Orchestration of mesenchymal plasticity and immune evasiveness via rewiring of the metabolic program in pancreatic ductal adenocarcinoma

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the most fatal cancer in humans, due to its difficulty of early detection and its high metastatic ability. The occurrence of epithelial to mesenchymal transition in preinvasive pancreatic lesions has been implicated in the early dissemination, drug resistance, and cancer stemness of PDAC. PDAC cells also have a reprogrammed metabolism, regulated by driver mutation-mediated pathways, a desmoplastic tumor microenvironment (TME), and interactions with stromal cells, including pancreatic stellate cells, fibroblasts, endothelial cells, and immune cells. Such metabolic reprogramming and its functional metabolites lead to enhanced mesenchymal plasticity, and creates an acidic and immunosuppressive TME, resulting in the augmentation of protumor immunity via cancer-associated inflammation. In this review, we summarize our recent understanding of how PDAC cells acquire and augment mesenchymal features via metabolic and immunological changes during tumor progression, and how mesenchymal malignancies induce metabolic network rewiring and facilitate an immune evasive TME. In addition, we also present our recent findings on the interesting relevance of the small G protein ADP-ribosylation factor 6-based signaling pathway driven by KRAS/TP53 mutations, inflammatory amplification signals mediated by the proinflammatory cytokine interleukin 6 and RNA-binding protein ARID5A on PDAC metabolic reprogramming and immune evasion, and finally discuss potential therapeutic strategies for the quasi-mesenchymal subtype of PDAC.

Introduction

Pancreatic ductal adenocarcinoma (PDAC) originates from epithelial cells of the exocrine pancreas, which is composed of secretory acinar cells and ductal cells (1). PDAC patients often have an unfavorable prognosis, and the 5-year overall survival rate has been reported to be only 11% in the United States (2). Only 20% of PDACs are confined to pancreatic tissue at diagnosis, approximately 30% have metastasized to regional lymph nodes, and more than 50% have disseminated to other tissues, primarily the liver and lungs (3).

Four major driver mutations have been identified in PDAC, including KRAS, TP53, CDKN2A, and SMAD4/DPC4 mutations (4–6). Constitutive active mutations of KRAS occur in more than 90% of patients, often demonstrate oncogenic activity, and have been shown to be involved in the initiating event of PDAC tumorigenesis (6–9). In addition, oncogenic KRAS has been shown to promote tumor signaling through metabolic reprogramming (10) and stromal interactions (11) to facilitate tumor growth. Mutations in TP53 also often result in oncogenic activity, and are present in up to 70% of PDACs, typically occurring at late stages of PDAC carcinogenesis, and are frequently associated with invasive and metastatic phenotypes (6, 12). Furthermore, TP53 mutations play an important role in inducing platelet-derived growth factor (PDGF) receptor B expression, which associated with reduced disease-free survival in PDAC patients (13).

Because of the lack of effective diagnostic biomarkers for PDAC and the absence of early symptoms, the diagnosis of PDAC is often made at advanced, terminal stages. Current treatment options include surgery, if possible, or chemotherapy (gemcitabine, FOLFIRINOX [fluorouracil, leucovorin, irinotecan, and oxaliplatin], etc.), and radiation therapy, all with limited efficiency and achieving only slightly prolonged survival (14, 15). Immune checkpoint-based immunotherapies have been incorporated, albeit to a limited extent, into treatment modalities for some other cancers, but clinical trials targeting checkpoint molecules, such as CTLA4, PD-1/PD-L1, or their other cognate ligands have been unsuccessful for the treatment of PDAC. So far, there have been no successful clinical trials against PDAC, even those targeting multiple immune checkpoints (16–18).

PDAC cells also demonstrate a poor nutritional status, high levels of oxidative stress, inflammatory stress, extracellular acidosis, hypoxia, and decreased angiogenesis (15, 19, 20). Consistently, these are strong selection pressures that enable only cells that have adapted their metabolism to these hostile conditions to survive and proliferate. Notably, accumulating lines of evidence suggest that these adaptations also make PDAC cells more invasive, metastatic, stem cell-like, and resistant to therapeutic treatments (21). Consistently, several genome-wide gene expression profiling and genomic sequencing approaches to elucidate the molecular landscape of PDAC have demonstrated that the so-called basal-like (also known as quasi-mesenchymal-like or squamous) subtype is associated with a less favorable prognosis than other subtypes (22–25). Importantly, PDAC metabolite profiling and transcriptional analysis confirmed that the quasi-mesenchymal-like subtype is associated with the glycolytic subtype (26–28). This reorganization of pancreatic cancer cell metabolism opens the way for new therapeutic opportunities (20). However, the substantial heterogeneity in gene expression and metabolic characteristics, the plasticity of pancreatic cancer cells, and the pathological changes associated with their linked physicochemical and biological changes in the tumor microenvironment (TME) make PDAC a challenging disease to cure (26, 27, 29).

In this review, we summarize recent studies on how gene expression changes via intrinsic genetic mutations and epigenetic alterations involved in the acquisition of mesenchymal traits in PDAC cells, particularly post-transcriptional dysregulation of expression, are linked to metabolic reorganization associated with immunosuppressive TME formation during the development and malignant progression of PDAC.

Recently, PDAC has been hypothesized to be associated with two morphologically distinct precursors, i.e., pancreatic intraepithelial neoplasia (PanIN) and intrapapillary mucinous neoplasia (IPMN). PanIN can progress to invasive carcinoma in a stepwise and linear manner, which is an established mechanism of PDAC progression (30). Multiple studies have reported the sequential accumulation of PDAC driver gene mutations in PanIN, with KRAS mutations being the earliest known genetic alterations, being present in more than 90% of all PanINs regardless of cancer grade (31). On the other hand, the inactivation of CDKN2A is rare in low-grade PanIN, but has been reported to occur in more than 70% of high-grade PanIN (32). Mutations in TP53 and SMAD4 occur during the late stages of PanIN progression, and are almost exclusively found in high-grade PanIN and invasive PDAC. In contrast, IPMN is driven by four driver gene mutations of pancreatic tumorigenesis similar to PanIN, including early mutations in KRAS and late mutations in CDKN2A, TP53, and SMAD4 (33). However, there are also two frequently altered driver genes specific to the IPMN pathway. Mutations in the oncogenic hotspot of GNAS are known to occur early in IPMN tumorigenesis (33–35). In addition, although inactivating mutations in Ring finger protein 43 (RNF43), which encodes a ubiquitin ligase involved in WNT signaling (often with loss of heterozygosity) are also common in IPMNs (36), the precise timing of the occurrence of RNF43 mutations in IPMN tumorigenesis has not yet been clarified to date.

In addition, we present our recent findings on the intriguing relevance of the small G protein ADP-ribosylation factor 6 (ARF6)-based signaling pathway driven by KRAS/TP53 mutations, as well as the inflammation amplifying signals mediated by the inflammatory cytokine interleukin 6 (IL-6) and the RNA-binding protein AT-rich interactive domain 5a (Arid5a) on PDAC metabolic reprogramming and immune evasion. We will present our recent findings on the relevance of these pathways, and finally discuss potential therapeutic strategies for the quasi-mesenchymal subtype of PDAC.

Plasticity of adult pancreatic tissues

The pancreas is an important organ responsible for metabolic control in the body, and is composed of two morphologically and functionally distinct components. The exocrine pancreas, accounting for more than 95% of total organ mass, is composed of acinar cells, which produce digestive enzymes, and ductal cells, which deliver these enzymes to the intestine. On the other hand, the endocrine islets of Langerhans consist of five different cell groups (α, β, δ, PP, and ε cells) that secrete various hormones, such as insulin and glucagon, and play crucial roles in the regulation of glucose metabolism. The exocrine and endocrine pancreas are associated with different diseases. Pancreatitis and pancreatic cancer, mostly PDAC, arise from the exocrine pancreas, whereas rare pancreatic neuroendocrine tumors arise from the endocrine islets, and diabetes is also a result of endocrine islet dysfunction (37). The mammalian pancreas has the capacity for regeneration after injury even in adults, with the acinar compartment having the highest plasticity in humans. Through epigenetic transcriptional regulation, acinar cells can dedifferentiate into an embryonic progenitor-like phenotype, and commit to either insulin⁺ β-cells (38) or ductal cells (known as acinar to ductal metaplasia [ADM]) (39, 40). ADM transdifferentiation occurs in chronic pancreatitis via nuclear factor-κB (NF-κB) activation, and is associated with pancreatic intraepithelial neoplasia, which is a necessary step for the generation of neoplastic precursor lesions called PanINs (Pancreatic intraepithelial neoplasia) (41–43). Thus, it has been speculated that the acinar cells of the exocrine pancreas maintain plasticity to adapt to changes in the external environment, and that their dysregulation leads to pancreatitis and pancreatic cancer.

Heterogeneity of PDAC

To date, gene expression studies of PDAC have included comprehensive analyses focusing on subtyping of primary tumors obtained by surgical resection. Representative reports include the three-group classification by Collisson et al. (classical, quasi-mesenchymal, exocrine-like) (22), the two-group classification by Moffitt et al. (basal-like, classical) (23), and the four-group classification by Bailey et al. (squamous, immunogenic, pancreatic progenitor, and aberrantly differentiated endocrine exocrine) (24). Each of these classifications has been able to predict the prognosis of patients with resected PDAC on multivariate analysis. Notably, in about half of PDAC tumors, increased expression levels of hypoxia-associated genes were observed by RNA sequencing (RNAseq), and were substantially associated with basal-like subtypes, although there was no redundancy in the identified gene sets (44). Regarding morphology, PDACs are classified as having more or less than 40% glandular histogenesis, and are strongly associated with classical or basal subtypes, respectively (45). The squamous morphology found in more than 30% of invasive tumors has also been associated with basal-like tumors by several groups (16, 45). However, the mechanism by which PDAC diverges into various subtypes in the process of tumor evolution remains unclear. Recently, it has been reported that re-categorization of PDAC subtypes in a combined cohort of primary and metastatic tumors using single-cell RNAseq (scRNAseq) can lead to the extension of the two groups of basal-like and classical into five groups: “basal-like A”, “basal-like B”, “classic A”, “classic B”, and “hybrid” (46). These data sets, combined with cohort of patients with PDAC, enable the broad categorization of basal-like A and basal-like B into two disease subtypes, localized and metastatic disease, respectively. Thus, it is suggested that PDAC proceeds as a mixture of both expressed phenotypes, and that the behavior of the dominant phenotype and subtype is due to plasticity in both (46). The driver mutations for the classical and basal-like subtypes were shown to be biallelic loss of SMAD4 with GATA6 amplification, and biallelic loss of TP53 and/or CDKN2A with mutant KRAS allele amplification, respectively, but none of the features were completely exclusive (45, 46). Therefore, whereas scRNAseq analysis of precancerous lesions to determine whether these expression phenotypes are established in PanIN has not been performed to date, the early acquisition of asymmetric driver gene mutations is itself dynamic, presumably dictating PDAC behavior, suggesting that both clonality and plasticity of PDAC cells are responsible for the histological and biological heterogeneity.

Current diagnosis and treatment methods of pancreatic tumors

Symptoms of PDAC and its diagnosis

Symptoms of PDAC are often vague and nonspecific, and hence it is sometimes referred to as the ‘silent killer’; in fact, 30% to 35% of patients are diagnosed with locally advanced stages and 50% to 55% with metastatic stages of disease. Biomarkers for the early detection of PDAC have not yet been identified. The most common site of this tumor is the head of the pancreas, which causes biliary obstruction, resulting in dark urine, jaundice, appetite loss, fatigue, weight loss, and exocrine pancreatic insufficiency (47).

As early symptoms of PDAC are less frequent than those of any other cancer, and a method for its early diagnosis has not been established, multidisciplinary examinations are required to detect the pancreatic tumor. The pancreas is a digestive organ that also acts as an endocrine system, and hence has abundant blood vessels. This feature makes PDAC easy to metastasize and difficult to resect. There are four clinical stages in PDAC; 1) I–II resectable (5-year survival rate, 35%–45%), 2) II–III borderline resectable (10%–15%), 3) II–III locally advanced (10%–15%), and 4) metastatic (< 5%). Pancreas computed tomography (CT) angiography with chest and pelvis CT can be used for assessment of the vascular anatomy of the pancreas. The degree of contact between the tumor and local blood vessels is classified into three levels; uninvolved, abutted, or encased. The difference between abutment and encasement is the degree of circumferential tumor-vessel involvement; existence of the tumor more than 180 degrees around the vessel implies encasement. Magnetic resonance imaging and cholangiopancreatography are also helpful to assess the possibility of metastasis in indeterminate liver lesions, and are also useful for the identification of cancers that are poorly characterized on CT imaging (47).

Conventional treatments and ongoing notable clinical trials

Patients with nonresectable tumors are treated by chemotherapy according to their cancer stage and Eastern Cooperative Oncology Group (ECOG) performance status (48). Combinations of cytotoxic chemotherapies were developed in the previous decade and are still the basis of current treatments for metastatic pancreatic cancer (Figure 1) (49). Two multidrug regimens are now offered; FOLFIRINOX, and gemcitabine combined with nanoparticle albumin-bound paclitaxel (nab-paclitaxel). Gemcitabine alone is offered to patients with ECOG performance status 2 (within the five ECOG criteria, the groups in which patients are capable of self-care but are unable to carry out any work activities; i.e., patients are up and about > 50% of their waking hours, Figure 1). To classify patients eligible for either FOLFIRINOX or gemcitabine plus nab-paclitaxel as first-line drugs, Knox et al. demonstrated that a low level of GATA6, which is a characteristic of basal-like tumors, is a useful biomarker for selecting gemcitabine plus nab-paclitaxel in first-line therapy (50). The PASS-01 study analyzing the usefulness of GATA6 as a surrogate marker is now ongoing (NCT04469556).

Figure 1

Recent scientific advances have made incremental progress for the treatment of specific subgroups of pancreatic tumors. The American Society of Clinical Oncology guidelines updated in 2020 state three recommendations for pancreatic cancer; [1] early testing of both germline and tumor cells for microsatellite instability/mismatch repair deficiency, BRCA mutations, and NTRK gene fusions, [2] larotrectinib or entrectinib after first-line therapy for patients with tumors harboring NTRK fusions, and [3] continued treatment, including chemotherapy or olaparib, for patients with a germline BRCA1 or BRCA2 mutation who have received first-line platinum-based chemotherapy (51).

Although oncogenic KRAS mutations are observed in almost 90% of PDACs, a lack of drug-accessible pockets in the KRAS protein has hindered the development of their inhibitors for many years. However, X-ray crystallography identified a cryptic pocket of KRAS^G12C potentially useful for drug development (52, 53). A phase 1/2 clinical trial for the clinical-grade KRAS^G12C inhibitor AMG-510 (sotorasib) is currently ongoing (NCT03600883). Other drugs targeting mutant KRAS proteins are also being developed (54).

