913

PubMed Abstract | Crossref Full Text | Google Scholar

187. Maurer B, Nivarthi H, Wingelhofer B, Pham HTT, Schlederer M, Suske T, et al. High activation of STAT5A drives peripheral T-cell lymphoma and leukemia. Haematologica. (2020) 105:43547. doi: 10.3324/haematol.2019.216986

PubMed Abstract | Crossref Full Text | Google Scholar

188. Koskela HLM, Eldfors S, Ellonen P, van Adrichem AJ, Kuusanmäki H, Andersson EI, et al. Somatic STAT3 mutations in large granular lymphocytic leukemia. N Engl J Med. (2012) 366:190513. doi: 10.1056/NEJMoa1114885

PubMed Abstract | Crossref Full Text | Google Scholar

189. Waldmann TA and Chen J. Disorders of the JAK/STAT pathway in T cell lymphoma pathogenesis: implications for immunotherapy. Annu Rev Immunol. (2017) 35:53350. doi: 10.1146/annurev-immunol-110416-120628

PubMed Abstract | Crossref Full Text | Google Scholar

190. Pérez C, González-Rincón J, OnaIndia A, Almaráz C, García-Díaz N, Pisonero H, et al. Mutated JAK kinases and deregulated STAT activity are potential therapeutic targets in cutaneous T-cell lymphoma. Haematologica. (2015) 100:e4503. doi: 10.3324/haematol.2015.132837

PubMed Abstract | Crossref Full Text | Google Scholar

191. Gruszka AM, Valli D, and Alcalay M. Understanding the molecular basis of acute myeloid leukemias: where are we now? Int J Hematol Oncol. (2017) 6:4353. doi: 10.2217/ijh-2017-0002

PubMed Abstract | Crossref Full Text | Google Scholar

192. Tefferi A. Novel mutations and their functional and clinical relevance in myeloproliferative neoplasms: JAK2, MPL, TET2, ASXL1, CBL, IDH and IKZF1. Leukemia. (2010) 24:112838. doi: 10.1038/leu.2010.69

PubMed Abstract | Crossref Full Text | Google Scholar

193. de Bock CE, Demeyer S, Degryse S, Verbeke D, Sweron B, Gielen O, et al. HOXA9 cooperates with activated JAK/STAT signaling to drive leukemia development. Cancer Discov. (2018) 8:61631. doi: 10.1158/2159-8290.CD-17-0583

PubMed Abstract | Crossref Full Text | Google Scholar

194. Barosi G, Bergamaschi G, Marchetti M, Vannucchi AM, Guglielmelli P, Antonioli E, et al. JAK2 V617F mutational status predicts progression to large splenomegaly and leukemic transformation in primary myelofibrosis. Blood. (2007) 110:40306. doi: 10.1182/blood-2007-07-099184

PubMed Abstract | Crossref Full Text | Google Scholar

195. Mesa RA, Powell H, Lasho T, Dewald G, McClure R, and Tefferi A. JAK2(V617F) and leukemic transformation in myelofibrosis with myeloid metaplasia. Leuk Res. (2006) 30:145760. doi: 10.1016/j.leukres.2006.01.008

PubMed Abstract | Crossref Full Text | Google Scholar

196. Griesinger F, Hennig H, Hillmer F, Podleschny M, Steffens R, Pies A, et al. A BCR-JAK2 fusion gene as the result of a t(9,22)(p24;q11.2) translocation in a patient with a clinically typical chronic myeloid leukemia. Genes Chromosomes Cancer. (2005) 44:32933. doi: 10.1002/gcc.20235

PubMed Abstract | Crossref Full Text | Google Scholar

197. Mizuki M, Schwable J, Steur C, Choudhary C, Agrawal S, Sargin B, et al. Suppression of myeloid transcription factors and induction of STAT response genes by AML-specific Flt3 mutations. Blood. (2003) 101:3164−73. doi: 10.1182/blood-2002-06-1677

PubMed Abstract | Crossref Full Text | Google Scholar

198. Moser B, Edtmayer S, Witalisz-Siepracka A, and Stoiber D. The ups and downs of STAT inhibition in acute myeloid leukemia. Biomedicines. (2021) 9:1051. doi: 10.3390/biomedicines9081051

PubMed Abstract | Crossref Full Text | Google Scholar

199. Guarnera L, D’Addona M, Bravo-Perez C, and Visconte V. KMT2A rearrangements in leukemias: molecular aspects and therapeutic perspectives. Int J Mol Sci. (2024) 25:9023. doi: 10.3390/ijms25169023

