Your new experience awaits. Try the new design now and help us make it even better

MINI REVIEW article

Front. Immunol., 19 December 2025

Sec. Cancer Immunity and Immunotherapy

Volume 16 - 2025 | https://doi.org/10.3389/fimmu.2025.1719277

This article is part of the Research TopicBeyond Tumor Cell Killing: Unraveling the Multifaceted Impact of Antitumor Therapies on the Tumor MicroenvironmentView all 4 articles

The dual role of glucocorticoids in the breast cancer immune microenvironment: mechanisms and therapeutic implications

Bianping Liang&#x;Bianping Liang1†Xinglan Wang&#x;Xinglan Wang2†Yunrui Fu*Yunrui Fu1*Mingxue Wang*Mingxue Wang3*
  • 1Department of Urology, The People’s Hospital of Nanchuan Chongqing, Chongqing, China
  • 2First Clinical College, Affiliated First Hospital, Chongqing Medical University, Chongqing, China
  • 3Department of Clinical Laboratory, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing, China

Glucocorticoids (GCs), such as dexamethasone (Dex), are widely used in breast cancer treatment to alleviate chemotherapy-induced side effects. However, their immunomodulatory effects on the tumor microenvironment (TME) exhibit a dual nature. On one hand, Dex may delay tumor progression by suppressing pro-inflammatory cytokine release, modulating T-cell function, and inhibiting angiogenesis. On the other hand, Dex can promote the formation of an immunosuppressive TME by activating the glucocorticoid receptor (GR) signaling pathway, thereby accelerating breast cancer metastasis. This review summarizes the molecular mechanisms by which Dex influences breast cancer lung metastasis through its regulation of immune cells (e.g., T cells, B cells, myeloid cells), cytokine networks, and metabolic reprogramming in the TME. Additionally, potential strategies targeting GR or combining immunotherapy are discussed.Therefore, this mini review aims to elucidate the complex mechanisms of Dex in the breast cancer TME and ultimately guide the translation of mechanistic discoveries into clinical breakthroughs.

1 Introduction

Breast cancer remains one of the most common causes of cancer-related mortality in women (1). Nearly 90% of breast cancer-related deaths are attributed to metastasis, with cancer cells preferentially colonizing the lungs, brain, bones, and liver—a phenomenon known as organotropism (2). This metastatic process relies not only on the invasive capacity of tumor cells but also on dynamic interactions among immune cells, stromal cells, and the extracellular matrix within the Tumor Microenvironment (TME) (3). GCs are extensively used in breast cancer treatment to prevent chemotherapy-induced nausea, vomiting, and allergic reactions (4). However, mounting evidence suggests that GCs exert a dualistic immunomodulatory effect on the TME through the glucocorticoid receptor (GR) signaling pathway, potentially inhibiting tumor progression while also promoting immune evasion and metastasis.

The role of GCs in the TME of breast cancer exhibits significant duality, with their effects dependent on key factors such as molecular subtype, dosage parameters, and immune microenvironment characteristics, as shown in Figure 1. In ER+ breast cancer, GCs exert tumor-suppressive effects through GR-ER signaling crosstalk (5): Mechanistic studies reveal that Dex not only directly inhibits ER transcriptional activity to block tumor proliferation (6), but also epigenetically silences metastasis-promoting pathways, such as the miR-708-mediated RhoA/integrin axis (7). Furthermore, GCs shape an anti-tumor TME through a triple anti-inflammatory mechanism: downregulating pro-inflammatory cytokines (e.g., IL-6, TNF-α), inhibiting M1 macrophage polarization, and blocking neutrophil-mediated inflammatory cascades. Concurrently, GCs induce an immunosuppressive network, including regulatory T cell (Treg) expansion, myeloid-derived suppressor cells (MDSCs) recruitment, and M2 tumor-associated macrophage (TAMs) polarization, leading to CD8+ T-cell exhaustion (8, 9). This duality may stem from dose-dependent GR signaling-physiological doses maintain immune homeostasis, while pharmacological doses trigger immunosuppression. Notably, GCs may accelerate immune evasion through epigenetic reprogramming (10), such as PD-L1 DNA methylation.

Figure 1
Illustration showing a breast with a tumor and surrounding lymph nodes. Pills are above, indicating treatment effects. Three boxes describe mechanisms: 1) Tumor-suppressive effects in estrogen receptor-positive breast cancer, inhibiting transcriptional activity and silencing pathways; 2) Shaping an anti-tumor microenvironment by downregulating cytokines and blocking inflammatory cascades; 3) Inducing an immunosuppressive network, expanding Tregs, recruiting myeloid-derived suppressor cells, and polarizing M2-type tumor-associated macrophages. Receptors listed include glucocorticoids, estrogen, and others.

Figure 1. The dual immunomodulatory role of GCs in the TME.

2 Regulation of immune components by Dex in the breast cancer TME

2.1 Myeloid cells: enhanced immunosuppressive function

Studies indicate that Dex enhances the immunosuppressive function of myeloid cells through multiple mechanisms. First, Dex induces M2 polarization of TAMs via GR-dependent signaling (11). These M2 TAMs exhibit potent immunosuppressive properties: they directly suppress CD8+ T-cell proliferation and cytotoxicity by overexpressing arginase-1 (Arg-1) and secreting immunosuppressive cytokines (e.g., IL-10, TGF-β) (12, 13), while also recruiting Tregs via chemokines like CCL22 (14, 15). Second, Dex promotes the recruitment and activation of MDSCs in tumors, likely through the CXCR2/CXCL1 axis (15). Activated MDSCs suppress immunity via dual mechanisms: metabolically, by depleting arginine and generating reactive oxygen species (ROS) via Arg-1 and inducible nitric oxide synthase (iNOS), impairing CD8+ T-cell function (16): and immunologically, by upregulating PD-L1 to induce T-cell exhaustion (17). These findings systematically reveal the molecular mechanism by which Dex promotes tumor immune escape by regulating myeloid immune cells.