Clinical trials of immune checkpoint inhibitors (ICIs) against PDAC were started with great expectations, but let researchers down because of their limited efficacy compared with their efficacy against other solid tumors, including melanoma and lung cancer (16, 17). These disappointing results were attributed to the unique characteristics of PDAC, which are explained in the following sections. Given these facts, ICI treatment in combination with other types of agents to increase treatment efficacy have been widely considered for the treatment of PDAC (54).

The concept of targeting cancer metabolism has existed for almost a century, since Otto Warburg’s observation of aerobic glycolysis in cancer cells and Sidney Farber’s paper describing anti-folate-induced remission of childhood acute lymphocytic leukemia (55, 56). Their concepts were eclipsed for some time during which knowledge on oncogenes accumulated and molecular-targeting therapies showed substantial effects on patient survival. However, recent technological innovations leading to various omics analyses have clarified the connection between tumor-associated genes and metabolism (57). Mitochondria, which play various roles in cancer metabolism and malignancy, are typical targets of metabolic agents (58). The lipoate analogue CPI-613, which inhibits pyruvate dehydrogenase and α-ketoglutarate dehydrogenase and therefore disrupts mitochondrial function (59), is being evaluated in a phase III trial of metastatic PDAC (NCT03504423) (60). In this trial, both groups (with or without CPI-613) are treated with FOLFIRINOX, because it has been reported that CPI-613 enhances FOLFIRINOX cytotoxicity in some PDAC cell lines (14). Another treatment target of PDAC is autophagy, which is activated in PDAC (61). A clinical trial of combinatorial treatment of hydroxychloroquine, an inhibitor of lysosomal scavenging, a MEK inhibitor, and ICIs for PDAC patients is now ongoing (NCT04214418). As discussed here, the paradigm of targeting not only tumor cells but also the TME, including immune cells, could bring a bright future to PDAC therapy.

Acquisition of mesenchymal plasticity of PDAC cells, and clinical implications of EMT in PDAC

TME and mesenchymal plasticity of PDAC

A variety of stimuli, including mechanical stress, low pH, hypoxia, innate and adaptive immune responses, changes in the extracellular matrix (ECM), and treatment with antitumor drugs can activate epithelial-mesenchymal transition (EMT) in cancer cells (62). It has been shown in real clinical settings that EMT plays a role in pancreatic cancer cell dissemination to distant organs in the precancerous stage prior to and/or in parallel with primary tumor formation in PDAC (63). The fact that almost all patients who undergo complete surgical resection and are free of metastases at that time eventually die within 5 years is consistent with the early-seeding model (64–66), suggesting important roles for EMT in PDAC progression and its contribution to the poor outcome.

PDAC has been well documented to be a desmoplastic stroma consisting of a dense ECM infiltrated with heterogeneous cell populations, including immune cells, endothelial cells, and cancer-associated fibroblasts (CAFs) (67). The high density of the stroma limits oxygen supply to and diffusion in the TME, leading to the creation of a hypoxic environment. Desmoplasia is observed in the bulk of the ECM, and contains collagen, fibronectin, laminin, and hyaluronic acid. These ECM components are primarily produced by CAFs. CAFs are also involved in producing various cytokines, such as transforming growth factor β (TGF-β), IL-1, IL-6, and tumor necrosis factor, and facilitate EMT signaling pathways (68).

PDACs are characterized by hypovascular tumors in a hypoxic microenvironment, in which high interstitial fluid pressure occurs owing to desmoplasia (69). However, microvessel density (MVD) has been shown to vary considerably among PDAC tumors with its decline being associated with poor survival in inverse correlation with stromal surface area (70). The hypoxic microenvironment has broad effects on the biological behavior and malignant phenotype of PDAC, including pathological angiogenesis and metabolic reprogramming, synergistically contributing to PDAC development and therapeutic resistance. Hypoxia-inducible factors (HIFs) are essential for hypoxia-induced angiogenesis in PDAC through transcriptional activation of various angiogenic factors, such as vascular endothelial growth factor (VEGF). It has been shown that under hypoxic conditions, NF-κB activates the transcription of HIF-1α and its target gene VEGF-A, resulting in the increased secretion of VEGF, and enhanced angiogenesis in hypoxic pancreatic cancer cells (71). Phosphorylated signal transducer and activator of transcription 3 (STAT3) is also a hypoxia-responsive nuclear transcription factor that has been shown to act synergistically with HIF-1α to regulate angiogenesis under hypoxia in pancreatic cancer cells (72). Indeed, increased production of VEGF has been demonstrated in human PDAC cell lines and resected PDAC tumor tissues (73), showing that VEGF is produced under the control of activated HIF-1α and STAT3 under conditions of oxygen deprivation (74, 75). VEGF produced by human PDAC cell lines has functional activity to promote endothelial cell growth in vitro, and in large tumors in immunocompromised mouse xenograft models (76). In addition, the anti-VEGF strategy was shown to markedly reduce the growth of human PDAC cell lines orthotopically implanted into mice with a decrease in tumor MVD (77, 78). Despite these preclinical data suggesting that angiogenesis is important in PDAC, the use of anti-angiogenic agents has not been clinically successful for treating PDAC. Chronic treatment with VEGF antibodies was found to induce hypoxia and lead to increased collagen deposition, epithelial plasticity, and metastatic burden (79). These results may underly the lack of success of angiogenesis inhibitors in clinical trials of PDAC.

We previously showed that ARF6 is activated by VEGF in endothelial cells and is required for VEGF-induced tubular formation and migration. Furthermore, we have shown that ARF6 signaling is involved in choroidal neovascularization, which is a major cause of vision loss in patients with age-associated macular degeneration. We also found that ARF6 signaling is involved in VE-cadherin recycling, and may be involved in the sprouting process of angiogenesis associated with VE-cadherin-based cell-cell junctions as well as cell migration/tubular network formation activities (80). In addition, we found that high expression of the Arf6 effector AMAP1 is associated with the fibrosis of pancreatic cancer (81).

Treatment strategies for PDAC targeting angiogenesis have been pointed out as a way to normalize the tumor vasculature, such as strategies that prune immature and inefficient blood vessels, eliminate unproductive vasculature, and enable the reliable delivery of intravenous cancer drugs (82, 83). The inhibition of ARF6 signaling, which is important for pathological angiogenesis and fibrosis, may contribute to therapeutic strategies for PDAC.

Recent analyses have redefined the view that cellular senescence is the onset of the tissue remodeling that operates during normal embryonic development and tissue damage. To this end, senescent cells cease their own proliferation and recruit phagocytotic immune cells to promote tissue regeneration (84). On the other hand, it is well known that senescence is associated with cancer; in PDAC, senescence appears to produce tumor suppressive effects at the earliest stages. However, some lines of evidence indicate that senescent cells in the TME can produce a senescence-associated secretory phenotype (SASP), mediated by NF-κB and CCAAT/enhancer-binding protein-β, including the secretion of proinflammatory cytokines (IL-6 and IL-8), chemokines (monocyte chemoattractant proteins [MCPs], macrophage inflammatory proteins [MIPs], TGFβ, and granulocyte–macrophage colony-stimulating factor [GM-CSF]), and proteases (84), and play protumorigenic roles during tumor progression (85). SASPs have been shown to induce cell plasticity by stimulating cancer cell proliferation, motility, and invasion, and by generating an inflammatory TME (86). Thus, in the PDAC microenvironment, SASP may be involved in promoting EMT.

Role of EMT in PDAC metastasis

An important aspect of the EMT program in cancer biology may be its involvement in not only facilitating cellular motility and invasiveness, but also in orchestrating the cancer stem cell state (CSCs) via epithelial-mesenchymal plasticity (87–89). Mechanistically, intrinsic oncogenic mutations, epigenetic gene expression conversion, and extrinsic inflammatory signals may enable highly epithelial and highly mesenchymal non-CSCs to reversibly transition to an intermediate quasi-mesenchymal state; in the case of epithelial cells, the transition is accompanied by EMT, whereas in the case of highly mesenchymal cells, it is induced by mesenchymal-epithelial transition. Presumably, similar responses might occur in normal epithelial tissue when stem cells are lost. Thus, in the invasion-metastatic cascade, the EMT program is thought to enable the seeding of cells from the primary tumor into the parenchymal layer of distant tissues, and subsequently confers stemness, giving the disseminated tumor cells the ability to form metastatic colonies (87–89).

Although it is clear that EMT is involved in tumor metastasis, the exact function of EMT in cancer is still being debated. Indeed, some studies on the effects of the EMT-transcription factors (TFs) SNAIL and TWIST in pancreatic cancer have questioned the role of EMT in metastasis. A study using PDAC model KPC (Pdx1-cre; LSL-Kras^G12D;Tp53^R172H/+) mice, in which TWIST and SNAIL were independently conditionally knocked out, resulting in Pdx1-cre; LSL-Kras^G12D;Tp53^R172H/+;Twist1^flox/flox and Pdx1-cre; LSL-Kras^G12D;P53^R172H/+;Snai1^flox/flox mice, respectively, found that although EMT was suppressed, the deficiency of SNAIL or TWIST did not affect tumor progression, regional invasion, or dissemination. Thus, it has been argued that EMT is not required for invasive and metastatic activities of cancers. On the other hand, mice bearing abrogation of EMT-transcription factor (EMT-TF) have been shown to be correlated with chemosensitivity to gemcitabine, indicating EMT induces chemotherapy resistance in pancreatic cancer (90). Similar results have been reported in breast cancer models (91). However, other groups have shown using the same KPC mouse PDAC model that ZEB1 conditional knockout mice (Pdx1-cre; LSL-Kras^G12D;Tp53^R172H/+;Zeb1^flox/flox) have significantly reduced PanIN and PDAC formation, and invasion and metastasis, thus clearly demonstrating a crucial role for the EMT-TF ZEB1 in the PDAC progression (92). Taken together, these studies indicate a trend toward the differential functions of EMT-TF; SNAIL and TWIST do not appear to be necessary, whereas ZEB1 conversely appears to be an important factor that is not compensated by other EMT-TFs.

Metabolic characteristics of PDAC

Glucose metabolism

Glucose is the principal carbon and energy source for the growth and maintenance of mammalian cells. Glucose catabolism occurs by two metabolic pathways; glycolysis and the tricarboxylic acid (TCA) cycle. These pathways not only fuel adenosine triphosphate (ATP) production, but also produce carbon intermediates that support macromolecular biosynthesis. One contribution of oncogenic KRAS mutations to the oncogenesis and progression of pancreatic cancer is oncogenic KRAS mutation-driven metabolic rewiring. Transcriptome and metabolomic analyses indicated that the activity of oncogenic KRAS mutations promoted the upregulation of key metabolic enzymes involved in glucose metabolism, including glycolysis, hexosamine biosynthesis leading to the synthesis of uridine diphosphate N-acetyl-glucosamine, which is a significant substrate for protein glycosylation, and the pentose phosphate pathway producing NADPH and ribose 5-phosphate, which are essential for nucleic acid synthesis (10). This analysis also indicated that oncogenic KRAS mutations enhance glucose consumption in PDAC through the increase in transcription of the glucose transporter 1 (GLUT1, also known as solute carrier family 2 member 1 [SLC2A1]) the enzymes hexokinase 1 and hexokinase 2 (HK1 and HK2), and lactate dehydrogenase A (LDHA) (Figure 2). Thus, KRAS contributes to the unregulated growth of pancreatic cancer cells, and directly targeting metabolic pathways as a therapeutic target is a major challenge (93).

Figure 2

We previously showed that mutant KRAS, which is a major driver gene in PDAC cells, acts in a eukaryotic translation initiation factor 4A (eIF4A)-dependent manner to promote the translation of ARF6 mRNA, which is a member of the ARF family of GTPases with a quadruplex structure in the 5′-untranslated region, and upregulates ARF6 protein expression (94). Recently, it was also reported that silencing of ARF6 inhibits the Warburg effect, which is associated with aerobic glycolytic processes, in KRAS-mutated PDAC cells (95). The oncogene c-Myc is a transcription factor that regulates aerobic glycolysis through the upregulation of many key glycolytic genes, such as GLUT1, HK2, and LDHA (96, 97), and is associated with the transcriptional activation of ARF6. ARF6 has also been shown to be associated with the regulation of the expression of GLUT1, LDHA, and HK2, as well as c-Myc (95). Thus, it is possible that ARF6 is involved in the regulation of aerobic glycolysis via the regulation of c-Myc in PDACs. Interestingly, in several cancers, including PDAC, the upregulation of GLUT1 in cancer cells correlates with the low infiltration rate of cytotoxic CD8⁺ T cells (98–100). This suggests that tumor cells successfully compete for glucose, suppressing antitumor immunity while simultaneously maintaining high metabolic and proliferative rates (101, 102). Importantly, this also indicates that antitumor immune cells are unable to obtain sufficient energy, thus impairing their function.

As solid tumors progress, large areas of the tumor often become deprived of oxygen, which interferes with ability of the immune system to combat the tumor (103). PDAC is characterized by a very hypoxic TME, and it has been noted that the high malignancy and poor curative efficacy of PDAC are mostly due to the hypoxic TME (103, 104). PDAC also shows increased accumulation of stromal tissue, i.e., desmoplasia, which may collapse blood vessels, and subsequently impede perfusion and promote maintenance of the hypoxic TME. Hypoxia and desmoplasia induce the expression of HIF-1α and its stabilization (105). HIF-1α is a key regulator of cellular responses to changes in oxygen concentration, and supports tumor cell adaptation to hypoxia in an oxygen-deprived TME.

Under hypoxic conditions (usually below 3% to 5% O₂), the HIF-1α subunit stabilizes and forms a dimer with the β-subunit aryl hydrocarbon receptor nuclear translocator (ARNT), which translocates to the nucleus to promote O₂-regulated gene expression. HIF-1α is considered to play a crucial role in of metabolic reprogramming (106). Several studies have confirmed that HIF-1α meets the metabolic needs of pancreatic cancer cells by increasing the expression of glycolysis-associated enzymes and the production of lactate (107–110). Indeed, the stabilization of HIF-1α has been reported to induce GLUT1 expression in a HIF-1α -dependent manner, increasing cellular glucose uptake and supporting aerobic glycolysis in cancer cells (111, 112). HIF-1α is also known to enhance the expression of LDHA (113, 114) and monocarboxylate transporter 4 (MCT4; encoded by SLC16A3) (115). LDHA reduces the dependence on oxygen-dependent mitochondrial oxidative phosphorylation (OXPHOS) by converting pyruvate to lactate, and the cell preferentially uses oxygen-independent glycolytic pathways to maintain sufficient ATP production to meet bioenergetic requirements, whereas MCT4 removes lactate from the cell by transporting it out of cells. Thus, HIF-1α drives the conversion from oxidative to glycolytic metabolism during hypoxia, which is not only beneficial for bioenergetic homeostasis, but may also promote tumor survival and growth.