PubMed Abstract | Crossref Full Text | Google Scholar

200. Ye YX, Zhou J, Zhou YH, Zhou Y, Song XB, Wang J, et al. Clinical significance of BCR-ABL fusion gene subtypes in chronic myelogenous and acute lymphoblastic leukemias. Asian Pac J Cancer Prev APJCP. (2014) 15:99616. doi: 10.7314/APJCP.2014.15.22.9961

PubMed Abstract | Crossref Full Text | Google Scholar

201. Wang JQ, Jeelall YS, Ferguson LL, and Horikawa K. Toll-like receptors and cancer: MYD88 mutation and inflammation. Front Immunol. (2014) 5:367/full. doi: 10.3389/fimmu.2014.00367/full

Crossref Full Text | Google Scholar

202. Metzeler KH, Herold T, Rothenberg-Thurley M, Amler S, Sauerland MC, Görlich D, et al. Spectrum and prognostic relevance of driver gene mutations in acute myeloid leukemia. Blood. (2016) 128:68698. doi: 10.1182/blood-2016-01-693879

PubMed Abstract | Crossref Full Text | Google Scholar

203. Choudhary C, Brandts C, Schwable J, Tickenbrock L, Sargin B, Ueker A, et al. Activation mechanisms of STAT5 by oncogenic Flt3-ITD. Blood. (2007) 110:3704. doi: 10.1182/blood-2006-05-024018

PubMed Abstract | Crossref Full Text | Google Scholar

204. Ren Z, Aerts JL, Pen JJ, Heirman C, Breckpot K, and De Grève J. Phosphorylated STAT3 physically interacts with NPM and transcriptionally enhances its expression in cancer. Oncogene. (2015) 34:16507. doi: 10.1038/onc.2014.109

PubMed Abstract | Crossref Full Text | Google Scholar

205. Braun TP, Coblentz C, Curtiss BM, Coleman DJ, Schonrock Z, Carratt SA, et al. Combined inhibition of JAK/STAT pathway and lysine-specific demethylase 1 as a therapeutic strategy in CSF3R/CEBPA mutant acute myeloid leukemia. Proc Natl Acad Sci U.S.A. (2020) 117:136709. doi: 10.1073/pnas.1918307117

PubMed Abstract | Crossref Full Text | Google Scholar

206. Ahmadi SE, Rahimian E, Rahimi S, Zarandi B, Bahraini M, Soleymani M, et al. From regulation to deregulation of p53 in hematologic Malignancies: implications for diagnosis, prognosis and therapy. biomark Res. (2024) 12:137. doi: 10.1186/s40364-024-00676-9

PubMed Abstract | Crossref Full Text | Google Scholar

207. Ilangumaran S, Finan D, and Rottapel R. Flow cytometric analysis of cytokine receptor signal transduction. J Immunol Methods. (2003) 278:22134. doi: 10.1016/S0022-1759(03)00177-7

PubMed Abstract | Crossref Full Text | Google Scholar

208. Jankovic DL, Gibert M, Baran D, Ohara J, Paul WE, and Theze J. Activation by IL-2, but not IL-4, up-regulates the expression of the p55 subunit of the IL-2 receptor on IL-2- and IL-4-dependent T cell lines. J Immunol. (1989) 142:311320. doi: 10.4049/jimmunol.142.9.3113

Crossref Full Text | Google Scholar

209. Ehret GB, Reichenbach P, Schindler U, Horvath CM, Fritz S, Nabholz M, et al. DNA binding specificity of different STAT proteins. Comparison of in vitro specificity with natural target sites. J Biol Chem. (2001) 276:667588. doi: 10.1074/jbc.M001748200

PubMed Abstract | Crossref Full Text | Google Scholar

210. Müller P, Pugazhendhi D, and Zeidler MP. Modulation of human JAK-STAT pathway signaling by functionally conserved regulators. JAK-STAT. (2012) 1:3443. doi: 10.4161/jkst.18006

PubMed Abstract | Crossref Full Text | Google Scholar

211. Ruijter JM, Ramakers C, Hoogaars WMH, Karlen Y, Bakker O, van den Hoff MJB, et al. Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic Acids Res. (2009) 37:e45. doi: 10.1093/nar/gkp045

PubMed Abstract | Crossref Full Text | Google Scholar

212. Martinez-Fabregas J, Wang L, Pohler E, Cozzani A, Wilmes S, Kazemian M, et al. CDK8 fine-tunes IL-6 transcriptional activities by limiting STAT3 resident time at the gene loci. Cell Rep. (2020) 33:108545. doi: 10.1016/j.celrep.2020.108545

PubMed Abstract | Crossref Full Text | Google Scholar

213. Vignali DA. Multiplexed particle-based flow cytometric assays. J Immunol Methods. (2000) 243:24355. doi: 10.1016/S0022-1759(00)00238-6