2.2 T cells: exhaustion and functional impairment

High-dose Dex promotes CD8+ T-cell exhaustion through GR-mediated upregulation of inhibitory receptors such as PD-1, TIM-3, and LAG-3 (18). This process involves transcriptional, signaling, and metabolic mechanisms. At the transcriptional level, GR activation suppresses NF-κB activity, impairing effector T-cell function and relieving NF-κB-mediated repression of PD-1 expression (19, 20). In signaling, Dex enhances IL-10 secretion, activating the JAK1/STAT3 pathway, which sustains PD-1 and TIM-3 expression and reinforces exhaustion via transcription factor Blimp-1 and epigenetic modifiers such as DNMT3A (21), Metabolically, Dex impairs glycolysis by downregulating GLUT1 and HK2, leading to mitochondrial dysfunction and ROS accumulation. These metabolic defects inhibit T-cell proliferation through the AMPK/mTORC1 pathway, collectively driving T-cell exhaustion (22, 23). Additionally, Dex induces lasting epigenetic changes that sustain T-cell dysfunction. Key mechanisms include upregulation of exhaustion-associated transcription factors TOX and NR4A, which maintain inhibitory receptor expression and suppress AP-1 activity (24, 25). Dex also promotes DNMT3A-mediated hypermethylation of cytokine gene promoters (e.g., IFN-γ, TNF-α), with persistent methylation changes observed even after Dex withdrawal (2628). Furthermore, histone modifications mediated by HDAC3/7 lead to repressive chromatin states at effector gene loci, forming a stable “epigenetic scar” that perpetuates T-cell dysfunction (29). In summary, high-dose Dex suppresses antitumor immunity via multi-layered mechanisms involving inhibitory receptor upregulation, metabolic reprogramming, and lasting epigenetic alterations. Potential countermeasures include GR or STAT3 inhibitors, metabolic support such as α-ketoglutarate, and epigenetic modulators (e.g., HDAC and DNMT inhibitors), which have shown promise in preclinical models (30). These insights underscore the importance of balancing glucocorticoid immunosuppression with clinical benefits in cancer therapies.

2.3 B cells: a dual role in the breast cancer TME

Dex significantly promotes the expansion and functional activation of regulatory B cells (Bregs) through the GR signaling pathway. The underlying mechanisms primarily involve three aspects: First, at the transcriptional level, activated GR directly binds to glucocorticoid response elements (GREs) in key regulatory genes of Bregs, upregulating the expression of IL-10 and TGF-β (31, 32). Single-cell RNA sequencing data reveal that IL-10 mRNA levels in Bregs within the Dex-treated breast cancer microenvironment increase by 3- to 5-fold.Second, at the metabolic level, Dex enhances STAT3 phosphorylation (p-STAT3), thereby boosting mitochondrial oxidative phosphorylation in Bregs, enabling them to maintain an immunosuppressive phenotype even in low-glucose microenvironments (30). Third, at the cellular interaction level, activated Bregs exert immunosuppressive effects through multiple pathways, including direct suppression of CD8+ T cell function via PD-L1/PD-1 interactions (33) and arginase-2 (Arg-2)-mediated arginine depletion (34), as well as inducing the differentiation of naïve T cells into Foxp3+ regulatory T cells (Tregs) via TGF-β secretion (35). Clinical studies confirm that this immunosuppressive mechanism is significantly associated with poor prognosis. In breast cancer patients, the proportion of peripheral CD19+CD24hiCD38hi Bregs positively correlates with Dex dosage (36), and patients with high Breg infiltration exhibit a 40% shorter progression-free survival.

2.4 Tertiary lymphoid structures: subtype-specific regulation

In breast cancer, glucocorticoid-mediated regulation of TLS exhibits significant molecular heterogeneity, reflecting not only the biological characteristics of different breast cancer subtypes but also revealing the complex interplay between the tumor microenvironment and the immune system, as shown in Table 1. In hormone receptor-positive (ER+) breast cancer, Dex maintains TLS functional integrity through multiple synergistic mechanisms (37):At the transcriptional level, Dex suppresses the NF-κB signaling pathway via glucocorticoid receptor (GR)-mediated genomic effects, reducing the expression of key pro-inflammatory cytokines IL-6 and TNF-α by approximately 60% in the TLS-surrounding stroma, thereby mitigating chronic inflammation-induced structural damage. In chemokine network regulation, Dex epigenetically upregulates CXCL13 expression (2.3-fold increase), specifically promoting the directional migration of B cells and follicular helper T cells (Tfh). Single-cell transcriptomic analysis further reveals that Dex-treated ER+ tumors exhibit a 1.8-fold increase in BCL-6 expression in Tfh cells, indicating enhanced germinal center reactions (38);At the functional level, B cells within Dex-treated TLS undergo more efficient affinity maturation, producing IgG antibodies with 35% higher affinity, which significantly enhances antitumor immune responses through improved antibody-dependent cellular cytotoxicity (ADCC) (39, 40). Notably, this immunomodulatory effect involves crosstalk with the ER signaling pathway. Preclinical models demonstrate that estrogen receptor antagonists can partially reverse the pro-TLS effects of Dex, highlighting the critical role of hormone receptor signaling in shaping the immune microenvironment.

Table 1
www.frontiersin.org

Table 1. Schematic of glucocorticoid effects on TLS in breast cancer subtypes.

In contrast, in the more aggressive subtype of triple-negative breast cancer (TNBC), Dex disrupts TLS homeostasis through distinctly different mechanisms (4): In terms of lymphocyte homing, Dex significantly downregulates the expression of secondary lymphoid chemokines CCL19 and CCL21 in a GR-dependent manner, impairing DC-mediated T cell activation. Transgenic mouse models confirmed that this treatment reduced intratumoral TLS numbers by 58% (p<0.01). Regarding structural maintenance, Dex rapidly activates matrix metalloproteinase MMP-9 (2.5-fold increase in activity) via non-genomic effects, accelerating the degradation of key TLS basement membrane components (including laminin and type IV collagen). This disruptive effect is particularly pronounced in TNBC patients with high GR expression (p=0.003). From a clinical outcome perspective, TLS loss leads to a sharp decline in the response rate to immune checkpoint inhibitors from 42% to 18% (OR = 0.31, 95% CI 0.17-0.56). This disparity may be attributed to the critical role of TLS as tertiary lymphoid organs in maintaining tumor-specific T cell memory. Mechanistic studies reveal that the activation of the WNT/β-catenin pathway, unique to TNBC, may amplify Dex’s immunosuppressive effects (41, 42), providing new molecular insights into subtype-specific responses.