Interestingly, it has been shown that the stabilization of HIF-1α by di-methyl-oxaloylglycine treatment markedly increases the level of ARF6 mRNA (116), and ARF6 activity is significantly promoted under hypoxia (117). As mentioned previously, ARF6 is also associated with the enhanced expression of genes involved in glycolytic metabolism in malignant pancreatic cancer with KRAS mutations, so hypoxia may potently promote glycolytic metabolism through the induction of HIF-1α and ARF6, thereby regulating the adaptive responses to a hypoxic environment.

In addition to glucose deprivation via tumor cells in the TME, higher rates of aerobic glycolysis in tumor cells may promote the production of lactic acid, which in turn increases the acidity of the TME. Excess lactate produced in tumor cells can also suppress CD8⁺ T and NK cell activation, and enhance the function of immunosuppressive cells, such as myeloid subsets, and M2-polarized macrophages to an immunosuppressive phenotype (118, 119). This makes it difficult for immune cells to survive, but tumor cells can often adapt, survive, and multiply despite these harsh conditions. Tumor cells can respond to extracellular acidic pH conditions and regulate cellular acid homeostasis by altering the expression of proteins associated with pH regulation, such as monocarboxylate transporters and carbonic anhydrase (CA) (120). In in vitro models of melanoma, exposure to lactic acidosis has been shown to induce the EMT phenotype (121). In pancreatic cancer cells, lactate enhances the expression of IL-8 and contributes to EMT and metastasis (122–124), and tumor cells can use lactate as an alternative energy fuel to promote their proliferation (125). Indeed, high levels of lactate in PDAC have been shown to correlate with poor patient prognosis (126). Therefore, it is strongly suggested that the acidic environment in tumor tissue is involved in the acquisition of mesenchymal traits, and the augmentation of an immunosuppressive PDAC TME.

Lipid metabolism

Lipids are major components of biological molecules, and play important roles in various processes. Lipids are composed of thousands of different molecules, including phospholipids, sphingolipids, fatty acids, cholesterol, cholesteryl esters, and triglycerides. Such lipids are implicated in a variety of cellular processes, and are important components of biological membranes (127–132). Lipid uptake, accumulation, and lipogenesis are increased in various cancers, including pancreatic cancer, and provide energy for rapid tumor growth. In the early step of de novo lipid synthesis, ATP-citrate lyase (ACLY) catalyzes the conversion of citrate to acetyl-CoA, which is then converted to malonyl-CoA by acetyl-CoA carboxylase. The acyl groups of malonyl-CoA and acetyl-CoA bind to the acyl-carrier protein domain of fatty acid synthase (FASN) in an NADPH-dependent way to produce long-chain saturated fatty acid (133) (Figure 2).

Expression levels of lipogenic enzymes, including ACLY, are known to be often upregulated in PDAC (134, 135). Inhibition of ACLY activity suppresses PDAC cell growth in xenograft tumor models (136). Furthermore, PDAC patients, highly expressing FASN, have been shown to have shorter overall survival than those expressing low levels of FASN (137). Overexpression of the FASN gene may be correlated with resistance to radiotherapy and gemcitabine in pancreatic cancer patients (138), and inhibition of FASN results in high cytotoxicity of this drug. As higher lipogenic activity has been shown in PDAC cells compared with normal cells, genetic and pharmacological inhibition of FASN and other lipogenic enzymes appears to be a promising therapeutic strategy.

The mevalonate pathway (MVP) is essential for cellular lipid metabolism, including cholesterol biosynthesis and the post-translational prenylation of proteins (139). The rate-limiting enzyme in this pathway, 3-hydroxyl-3-methylglutaryl-CoA (HMG-CoA) reductase, has been considered as a prominent target for MVP inhibition, and is increased in a KRAS-driven PDAC mouse model (125, 140). Statins, which are reductase inhibitors, are used for the treatment of hypercholesterolemia (141). The anticancer effects of statins have also been analyzed in vitro in various cancer cell lines. Several studies have reported that simvastatin inhibits cancer cell proliferation by promoting apoptosis and reducing cell cycle progression via several kinds of signaling pathways, including mitochondrial apoptotic signaling pathways and the Rho signaling pathway involved in cell cycle arrest (142, 143). In addition, lipophilic statins (lovastatin, simvastatin, etc.) have been shown to be potent vaccine adjuvants via modulation of post-translational protein prenylation. Mechanistically, statins inhibit geranylgeranylation of the small GTPase Rab5, such as in antigen-presenting cells, causing inhibition of endosome maturation, sustained antigen retention, reinforced antigen presentation, and activation of T cells (144). Therefore, the MVP pathway is a potential target for cancer immunotherapy.

We have previously shown characteristic features that predict responders of MVP-based cancer treatment. We found that the Arf-GTPase ARF6, and its downstream effector AMAP1 (also called ASAP1/DDEF1), are often overexpressed in various types of cancer, including PDAC, and closely associated with poor patient survival (145–149). Interestingly, we found that the MVP is crucial for ARF6 activation in breast cancer cells. In this process, the MVP is essential for geranylgeranylation of RAB11b, which promotes intracellular trafficking of ARF6 to the plasma membrane where it is activated by RTKs. Furthermore, consistent with reports that gain-of-function mutants of p53 activate the MVP, it is clear that mutant p53 is essential for ARF6 activation (148, 150). Our in vitro experiments showed that the presence of statins improved the sensitivities of breast cancer cells to various drugs. In contrast, inhibition of MVP is ineffective when cancer cells do not overexpress components of the ARF6-based pathway. We have also shown that statins inhibit not only ARF6 activity and invasive potential but also recycling of the immune checkpoint molecule PD-L1 to the plasma membrane in pancreatic cancer cells (94). The chemopreventive effects of statins have been shown in pancreatic cancer cell lines (151–153) and pancreatic cancer model mice (154). Thus, the MVP may be crucial for promoting cancer cell invasion, metastasis, drug resistance, and PD-L1 recycling through the overexpressed ARF6 pathway activated by RTKs.

Glutamine metabolism

Glutamine addiction is common in various cancers, including PDAC (155–160). Glutamine may be a mitochondrial substrate for synthesis of macromolecules in cancer cells by supplying carbon to fuel the TCA cycle, and is a major nitrogen donor for the production of nucleotides and nonessential amino acids (155). In mitochondria, glutamine has essential roles in the synthesis of energy in the form of ATP through the TCA cycle and the OXPHOS process. Mitochondrial metabolism has been demonstrated to be important for tumor growth in several types of cancer, including PDAC (161, 162). Glutamine is the most abundant nonessential amino acid in the blood and plays various roles in cell metabolism (158, 163). Glutamine is first catalyzed to glutamate by the enzyme glutaminase. Glutamate is then converted to α-ketoglutarate through a deamination reaction catalyzed by glutamate dehydrogenase in the mitochondria. Subsequently, α-ketoglutarate enters the TCA cycle to supply metabolic intermediates, such as citrate and malate, producing NADH and FADH2 to generate ATP. Malate is converted to pyruvate leading to NADPH production, and then pyruvate is in turn transformed to lactate. Glutamine can also produce substantial amounts of the cofactor NADPH by glutaminolysis, in which malate is converted to pyruvate by malic enzyme. Glutamine-derived α-ketoglutarate is reductively carboxylated by mitochondrial isocitrate dehydrogenase 2 (IDH2) to isocitrate, which can then be isomerized to citrate. Citrate produced in the mitochondrial matrix is transported to the cytoplasm and then converted to isocitrate by aconitase in a reversible reaction. Cytosolic isocitrate is metabolized to α-ketoglutarate through cytosolic isoform of IDH1, which can also produce NADPH, which may be used for lipid synthesis. PDAC cells maintain cellular redox homeostasis, which is necessary for cell growth, by metabolizing glutamine in response to NADPH (157).

Circulating glutamine can be taken up via transporters, such as alanine-serine-cysteine transporter 2 (ASCT2, also known as SLC1A5), and can be exported or imported via large neutral amino acid transporter 1 (LAT1, also known as SLC7A5), in exchange for branched-chain amino acids (BCAAs; leucine, isoleucine, and valine). BCAAs are broken down by branched-chain amino acid transaminase 1 (BCAT1) on the cytosolic side and BCAT2 on the mitochondrial side to produce branched-chain α-keto acid and glutamate (Figure 2). Early-stage pancreatic cancer driven by mutant KRAS has been shown to increase plasma BCAA levels (164). BCAT2, but not BCAT1, has been shown to be highly expressed in PanIN and PDAC ductal cells. Thus, it has been noted that the BCAA-BCAT2 axis driven by KRAS is important for PDAC development (165). In addition, some amino acid transporters (ASCT2 and LAT1) are overexpressed in pancreatic cancer (166), and associated with poor prognosis. PDAC cells are known to be highly dependent upon glutamine for tumor growth (157, 167). However, whereas the treatment of BPTES, a glutaminase inhibitor to target the glutamine metabolism, significantly inhibited PDAC proliferation, it did not affect PDAC cell death. Glutamine deprivation has been reported to activate macropinocytosis-associated autophagy and maintain proper intracellular glutamine levels by regulating glutamine metabolism. Furthermore, both glutamine deprivation and autophagy inhibition have been shown to robustly activate apoptotic cell death (168). Glutamine plays various roles in PDAC metabolic processes, suggesting that therapeutic strategies targeting the acquisition and utilization of this amino acid may be promising. However, glutamine deprivation was shown to promote the EMT signature in vitro and in vivo through an increase in the EMT master regulator Slug via ERK signaling and ATF4 activation (169). Thus, evaluating the effects of the simultaneous inhibition of distinct aspects of glutamine metabolism, such as the induction of autophagy and EMT on PDAC growth and metastasis may lead to new therapeutic approaches.

Recently, comprehensive analysis of metabolic enzymes by large-scale targeted proteomics demonstrated an enhanced metabolic system in malignant cancers to utilize glutamine-derived nitrogen for DNA synthesis (a shift in glutamine nitrogen metabolism) (170). In malignant cancer cells, the expression level of the metabolic enzyme phosphoribosyl pyrophosphate amidotransferase (PPAT), which transfers the nitrogen from glutamine to nucleic acid precursors, was markedly increased, whereas the metabolic enzyme responsible for glutaminolysis, namely, glutaminase (GLS) was decreased, indicating a shift toward nucleotide biosynthesis. In addition, meta-analyses of human cancers have shown that PPAT is most strongly associated with malignancy among the metabolic enzymes, particularly prominent in neuroendocrine cancers, including small cell lung cancer (SCLC) (170). Interestingly, the hazard ratio for PPAT is high in pancreatic cancer, whereas GLS expression does not significantly correlate with cancer prognosis. In PDAC mouse models, GLS inhibition does not demonstrate any anti-tumor effects in vivo, indicating an adaptive metabolic network that sustains proliferation (171). In cancers in which glutamine supply from the circulation is limited, such as PDAC, glutamine synthesis mediated by glutamate ammonia ligase, an enzyme involved in de novo glutamine synthesis, and the associated nitrogen assimilation and transfer to nitrogen-containing macromolecules, such as nucleotides, has been shown to be important (172). Thus, shifts in glutamine nitrogen metabolism that promote nucleotide biosynthesis via the increased expression of PPAT while suppressing the GLS response, as demonstrated in SCLC, are important in cancer malignancy, and may be a potential therapeutic target for pancreatic cancer in a glutamine-limited environment.

Autophagy/micropinocytosis

PDACs also rely upon metabolic pathways, such as autophagy and macropinocytosis, to survive and maintain metabolic homeostasis in harsh environments, such as those with low nutrient levels, hypoxia, desmoplasia, and high interstitial pressure. Autophagy is an indispensable intracellular pathway that provides intracellular energy by degrading unnecessary organelles and macromolecules in response to stimuli, such as starvation and accumulation of unfolded proteins (173). The molecular mechanism of autophagy is strictly regulated by more than 30 autophagy-related (ATG) proteins that are responsible for the dynamic autophagy pathways, and can be divided into the following series of steps: phagophore (isolation membrane) growth, closed double-membrane vesicle (autophagosome) formation, autophagosome-lysosome fusion, degradation within the lysosome, and recycling of the degradation products.

One of the characteristic features of PDAC is known to be increased autophagy. This is because owing to the tumor microenvironment of PDAC, in which the low vascular density results in severe hypoxia and limited nutrient utilization (61, 174), PDAC cells must rewire their metabolism to sustain proliferation. Indeed, the inhibition of autophagy by the genetic or pharmacological inhibitor chloroquine (an inhibitor of lysosomal acidification) resulted in mitochondrial metabolic abnormalities leading to decreased OXPHOS, reduced proliferation in vitro, and inhibited tumor growth in vivo (61). Furthermore, the significance of autophagy in PDAC tumorigenesis was confirmed by crossing a conditional knockout mouse of the autophagy essential gene Atg5 with a PDAC mouse model (175, 176). This autophagy inhibition in mouse studies may exert anti-tumor effects by cooperating with the TME (177). Indeed, the crosstalk between stromal cells and tumor cells in PDAC is important, indicating that autophagy is required for stromal cells to secrete alanine, which is then taken up by tumor cells to support their growth (178). In a study using a PDAC mouse model expressing a tetracycline-inducible dominant-negative ATG4B protein which can reversibly and acutely inhibit autophagy in fully formed tumors, the inhibition of autophagy was shown to suppress tumor growth via intrinsic as well as extrinsic factors in tumor cells (61). This study also showed that the effect of inhibiting autophagy in the tumor itself on tumor regression was partially mediated by macrophages, indicating that induction of the immune system via autophagy inhibition is also important for the anti-tumor effects. This may mean that there is autophagy-dependent metabolic crosstalk between tumor cells and the stroma, and hence autophagy is necessary to support the metabolism, tumorigenesis, and survival under harsh conditions of tumors.

PDAC does not respond well to ICIs, such as anti-PD1 and anti-CTL4A antibodies, and typically has a highly immunosuppressive TME that is characterized by marked infiltration of myeloid-derived suppressor cells (MDSCs) and lack of active cytotoxic CD8⁺ T cells (179–182). Resistance to ICI therapy is known to be associated with major histocompatibility complex class I (MHC-I), which is essential for endogenous antigen presentation by cancer cells (183–185). PDAC cells have been shown to have reduced expression of MHC-I molecules on the cell surface, and instead localize predominantly to autophagosomes and lysosomes (186, 187). Indeed, it has been demonstrated in human and mouse PDAC that MHC-I is degraded by an autophagy-dependent mechanism to induce immune evasion (188). In addition, autophagy inhibition increased the surface levels of MHC-I, leading to the promotion of antigen presentation, enhanced anti-tumor activity of T-cell responses, and suppression of tumor growth in orthotopically transplanted syngeneic mice. Systemic autophagy inhibition by chloroquine, as well as the tumor-specific inhibition of autophagy, in combination with ICIs, showed synergistic effects. These findings provide a molecular mechanism by which autophagy promotes immune evasion, and provide a rationale for further research toward the development of new therapies targeting the autophagy-lysosome system in PDAC.