PubMed Abstract | Crossref Full Text | Google Scholar

214. Bastarache JA, Koyama T, Wickersham NE, and Ware LB. Validation of a multiplex electrochemiluminescent immunoassay platform in human and mouse samples. J Immunol Methods. (2014) 408:13–23. doi: 10.1016/j.jim.2014.04.006

PubMed Abstract | Crossref Full Text | Google Scholar

215. Kellar KL and Iannone MA. Multiplexed microsphere-based flow cytometric assays. Exp Hematol. (2002) 30:122737. doi: 10.1016/S0301-472X(02)00922-0

PubMed Abstract | Crossref Full Text | Google Scholar

216. Leng SX, McElhaney JE, Walston JD, Xie D, Fedarko NS, and Kuchel GA. ELISA and multiplex technologies for cytokine measurement in inflammation and aging research. J Gerontol A Biol Sci Med Sci. (2008) 63:87984. doi: 10.1093/gerona/63.8.879

PubMed Abstract | Crossref Full Text | Google Scholar

217. Malekzadeh A, Twaalfhoven H, Wijnstok NJ, Killestein J, Blankenstein MA, and Teunissen CE. Comparison of multiplex platforms for cytokine assessments and their potential use for biomarker profiling in multiple sclerosis. Cytokine. (2017) 91:14552. doi: 10.1016/j.cyto.2016.12.021

PubMed Abstract | Crossref Full Text | Google Scholar

218. de Jager W, Prakken B, and Rijkers GT. Cytokine multiplex immunoassay: methodology and (clinical) applications. Methods Mol Biol Clifton NJ. (2009) 514:11933. doi: 10.1007/978-1-60327-527-9_9

PubMed Abstract | Crossref Full Text | Google Scholar

219. Khazeem MM. Frequency of JAK2V617F mutation zygosity and impact on disease outcome in MPN patients. Asian Pac J Cancer Prev APJCP. (2025) 26:67784. doi: 10.31557/APJCP.2025.26.2.677

PubMed Abstract | Crossref Full Text | Google Scholar

220. Vainchenker W and Constantinescu SN. A unique activating mutation in JAK2 (V617F) is at the origin of polycythemia vera and allows a new classification of myeloproliferative diseases. Hematology. (2005) 2005:195200. doi: 10.1182/asheducation-2005.1.195

PubMed Abstract | Crossref Full Text | Google Scholar

221. McLornan D, Percy M, and McMullin MF. JAK2 V617F: A single mutation in the myeloproliferative group of disorders. Ulster Med J. (2006) 75:1129.

PubMed Abstract | Google Scholar

222. Campbell PJ, Scott LM, Buck G, Wheatley K, East CL, Marsden JT, et al. Definition of subtypes of essential thrombocythaemia and relation to polycythaemia vera based on JAK2 V617F mutation status: a prospective study. Lancet Lond Engl. (2005) 366:194553. doi: 10.1016/S0140-6736(05)67785-9

PubMed Abstract | Crossref Full Text | Google Scholar

223. Cankovic M, Whiteley L, Hawley RC, Zarbo RJ, and Chitale D. Clinical performance of JAK2 V617F mutation detection assays in a molecular diagnostics laboratory: evaluation of screening and quantitation methods. Am J Clin Pathol. (2009) 132:71321. doi: 10.1309/AJCPFHUQZ9AGUEKA

PubMed Abstract | Crossref Full Text | Google Scholar

224. Tefferi A, Lasho TL, Finke CM, Elala Y, Hanson CA, Ketterling RP, et al. Targeted deep sequencing in primary myelofibrosis. Blood Adv. (2016) 1:10511. doi: 10.1182/bloodadvances.2016000208

PubMed Abstract | Crossref Full Text | Google Scholar

225. Klampfl T, Gisslinger H, Harutyunyan AS, Nivarthi H, Rumi E, Milosevic JD, et al. Somatic mutations of calreticulin in myeloproliferative neoplasms. N Engl J Med. (2013) 369:237990. doi: 10.1056/NEJMoa1311347

PubMed Abstract | Crossref Full Text | Google Scholar

226. Scott LM, Tong W, Levine RL, Scott MA, Beer PA, Stratton MR, et al. JAK2Exon 12 mutations in polycythemia vera and idiopathic erythrocytosis. N Engl J Med. (2007) 356:45968. doi: 10.1056/NEJMoa065202