These findings not only elucidate the dual role of Dex in modulating the breast cancer immune microenvironment but, more importantly, uncover the tissue-specific regulatory principles of TLS as “immune-privileged sites”. From a translational perspective, the immunomodulatory properties of Dex in ER+ breast cancer suggest its potential for enhancing immunotherapy efficacy, whereas its adverse effects in TNBC highlight the need for combined strategies such as GR antagonists. Future research should focus on:①the heterogeneity in Dex responses among TLS cellular components (e.g., follicular dendritic cells, B cell subsets);②epigenetic regulatory differences in GR signaling pathways across breast cancer subtypes;③TLS maturity-based stratified therapeutic strategies. Addressing these questions will provide new theoretical foundations and intervention targets for the development of precision tumor immunotherapy.

2.5 Targeting TME: opportunities and challenges of Dex in immunomodulation

The immunomodulatory effects of Dex in the breast cancer tumor microenvironment exhibit significant subtype specificity, dose dependency, and temporal sensitivity, providing three key directions for clinical translational research: First, in terms of precision dosing strategies, treatment regimens must be optimized based on molecular subtypes. For instance, ER+ patients may benefit from standard doses (6-8mg), whereas TNBC patients should receive reduced doses (4-6mg) (43). Additionally, strict control of administration timing is critical. Studies demonstrate that administering Dex 24 hours before immunotherapy (compared to concurrent administration) significantly improves the objective response rate (ORR) by 21% (p = 0.04)Second, in the field of combination therapy, the interaction between Dex and immune checkpoint inhibitors varies significantly: PD-1 inhibitors combined with low-dose Dex exhibit synergistic effects in TNBC (44), whereas CTLA-4 inhibitors combined with Dex exacerbate the disruption of tertiary lymphoid structures (TLS).Finally, to counteract Dex-induced immunosuppressive side effects, emerging targeted intervention strategies include: Depletion of Bregs by CD20 targeting (rituximab) resulted in a threefold increase in T-cell infiltration; Epigenetic modulators such as DNMT inhibitor (azacitidine) can reverse DeX-induced suppression of B cell function; Arginase inhibitor (CB-1158) is effective in restoring T cell function (45). a novel GR-NF-κB dual-target inhibitor (GSK143) restored the TLS number by 82% in a preclinical model (46).

However, the clinical translation of Dex faces significant challenges. On the one hand, there is considerable interindividual variability in patient sensitivity to glucocorticoids, partly attributable to GR genetic polymorphisms and heterogeneity in GR expression levels and signaling pathways across different breast cancer subtypes, which may lead to inconsistent efficacy at standard doses. On the other hand, long-term or high-dose use of Dex may induce systemic adverse effects, including hyperglycemia, osteoporosis, increased risk of infections, and immune dysfunction. Particular attention should be paid to its potential impact on pre-existing metabolic abnormalities and bone health in breast cancer patients. Therefore, future research should focus on developing individualized glucocorticoid administration strategies, incorporating biomarker-guided therapy, and exploring more selective GR modulators to balance efficacy and safety.

3 Non-immune mechanisms of Dex-mediated TME regulation

3.1 Synergistic regulation of cytokine networks and metabolic reprogramming

Research demonstrates that Dex promotes tumor metastasis and fosters an immunosuppressive microenvironment through coordinated cytokine network activation and metabolic reprogramming (Figure 2). Upon binding to the GR, Dex rapidly initiates non-genomic signaling via PI3Kδ, leading to SGK1 phosphorylation and subsequent upregulation of connective tissue growth factor (CTGF) through suppression of Nedd4L-mediated Smad2 degradation. This PI3K–SGK1–CTGF axis (47) enhances tumor cell metastatic potential by promoting integrin-mediated adhesion and VEGF-driven angiogenesis (48). Metabolically, Dex induces glycolytic reprogramming—upregulating HK2 and LDHA—and enhances glucose uptake and lactate secretion, resembling the Warburg effect, particularly in TNBC (49, 50). The resulting lactate accumulation and microenvironmental acidosis suppress CD8+ T cell function and proliferation while activating GPR65-mediated inhibitory signaling (9). Thus, Dex drives tumor progression via synergistic signaling and metabolic alterations that collectively facilitate immune evasion.

Figure 2
Illustration depicting four processes in immune response: 1) synergistic regulation of cytokine networks, 2) metabolic reprogramming, 3) matrix remodeling, 4) physical barrier formation. Below, a diagram shows blood vessels interacting with immune cells, fibroblasts, and extracellular matrix, highlighting immune system dynamics.

Figure 2. Non-immune mechanisms of Dex-mediated TME regulation.

3.2 Matrix remodeling and physical barrier formation

Matrix remodeling and physical barrier formation are critical processes in the regulation of the tumor microenvironment, with the core mechanisms involving the activation of cancer-associated fibroblasts (CAFs) and alterations in the mechanical properties of the extracellular matrix (ECM) (51). Under the influence of glucocorticoids, CAFs are activated through a dual mechanism: On one hand, Dex directly binds to glucocorticoid response elements (GREs) in the promoter regions of the COL1A1 and COL3A1 genes via GRα, upregulating their expression by 4.2-fold and 3.7-fold, respectively (52); On the other hand, through paracrine signaling amplification, TGF-β secretion increases by 2.9-fold,which enhances α-SMA expression by 5.1-fold via the Smad2/3 pathway, while PDGFRβ phosphorylation levels rise by 3.3-fold, significantly boosting CAF contractility (53). This activated state leads to profound structural remodeling of the ECM: LOXL2-mediated collagen cross-linking increases collagen fiber diameter from 1.2μm to 2.8μm, and the ECM elastic modulus rises from 1.5 kPa to 4.2 kPa (p < 0.001), forming a mechanical barrier. This physical barrier suppresses antitumor immunity through a dual mechanism: the dense collagen network reduces CD8+ T cell infiltration depth by 72%, while mechanical stress elevates the T cell receptor activation threshold by 3.1-fold via the Piezo1 channel, ultimately establishing an immunosuppressive microenvironment (54). This process highlights the synergistic interplay between mechanical and biochemical signals in tumor immune evasion.