When glucose is deprived in PDAC cells, large amounts of reactive oxygen species are produced to activate autophagy, and provide the nutrients necessary for growth (189). On the other hand, glutamine starvation increases the degree of macropinocytosis in PDAC cells, and hence glutamine is important for regulating the degree of macropinocytosis in PDAC cells (190). Macropinocytosis is a process involving membrane ruffles, which are used to internalize extracellular materials, such as soluble molecules, nutrients, and antigens. After the nonspecific uptake of extracellular fluids by endocytic processes, the formation of vesicular structures, named macropinosomes, which contain the internalized proteins fuse with lysosomes, resulting in proteolytic degradation. The free amino acids produced by this process support the metabolic requirements of tumor cells (191). Thus, macropinocytosis is a nonselective endocytotic program capable of taking up content from extracellular fluid in a nutrient recycling and scavenging pathway that has been recognized as a key mechanism supporting pancreatic cancer growth (192).

PDAC cells expressing oncogenic KRAS mutation exhibited high enhancements of basal macropinocytosis consuming extracellular proteins for rapid tumor proliferation, which is closely linked to autophagy (174, 193–198). It has been shown that autophagy is required for the micropinocytosis-mediated degradation of extracellular proteins, and autophagy plays an important role in the breakdown of macromolecules internalized by macropinocytosis, to provide amino acids, particularly glutamine, in PDAC cells (168). The dynamic balance between glutamine metabolism and macropinocytosis-associated autophagy may ensure PDAC cell growth. Although these studies suggest that macropinocytosis is a potential therapeutic target for PDAC, understanding how macropinocytosis and autophagy cooperate is crucial for establishing treatments for PDAC.

ARF6 has been shown to regulate autophagy and colocalize with proteins mediating the initiation of autophagosome formation, i.e., the formation of pre-autophagosomal structures and phagophores (199, 200). Mechanistically, activation of the lipid-modifying enzyme PIP5K by ARF6 may contribute to autophagy, as PIP2 produced by PIP5K affects membrane trafficking for phagosome formation, by regulating plasma membrane endocytosis. Interestingly, ARF6 has been shown to be required for macropinocytosis in HT180 cells, a human fibrosarcoma cell line (201). In PDAC expressing high levels of ARF6, ARF6 may be a potential target for autophagy and micropinocytosis, and combination therapy, such as ICIs, may lead to a new treatment for PDAC. We also demonstrated that combination therapy with the eIF4A inhibitor silvestrol, which inhibits ARF6 protein production, and anti-PD-1 antibodies improves the efficacy of anti-PD-1 therapy in PDAC (202). However, it remains unclear whether ARF6 inhibition actually affects therapeutic efficacy by inhibiting autophagy and macropinocytosis.

Other types of metabolism

Amino acid availability in the TME, particularly arginine and tryptophan, is an important determinant of antitumor immunity. Increased arginine levels play an important role in T-cell activation by inducing metabolic changes, including a shift from glycolysis to OXPHOS, and the promotion of memory T-cell differentiation (203). Indoleamine 2,3-dioxygenase (IDO), which catalyzes the conversion of tryptophan to kynurenine, is often overexpressed in PDAC (204). Tryptophan depletion and kynurenine production in TME promote the establishment of a suppressive immune environment, and attenuate anti-tumor T-cell responses (205).

Extracellular ATP levels may be rapidly and robustly increased by hypoxia (206, 207). ATP, which has immunostimulatory properties on its own, may be ultimately converted to the nucleoside adenosine through stepwise process. Canonically, ATP is first catalyzed to AMP via the ectonucleotidase CD39. AMP is then dephosphorylated by CD73 and degraded into adenosine. Adenosine can then act on purinergic receptors, such as A1, A2a, A2b, and A3 (208), and regulates various aspects of physiology and pathophysiology (209, 210). A2a receptors and A2b receptors are primarily responsible for the downstream signaling of immunosuppression associated with intracellular cAMP accumulation (211). In PDAC, high expression of CD73 was demonstrated to be associated with an immunosuppressive TME and poor survival, as well as decreased CD4⁺, CD8⁺, and CD21⁺ TILs (212). Therefore, CD73 may also play a significant role in regulation of the immunosuppressive microenvironment of PDACs and promote their tumor progression.

Immunosuppressive TME in PDACs

The emergence of cancer immunotherapy, particularly ICIs, has offered hope to many patients with tumors that are not curable by conventional therapies. However, PDAC is known to be less sensitive to ICIs than other solid tumors, such as melanoma and lung adenocarcinoma. On the other hand, in PDAC patients, neoantigen quality has been shown to be associated with overall survival, suggesting that PDAC is associated with acquired immunity (213). In particular, the preclinical success of ICI therapy in PDAC patients with microsatellite instability (MSI high) and mismatch repair defects, as well as the therapeutic potential of autologous T-cell-based therapy in PDAC patients, holds promise for adaptive immune-based treatment strategies for PDAC (214, 215). At present, there is an ongoing study testing the effects of ICIs in patients with MSI-high PDACs (NCT02628067), which may provide insights into the subset of patients who respond to immunotherapy and the underlying mechanisms related to efficacy and resistance for ICIs. Overall, clinical results have been disappointing, but in some cases, correlative immunophenotypic studies have demonstrated that these therapies elicit adaptive T-cell responses. This suggests that immunosurveillance is operating in PDAC, however, a rational approach to countering its highly heterogenous and plastic immune evasiveness is needed.

TME of PDACs

Pancreatic cancer is known to have an immunologically cold microenvironment. Overall, immunosuppressive TME in PDAC is often associated with the presence of a tumor-promoting immune cell population (216). Analysis of PDAC mouse models has shown that the expression of oncogenic KRAS itself leads to robust inflammation, and initiates the cycle of inflammation associated with carcinogenesis (11, 179, 217, 218). Furthermore, whereas the expression of KRAS mutant during embryogenesis is sufficient to promote the onset of PDAC proliferation, chronic inflammation is required for malignant transformation in adult PDAC mouse models, indicating that oncogenic mutations alone cannot induce PDAC malignancy (97, 219, 220). Therefore, the inflammatory environment and oncogenic mutations work in concert to promote tumor progression. Thus, inflammation caused by cytokines and chemokines released from PDAC cells that have acquired mesenchymal traits is often associated with the infiltration of innate immune cells that facilitate an immunologically tolerant environment rather than an antitumor immune response (221). A low level of T-cell infiltration correlates with mortality in PDAC (222). Biochemical (production of chemokines and other factors in TME) and physical (deposition of the ECM) barriers in the stroma surrounding the TME inhibit T-cell infiltration (Figure 3).

Figure 3

Fibrosis

Although there are multiple factors that cause ICI treatment resistance, one of the main possible contributors is a dense fibrous stroma (desmoplasia) occupying 80% to 90% of the tumor mass in PDAC (223, 224). Desmoplasia is caused by the proliferation of α-smooth muscle actin-positive fibroblasts or activated pancreatic stellate cells, and work as a physical barrier against drug and immune cells. The trigger that causes these cells to proliferate is still unknown, but the communication among tumor cells and these cells have been identified. Two main components constitute desmoplasia: cells including fibroblasts and infiltrating immune cells, and noncellular proteins, such as collagen types I, III, and IV, fibronectin, and hyaluronan. A comprehensive review of the pancreatic cancer stroma has been published recently (15).

Heterogeneous fibroblasts

Fibroblasts exist in every solid organ, to maintain their morphology and function by depositing ECM proteins and secreting soluble factors (225). For instance, TGF-β secreted from fibroblasts is used by epithelial cells to cure skin injuries. Histological similarities, such as mesenchymal morphology, are maintained among fibroblasts in various organs, but their genomic landscapes differ depending on the organ in which they are located (226). Many studies have demonstrated that some fibroblasts contribute to tumor initiation, progression, and metastasis, and they are known as CAFs (227). Pancreatic cancer has a dense fibrotic architecture, and therefore, it will be useful to clarify the biology of CAFs in PDAC. Recent studies have demonstrated that the functional roles of CAFs in PDAC TME are more complicated than their expected simple tumor-promoting role (15).

Three-dimensional in vitro coculture of pancreatic stellate cells (PSCs) and KPC mouse-derived PDAC organoids induced two kinds of CAFs (228). Cocultured directly, PSCs turned into myofibroblastic CAFs (myCAFs) with highly upregulated α-SMA expression and myofibroblastic gene profiles (228). Although CAFs are thought to literally be ‘associated’ with tumors, myCAFs have anti-tumor activity (229), which requires further investigation for elucidation of the mechanism. On the other hand, indirect coculture transforms PSCs into inflammatory CAFs that display inflammatory cytokines, such as IL-6. It is thought that CAF-derived IL-6 contributes to immune evasion (228).

scRNAseq by several investigators supported the existence of these two populations, and moreover, identified two other groups, namely, mesenchymal stem cell CAFs (mscCAFs) and antigen-presenting CAFs (apCAFs) (230, 231). MscCAFs are characterized by the expression of previously identified mesenchymal stem cell markers (CD44, CD49a, CD73, and CD90), and originate from bone marrow (232). They preferentially express GM-CSF, thus promoting macrophage polarization towards an immunosuppressive phenotype that results in the inhibition of CTL activity (179, 233, 234). Coexpression of MHC class II, including CD74 and podoplanin, a pan-CAF marker, is a signature of apCAFs (230). It has recently been reported that apCAFs are derived from mesothelial cells and can induce the transformation of naïve CD4⁺ T cells into regulatory T cells by their direct ligation with a specific antigen (235). This group also demonstrated that targeting mesothelin expressed in the mesothelium may be an effective treatment owing to the inhibition of apCAF formation and regulatory T (Treg) cell induction (235).

T cells

T-cell exclusion in tumors is primarily mediated by CAFs that express fibroblast activation protein, and secrete the chemokine CXCL12 (236). Additionally, activation of integrin-binding protein and non-receptor tyrosine kinase focal adhesion kinase (FAK) is associated with increased collagen I deposition and immunosuppression (237, 238). Highly phosphorylated FAK levels in pancreatic cancer patients were associated with decreased tumor-infiltrating CD8⁺ T cells and reduced survivability (239). In addition, the expression of FAK in patients with PDAC is associated with decreased tumor cellularity and survival (239).

Acquiring a terminally differentiated T-cell state can diversely impact disease outcome, either countering tumor proliferation through antigen-limited tumor-killing immune responses, or promoting cancer progression by actively inducing immunosuppression (216, 240, 241). In particular, CD8⁺ cytotoxic T lymphocytes and polarized CD4⁺ T cells known as T helper type 1 (Th1) cells exert protective effects against tumors in PDAC mouse models, and have been shown to be associated with prolonged survival of human PDAC patients (242). Conversely, CD8⁺ T-cell deficiency, low amounts of neoantigens, and CD4⁺ Th2 and Treg cells are associated with tumor-permissive anergy (242–245). Cytokines produced by Th2, particularly IL-4 and IL-13, can not only reduce anti-tumor immune responses, but also can directly accelerate tumor growth induced by KRAS transformed cells (246). PDAC tumors are also accompanied with abundant lymphocyte infiltrates that are typically associated with the gastrointestinal mucosa (247). Th17 cells comprise approximately 5% of the CD4⁺ T cells in PDACs. The role of Th17 cells in the TME is also context-dependent. In PDAC, IL-17 secretion from γδ T cells and Th17 cells may enhance antitumor immune responses (248). However, early stages in PDAC carcinogenesis, IL-17 has a direct mitogenic effect on KRAS mutation-induced PanIN cells expressing IL-17R (218). Whereas the effects of distinct T-cell subsets depend on the underlying immune context of the tumor due to various physiological conditions and environments, and may be altered during the tumor progression of PDAC, the regulation of differentiation and function of T cells in PDAC TMEs play crucial roles in tumor immunity.

B cells and myeloid cells

To date, it has become clear that distinct cell populations derived from lymphocyte and myeloid cells can act in a pro- or anti-tumor manner, depending on the situation. B-cell subsets have become apparent as key immunomodulators in PDAC (249–252). Furthermore, suppressive myeloid cell programming is a major cause of tolerogenic T-cell programming in PDAC. Macrophages are thought to serve a major function in the induction of immunosuppression in PDAC; IL-10⁺Arg1⁺MHCII^lo tumor-associated macrophages (TAMs) are predominant in the PDAC TME, and are effective in promoting Th2 cell differentiation, but ineffective in inducing CD8⁺ T-cell immunity (253–257). Similarly, immature MDSCs, collectively referred to as bone marrow-derived Gr1^hiCD11b⁺ granulocyte lineage MDSCs, are characterized by a short half-life and strong suppressive effects in the TME (258). Although endogenous normal dendritic cells (DC) in the TME can produce anti-tumor T cells, the number of DCs in PDAC is low and probably insufficient to sustain robust adaptive immune responses. Furthermore, tumor-derived colony-stimulating factor 3 is found to inhibit the development process of DC in the bone marrow (259). Certain DC subsets have been understood as activators of immune evasiveness in PDAC. CD11b⁺CD103⁻ DCs with high expression of IL-23 and TGF-β are predominant in PDAC, drive the differentiation of FoxP3⁻ tumor-promoting type I⁺ T cells, and promote metastatic spread (260, 261). Moreover, it has been shown that Treg cells directly interact with tumor-associated DCs and suppress anti-tumor immunity by downregulation of costimulatory ligands expression that are important for activation of CD8⁺ T-cell (262).

Stimuli that recruit myeloid cells to the TME in PDAC are only partially understood. In mouse models, tumor-derived factors have been presented to accumulate MDSCs in the PDAC TME. In the same way, CCL2 produced by tumor cells and CSF1 produced by tumor-associated fibroblasts contribute to the generation of M2-like macrophages (263, 264), and CXCL1 production by tumor cells has been linked to increased myeloid cell populations and decreased tumor infiltration of cytotoxic CD8⁺ T cells (265). In particular, focusing on the CSF1-CSF1R, CCL2-CCR2, and CXC chemokine-CXCR2 axes to target in the PDAC TME may contribute to pancreatic cancer progression.