PubMed Abstract | Crossref Full Text | Google Scholar

227. Pabinger S, Dander A, Fischer M, Snajder R, Sperk M, Efremova M, et al. A survey of tools for variant analysis of next-generation genome sequencing data. Brief Bioinform. (2014) 15:25678. doi: 10.1093/bib/bbs086

PubMed Abstract | Crossref Full Text | Google Scholar

228. Rehm HL, Bale SJ, Bayrak-Toydemir P, Berg JS, Brown KK, Deignan JL, et al. ACMG clinical laboratory standards for next-generation sequencing. Genet Med Off J Am Coll Med Genet. (2013) 15:73347. doi: 10.1038/gim.2013.92

PubMed Abstract | Crossref Full Text | Google Scholar

229. Strande NT, Riggs ER, Buchanan AH, Ceyhan-Birsoy O, DiStefano M, Dwight SS, et al. Evaluating the clinical validity of gene-disease associations: an evidence-based framework developed by the clinical genome resource. Am J Hum Genet. (2017) 100:895906. doi: 10.1016/j.ajhg.2017.04.015

PubMed Abstract | Crossref Full Text | Google Scholar

230. Nijman IJ, van Montfrans JM, Hoogstraat M, Boes ML, van de Corput L, Renner ED, et al. Targeted next-generation sequencing: a novel diagnostic tool for primary immunodeficiencies. J Allergy Clin Immunol. (2014) 133:52934. doi: 10.1016/j.jaci.2013.08.032

PubMed Abstract | Crossref Full Text | Google Scholar

231. Gallo V, Dotta L, Giardino G, Cirillo E, Lougaris V, D’Assante R, et al. Diagnostics of primary immunodeficiencies through next-generation sequencing. Front Immunol. (2016) 7:466/full. doi: 10.3389/fimmu.2016.00466/full

Crossref Full Text | Google Scholar

232. Torreggiani S, Castellan FS, Aksentijevich I, and Beck DB. Somatic mutations in autoinflammatory and autoimmune disease. Nat Rev Rheumatol. (2024) 20:68398. doi: 10.1038/s41584-024-01168-8

PubMed Abstract | Crossref Full Text | Google Scholar

233. Vainchenker W, Leroy E, Gilles L, Marty C, Plo I, and Constantinescu SN. JAK inhibitors for the treatment of myeloproliferative neoplasms and other disorders. F1000Research. (2018) 7:82. doi: 10.12688/f1000research.13167.1

PubMed Abstract | Crossref Full Text | Google Scholar

234. Yu H, Pardoll D, and Jove R. STATs in cancer inflammation and immunity: a leading role for STAT3. Nat Rev Cancer. (2009) 9:798809. doi: 10.1038/nrc2734

PubMed Abstract | Crossref Full Text | Google Scholar

235. Levine RL and Gilliland DG. Myeloproliferative disorders. Blood. (2008) 112:21908. doi: 10.1182/blood-2008-03-077966

PubMed Abstract | Crossref Full Text | Google Scholar

236. Quintás-Cardama A and Verstovsek S. Molecular pathways: Jak/STAT pathway: mutations, inhibitors, and resistance. Clin Cancer Res Off J Am Assoc Cancer Res. (2013) 19:193340. doi: 10.1158/1078-0432.CCR-12-0284

PubMed Abstract | Crossref Full Text | Google Scholar

237. Ng SB, Turner EH, Robertson PD, Flygare SD, Bigham AW, Lee C, et al. Targeted capture and massively parallel sequencing of 12 human exomes. Nature. (2009) 461:2726. doi: 10.1038/nature08250

PubMed Abstract | Crossref Full Text | Google Scholar

238. Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alföldi J, Wang Q, et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature. (2020) 581:43443. doi: 10.1038/s41586-020-2308-7

PubMed Abstract | Crossref Full Text | Google Scholar

239. Stenson PD, Mort M, Ball EV, Evans K, Hayden M, Heywood S, et al. The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies. Hum Genet. (2017) 136:66577. doi: 10.1007/s00439-017-1779-6

PubMed Abstract | Crossref Full Text | Google Scholar

240. O’Rawe J, Jiang T, Sun G, Wu Y, Wang W, Hu J, et al. Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing. Genome Med. (2013) 5:28. doi: 10.1186/gm432

PubMed Abstract | Crossref Full Text | Google Scholar

241. Stavropoulos DJ, Merico D, Jobling R, Bowdin S, Monfared N, Thiruvahindrapuram B, et al. Whole genome sequencing expands diagnostic utility and improves clinical management in pediatric medicine. NPJ Genomic Med. (2016) 1:15012–. doi: 10.1038/npjgenmed.2015.12