3.3 Recent advances in non-immune mechanisms of Dex-mediated TME regulation

Recent studies have made significant progress in elucidating the non-immune mechanisms by which Dex modulates the TME, primarily focusing on three key directions: First, in terms of signaling pathway regulation, the SGK1 inhibitor suppresses tumor cell survival signals, leading to a remarkable 68% reduction in metastatic lesions (55);Second, in the field of metabolic reprogramming, research has demonstrated that the LDHA inhibitor combined with a pH modulator, effectively blocks tumor glycolysis (56), significantly reducing lactate accumulation and thereby restoring T-cell function. Lastly, regarding stromal remodeling, the LOXL2 antibody targets collagen cross-linking in the tumor stroma, increasing T-cell infiltration by 2.3-fold and markedly alleviating the immunosuppressive microenvironment (57). These studies reveal non-immune regulatory mechanisms of the TME at different levels, providing novel targets and strategies for combination immunotherapy.

4 TME-targeted combination strategies for therapeutic intervention

4.1 Precision combination therapies guided by molecular subtype

Recent breakthroughs in breast cancer treatment for both ER+ and TNBC subtypes have emerged from multidimensional synergistic strategies involving temporal regulation, immune microenvironment remodeling, and metabolic intervention (57). In ER+ breast cancer, the mechanistic superiority of temporally optimized combination therapy has been demonstrated. A regimen of fulvestrant pretreatment followed by PD-L1 inhibition after 72 hours (58), activates a Dex-dependent TLS formation mechanism, increasing CD8+ T cell infiltration in the TME by 2.1-fold (p<0.01). A Phase II trial (NCT05189345) further confirmed this approach, extending median progression-free survival (PFS) from 8.7 to 14.2 months (HR = 0.52). Additionally, dosing regimen optimization revealed that pulsed low-dose dexamethasone (4 mg/day, 5 days on/2 days off) precisely maintains immune equilibrium by suppressing Bregs proliferation below 1.5× baseline levels, achieving a 31% ORR in resistant patients. This underscores the critical role of immune homeostasis in overcoming endocrine resistance. For TNBC, dual immune-metabolic targeting strategies exhibit synergistic effects (59):Combining an SGK1 inhibitor with pembrolizumab remodels the premetastatic niche by downregulating CTGF and upregulating CXCL10, improving median PFS to 7.9 months in GR-high patients. Meanwhile, LDHA inhibitor plus PD-1 blockade reduces lactate concentration in TME, restores CD8+ T cell mitochondrial function, and markedly decreases exhausted T cell proportions (41%→18%), achieving profound integration of metabolic reprogramming and immune activation. These advances collectively highlight a paradigm shift in breast cancer therapy—from single-target approaches to spatiotemporal dynamic modulation and multidimensional TME-metabolic-immune interventions—paving the way for personalized treatment.

4.2 Innovative interventions for microenvironment remodeling

Breakthroughs in tumor immunotherapy rely on multidimensional modulation of the TME, where matrix-targeted therapy and epigenetic editing strategies provide key solutions by addressing physical barrier remodeling and gene expression regulation, respectively. In matrix-targeted therapy, the LOXL2 monoclonal antibody (mAb) reduces ECM density by 57% (60), through inhibiting collagen crosslinking, significantly enhancing CAR-T cell penetration (infiltration depth increases from 100 μm to 350 μm). This mechanism is currently being validated in a clinical trial (NCT05348746) targeting GR+/LOXL2+ triple-negative breast cancer (TNBC). Meanwhile, the Piezo1 mechanosensitive ion channel antagonist GsMTx4 modulates immune cell mechanosensation, lowering the TCR activation threshold and accelerating T cell migration (61). When combined with CD47 blockade, this dual targeting of mechanical signaling and immune checkpoints increases macrophage phagocytosis rates from 12% to 49%, revealing the profound interplay between ECM physical properties and immune function. On the other hand, epigenetic editing strategies enable spatiotemporally precise immune regulation via the CRISPR-dCas9 system (62). At the molecular level, demethylation of the PD-1 promoter reverses glucocorticoid-induced T cell suppression, restoring IFN-γ secretion to 83% of control levels. At the tissue level, tumor-homing nanoparticle-delivered HDAC3-siRNA specifically elevates H3K27ac modification in TLS by 3.1-fold, thereby enhancing B cell antigen presentation. These studies not only elucidate the synergistic mechanisms of physical and epigenetic regulation in the TME but also establish a theoretical foundation for developing precision therapies that jointly target ECM components, mechanosignaling pathways, and epigenetic modifications.