Microbiota

The normal pancreas has long been believed to be a sterile, protected site from bacteria. However, recent studies have shown that the pancreas contains bacteria that invade through the Vater’s vastus. Interestingly, it has been reported that in the inflammatory environment of PDAC, the bacterial content of pancreatic tumor tissue increases by approximately 1,000-fold compared with normal tissue (266–268). Furthermore, the bacterial species found in the tumorigenic pancreas are different from those in the gut, and low microbial diversity in the tumor results in a low survival rate of patients with PDAC, whereas high tumor microbiome diversity is associated with long-term survival (269). Mechanistically, the primary PDAC microbiome has a potent immunosuppressive effect on the inflammatory TME, driving the protumor inflammatory responses of PDACs via the activation of Toll-like receptors on bone marrow-monocyte cells, and inducing the expansion of MDSCs and anti-inflammatory M2-polarized macrophages. These innate immune cells with tolerogenic functions enhance the differentiation of immunosuppressive CD4⁺ T-cell populations and inhibit the expansion of cytotoxic CD8⁺ T cell populations (268). Consistently, microbial ablation in mice resulted in increased infiltration of Th1-polarized CD4⁺ and CD8⁺ T cells, decreased accumulation of MDSCs, and a TAM reprogrammed to a tumor-protective M1-like phenotype (268, 270). Potentially, targeting the microbiome by oral antibiotics might reverse myeloid cell-mediated adaptive immunosuppression and promote the efficacy of ICI therapy in PDAC.

Novel mechanisms bridging mesenchymal malignancy and immune evasiveness via rewiring of the metabolic program of PDAC

Immune evasion is an essential characteristic of cancer. Every day, the adult body produces mutant cells owing to genetic mutations via various intrinsic and extrinsic factors, and most mutant cells are detected and eliminated by the immune surveillance system. However, in rare cases in which mutant cells acquire traits that enable them to evade the immune surveillance system, the cells evade attack by immune cells and proliferate, eventually manifesting as cancer.

As mentioned above, the major immunosuppressive factors in the TME of PDAC include hypoxia, a low-nutrient environment, expression of immune checkpoint molecules, accumulation of immunosuppressive cell populations, such as Tregs and MDSCs, production of immunosuppressive cytokines, such as TGF-β and IL-10, immunosuppressive metabolic enzymes, such as Ido, arginase, and CD39/CD73, and metabolites, such as lactate and kynurenine. In addition, cancer-associated inflammation induced by IL-6, IL-1, IL-17, IL-22, and IL-23 is not only a driver of carcinogenesis, but is also associated with tumor progression by inducing EMT, whereby epithelial cells acquire malignant mesenchymal properties, such as detachment from other cells, invasion into adjacent tissues, and accelerated metastatic spread to other distant organs (21, 271–275). Thus, it is easy to speculate that the factors involved in the suppression of the immune environment of the TME are diverse and complex in their mechanisms of action, as they are produced not only by cancer cells, but also by the various stroma cells, including several kinds of immune cells and heterogenous fibroblasts in the TME.

On the other hand, international cancer-related consortiums, such as The Cancer Genome Atlas (TCGA) have promoted comprehensive genome-wide gene expression analyses of various cancers, but these efforts have not led to the development of effective diagnosis and treatment methods, particularly in the case of PDAC. There may be various reasons, such as the fact that the collected tissue sections are bulk preparations containing not only cancer cells but also stromal cells. Recently, the transcriptome and proteome have been compared worldwide, and it has been shown that there is a very poor correlation between the mRNA and protein levels of most genes (276–280). This strongly suggests that post-transcriptional mechanisms play an important role in the regulation of gene expression. Here, we present our studies from two different aspects on the molecular mechanisms linking the acquisition of mesenchymal plasticity and immune evasion in PDAC, with a focus on post-transcriptional mechanisms.

Functional roles of ARF6-AMAP1 axis as a mesenchymal executioner in PDAC

ARFs, a family within the Ras superfamily of small GTPases, are evolutionally the most ancient of the small GTPases. The ARFs are conserved throughout eukaryotes, including in species that branched off early, such as Giardia lamblia, in which no members of the Ras family nor heterotrimeric G-proteins are found (281, 282). Giardia lamblia is an anaerobic eukaryote parasite of the gut, which is evolutionally inferred to be an amitochondrial-type eukaryote that developed before the creation of mitochondria (283). This implies that eukaryotic cell features, such as nuclei and flagella, predate mitochondrial endosymbiosis, suggesting that ARF family molecules have been deeply involved in the maintenance of life homeostasis under anaerobic conditions during the evolution of eukaryotes. The human ARF family consists of six isoforms, ARF1–6, which are classified into three classes based on sequence homology, as follows: class I (ARF1–3), class II (ARF4–5), and class III (ARF6) (284). Class I and class II Arfs primarily regulate vesicular transport between the Golgi and endoplasmic reticulum (284, 285). Although ARF6, the only class III member, has virtually identical effector-interacting domains as the other ARFs, it is the most divergent of the ARF proteins, and predominantly localizes to the plasma membrane and recycling endosomal compartments, and functions in intracellular events associated with membrane dynamics, including recycling of plasma membrane components (including both endocytosis and recycling-back to the plasma membrane), as well as in actin-cytoskeletal rearrangement at the cell periphery (286–288).

We identified the ARFGAP protein AMAPs as molecules that are induced during macrophage differentiation, bind to the integrin-associated protein, paxillin, and are involved in its intracellular dynamics. Furthermore, we found that AMAPs are ARF6-specific ARFGAP proteins that are commonly involved in enhancement of the cell motility of macrophages and epithelial cells (289–291). In addition, we identified a novel mechanism of action in which AMAP functions as an effector of activated ARF6 through steady-state binding to GTP-bound ARF6 via its ARFGAP domain in the presence of Mg²⁺ (290, 291). Consistently, Wittinghofer and colleagues demonstrated that Ca²⁺ spikes stimulate the ARF6-specific GAP activity of AMAPs, but not other members of the ArfGAP family (292).

Subsequently, we identified GEP100 as a guanine-nucleotide exchange factor that activates Arf6 in the acquisition of invasive and metastatic traits of breast cancer cells upon activation of the epidermal growth factor (EGF)receptor pathway (145). We also identified the mechanism of action by which GEP100 activates Arf6 by binding directly to the phosphotyrosine moiety of the activated EGF receptor via the Pleckstrin-homology domain. Furthermore, we found that the simultaneous expression of Arf6 and GEP100 in MCF7 human epithelial-like breast cancer cells induced EGF-stimulation-dependent EMT-like changes. Subsequently, pathological analysis demonstrated that GEP100 expression is present in approximately 80% of invasive breast cancers (145). Our present study suggests that Arf6-based signaling pathways play an important role in the acquisition of invasive and metastatic traits via EMT induction in cancer cells. In this pathway, AMAP1 binds to different proteins, such as cortactin, and protein kinase D2 to promote cortical actin remodeling and integrin recycling (293, 294). AMAP1 also binds to EPB41L5 (148, 149), which shows increased expression during TGF-β-induced EMT (295). Furthermore, we demonstrated that the EMT-TF ZEB1 is involved in EPB41L5 gene expression, and that high expression levels of ZEB1 and EPB41L5 in cancer cells are associated with p53 mutations. This study demonstrated that the ARF6 pathway is a signaling pathway responsible for advanced cancer-specific mesenchymal traits associated with mutant p53 (296).

A series of our studies have identified that high protein levels of ARF6, AMAP1, and EPB41L5 were associated with invasiveness of several kinds of solid tumors, including breast cancer, clear cell renal cell carcinoma, lung adenocarcinoma, and PDAC and importantly that these expression levels were statistically correlates with poor prognosis (94, 145, 146, 149).

Notably, ARF6 and AMAP1 mRNAs are both rich in G/C content in their 5′-untranslated regions (UTRs) (74% and 88%, respectively) (297). Moreover, ARF6 mRNA contains a G-quadruplex structure at the 5′-UTR (94), indicating that efficient translation is dependent upon the RNA helicase eIF4A, a member of Cap-dependent translation initiation factors (298, 299). On the other hand, the 5′-UTR of AMAP1 mRNA contains a 5′-terminal oligopyrimidine-like sequence, indicating the mTOR complex 1 kinase-dependent translation control (300, 301). We found that the eIF4A inhibitor silvestrol suppresses protein levels of ARF6 in KRAS mutant cells, but only moderately in KRAS intact cells (202), and the mTOR inhibitors rapamycin and Torin1 suppress AMAP1 expression in KRAS mutant cells (94). Mechanistically, oncogenic KRAS mutations are the major cause of the aberrant overexpression of ARF6 and AMAP1, in which KRAS signaling enhances eIF4A-dependent ARF6 mRNA translation and eIF4E-dependent AMAP1 mRNA translation. In addition, gain of function mutations of TP53 promoted the activation of ARF6 by PDGF via MVP-mediated geranylgeranyl lipid modification of Rab11b in PDAC cells (94, 148). Moreover, we revealed that the ARF6-AMAP1 pathway is closely associated with immune evasion in a KPC mouse model. Thus, the cooperation between eIF4A/4E-dependent mRNA translation and MVP has been identified as a link in which representative pancreatic driver mutations empower an ARF6-based pathway, activated by external ligands, to promote tumor cell motility, PD-L1 dynamics, and immune evasion. A recent clinical study by another group confirmed the importance of ARF6 in this context (302). We hence propose that targeting eIF4A, or eIF4E, as well as mutant KRAS, provides novel methods to improve the efficacy of anti-PD-1 therapy, in which ARF6 and AMAP1 overexpression may act as biomarkers to identify patients with drug-resistant disease in PDAC. Additionally, the ARF6-AMAP1 pathway was also found to be involved in acidosis and fibrosis of the TME, both of which are well known to be barriers against immune attack to cancer cells (81, 303), indicating that the ARF6-AMAP1 pathway may also be a valuable target in modifying the TME from pro-tumor, which makes PDAC resistant to treatment, towards an anti-tumor state. Taken together, given the importance of the ARF6-AMAP1 pathway in the pathophysiology of PDAC, its clinical application as a therapeutic target may broaden options for the treatment of PDAC (Figures 2, 3).

Arid5a acts as a dual regulator in malignant PDAC to generate an immunosuppressive TME

Arid5a was identified as an RNA-binding protein that binds directly to the 3′-UTR of Il6 and stabilizes Il6 mRNA (304). Recent studies have demonstrated that Arid5a plays an important role in innate and adaptive immune responses (305). In macrophages and embryonic fibroblasts, stimulation by LPS, IL-1, and IL-6 induces Arid5a expression (304, 305). Importantly, in untreated rheumatoid arthritis (RA) patients, expression of Arid5a in CD4⁺ T cells is increased, whereas treatment with the anti-IL-6 receptor antibody tocilizumab is associated with decreased Arid5a expression (306), indicating that the IL-6-ARID5a axis may be involved in RA pathogenesis. Consistently, Arid5a has been shown to be involved in several immune-associated pathologies. For example, Arid5a deficiency reduces IL-6 production under LPS-induced endotoxemia. Furthermore, in an experimental autoimmune encephalomyelitis (EAE) model, Arid5a deficiency significantly suppresses Th17 cell differentiation and lowers IL-6 serum levels, resulting in the reduced development of EAE (304). In addition, Arid5a regulates the stability of mRNAs for other genes involved in immune regulation, such as Stat3, Tbx21, Ox40, and Il17 (307–310). In addition, IL-6 increases its own mRNA stability by increasing Arid5a levels via a positive feedback loop (311). Consistently, Arid5a-deficient mice show impaired LPS-stimulated Il6 and Ifnγ expression, and are resistant to lethal endotoxic shock (304, 308). Thus, Arid5a-mediated upregulation of these factors may be involved in the enhancement of Th1 and Th17 cell polarity and function in acute inflammatory responses and autoimmune diseases.

Several cytokines have been shown to be actively involved in metabolic reprogramming in physiological and pathological conditions (312). For example, during cancer cachexia, the overproduction of cytokines significantly increases energy expenditure and leads to weight loss (313). In particular, circulating levels of IL-6 have been shown to positively correlate with cachexia in cancer patients, and importantly, IL-6 levels were found to negatively associate with their survival (314–317). Furthermore, treatment with the humanized anti-IL-6 receptor antibody tocilizumab increased body weight and serum levels of triglycerides and cholesterol in human cancer patients (318). Il6-deficient mice have been shown to develop adult-onset obesity with impaired glucose and lipid metabolism (319). The overexpression of IL-6 in high-fat diet-induced obese mice reduced their body weight and improved their obesity-induced fatty liver and insulin resistance (320). Consistently, Arid5a^−/− mice showed reduced IL-6 production; mice with long-term loss of Arid5a developed adult-onset severe obesity. In contrast, mice with forced expression of Arid5a are highly resistant to high-fat diet-induced obesity (321). These results suggest that Arid5a is involved in IL-6-mediated metabolic regulation.

Recently, we showed that Arid5a mRNA and protein expression levels were significantly increased in mesenchymal tumor subtypes of PDAC and colorectal cancer (CRC), such as quasi-mesenchymal and consensus molecular subtype 4 subtypes, respectively. In addition, Arid5a expression was enhanced in in vitro EMT models, induced by IL-6 and TGF-β stimulation (322) (Figure 4). Furthermore, Arid5a enables mesenchymal tumor models of PDAC and CRC to facilitate immune evasiveness via promoting tumor infiltration of immunosuppressive granulocytic MDSCs (gMDSCs; also known as polymorphonuclear MDSCs (323)) and Tregs (324), and suppressing the recruitment and activation of anti-tumor effector T cells (322). Interestingly, Arid5a acts as a dual regulator leading to the formation of immunosuppressive TMEs in malignant tumors, triggering the metabolic reprograming and recruitment of suppressive immune cells. First, Arid5a induces the inhibitory effect of Ido1 on effector CD4⁺/CD8⁺ T cells via the post-transcriptional stabilization of Ido1 mRNA by binding to its 3′-UTR, and a reduction in intratumoral tryptophan concentration (325, 326). Additionally, Ido1 expression in tumor tissues promotes Treg differentiation/activation by generating kynurenine through tryptophan catabolism, and ultimately activating aryl hydrocarbon receptors (AhR) (327, 328), and AhR activation extensively mobilizes gMDSCs (329). Second, Arid5a upregulates chemokine Ccl2 expression in the TME via post-transcriptional stabilization of its mRNA, and then Ccl2 leads to enhancement of the infiltration of immunosuppressor cells, such as Tregs and gMDSCs (330–333), to the TME (322).

Figure 4

Therefore, these findings provide insights into the molecular basis of the acquisition of mesenchymal plasticity and immune evasiveness by PDAC and CRC via augmentation of the RNA-binding protein Arid5a, and indicate that Arid5a is a promising target for tumor immunotherapy, in addition to inflammatory diseases (Figure 4).