PubMed Abstract | Crossref Full Text | Google Scholar

242. Short PJ, McRae JF, Gallone G, Sifrim A, Won H, Geschwind DH, et al. De novo mutations in regulatory elements in neurodevelopmental disorders. Nature. (2018) 555:6116. doi: 10.1038/nature25983

PubMed Abstract | Crossref Full Text | Google Scholar

243. Gilissen C, Hehir-Kwa JY, Thung DT, van de Vorst M, van Bon BWM, Willemsen MH, et al. Genome sequencing identifies major causes of severe intellectual disability. Nature. (2014) 511:3447. doi: 10.1038/nature13394

PubMed Abstract | Crossref Full Text | Google Scholar

244. Liu X, Hu F, Zhang D, Li Z, He J, Zhang S, et al. Whole genome sequencing enables new genetic diagnosis for inherited retinal diseases by identifying pathogenic variants. NPJ Genomic Med. (2024) 9:6. doi: 10.1038/s41525-024-00391-2

PubMed Abstract | Crossref Full Text | Google Scholar

245. Mantere T, Kersten S, and Hoischen A. Long-read sequencing emerging in medical genetics. Front Genet. (2019) 10:426/full. doi: 10.3389/fgene.2019.00426/full

PubMed Abstract | Crossref Full Text | Google Scholar

246. Michels E, De Preter K, Van Roy N, and Speleman F. Detection of DNA copy number alterations in cancer by array comparative genomic hybridization. Genet Med. (2007) 9:57484. doi: 10.1097/GIM.0b013e318145b25b

PubMed Abstract | Crossref Full Text | Google Scholar

247. Yoshikawa H, Matsubara K, Qian GS, Jackson P, Groopman JD, Manning JE, et al. SOCS-1, a negative regulator of the JAK/STAT pathway, is silenced by methylation in human hepatocellular carcinoma and shows growth-suppression activity. Nat Genet. (2001) 28:2935. doi: 10.1038/ng0501-29

PubMed Abstract | Crossref Full Text | Google Scholar

248. Keewan E and Matlawska-Wasowska K. The emerging role of suppressors of cytokine signaling (SOCS) in the development and progression of leukemia. Cancers. (2021) 13:4000. doi: 10.3390/cancers13164000

PubMed Abstract | Crossref Full Text | Google Scholar

249. Sciumè G, Mikami Y, Jankovic D, Nagashima H, Villarino AV, Morrison T, et al. Rapid enhancer remodeling and transcription factor repurposing enable high magnitude gene induction upon acute activation of NK cells. Immunity. (2020) 53:745–758.e4. doi: 10.1016/j.immuni.2020.09.008

PubMed Abstract | Crossref Full Text | Google Scholar

250. Pandolfi S and Stecca B. Luciferase reporter assays to study transcriptional activity of hedgehog signaling in normal and cancer cells. Methods Mol Biol Clifton NJ. (2015) 1322:719. doi: 10.1007/978-1-4939-2772-2_7

PubMed Abstract | Crossref Full Text | Google Scholar

251. Schroder K, Hertzog PJ, Ravasi T, and Hume DA. Interferon-gamma: an overview of signals, mechanisms and functions. J Leukoc Biol. (2004) 75:16389. doi: 10.1189/jlb.0603252

PubMed Abstract | Crossref Full Text | Google Scholar

252. Qin HR, Kim HJ, Kim JY, Hurt EM, Klarmann GJ, Kawasaki BT, et al. Activation of signal transducer and activator of transcription 3 through a phosphomimetic serine 727 promotes prostate tumorigenesis independent of tyrosine 705 phosphorylation. Cancer Res. (2008) 68:773641. doi: 10.1158/0008-5472.CAN-08-1125

PubMed Abstract | Crossref Full Text | Google Scholar

253. Elbashir SM, Harborth J, Lendeckel W, Yalcin A, Weber K, and Tuschl T. Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells. Nature. (2001) 411:4948. doi: 10.1038/35078107

PubMed Abstract | Crossref Full Text | Google Scholar

254. Campeau E, Ruhl VE, Rodier F, Smith CL, Rahmberg BL, Fuss JO, et al. A versatile viral system for expression and depletion of proteins in mammalian cells. PloS One. (2009) 4:e6529. doi: 10.1371/journal.pone.0006529

PubMed Abstract | Crossref Full Text | Google Scholar

255. Aaronson DS and Horvath CM. A road map for those who don’t know JAK-STAT. Science. (2002) 296:16535. doi: 10.1126/science.1071545

PubMed Abstract | Crossref Full Text | Google Scholar

256. Shuai K and Liu B. Regulation of JAK-STAT signalling in the immune system. Nat Rev Immunol. (2003) 3:90011. doi: 10.1038/nri1226