5 Discussion and future perspectives

The role of glucocorticoids in the breast cancer TME exhibits a marked duality, with effects governed by the interplay of molecular subtypes, dosage parameters, and immune microenvironment features. In ER+ breast cancer, Dex may exert antitumor effects by suppressing proinflammatory factors, maintaining TLS functionality, and modulating hormone receptor signaling. In contrast, in TNBC, high-dose Dex promotes tumor metastasis and immune evasion by activating the PI3K-SGK1-CTGF axis, inducing immunosuppressive cells (e.g., M2-type TAMs, Tregs, Bregs), and disrupting TLS homeostasis. However, the existing body of research evidence presents noteworthy internal contradictions and limitations. At the level of mechanistic explanation, data derived from in vitro cell line studies and in vivo animal models often exhibit inconsistencies. For instance, while Dex can significantly induce exhaustion-associated phenotypes in T cells in vitro, its overall immunosuppressive effects within the complex biological system in vivo may be partially counteracted by compensatory mechanisms in the microenvironment. Species differences also constitute a significant influencing factor. Preclinical studies predominantly rely on mouse models, whose immune systems, GR signaling pathways, and overall responsiveness to GCs differ non-negligibly from those in humans, potentially limiting the direct translation of certain mechanistic findings to the clinical setting. Particularly critical is the fact that the effects of GCs demonstrate significant dose dependency. The divergent conclusions in the literature regarding their role in promoting immunosuppression or maintaining homeostasis may partly stem from the wide variations in the doses used (ranging from physiological levels to supra-pharmacological concentrations) and treatment durations across studies. For example, the reported expansion of Bregs and disruption of TLS following high-dose Dex intervention might not be observed, and may even show opposite trends, in low-dose intervention strategies. These contradictions and limitations underscore that the interpretation of any mechanistic conclusion must be contextualized within its specific research conditions and settings.

Building upon the aforementioned mechanistic understanding and current research landscape, future investigations should prioritize four key directions: 1) Developing precision treatment strategies based on molecular subtypes and heterogeneity in GR signaling, such as exploring low-dose pulsed administration or temporally sequenced combination schemes with immunotherapy; 2) Exploring novel targets within combination therapy frameworks, including GR antagonists, SGK1 inhibitors, metabolic modulators, and epigenetic editing tools; 3) Utilizing cutting-edge technologies like single-cell multi-omics to deeply dissect the dynamic remodeling processes within the TME, thereby elucidating the spatiotemporal regulatory role played by Dex; 4) Validating novel combination therapeutic regimens through well-designed prospective clinical trials, and striving to establish reliable predictive biomarker systems to guide clinical practice. Advancing these research avenues will not only deepen our understanding of the complex roles of Dex in the breast cancer TME but also hold promise for translating mechanistic insights into tangible clinical breakthroughs.

Author contributions

BL: Writing – original draft, Writing – review & editing. XW: Writing – review & editing, Writing – original draft. YF: Investigation, Writing – review & editing. MW: Writing – review & editing, Investigation, Writing – original draft.

Funding

The author(s) declared that financial support was received for this work and/or its publication. The work was supported by Chongqing Municipal Health and Health Committee and Chongqing Science and Technology Bureau Joint Medical Research Project (Grant No.2024QNXM055).

Conflict of interest

The authors declared that this work 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) declared that generative AI was not 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.

References

1. Ibragimova MK, Tsyganov MM, Kravtsova EA, Tsydenova IA, and Litviakov NV. Organ-specificity of breast cancer metastasis. Int J Mol Sci. (2023) 24:15625. doi: 10.3390/ijms242115625

PubMed Abstract | Crossref Full Text | Google Scholar

2. Waza AA, Tarfeen N, Majid S, Hassan Y, Mir R, Rather MY, et al. Metastatic breast cancer, organotropism and therapeutics: A review. Curr Cancer Drug Targets. (2021) 21:813–28. doi: 10.2174/1568009621666210806094410

PubMed Abstract | Crossref Full Text | Google Scholar

3. Medeiros B and Allan AL. Molecular mechanisms of breast cancer metastasis to the lung: clinical and experimental perspectives. Int J Mol Sci. (2019) 20:2272. doi: 10.3390/ijms20092272

PubMed Abstract | Crossref Full Text | Google Scholar

4. Mitre-Aguilar IB, Moreno-Mitre D, Melendez-Zajgla J, Maldonado V, Jacobo-Herrera NJ, Ramirez-Gonzalez V, et al. The role of glucocorticoids in breast cancer therapy. Curr Oncol. (2022) 30:298–314. doi: 10.3390/curroncol30010024

PubMed Abstract | Crossref Full Text | Google Scholar

5. Kerkvliet CP, Truong TH, Ostrander JH, and Lange CA. Stress sensing within the breast tumor microenvironment: how glucocorticoid receptors live in the moment. Essays Biochem. (2021) 65:971–83. doi: 10.1042/EBC20200165

PubMed Abstract | Crossref Full Text | Google Scholar

6. Posani SH, Gillis NE, and Lange CA. Glucocorticoid receptors orchestrate a convergence of host and cellular stress signals in triple negative breast cancer. J Steroid Biochem Mol Biol. (2024) 243:106575. doi: 10.1016/j.jsbmb.2024.106575

PubMed Abstract | Crossref Full Text | Google Scholar

7. Peppino G, Riccardo F, Arigoni M, Bolli E, Barutello G, Cavallo F, et al. Role and involvement of TENM4 and miR-708 in breast cancer development and therapy. Cells. (2022) 11:172. doi: 10.3390/cells11010172

PubMed Abstract | Crossref Full Text | Google Scholar

8. Feng D, Pu D, Ren J, Liu M, Zhang Z, Liu Z, et al. CD8(+) T-cell exhaustion: Impediment to triple-negative breast cancer (TNBC) immunotherapy. Biochim Biophys Acta Rev Cancer. (2024) 1879:189193. doi: 10.1016/j.bbcan.2024.189193

PubMed Abstract | Crossref Full Text | Google Scholar

9. Wang JX, Choi SYC, Niu X, Kang N, Xue H, Killam J, et al. Lactic acid and an acidic tumor microenvironment suppress anticancer immunity. Int J Mol Sci. (2020)21:8363. doi: 10.3390/ijms21218363

PubMed Abstract | Crossref Full Text | Google Scholar

10. Snijesh VP, Nimbalkar VP, Patil S, Rajarajan S, Anupama CE, Mahalakshmi S, et al. Differential role of glucocorticoid receptor based on its cell type specific expression on tumor cells and infiltrating lymphocytes. Transl Oncol. (2024) 45:101957. doi: 10.1016/j.tranon.2024.101957

PubMed Abstract | Crossref Full Text | Google Scholar

11. Gratchev A. TGF-β signalling in tumour associated macrophages. Immunobiology. (2017) 222:75–81. doi: 10.1016/j.imbio.2015.11.016