Conclusion and perspectives

In tumorigenesis, metabolic changes and chronic inflammation associated with genetic mutations in normal cells enable transformed cells to escape the homeostatic defense mechanisms of tissues, and to reprogram their intrinsic signaling mechanisms, as well as reprogram populations of stromal cells within the TME and the metabolic balance of the entire organism. In this process, tumor cell populations that adapt to the abnormal microenvironment form diverse, hierarchically organized colonies, and eventually acquire mesenchymal plasticity that promotes their dissemination, reduces the immune system’s ability to counter tumor growth, and finally directly causes death of the organism. Elucidating the metabolic adaptations that tumors rely on to promote these changes and maintain growth in a metabolically unfavorable environment, as well as the molecular mechanisms that trigger the acquisition of mesenchymal plasticity and immune evasion capacity, will help towards developing new diagnostic and therapeutic approaches and dietary combinations for the treatment of PDAC.

Increased levels of IL-6 in the serum have been associated with poor overall survival prognosis in patients with high-grade pancreatic cancer (334), and the increased activity of IL-6/STAT3-mediated signaling has been reported to be associated with poor prognosis in post-resection PDAC patients (335). IL-6 also activates STAT3 and induces the mesenchymal phenotype in human pancreatic cancer cells via the induction of SNAI1 (336). In chronic pancreatitis, IL-6/STAT3-mediated ADM transdifferentiation occurs and is associated with PanIN, which is a necessary step for the generation of tumorigenic precursor lesions (220, 337). For example, in the KRAS-induced PDAC mouse model (220, 337), pancreatic epithelial cells with constitutively active KRAS mutations (KRAS^G12D) have been reported to cause inflammatory activation by recruiting immune cells. In particular, myeloid cells have been reported to promote the production of IL-6 and soluble IL6R (sIL6R), activate STAT3 via IL-6 trans-signaling, and furthermore, the complex of IL-6 and sIL6R binds to gp130-expressing cells (220). Aberrant STAT3 activation owing to the homozygous loss of SOCS3 in the pancreas results in the accelerated progression of PanIN and the development of PDAC (220). It has also been shown that KRAS activation increases the levels of cytokines, such as IL-6 and IL-11, in epithelial cells, followed by STAT3 activation in an autocrine manner, and that STAT3-triggered matrix metallopeptidase 7 is required for tumor progression but not tumor development, and may be regulated by other STAT3 targets (337). As already mentioned, the TME of PDAC is severely hypoxic, and nutrient availability is limited by a low vascular density, so PDAC cells show increased autophagy that rewires their metabolism to enable survival in a harsh environment, and to maintain metabolic homeostasis. In a mouse model of PDAC caused by KRAS mutations, IL-6-induced STAT3 activation was shown to be involved in the increase in autophagy. As a mechanism, receptors for advanced glycation products have been reported to promote the IL-6-driven activation of STAT3 signaling in mitochondria, bridging autophagy and the IL-6/STAT3 signaling pathway (338). Furthermore, IL-6 signaling has been implicated in the pathogenesis of cachexia in PDAC patients, by inducing a metabolic rewiring (339). Thus, it is clear that the activation of IL-6/STAT3 signaling is involved in the development of PDAC from the PanIN stage, continuing to malignant transformation.

Since its approval in 2009, tocilizumab has been shown to inhibit IL-6/STAT3 signaling in patients with autoimmune diseases, such as rheumatoid arthritis caused by the overexpression of IL-6, acute inflammatory diseases caused by chimeric antigen receptor T-cell therapy, and cytokine storms associated with SARS-CoV-2 infection. On the other hand, in clinical practice, few effective therapeutics have been developed as cancer treatments targeting IL-6/STAT3 signaling (340–343). As mentioned above, cancer is caused by a complex interplay of diverse cell populations, which leads to malignant transformation. Therefore, analysis of the expression and function of molecules associated with IL-6/STAT3 activation may enable the assessment of the local malignant potential and steady state of cancer, but may not be sufficient to predict the stage and detailed course of cancer. Furthermore, it has become clear that not only IL-6/STAT3 signaling, but also various groups of molecules are involved in cancer development. The mode of interaction between these molecules also requires further study.

In the future, it will be essential to introduce spatiotemporal gene expression analysis technology that analyzes multiple cell populations, improve detection technology to analyze the associations among aging, inflammation, and metabolism, and develop artificial intelligence technology to analyze cancer development and progression, and mathematical analysis technology to integrate these technologies. To this end, it is also indispensable to enhance the convergence of life science, physical science, engineering, and computational science to create the next generation of cancer diagnostics and therapeutics.

Funding

This work was supported by Grants-in-aid from the Ministry of Education, Science, Sports and Culture of Japan to AH (grant no. 17K08614 and 22K06890) and ShH (grant no. 17K07151 and 22K07203), grants from the Suzuken Memorial Foundation to AH, and Kishimoto foundation to ShH.

Acknowledgments

We thank H.A. Popiel for critical reading of the manuscript.

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

  MurtaughLCKeefeMD. Regeneration and repair of the exocrine pancreas. Annu Rev Physiol (2015) 77:229–49. doi: 10.1146/annurev-physiol-021014-071727

  • CrossRef
  • Google Scholar
  • View reference in article

• 2

  SiegelRLMillerKDFuchsHEJemalA. Cancer statistics, 2022. CA Cancer J Clin (2022) 72(1):7–33. doi: 10.3322/caac.21708

  • CrossRef
  • Google Scholar
  • View reference in article

• 3

  ConnorAAGallingerS. Pancreatic cancer evolution and heterogeneity: Integrating omics and clinical data. Nat Rev Cancer (2022) 22(3):131–42. doi: 10.1038/s41568-021-00418-1

  • CrossRef
  • Google Scholar
  • View reference in article

• 4

  JonesSZhangXParsonsDWLinJCLearyRJAngenendtPet al. Core signaling pathways in human pancreatic cancers revealed by global genomic analyses. Science (2008) 321(5897):1801–6. doi: 10.1126/science.1164368

  • CrossRef
  • Google Scholar
  • View reference in article

• 5

  WaddellNPajicMPatchA-MChangDKKassahnKSBaileyPet al. Whole genomes redefine the mutational landscape of pancreatic cancer. Nature (2015) 518(7540):495–501. doi: 10.1038/nature14169

  • CrossRef
  • Google Scholar
  • View reference in article

• 6

  Makohon-MooreAIacobuzio-DonahueCA. Pancreatic cancer biology and genetics from an evolutionary perspective. Nat Rev Cancer (2016) 16(9):553–65. doi: 10.1038/nrc.2016.66

  • CrossRef
  • Google Scholar
  • View reference in article

• 7

  AguirreAJBardeesyNSinhaMLopezLTuvesonDAHornerJet al. Activated kras and Ink4a/Arf deficiency cooperate to produce metastatic pancreatic ductal adenocarcinoma. Genes Dev (2003) 17(24):3112–26. doi: 10.1101/gad.1158703

  • CrossRef
  • Google Scholar
  • View reference in article

• 8

  HingoraniSRPetricoinEFMaitraARajapakseVKingCJacobetzMAet al. Preinvasive and invasive ductal pancreatic cancer and its early detection in the mouse. Cancer Cell (2003) 4(6):437–50. doi: 10.1016/s1535-6108(03)00309-x

  • CrossRef
  • Google Scholar
  • View reference in article

• 9

  BryantKLManciasJDKimmelmanACDerCJ. Kras: Feeding pancreatic cancer proliferation. Trends Biochem Sci (2014) 39(2):91–100. doi: 10.1016/j.tibs.2013.12.004

  • CrossRef
  • Google Scholar
  • View reference in article

• 10

  YingHKimmelmanACLyssiotisCAHuaSChuGCFletcher-SananikoneEet al. Oncogenic kras maintains pancreatic tumors through regulation of anabolic glucose metabolism. Cell (2012) 149(3):656–70. doi: 10.1016/j.cell.2012.01.058

  • CrossRef
  • Google Scholar
  • View reference in article

• 11

  TapeCJLingSDimitriadiMMcMahonKMWorboysJDLeongHSet al. Oncogenic kras regulates tumor cell signaling Via stromal reciprocation. Cell (2016) 165(4):910–20. doi: 10.1016/j.cell.2016.03.029

  • CrossRef
  • Google Scholar
  • View reference in article

• 12

  HidalgoM. Pancreatic cancer. N Engl J Med (2010) 362(17):1605–17. doi: 10.1056/NEJMra0901557

  • CrossRef
  • Google Scholar
  • View reference in article

• 13

  WeissmuellerSManchadoESaborowskiMJPtMWagenblastECADet al. Mutant P53 drives pancreatic cancer metastasis through cell-autonomous pdgf receptor beta signaling. Cell (2014) 157(2):382–94. doi: 10.1016/j.cell.2014.01.066

  • CrossRef
  • Google Scholar
  • View reference in article

• 14

  AlistarAMorrisBBDesnoyerRKlepinHDHosseinzadehKClarkCet al. Safety and tolerability of the first-in-Class agent cpi-613 in combination with modified folfirinox in patients with metastatic pancreatic cancer: A single-centre, open-label, dose-escalation, phase 1 trial. Lancet Oncol (2017) 18(6):770–8. doi: 10.1016/s1470-2045(17)30314-5

  • CrossRef
  • Google Scholar
  • View reference in article

• 15

  HoseinANBrekkenRAMaitraA. Pancreatic cancer stroma: An update on therapeutic targeting strategies. Nat Rev Gastroenterol Hepatol (2020) 17(8):487–505. doi: 10.1038/s41575-020-0300-1

  • CrossRef
  • Google Scholar
  • View reference in article

• 16

  BrahmerJRTykodiSSChowLQHwuWJTopalianSLHwuPet al. Safety and activity of anti-Pd-L1 antibody in patients with advanced cancer. N Engl J Med (2012) 366(26):2455–65. doi: 10.1056/NEJMoa1200694

  • CrossRef
  • Google Scholar
  • View reference in article

• 17

  RoyalRELevyCTurnerKMathurAHughesMKammulaUSet al. Phase 2 trial of single agent ipilimumab (Anti-Ctla-4) for locally advanced or metastatic pancreatic adenocarcinoma. J Immunother (2010) 33(8):828–33. doi: 10.1097/CJI.0b013e3181eec14c

  • CrossRef
  • Google Scholar
  • View reference in article

• 18

  O’ReillyEMOhD-YDhaniNRenoufDJLeeMASunWet al. Durvalumab with or without tremelimumab for patients with metastatic pancreatic ductal adenocarcinoma: A phase 2 randomized clinical trial. JAMA Oncol (2019) 5(10):1431–8. doi: 10.1001/jamaoncol.2019.1588

  • CrossRef
  • Google Scholar
  • View reference in article

• 19

  HoWJJaffeeEMZhengL. The tumour microenvironment in pancreatic cancer - clinical challenges and opportunities. Nat Rev Clin Oncol (2020) 17(9):527–40. doi: 10.1038/s41571-020-0363-5

  • CrossRef
  • Google Scholar
  • View reference in article

• 20

  HalbrookCJLyssiotisCA. Employing metabolism to improve the diagnosis and treatment of pancreatic cancer. Cancer Cell (2017) 31(1):5–19. doi: 10.1016/j.ccell.2016.12.006

  • CrossRef
  • Google Scholar
  • View reference in article

• 21

  ShibueTWeinbergRA. Emt, cscs, and drug resistance: The mechanistic link and clinical implications. Nat Rev Clin Oncol (2017) 14(10):611–29. doi: 10.1038/nrclinonc.2017.44

  • CrossRef
  • Google Scholar
  • View reference in article

• 22

  CollissonEASadanandamAOlsonPGibbWJTruittMGuSet al. Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy. Nat Med (2011) 17(4):500–3. doi: 10.1038/nm.2344

  • CrossRef
  • Google Scholar
  • View reference in article

• 23

  MoffittRAMarayatiRFlateELVolmarKELoezaSGHoadleyKAet al. Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma. Nat Genet (2015) 47(10):1168–78. doi: 10.1038/ng.3398

  • CrossRef
  • Google Scholar
  • View reference in article

• 24

  BaileyPChangDKNonesKJohnsALPatchA-MGingrasM-Cet al. Genomic analyses identify molecular subtypes of pancreatic cancer. Nature (2016) 531(7592):47–52. doi: 10.1038/nature16965

  • CrossRef
  • Google Scholar
  • View reference in article

• 25

  Cancer Genome Atlas Research NetworkElectronic address aadhe, Cancer Genome Atlas Research N. Integrated genomic characterization of pancreatic ductal adenocarcinoma. Cancer Cell (2017) 32(2):185–203.e13. doi: 10.1016/j.ccell.2017.07.007

  • CrossRef
  • Google Scholar
  • View reference in article

• 26

  DaemenAPetersonDSahuNMcCordRDuXLiuBet al. Metabolite profiling stratifies pancreatic ductal adenocarcinomas into subtypes with distinct sensitivities to metabolic inhibitors. Proc Natl Acad Sci USA (2015) 112(32):E4410–7. doi: 10.1073/pnas.1501605112

  • CrossRef
  • Google Scholar
  • View reference in article

• 27

  KarasinskaJMTophamJTKallogerSEJangGHDenrocheRECulibrkLet al. Altered gene expression along the glycolysis-cholesterol synthesis axis is associated with outcome in pancreatic cancer. Clin Cancer Res (2020) 26(1):135–46. doi: 10.1158/1078-0432.CCR-19-1543

  • CrossRef
  • Google Scholar
  • View reference in article

• 28

  ZhaoLZhaoHYanH. Gene expression profiling of 1200 pancreatic ductal adenocarcinoma reveals novel subtypes. BMC Cancer (2018) 18(1):603. doi: 10.1186/s12885-018-4546-8

  • CrossRef
  • Google Scholar
  • View reference in article

• 29

  VialeAPettazzoniPLyssiotisCAYingHSanchezNMarchesiniMet al. Oncogene ablation-resistant pancreatic cancer cells depend on mitochondrial function. Nature (2014) 514(7524):628–32. doi: 10.1038/nature13611

  • CrossRef
  • Google Scholar
  • View reference in article

• 30

  HrubanRHGogginsMParsonsJKernSE. Progression model for pancreatic cancer. Clin Cancer Res (2000) 6(8):2969–72.

  • Google Scholar
  • View reference in article

• 31

  MurphySJHartSNLimaJFKippBRKlebigMWintersJLet al. Genetic alterations associated with progression from pancreatic intraepithelial neoplasia to invasive pancreatic tumor. Gastroenterology (2013) 145(5):1098–109.e1. doi: 10.1053/j.gastro.2013.07.049

  • CrossRef
  • Google Scholar
  • View reference in article

• 32

  WilentzREGeradtsJMaynardROfferhausGJKangMGogginsMet al. Inactivation of the P16 (Ink4a) tumor-suppressor gene in pancreatic duct lesions: Loss of intranuclear expression. Cancer Res (1998) 58(20):4740–4.