PubMed Abstract | Crossref Full Text | Google Scholar

257. Bromberg JF, Wrzeszczynska MH, Devgan G, Zhao Y, Pestell RG, Albanese C, et al. Stat3 as an oncogene. Cell. (1999) 98:295303. doi: 10.1016/S0092-8674(00)81959-5

PubMed Abstract | Crossref Full Text | Google Scholar

258. Villarino AV, Kanno Y, and O’Shea JJ. Mechanisms and consequences of Jak–STAT signaling in the immune system. Nat Immunol. (2017) 18:37484. doi: 10.1038/ni.3691

PubMed Abstract | Crossref Full Text | Google Scholar

259. Vogel TP, Leiding JW, Cooper MA, and Forbes Satter LR. STAT3 gain-of-function syndrome. Front Pediatr. (2022) 10:770077. doi: 10.3389/fped.2022.770077

PubMed Abstract | Crossref Full Text | Google Scholar

260. Unal H. Luciferase reporter assay for unlocking ligand-mediated signaling of GPCRs. Methods Cell Biol. (2019) 149:1930. doi: 10.1016/bs.mcb.2018.08.001

PubMed Abstract | Crossref Full Text | Google Scholar

261. Calò V, Migliavacca M, Bazan V, Macaluso M, Buscemi M, Gebbia N, et al. STAT proteins: from normal control of cellular events to tumorigenesis. J Cell Physiol. (2003) 197:15768. doi: 10.1002/jcp.10364

PubMed Abstract | Crossref Full Text | Google Scholar

262. Ramos A, Koch CE, Liu-Lupo Y, Hellinger RD, Kyung T, Abbott KL, et al. Leukemia-intrinsic determinants of CAR-T response revealed by iterative in vivo genome-wide CRISPR screening. Nat Commun. (2023) 14:8048. doi: 10.1038/s41467-023-43790-2

PubMed Abstract | Crossref Full Text | Google Scholar

263. Patel SJ, Sanjana NE, Kishton RJ, Eidizadeh A, Vodnala SK, Cam M, et al. Identification of essential genes for cancer immunotherapy. Nature. (2017) 548:53742. doi: 10.1038/nature23477

PubMed Abstract | Crossref Full Text | Google Scholar

264. O’Shea JJ and Plenge R. JAK and STAT signaling molecules in immunoregulation and immune-mediated disease. Immunity. (2012) 36:54250. doi: 10.1016/j.immuni.2012.03.014

PubMed Abstract | Crossref Full Text | Google Scholar

265. Stark GR and Darnell JE. The JAK-STAT pathway at twenty. Immunity. (2012) 36:50314. doi: 10.1016/j.immuni.2012.03.013

PubMed Abstract | Crossref Full Text | Google Scholar

266. Shalem O, Sanjana NE, Hartenian E, Shi X, Scott DA, Mikkelson T, et al. Genome-scale CRISPR-cas9 knockout screening in human cells. Science. (2014) 343:847. doi: 10.1126/science.1247005

PubMed Abstract | Crossref Full Text | Google Scholar

267. Cong L, Ran FA, Cox D, Lin S, Barretto R, Habib N, et al. Multiplex genome engineering using CRISPR/Cas systems. Science. (2013) 339:81923. doi: 10.1126/science.1231143

PubMed Abstract | Crossref Full Text | Google Scholar

268. Zou S, Tong Q, Liu B, Huang W, Tian Y, and Fu X. Targeting STAT3 in cancer immunotherapy. Mol Cancer. (2020) 19:145. doi: 10.1186/s12943-020-01258-7

PubMed Abstract | Crossref Full Text | Google Scholar

269. Zhang Z, Zhang Y, Gao F, Han S, Cheah KS, Tse HF, et al. CRISPR/cas9 genome-editing system in human stem cells: current status and future prospects. Mol Ther Nucleic Acids. (2017) 9:23041. doi: 10.1016/j.omtn.2017.09.009

PubMed Abstract | Crossref Full Text | Google Scholar

270. Nishimoto N, Miyasaka N, Yamamoto K, Kawai S, Takeuchi T, and Azuma J. Long-term safety and efficacy of tocilizumab, an anti-IL-6 receptor monoclonal antibody, in monotherapy, in patients with rheumatoid arthritis (the STREAM study): evidence of safety and efficacy in a 5-year extension study. Ann Rheum Dis. (2009) 68:15804. doi: 10.1136/ard.2008.092866

PubMed Abstract | Crossref Full Text | Google Scholar

271. Verstovsek S, Mesa RA, Gotlib J, Levy RS, Gupta V, DiPersio JF, et al. A double-blind, placebo-controlled trial of ruxolitinib for myelofibrosis. N Engl J Med. (2012) 366:799807. doi: 10.1056/NEJMoa1110557