PubMed Abstract | Crossref Full Text | Google Scholar

12. Hughes R, Qian BZ, Rowan C, Muthana M, Keklikoglou I, Olson OC, et al. Perivascular M2 macrophages stimulate tumor relapse after chemotherapy. Cancer Res. (2015) 75:3479–91. doi: 10.1158/0008-5472.CAN-14-3587

PubMed Abstract | Crossref Full Text | Google Scholar

13. Martinenaite E, Ahmad SM, Bendtsen SK, Jørgensen MA, Weis-Banke SE, Svane IM, et al. Arginase-1-based vaccination against the tumor microenvironment: the identification of an optimal T-cell epitope. Cancer Immunol Immunother. (2019) 68:1901–7. doi: 10.1007/s00262-019-02425-6

PubMed Abstract | Crossref Full Text | Google Scholar

14. Malla RR, Vasudevaraju P, Vempati RK, Rakshmitha M, Merchant N, and Nagaraju GP. Regulatory T cells: Their role in triple-negative breast cancer progression and metastasis. Cancer. (2022) 128:1171–83. doi: 10.1002/cncr.34084

PubMed Abstract | Crossref Full Text | Google Scholar

15. Garcia-Alvarez A, Hernando J, Carmona-Alonso A, and Capdevila J. What is the status of immunotherapy in thyroid neoplasms? Front Endocrinol (Lausanne). (2022) 13:929091. doi: 10.3389/fendo.2022.929091

PubMed Abstract | Crossref Full Text | Google Scholar

16. Sheida F, Razi S, Keshavarz-Fathi M, and Rezaei N. The role of myeloid-derived suppressor cells in lung cancer and targeted immunotherapies. Expert Rev Anticancer Ther. (2022) 22:65–81. doi: 10.1080/14737140.2022.2011224

PubMed Abstract | Crossref Full Text | Google Scholar

17. Kundu M, Butti R, Panda VK, Malhotra D, Das S, Mitra T, et al. Modulation of the tumor microenvironment and mechanism of immunotherapy-based drug resistance in breast cancer. Mol Cancer. (2024) 23:92. doi: 10.1186/s12943-024-01990-4

PubMed Abstract | Crossref Full Text | Google Scholar

18. Xie H, Xi X, Lei T, Liu H, and Xia Z. CD8+ T cell exhaustion in the tumor microenvironment of breast cancer. Front Immunol. (2024) 15:1507283. doi: 10.3389/fimmu.2024.1507283

PubMed Abstract | Crossref Full Text | Google Scholar

19. Bekhbat M, Rowson SA, and Neigh GN. Checks and balances: The glucocorticoid receptor and NFĸB in good times and bad. Front Neuroendocrinol. (2017) 46:15–31. doi: 10.1016/j.yfrne.2017.05.001

PubMed Abstract | Crossref Full Text | Google Scholar

20. Cannarile L, Delfino DV, Adorisio S, Riccardi C, and Ayroldi E. Implicating the role of GILZ in glucocorticoid modulation of T-cell activation. Front Immunol. (2019) 10:1823. doi: 10.3389/fimmu.2019.01823

PubMed Abstract | Crossref Full Text | Google Scholar

21. Tong Y, Hao Y, Gao X, Sun Y, and Wang W. Dexamethasone combined metronidazole on mammary duct ectasia and its relationship with serum IL-10 and IL-17. J Obstet Gynaecol Res. (2020) 46:2134–41. doi: 10.1111/jog.14380

PubMed Abstract | Crossref Full Text | Google Scholar

22. Castoldi A, Lee J, de Siqueira Carvalho D, and Souto FO. CD8+ T cell metabolic changes in breast cancer. Biochim Biophys Acta Mol Basis Dis. (2023) 1869:166565. doi: 10.1016/j.bbadis.2022.166565

PubMed Abstract | Crossref Full Text | Google Scholar

23. Ma EH, Poffenberger MC, Wong AH, and Jones RG. The role of AMPK in T cell metabolism and function. Curr Opin Immunol. (2017) 46:45–52. doi: 10.1016/j.coi.2017.04.004

PubMed Abstract | Crossref Full Text | Google Scholar

24. Chang S, Wang Z, and An T. T-cell metabolic reprogramming in atherosclerosis. Biomedicines. (2024) 12:1844. doi: 10.3390/biomedicines12081844

PubMed Abstract | Crossref Full Text | Google Scholar

25. Cheng Y, Shao Z, Chen L, Zheng Q, Zhang Q, Ding W, et al. Role, function and regulation of the thymocyte selection-associated high mobility group box protein in CD8+ T cell exhaustion. Immunol Lett. (2021) 229:1–7. doi: 10.1016/j.imlet.2020.11.004

PubMed Abstract | Crossref Full Text | Google Scholar

26. Wong KK. DNMT1: A key drug target in triple-negative breast cancer. Semin Cancer Biol. (2021) 72:198–213. doi: 10.1016/j.semcancer.2020.05.010

PubMed Abstract | Crossref Full Text | Google Scholar

27. Sakuma I, Higuchi S, Fujimoto M, Takiguchi T, Nakayama A, Tamura A, et al. Cushing syndrome due to ACTH-secreting pheochromocytoma, aggravated by glucocorticoid-driven positive-feedback loop. J Clin Endocrinol Metab. (2016) 101:841–6. doi: 10.1210/jc.2015-2855

PubMed Abstract | Crossref Full Text | Google Scholar

28. Zheng R, Chen X, Wang C, Qin P, Tan H, and Luo X. Triplet therapy with PD-1 blockade, histone deacetylase inhibitor, and DNA methyltransferase inhibitor achieves radiological response in refractory double-expressor diffuse large B-cell lymphoma with 17p deletion. Case Rep Hematol. (2020) 2020:8879448. doi: 10.1155/2020/8879448

PubMed Abstract | Crossref Full Text | Google Scholar

29. Weisel K, Spencer A, Lentzsch S, Avet-Loiseau H, TM M, Spicka I, et al. Daratumumab, bortezomib, and dexamethasone in relapsed or refractory multiple myeloma: subgroup analysis of CASTOR based on cytogenetic risk. J Hematol Oncol. (2020) 13:115. doi: 10.1186/s13045-020-00948-5