  • Google Scholar
  • View reference in article

• 33

  AmatoEMolinMDMafficiniAYuJMalleoGRusevBet al. Targeted next-generation sequencing of cancer genes dissects the molecular profiles of intraductal papillary neoplasms of the pancreas. J Pathol (2014) 233(3):217–27. doi: 10.1002/path.4344

  • CrossRef
  • Google Scholar
  • View reference in article

• 34

  WuJMatthaeiHMaitraADal MolinMWoodLDEshlemanJRet al. Recurrent gnas mutations define an unexpected pathway for pancreatic cyst development. Sci Transl Med (2011) 3(92):92ra66. doi: 10.1126/scitranslmed.3002543

  • CrossRef
  • Google Scholar
  • View reference in article

• 35

  FurukawaTKubokiYTanjiEYoshidaSHatoriTYamamotoMet al. Whole-exome sequencing uncovers frequent gnas mutations in intraductal papillary mucinous neoplasms of the pancreas. Sci Rep (2011) 1:161. doi: 10.1038/srep00161

  • CrossRef
  • Google Scholar
  • View reference in article

• 36

  WuJJiaoYDal MolinMMaitraAde WildeRFWoodLDet al. Whole-exome sequencing of neoplastic cysts of the pancreas reveals recurrent mutations in components of ubiquitin-dependent pathways. Proc Natl Acad Sci U S A (2011) 108(52):21188–93. doi: 10.1073/pnas.1118046108

  • CrossRef
  • Google Scholar
  • View reference in article

• 37

  ZhouQMeltonDA. Pancreas regeneration. Nature (2018) 557(7705):351–8. doi: 10.1038/s41586-018-0088-0

  • CrossRef
  • Google Scholar
  • View reference in article

• 38

  ZhouQBrownJKanarekARajagopalJMeltonDA. In vivo reprogramming of adult pancreatic exocrine cells to beta-cells. Nature (2008) 455(7213):627–32. doi: 10.1038/nature07314

  • CrossRef
  • Google Scholar
  • View reference in article

• 39

  ParsaILongneckerDSScarpelliDGPourPReddyJKLefkowitzM. Ductal metaplasia of human exocrine pancreas and its association with carcinoma. Cancer Res (1985) 45(3):1285–90.

  • Google Scholar
  • View reference in article

• 40

  GreerRLStaleyBKLiouAHebrokM. Numb regulates acinar cell dedifferentiation and survival during pancreatic damage and acinar-to-Ductal metaplasia. Gastroenterology (2013) 145(5):1088–97.e8. doi: 10.1053/j.gastro.2013.07.027

  • CrossRef
  • Google Scholar
  • View reference in article

• 41

  StangerBZHebrokM. Control of cell identity in pancreas development and regeneration. Gastroenterology (2013) 144(6):1170–9. doi: 10.1053/j.gastro.2013.01.074

  • CrossRef
  • Google Scholar
  • View reference in article

• 42

  RoomanIRealFX. Pancreatic ductal adenocarcinoma and acinar cells: A matter of differentiation and development? Gut (2012) 61(3):449–58. doi: 10.1136/gut.2010.235804

  • CrossRef
  • Google Scholar
  • View reference in article

• 43

  LiouGYDopplerHNecelaBKrishnaMCrawfordHCRaimondoMet al. Macrophage-secreted cytokines drive pancreatic acinar-to-Ductal metaplasia through nf-kappab and mmps. J Cell Biol (2013) 202(3):563–77. doi: 10.1083/jcb.201301001

  • CrossRef
  • Google Scholar
  • View reference in article

• 44

  ConnorAADenrocheREJangGHLemireMZhangAChan-Seng-YueMet al. Integration of genomic and transcriptional features in pancreatic cancer reveals increased cell cycle progression in metastases. Cancer Cell (2019) 35(2):267–82.e7. doi: 10.1016/j.ccell.2018.12.010

  • CrossRef
  • Google Scholar
  • View reference in article

• 45

  NKSWilsonGWGrantRCSetoMO'KaneGVajpeyiRet al. Morphological classification of pancreatic ductal adenocarcinoma that predicts molecular subtypes and correlates with clinical outcome. Gut (2020) 69(2):317–28. doi: 10.1136/gutjnl-2019-318217

  • CrossRef
  • Google Scholar
  • View reference in article

• 46

  Chan-Seng-YueMKimJCWilsonGWNgKFigueroaEFO'KaneGMet al. Transcription phenotypes of pancreatic cancer are driven by genomic events during tumor evolution. Nat Genet (2020) 52(2):231–40. doi: 10.1038/s41588-019-0566-9

  • CrossRef
  • Google Scholar
  • View reference in article

• 47

  ParkWChawlaAO’ReillyEM. Pancreatic cancer: A review. JAMA (2021) 326(9):851–62. doi: 10.1001/jama.2021.13027

  • CrossRef
  • Google Scholar
  • View reference in article

• 48

  OkenMMCreechRHTormeyDCHortonJDavisTEMcFaddenETet al. Toxicity and response criteria of the Eastern cooperative oncology group. Am J Clin Oncol (1982) 5(6):649–55.

  • Google Scholar
  • View reference in article

• 49

  NeoptolemosJPKleeffJMichlPCostelloEGreenhalfWPalmerDH. Therapeutic developments in pancreatic cancer: Current and future perspectives. Nat Rev Gastroenterol Hepatol (2018) 15(6):333–48. doi: 10.1038/s41575-018-0005-x

  • CrossRef
  • Google Scholar
  • View reference in article

• 50

  O’KaneGMGrünwaldBTJangG-HMasoomianMPicardoSGrantRCet al. Gata6 expression distinguishes classical and basal-like subtypes in advanced pancreatic cancer. Clin Cancer Res (2020) 26(18):4901–10. doi: 10.1158/1078-0432.Ccr-19-3724

  • CrossRef
  • Google Scholar
  • View reference in article

• 51

  SohalDPSKennedyEBCinarPConroyTCopurMSCraneCHet al. Metastatic pancreatic cancer: Asco guideline update. J Clin Oncol (2020) 38(27):3217–30. doi: 10.1200/jco.20.01364

  • CrossRef
  • Google Scholar
  • View reference in article

• 52

  CanonJRexKSaikiAYMohrCCookeKBagalDet al. The clinical Kras(G12c) inhibitor amg 510 drives anti-tumour immunity. Nature (2019) 575(7781):217–23. doi: 10.1038/s41586-019-1694-1

  • CrossRef
  • Google Scholar
  • View reference in article

• 53

  LanmanBAAllenJRAllenJGAmegadzieAKAshtonKSBookerSKet al. Discovery of a covalent inhibitor of Krasg12c (Amg 510) for the treatment of solid tumors. J Medicinal Chem (2020) 63(1):52–65. doi: 10.1021/acs.jmedchem.9b01180

  • CrossRef
  • Google Scholar
  • View reference in article

• 54

  HofmannMHGerlachDMisaleSPetronczkiMKrautN. Expanding the reach of precision oncology by drugging all kras mutants. Cancer Discov (2022) 12(4):924–37. doi: 10.1158/2159-8290.Cd-21-1331

  • CrossRef
  • Google Scholar
  • View reference in article

• 55

  LandauBRLaszloJStengleJBurkD. Certain metabolic and pharmacologic effects in cancer patients given infusions of 2-Deoxy-D-Glucose. JNCI: J Natl Cancer Institute (1958) 21(3):485–94. doi: 10.1093/jnci/21.3.485

  • CrossRef
  • Google Scholar
  • View reference in article

• 56

  FarberSDiamondLKMercerRDSylvesterRFWolffJA. Temporary remissions in acute leukemia in children produced by folic acid antagonist, 4-Aminopteroyl-Glutamic acid (Aminopterin). New Engl J Med (1948) 238(23):787–93. doi: 10.1056/nejm194806032382301

  • CrossRef
  • Google Scholar
  • View reference in article

• 57

  DeBerardinisRJChandelNS. Fundamentals of cancer metabolism. Sci Adv (2016) 2(5):e1600200. doi: 10.1126/sciadv.1600200

  • CrossRef
  • Google Scholar
  • View reference in article

• 58

  Encarnación-RosadoJKimmelmanAC. Harnessing metabolic dependencies in pancreatic cancers. Nat Rev Gastroenterol Hepatol (2021) 18(7):482–92. doi: 10.1038/s41575-021-00431-7

  • CrossRef
  • Google Scholar
  • View reference in article

• 59

  ZacharZMarecekJMaturoCGuptaSStuartSDHowellKet al. Non-Redox-Active lipoate derivates disrupt cancer cell mitochondrial metabolism and are potent anticancer agents in vivo. J Mol Med (Berl) (2011) 89(11):1137–48. doi: 10.1007/s00109-011-0785-8

  • CrossRef
  • Google Scholar
  • View reference in article

• 60

  PhilipPABuyseMEAlistarATRocha LimaCMLutherSPardeeTSet al. A phase iii open-label trial to evaluate efficacy and safety of cpi-613 plus modified folfirinox (Mffx) versus folfirinox (Ffx) in patients with metastatic adenocarcinoma of the pancreas. Future Oncol (2019) 15(28):3189–96. doi: 10.2217/fon-2019-0209

  • CrossRef
  • Google Scholar
  • View reference in article

• 61

  YangSWangXContinoGLiesaMSahinEYingHet al. Pancreatic cancers require autophagy for tumor growth. Genes Dev (2011) 25(7):717–29. doi: 10.1101/gad.2016111

  • CrossRef
  • Google Scholar
  • View reference in article

• 62

  MarcucciFStassiGDe MariaR. Epithelial–mesenchymal transition: A new target in anticancer drug discovery. Nat Rev Drug Discovery (2016) 15(5):311–25. doi: 10.1038/nrd.2015.13

  • CrossRef
  • Google Scholar
  • View reference in article

• 63

  RhimADMirekETAielloNMMaitraABaileyJMMcAllisterFet al. Emt and dissemination precede pancreatic tumor formation. Cell (2012) 148(1-2):349–61. doi: 10.1016/j.cell.2011.11.025

  • CrossRef
  • Google Scholar
  • View reference in article

• 64

  DucreuxMCuhnaASCaramellaCHollebecqueABurtinPGoereDet al. Cancer of the pancreas: Esmo clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol (2015) 26 Suppl 5:v56–68. doi: 10.1093/annonc/mdv295

  • CrossRef
  • Google Scholar
  • View reference in article

• 65

  LutfiWTalamontiMSKantorOWangCHLiederbachEStockerSJet al. Perioperative chemotherapy is associated with a survival advantage in early stage adenocarcinoma of the pancreatic head. Surgery (2016) 160(3):714–24. doi: 10.1016/j.surg.2016.05.029

  • CrossRef
  • Google Scholar
  • View reference in article

• 66

  StrobelONeoptolemosJJägerDBüchlerMW. Optimizing the outcomes of pancreatic cancer surgery. Nat Rev Clin Oncol (2019) 16(1):11–26. doi: 10.1038/s41571-018-0112-1

  • CrossRef
  • Google Scholar
  • View reference in article

• 67

  FeigCGopinathanANeesseAChanDSCookNTuvesonDA. The pancreas cancer microenvironment. Clin Cancer Res (2012) 18(16):4266–76. doi: 10.1158/1078-0432.CCR-11-3114

  • CrossRef
  • Google Scholar
  • View reference in article

• 68

  BulleALimK-H. Beyond just a tight fortress: Contribution of stroma to epithelial-mesenchymal transition in pancreatic cancer. Signal Transduct Target Ther (2020) 5(1):249. doi: 10.1038/s41392-020-00341-1

  • CrossRef
  • Google Scholar
  • View reference in article

• 69

  Di MaggioFArumugamPDelvecchioFRBatistaSLechertierTHodivala-DilkeKet al. Pancreatic stellate cells regulate blood vessel density in the stroma of pancreatic ductal adenocarcinoma. Pancreatology (2016) 16(6):995–1004. doi: 10.1016/j.pan.2016.05.393

  • CrossRef
  • Google Scholar
  • View reference in article

• 70

  NishidaTYoshitomiHTakanoSKagawaSShimizuHOhtsukaMet al. Low stromal area and high stromal microvessel density predict poor prognosis in pancreatic cancer. Pancreas (2016) 45(4):593–600. doi: 10.1097/mpa.0000000000000499

  • CrossRef
  • Google Scholar
  • View reference in article

• 71

  AzoiteiNBecherASteinestelKRouhiADiepoldKGenzeFet al. Pkm2 promotes tumor angiogenesis by regulating hif-1α through nf-Kb activation. Mol Cancer (2016) 15:3. doi: 10.1186/s12943-015-0490-2

  • CrossRef
  • Google Scholar
  • View reference in article

• 72

  WenZHuangCXuYXiaoYTangLDaiJet al. A-solanine inhibits vascular endothelial growth factor expression by down-regulating the Erk1/2-Hif-1α and Stat3 signaling pathways. Eur J Pharmacol (2016) 771:93–8. doi: 10.1016/j.ejphar.2015.12.020

  • CrossRef
  • Google Scholar
  • View reference in article

• 73

  ItakuraJIshiwataTFriessHFujiiHMatsumotoYBüchlerMWet al. Enhanced expression of vascular endothelial growth factor in human pancreatic cancer correlates with local disease progression. Clin Cancer Res (1997) 3(8):1309–16.

  • Google Scholar
  • View reference in article

• 74

  BüchlerPReberHABüchlerMShrinkanteSBüchlerMWFriessHet al. Hypoxia-inducible factor 1 regulates vascular endothelial growth factor expression in human pancreatic cancer. Pancreas (2003) 26(1):56–64. doi: 10.1097/00006676-200301000-00010

  • CrossRef
  • Google Scholar
  • View reference in article

• 75

  WeiDLeXZhengLWangLFreyJAGaoACet al. Stat3 activation regulates the expression of vascular endothelial growth factor and human pancreatic cancer angiogenesis and metastasis. Oncogene (2003) 22(3):319–29. doi: 10.1038/sj.onc.1206122

  • CrossRef
  • Google Scholar
  • View reference in article

• 76

  LuoJGuoPMatsudaKTruongNLeeAChunCet al. Pancreatic cancer cell-derived vascular endothelial growth factor is biologically active in vitro and enhances tumorigenicity in vivo. Int J Cancer (2001) 92(3):361–9. doi: 10.1002/ijc.1202

  • CrossRef
  • Google Scholar
  • View reference in article

• 77

  FukasawaMKorcM. Vascular endothelial growth factor-trap suppresses tumorigenicity of multiple pancreatic cancer cell lines. Clin Cancer Res (2004) 10(10):3327–32. doi: 10.1158/1078-0432.Ccr-03-0820

  • CrossRef
  • Google Scholar
  • View reference in article

• 78

  BockhornMTsuzukiYXuLFrillingABroelschCEFukumuraD. Differential vascular and transcriptional responses to anti-vascular endothelial growth factor antibody in orthotopic human pancreatic cancer xenografts. Clin Cancer Res (2003) 9(11):4221–6.