PubMed Abstract | Crossref Full Text | Google Scholar

272. Peeters P, Raynaud SD, Cools J, Wlodarska I, Grosgeorge J, Philip P, et al. Fusion of TEL, the ETS-variant gene 6 (ETV6), to the receptor-associated kinase JAK2 as a result of t(9,12) in a lymphoid and t(9,15,12) in a myeloid leukemia. Blood. (1997) 90:253540. doi: 10.1182/blood.V90.7.2535

PubMed Abstract | Crossref Full Text | Google Scholar

273. Bousquet M, Quelen C, De Mas V, Duchayne E, Roquefeuil B, Delsol G, et al. The t(8,9)(p22;p24) translocation in atypical chronic myeloid leukaemia yields a new PCM1-JAK2 fusion gene. Oncogene. (2005) 24:724852. doi: 10.1038/sj.onc.1208850

PubMed Abstract | Crossref Full Text | Google Scholar

274. James C, Ugo V, Le Couédic JP, Staerk J, Delhommeau F, Lacout C, et al. A unique clonal JAK2 mutation leading to constitutive signalling causes polycythaemia vera. Nature. (2005) 434:11448. doi: 10.1038/nature03546

PubMed Abstract | Crossref Full Text | Google Scholar

275. Holland SM, DeLeo FR, Elloumi HZ, Hsu AP, Uzel G, Brodsky N, et al. STAT3 mutations in the hyper-IgE syndrome. N Engl J Med. (2007) 357:160819. doi: 10.1056/NEJMoa073687

PubMed Abstract | Crossref Full Text | Google Scholar

276. Minegishi Y, Saito M, Tsuchiya S, Tsuge I, Takada H, Hara T, et al. Dominant-negative mutations in the DNA-binding domain of STAT3 cause hyper-IgE syndrome. Nature. (2007) 448:105862. doi: 10.1038/nature06096

PubMed Abstract | Crossref Full Text | Google Scholar

277. O’Shea JJ, Holland SM, and Staudt LM. JAKs and STATs in immunity, immunodeficiency, and cancer. N Engl J Med. (2013) 368:16170. doi: 10.1056/NEJMra1202117

PubMed Abstract | Crossref Full Text | Google Scholar

278. Belaid B, Lamara Mahammed L, Mohand Oussaid A, Migaud M, Khadri Y, Casanova JL, et al. Case report: interleukin-2 receptor common gamma chain defect presented as a hyper-igE syndrome. Front Immunol. (2021) 12:696350. doi: 10.3389/fimmu.2021.696350

PubMed Abstract | Crossref Full Text | Google Scholar

279. Nosaka T, van Deursen JM, Tripp RA, Thierfelder WE, Witthuhn BA, McMickle AP, et al. Defective lymphoid development in mice lacking Jak3. Science. (1995) 270:8002. doi: 10.1126/science.270.5237.800

PubMed Abstract | Crossref Full Text | Google Scholar

280. Noguchi M, Yi H, Rosenblatt HM, Filipovich AH, Adelstein S, Modi WS, et al. Interleukin-2 receptor gamma chain mutation results in X-linked severe combined immunodeficiency in humans. Cell. (1993) 73:14757. doi: 10.1016/0092-8674(93)90167-O

PubMed Abstract | Crossref Full Text | Google Scholar

281. McLornan DP, Pope JE, Gotlib J, and Harrison CN. Current and future status of JAK inhibitors. Lancet Lond Engl. (2021) 398:80316. doi: 10.1016/S0140-6736(21)00438-4

PubMed Abstract | Crossref Full Text | Google Scholar

282. Fischer M, Olbrich P, Hadjadj J, Aumann V, Bakhtiar S, Barlogis V, et al. JAK inhibitor treatment for inborn errors of JAK/STAT signaling: An ESID/EBMT-IEWP retrospective study. J Allergy Clin Immunol. (2024) 153:275–286.e18. doi: 10.1016/j.jaci.2023.10.018

PubMed Abstract | Crossref Full Text | Google Scholar

283. Masarova L, Mascarenhas J, Rampal R, Hu W, Livingston RA, and Pemmaraju N. Ten years of experience with ruxolitinib since approval for polycythemia vera: A review of clinical efficacy and safety. Cancer. (2025) 131:e35661. doi: 10.1002/cncr.35661

PubMed Abstract | Crossref Full Text | Google Scholar

284. Appeldoorn TYJ, Munnink THO, Morsink LM, de Hooge MNL, and Touw DJ. Pharmacokinetics and pharmacodynamics of ruxolitinib: A review. Clin Pharmacokinet. (2023) 62:55971. doi: 10.1007/s40262-023-01225-7

PubMed Abstract | Crossref Full Text | Google Scholar

285. Padda IS, Bhatt R, and Parmar M. Tofacitinib. In: StatPearls [Internet]. Treasure Island (FL): StatPearls; Publishing (2023). Available online at: https://www.ncbi.nlm.nih.gov/books/NBK572148/.