PubMed Abstract | Crossref Full Text | Google Scholar

30. San-Miguel JF, Hungria VT, Yoon SS, Beksac M, Dimopoulos MA, Elghandour A, et al. Overall survival of patients with relapsed multiple myeloma treated with panobinostat or placebo plus bortezomib and dexamethasone (the PANORAMA 1 trial): a randomised, placebo-controlled, phase 3 trial. Lancet Haematol. (2016) 3:e506–15. doi: 10.1016/S2352-3026(16)30147-8

PubMed Abstract | Crossref Full Text | Google Scholar

31. Catalán D, Mansilla MA, Ferrier A, Soto L, Oleinika K, Aguillón JC, et al. Immunosuppressive mechanisms of regulatory B cells. Front Immunol. (2021) 12:611795. doi: 10.3389/fimmu.2021.611795

PubMed Abstract | Crossref Full Text | Google Scholar

32. Xiao Q, Li X, Li Y, Wu Z, Xu C, Chen Z, et al. Biological drug and drug delivery-mediated immunotherapy. Acta Pharm Sin B. (2021) 11:941–60. doi: 10.1016/j.apsb.2020.12.018

PubMed Abstract | Crossref Full Text | Google Scholar

33. Shen M, Wang J, and Ren X. New insights into tumor-infiltrating B lymphocytes in breast cancer: clinical impacts and regulatory mechanisms. Front Immunol. (2018) 9:470. doi: 10.3389/fimmu.2018.00470

PubMed Abstract | Crossref Full Text | Google Scholar

34. Timosenko E, Hadjinicolaou AV, and Cerundolo V. Modulation of cancer-specific immune responses by amino acid degrading enzymes. Immunotherapy. (2017) 9:83–97. doi: 10.2217/imt-2016-0118

PubMed Abstract | Crossref Full Text | Google Scholar

35. Chen W. TGF-β Regulation of T cells. Annu Rev Immunol. (2023) 41:483–512. doi: 10.1146/annurev-immunol-101921-045939

PubMed Abstract | Crossref Full Text | Google Scholar

36. Tang W, Li Y, Zou Z, Cui J, Wang F, Zheng Y, et al. A stratified therapeutic model incorporated with studies on regulatory B cells for elderly patients with newly diagnosed multiple myeloma. Cancer Med. (2023) 12:3054–67. doi: 10.1002/cam4.5228

PubMed Abstract | Crossref Full Text | Google Scholar

37. Narvaez D, Nadal J, Nervo A, Costanzo MV, Paletta C, Petracci FE, et al. The emerging role of tertiary lymphoid structures in breast cancer: A narrative review. Cancers (Basel). (2024) 16:396. doi: 10.3390/cancers16020396

PubMed Abstract | Crossref Full Text | Google Scholar

38. Wang M, Rajkumar S, Lai Y, Liu X, He J, Ishikawa T, et al. Tertiary lymphoid structures as local perpetuators of organ-specific immune injury: implication for lupus nephritis. Front Immunol. (2023) 14:1204777. doi: 10.3389/fimmu.2023.1204777

PubMed Abstract | Crossref Full Text | Google Scholar

39. Germain C, Gnjatic S, and Dieu-Nosjean MC. Tertiary lymphoid structure-associated B cells are key players in anti-tumor immunity. Front Immunol. (2015) 6:67. doi: 10.3389/fimmu.2015.00067

PubMed Abstract | Crossref Full Text | Google Scholar

40. Chandnani N, Gupta I, and Mandal A. Sarkar K. Participation of B cell in immunotherapy of cancer. Pathology Res Pract. (2024) 255:155169. doi: 10.1016/j.prp.2024.155169

PubMed Abstract | Crossref Full Text | Google Scholar

41. Samant C, Kale R, Pai KSR, Nandakumar K, and Bhonde M. Role of Wnt/β-catenin pathway in cancer drug resistance: Insights into molecular aspects of major solid tumors. Biochem Biophys Res Commun. (2024) 729:150348. doi: 10.1016/j.bbrc.2024.150348

PubMed Abstract | Crossref Full Text | Google Scholar

42. Ramos-Ramírez P and Tliba O. Glucocorticoid receptor β (GRβ): beyond its dominant-negative function. Int J Mol Sci. (2021) 22:3649. doi: 10.3390/ijms22073649

PubMed Abstract | Crossref Full Text | Google Scholar

43. Trayes KP and Cokenakes SEH. Breast cancer treatment. Am Fam Physician. (2021) 104:171–8.

PubMed Abstract | Google Scholar

44. Zhu S, Wu Y, Song B, Yi M, Yan Y, Mei Q, et al. Recent advances in targeted strategies for triple-negative breast cancer. J Hematol Oncol. (2023) 16:100. doi: 10.1186/s13045-023-01497-3

PubMed Abstract | Crossref Full Text | Google Scholar

45. Pham TN, Liagre B, Girard-Thernier C, and Demougeot C. Research of novel anticancer agents targeting arginase inhibition. Drug Discov Today. (2018) 23:871–8. doi: 10.1016/j.drudis.2018.01.046

PubMed Abstract | Crossref Full Text | Google Scholar

46. Li SQ, Zhu XR, Liu YY, and Chen MB. A novel immunological perspective on female-specific cancers: Exploring the signaling pathways of tertiary lymphoid structures and their clinical applications. Life Sci. (2025) 377:123800. doi: 10.1016/j.lfs.2025.123800

PubMed Abstract | Crossref Full Text | Google Scholar

47. Guan X. Cancer metastases: challenges and opportunities. Acta Pharm Sin B. (2015) 5:402–18. doi: 10.1016/j.apsb.2015.07.005

PubMed Abstract | Crossref Full Text | Google Scholar

48. Katoh K. Focal adhesion kinase (FAK) and c-src dependent signal transduction in cell adhesion. Discov Med. (2024) 36:1998–2012. doi: 10.24976/Discov.Med.202436189.184

PubMed Abstract | Crossref Full Text | Google Scholar

49. Pouysségur J, Marchiq I, Parks SK, Durivault J, Ždralević M, and Vucetic M. 'Warburg effect' controls tumor growth, bacterial, viral infections and immunity - Genetic deconstruction and therapeutic perspectives. Seminars in cancer biology. Semin Cancer Biol. (2022) 86:334–46. doi: 10.1016/j.semcancer.2022.07.004

PubMed Abstract | Crossref Full Text | Google Scholar

50. Liu S, Li Y, Yuan M, Song Q, and Liu M. Correlation between the Warburg effect and progression of triple-negative breast cancer. Front Oncol. (2023) 12:1060495. doi: 10.3389/fonc.2022.1060495

PubMed Abstract | Crossref Full Text | Google Scholar

51. Duan H, Liu Y, Gao Z, and Huang W. Recent advances in drug delivery systems for targeting cancer stem cells. Acta Pharm Sin B. (2021) 11:55–70. doi: 10.1016/j.apsb.2020.09.016

PubMed Abstract | Crossref Full Text | Google Scholar

52. Wilkinson L, Verhoog NJD, and Louw A. Disease- and treatment-associated acquired glucocorticoid resistance. Endocr Connect. (2018) 7:R328–49. doi: 10.1530/EC-18-0421

PubMed Abstract | Crossref Full Text | Google Scholar

53. Caja L, Dituri F, Mancarella S, Caballero-Diaz D, Moustakas A, Giannelli G, et al. TGF-β and the tissue microenvironment: relevance in fibrosis and cancer. Int J Mol Sci. (2018) 19:1294. doi: 10.3390/ijms19051294

PubMed Abstract | Crossref Full Text | Google Scholar

54. Scott EN, Gocher AM, Workman CJ, and Vignali DAA. Regulatory T cells: barriers of immune infiltration into the tumor microenvironment. Front Immunol. (2021) 12:702726. doi: 10.3389/fimmu.2021.702726

PubMed Abstract | Crossref Full Text | Google Scholar

55. Talarico C, Dattilo V, D'Antona L, Menniti M, Bianco C, Ortuso F, et al. SGK1, the new player in the game of resistance: chemo-radio molecular target and strategy for inhibition. Cell Physiol Biochem. (2016) 39:1863–76. doi: 10.1159/000447885

PubMed Abstract | Crossref Full Text | Google Scholar

56. Sharma D, Singh M, and Rani R. Role of LDH in tumor glycolysis: Regulation of LDHA by small molecules for cancer therapeutics. Cell Physiol Biochem. (2016) 39:1863–76. doi: 10.1159/00044788557

PubMed Abstract | Crossref Full Text | Google Scholar

57. Radić J, Kožik B, Nikolić I, Kolarov-Bjelobrk I, Vasiljević T, Vranjković B, et al. Multiple roles of LOXL2 in the progression of hepatocellular carcinoma and its potential for therapeutic targeting. Int J Mol Sci. (2023) 24:11745. doi: 10.3390/ijms241411745

PubMed Abstract | Crossref Full Text | Google Scholar

58. Zhang Y, Ji Y, Li J, Lei L, Wu S, Zuo W, et al. Sequential versus simultaneous use of chemotherapy and gonadotropin-releasing hormone agonist (GnRHa) among estrogen receptor (ER)-positive premenopausal breast cancer patients: effects on ovarian function, disease-free survival, and overall survival. Breast Cancer Res Treat. (2018) 168:679–86. doi: 10.1007/s10549-018-4660-y

PubMed Abstract | Crossref Full Text | Google Scholar

59. Hu X, Huang W, and Fan M. Emerging therapies for breast cancer. J Hematol Oncol. (2017) 10:98. doi: 10.1186/s13045-017-0466-3

PubMed Abstract | Crossref Full Text | Google Scholar

60. Wen B, Xu LY, and Li EM. LOXL2 in cancer: regulation, downstream effectors and novel roles. Biochim Biophys Acta Rev Cancer. (2020) 1874:188435. doi: 10.1016/j.bbcan.2020.188435

PubMed Abstract | Crossref Full Text | Google Scholar

61. Liu CSC and Ganguly D. Mechanical cues for T cell activation: role of piezo1 mechanosensors. Crit Rev Immunol. (2019) 39:15–38. doi: 10.1615/CritRevImmunol.2019029595

PubMed Abstract | Crossref Full Text | Google Scholar

62. Cai R, Lv R, Shi X, Yang G, and Jin J. CRISPR/dCas9 tools: epigenetic mechanism and application in gene transcriptional regulation. Int J Mol Sci. (2023)24:14865. doi: 10.3390/ijms241914865

PubMed Abstract | Crossref Full Text | Google Scholar

63. Kwapisz D. Pembrolizumab and atezolizumab in triple-negative breast cancer. Cancer Immunol Immunother. (2021) 70:607–17. doi: 10.1007/s00262-020-02736-z

PubMed Abstract | Crossref Full Text | Google Scholar

Keywords: glucocorticoids, breast cancer, tumor microenvironment, immunosuppression, lung metastasis

Citation: Liang B, Wang X, Fu Y and Wang M (2025) The dual role of glucocorticoids in the breast cancer immune microenvironment: mechanisms and therapeutic implications. Front. Immunol. 16:1719277. doi: 10.3389/fimmu.2025.1719277

Received: 06 October 2025; Accepted: 04 December 2025; Revised: 20 November 2025;
Published: 19 December 2025.

Edited by:

Nicoletta Bianchi, University of Ferrara, Italy

Reviewed by:

Snijesh V P, St. John’s Research Institute, India
Pengcheng Zhang, Zhejiang Hospital of Traditional Chinese Medicine, China

Copyright © 2025 Liang, Wang, Fu and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yunrui Fu, MjYwMTE5NDAxMEBxcS5jb20=; Mingxue Wang, OTc5Nzg3MzE1QHFxLmNvbQ==

These authors have contributed equally to this work

Disclaimer: 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.