PubMed Abstract | Google Scholar

286. Reddy V and Cohen S. JAK inhibitors: what is new? Curr Rheumatol Rep. (2020) 22:50. doi: 10.1007/s11926-020-00931-6

PubMed Abstract | Crossref Full Text | Google Scholar

287. Yamaoka K and Oku K. JAK inhibitors in rheumatology. Immunol Med. (2023) 46:14352. doi: 10.1080/25785826.2023.2172808

PubMed Abstract | Crossref Full Text | Google Scholar

288. Bieber T, Feist E, Irvine AD, Harigai M, Haladyj E, Ball S, et al. A review of safety outcomes from clinical trials of baricitinib in rheumatology, dermatology and COVID-19. Adv Ther. (2022) 39:491060. doi: 10.1007/s12325-022-02281-4

PubMed Abstract | Crossref Full Text | Google Scholar

289. Mohamed MEF, Bhatnagar S, Parmentier JM, Nakasato P, and Wung P. Upadacitinib: Mechanism of action, clinical, and translational science. Clin Transl Sci. (2024) 17:e13688. doi: 10.1111/cts.13688

PubMed Abstract | Crossref Full Text | Google Scholar

290. Namour F, Anderson K, Nelson C, and Tasset C. Filgotinib: A clinical pharmacology review. Clin Pharmacokinet. (2022) 61:81932. doi: 10.1007/s40262-022-01129-y

PubMed Abstract | Crossref Full Text | Google Scholar

291. England JT and Gupta V. Fedratinib: a pharmacotherapeutic option for JAK-inhibitor naïve and exposed patients with myelofibrosis. Expert Opin Pharmacother. (2022) 23:167786. doi: 10.1080/14656566.2022.2135989

PubMed Abstract | Crossref Full Text | Google Scholar

292. Tm T, Gn P, A S, V T, and Bk R. Deucravacitinib: the first FDA-approved oral TYK2 inhibitor for moderate to severe plaque psoriasis. Ann Pharmacother. (2024) 58(4):416–27. doi: 10.1177/10600280231153863

PubMed Abstract | Crossref Full Text | Google Scholar

293. Samuel C, Cornman H, Kambala A, and Kwatra SG. A review on the safety of using JAK inhibitors in dermatology: clinical and laboratory monitoring. Dermatol Ther. (2023) 13:729−49. doi: 10.1007/s13555-023-00892-5

PubMed Abstract | Crossref Full Text | Google Scholar

294. Kirchhof MG, Prajapati VH, Gooderham M, Hong CH, Lynde CW, Maari C, et al. Practical recommendations on laboratory monitoring in patients with atopic dermatitis on oral JAK inhibitors. Dermatol Ther. (2024) 14:2653−68. doi: 10.1007/s13555-024-01243-8

PubMed Abstract | Crossref Full Text | Google Scholar

295. Keenan C, Nichols KE, and Albeituni S. Use of the JAK inhibitor ruxolitinib in the treatment of hemophagocytic lymphohistiocytosis. Front Immunol. (2021) 12:614704. doi: 10.3389/fimmu.2021.614704

PubMed Abstract | Crossref Full Text | Google Scholar

296. Satarker S, Tom AA, Shaji RA, Alosious A, Luvis M, and Nampoothiri M. JAK-STAT pathway inhibition and their implications in COVID-19 therapy. Postgrad Med. (2021) 133:489−507. doi: 10.1080/00325481.2020.1855921

PubMed Abstract | Crossref Full Text | Google Scholar

297. Qureshy Z, Johnson DE, and Grandis JR. Targeting the JAK/STAT pathway in solid tumors. J Cancer Metastasis Treat. (2020) 6:27. doi: 10.20517/2394-4722.2020.58

PubMed Abstract | Crossref Full Text | Google Scholar

298. Rah B, Rather RA, Bhat GR, Baba AB, Mushtaq I, Farooq M, et al. JAK/STAT signaling: molecular targets, therapeutic opportunities, and limitations of targeted inhibitions in solid Malignancies. Front Pharmacol. (2022) 13:821344. doi: 10.3389/fphar.2022.821344

PubMed Abstract | Crossref Full Text | Google Scholar