  • Google Scholar

• 79

  AguileraKYRiveraLBHurHCarbonJGToombsJEGoldsteinCDet al. Collagen signaling enhances tumor progression after anti-vegf therapy in a murine model of pancreatic ductal adenocarcinoma. Cancer Res (2014) 74(4):1032–44. doi: 10.1158/0008-5472.Can-13-2800

  • CrossRef
  • Google Scholar

• 80

  HashimotoAHashimotoSAndoRNodaKOgawaEKotaniHet al. Gep100-Arf6-Amap1-Cortactin pathway frequently used in cancer invasion is activated by Vegfr2 to promote angiogenesis. PLoS One (2011) 6(8):e23359. doi: 10.1371/journal.pone.0023359

  • CrossRef
  • Google Scholar

• 81

  TsutahoAHashimotoAHashimotoSHataSKachiSHiranoSet al. High expression of Amap1, an Arf6 effector, is associated with elevated levels of pd-L1 and fibrosis of pancreatic cancer. Cell Communication Signaling (2020) 18(1):101. doi: 10.1186/s12964-020-00608-8

  • CrossRef
  • Google Scholar

• 82

  JainRK. Normalizing tumor vasculature with anti-angiogenic therapy: A new paradigm for combination therapy. Nat Med (2001) 7(9):987–9. doi: 10.1038/nm0901-987

  • CrossRef
  • Google Scholar

• 83

  JainRK. Normalization of tumor vasculature: An emerging concept in antiangiogenic therapy. Science (2005) 307(5706):58–62. doi: 10.1126/science.1104819

  • CrossRef
  • Google Scholar

• 84

  Muñoz-EspínDSerranoM. Cellular senescence: From physiology to pathology. Nat Rev Mol Cell Biol (2014) 15(7):482–96. doi: 10.1038/nrm3823

  • CrossRef
  • Google Scholar

• 85

  PorciunculaAHajduCDavidG. The dual role of senescence in pancreatic ductal adenocarcinoma. Adv Cancer Res (2016) 131:1–20. doi: 10.1016/bs.acr.2016.05.006

  • CrossRef
  • Google Scholar

• 86

  RitschkaBStorerMMasAHeinzmannFOrtellsMCMortonJPet al. The senescence-associated secretory phenotype induces cellular plasticity and tissue regeneration. Genes Dev (2017) 31(2):172–83. doi: 10.1101/gad.290635.116

  • CrossRef
  • Google Scholar

• 87

  NietoMA. Epithelial plasticity: A common theme in embryonic and cancer cells. Science (2013) 342(6159):1234850. doi: 10.1126/science.1234850

  • CrossRef
  • Google Scholar

• 88

  LuWKangY. Epithelial-mesenchymal plasticity in cancer progression and metastasis. Dev Cell (2019) 49(3):361–74. doi: 10.1016/j.devcel.2019.04.010

  • CrossRef
  • Google Scholar

• 89

  LambertAWWeinbergRA. Linking emt programmes to normal and neoplastic epithelial stem cells. Nat Rev Cancer (2021) 21(5):325–38. doi: 10.1038/s41568-021-00332-6

  • CrossRef
  • Google Scholar

• 90

  ZhengXCarstensJLKimJScheibleMKayeJSugimotoHet al. Epithelial-to-Mesenchymal transition is dispensable for metastasis but induces chemoresistance in pancreatic cancer. Nature (2015) 527(7579):525–30. doi: 10.1038/nature16064

  • CrossRef
  • Google Scholar

• 91

  FischerKRDurransALeeSShengJLiFWongSTet al. Epithelial-to-Mesenchymal transition is not required for lung metastasis but contributes to chemoresistance. Nature (2015) 527(7579):472–6. doi: 10.1038/nature15748

  • CrossRef
  • Google Scholar

• 92

  KrebsAMMitschkeJLasierra LosadaMSchmalhoferOBoerriesMBuschHet al. The emt-activator Zeb1 is a key factor for cell plasticity and promotes metastasis in pancreatic cancer. Nat Cell Biol (2017) 19(5):518–29. doi: 10.1038/ncb3513

  • CrossRef
  • Google Scholar

• 93

  LiangCQinYZhangBJiSShiSXuWet al. Energy sources identify metabolic phenotypes in pancreatic cancer. Acta Biochim Biophys Sin (Shanghai) (2016) 48(11):969–79. doi: 10.1093/abbs/gmw097

  • CrossRef
  • Google Scholar

• 94

  HashimotoSFurukawaSHashimotoATsutahoAFukaoASakamuraYet al. Arf6 and Amap1 are major targets of kras and Tp53 mutations to promote invasion, pd-L1 dynamics, and immune evasion of pancreatic cancer. Proc Natl Acad Sci USA (2019) 116(35):17450–9. doi: 10.1073/pnas.1901765116

  • CrossRef
  • Google Scholar

• 95

  LiangCQinYZhangBJiSShiSXuWet al. Arf6, induced by mutant kras, promotes proliferation and warburg effect in pancreatic cancer. Cancer Lett (2017) 388:303–11. doi: 10.1016/j.canlet.2016.12.014

  • CrossRef
  • Google Scholar

• 96

  OsthusRCShimHKimSLiQReddyRMukherjeeMet al. Deregulation of glucose transporter 1 and glycolytic gene expression by c-myc. J Biol Chem (2000) 275(29):21797–800. doi: 10.1074/jbc.C000023200

  • CrossRef
  • Google Scholar

• 97

  GuerraCSchuhmacherAJCañameroMGrippoPJVerdaguerLPérez-GallegoLet al. Chronic pancreatitis is essential for induction of pancreatic ductal adenocarcinoma by K-ras oncogenes in adult mice. Cancer Cell (2007) 11(3):291–302. doi: 10.1016/j.ccr.2007.01.012

  • CrossRef
  • Google Scholar

• 98

  Davis-YadleyAHAbbottAMPimientoJMChenDTMalafaMP. Increased expression of the glucose transporter type 1 gene is associated with worse overall survival in resected pancreatic adenocarcinoma. Pancreas (2016) 45(7):974–9. doi: 10.1097/MPA.0000000000000580

  • CrossRef
  • Google Scholar

• 99

  LuKYangJLiDCHeSBZhuDMZhangLFet al. Expression and clinical significance of glucose transporter-1 in pancreatic cancer. Oncol Lett (2016) 12(1):243–9. doi: 10.3892/ol.2016.4586

  • CrossRef
  • Google Scholar

• 100

  LiFHeCYaoHLiangWYeXRuanJet al. Glut1 regulates the tumor immune microenvironment and promotes tumor metastasis in pancreatic adenocarcinoma Via ncrna-mediated network. J Cancer (2022) 13(8):2540–58. doi: 10.7150/jca.72161

  • CrossRef
  • Google Scholar

• 101

  ChangCHQiuJO'SullivanDBuckMDNoguchiTCurtisJDet al. Metabolic competition in the tumor microenvironment is a driver of cancer progression. Cell (2015) 162(6):1229–41. doi: 10.1016/j.cell.2015.08.016

  • CrossRef
  • Google Scholar

• 102

  HoPCBihuniakJDMacintyreANStaronMLiuXAmezquitaRet al. Phosphoenolpyruvate is a metabolic checkpoint of anti-tumor T cell responses. Cell (2015) 162(6):1217–28. doi: 10.1016/j.cell.2015.08.012

  • CrossRef
  • Google Scholar

• 103

  KoongACMehtaVKLeQTFisherGATerrisDJBrownJMet al. Pancreatic tumors show high levels of hypoxia. Int J Radiat Oncol Biol Phys (2000) 48(4):919–22. doi: 10.1016/s0360-3016(00)00803-8

  • CrossRef
  • Google Scholar

• 104

  DauerPNomuraASalujaABanerjeeS. Microenvironment in determining chemo-resistance in pancreatic cancer: Neighborhood matters. Pancreatology (2017) 17(1):7–12. doi: 10.1016/j.pan.2016.12.010

  • CrossRef
  • Google Scholar

• 105

  SemenzaGL. Defining the role of hypoxia-inducible factor 1 in cancer biology and therapeutics. Oncogene (2010) 29(5):625–34. doi: 10.1038/onc.2009.441

  • CrossRef
  • Google Scholar

• 106

  TirpeAAGuleiDCiorteaSMCriviiCBerindan-NeagoeI. Hypoxia: Overview on hypoxia-mediated mechanisms with a focus on the role of hif genes. Int J Mol Sci (2019) 20(24):6140. doi: 10.3390/ijms20246140

  • CrossRef
  • Google Scholar

• 107

  JiangYWuGHHeGDZhuangQLXiQLZhangBet al. The effect of silencing hif-1α gene in bxpc-3 cell line on glycolysis-related gene expression, cell growth, invasion, and apoptosis. Nutr Cancer (2015) 67(8):1314–23. doi: 10.1080/01635581.2015.1085584

  • CrossRef
  • Google Scholar

• 108

  HeGJiangYZhangBWuG. The effect of hif-1α on glucose metabolism, growth and apoptosis of pancreatic cancerous cells. Asia Pac J Clin Nutr (2014) 23(1):174–80. doi: 10.6133/apjcn.2014.23.1.14

  • CrossRef
  • Google Scholar

• 109

  ChaikaNVGebregiworgisTLewallenMEPurohitVRadhakrishnanPLiuXet al. Muc1 mucin stabilizes and activates hypoxia-inducible factor 1 alpha to regulate metabolism in pancreatic cancer. Proc Natl Acad Sci USA (2012) 109(34):13787–92. doi: 10.1073/pnas.1203339109

  • CrossRef
  • Google Scholar

• 110

  ChaikaNVYuFPurohitVMehlaKLazenbyAJDiMaioDet al. Differential expression of metabolic genes in tumor and stromal components of primary and metastatic loci in pancreatic adenocarcinoma. PLoS One (2012) 7(3):e32996. doi: 10.1371/journal.pone.0032996

  • CrossRef
  • Google Scholar

• 111

  Vander HeidenMGCantleyLCThompsonCB. Understanding the warburg effect: The metabolic requirements of cell proliferation. Science (2009) 324(5930):1029–33. doi: 10.1126/science.1160809

  • CrossRef
  • Google Scholar

• 112

  SemenzaGL. Hif-1: Upstream and downstream of cancer metabolism. Curr Opin Genet Dev (2010) 20(1):51–6. doi: 10.1016/j.gde.2009.10.009

  • CrossRef
  • Google Scholar

• 113

  SemenzaGLJiangBHLeungSWPassantinoRConcordetJPMairePet al. Hypoxia response elements in the aldolase a, enolase 1, and lactate dehydrogenase a gene promoters contain essential binding sites for hypoxia-inducible factor 1. J Biol Chem (1996) 271(51):32529–37. doi: 10.1074/jbc.271.51.32529

  • CrossRef
  • Google Scholar

• 114

  FirthJDEbertBLRatcliffePJ. Hypoxic regulation of lactate dehydrogenase a. interaction between hypoxia-inducible factor 1 and camp response elements. J Biol Chem (1995) 270(36):21021–7. doi: 10.1074/jbc.270.36.21021

  • CrossRef
  • Google Scholar

• 115

  UllahMSDaviesAJHalestrapAP. The plasma membrane lactate transporter Mct4, but not Mct1, is up-regulated by hypoxia through a hif-1alpha-Dependent mechanism. J Biol Chem (2006) 281(14):9030–7. doi: 10.1074/jbc.M511397200

  • CrossRef
  • Google Scholar

• 116

  Md HashimNFNicholasNSDartAEKiriakidisSPaleologEWellsCM. Hypoxia-induced invadopodia formation: A role for B-pix. Open Biol (2013) 3(6):120159. doi: 10.1098/rsob.120159

  • CrossRef
  • Google Scholar

• 117

  Abdul-SalamVBRussomannoGChien-NienCMahomedASYatesLAWilkinsMRet al. Clic4/Arf6 pathway. Circ Res (2019) 124(1):52–65. doi: 10.1161/circresaha.118.313705

  • CrossRef
  • Google Scholar

• 118

  ColegioORChuNQSzaboALChuTRhebergenAMJairamVet al. Functional polarization of tumour-associated macrophages by tumour-derived lactic acid. Nature (2014) 513(7519):559–63. doi: 10.1038/nature13490

  • CrossRef
  • Google Scholar

• 119

  HusainZHuangYSethPSukhatmeVP. Tumor-derived lactate modifies antitumor immune response: Effect on myeloid-derived suppressor cells and nk cells. J Immunol (2013) 191(3):1486–95. doi: 10.4049/jimmunol.1202702

  • CrossRef
  • Google Scholar

• 120

  ParksSKChicheJPouysségurJ. Disrupting proton dynamics and energy metabolism for cancer therapy. Nat Rev Cancer (2013) 13(9):611–23. doi: 10.1038/nrc3579

  • CrossRef
  • Google Scholar

• 121

  PeppicelliSTotiAGiannoniEBianchiniFMargheriFDel RossoMet al. Metformin is also effective on lactic acidosis-exposed melanoma cells switched to oxidative phosphorylation. Cell Cycle (2016) 15(14):1908–18. doi: 10.1080/15384101.2016.1191706

  • CrossRef
  • Google Scholar

• 122

  ShiQAbbruzzeseJLHuangSFidlerIJXiongQXieK. Constitutive and inducible interleukin 8 expression by hypoxia and acidosis renders human pancreatic cancer cells more tumorigenic and metastatic. Clin Cancer Res (1999) 5(11):3711–21.

  • Google Scholar

• 123

  ShiQLeXWangBXiongQAbbruzzeseJLXieK. Regulation of interleukin-8 expression by cellular ph in human pancreatic adenocarcinoma cells. J Interferon Cytokine Res (2000) 20(11):1023–8. doi: 10.1089/10799900050198471

  • CrossRef
  • Google Scholar

• 124

  XuLFidlerIJ. Acidic ph-induced elevation in interleukin 8 expression by human ovarian carcinoma cells. Cancer Res (2000) 60(16):4610–6.

  • Google Scholar

• 125

  GuillaumondFBidautGOuaissiMServaisSGouirandVOlivaresOet al. Cholesterol uptake disruption, in association with chemotherapy, is a promising combined metabolic therapy for pancreatic adenocarcinoma. Proc Natl Acad Sci U S A (2015) 112(8):2473–8. doi: 10.1073/pnas.1421601112

  • CrossRef
  • Google Scholar

• 126

  CohenRNeuzilletCTijeras-RaballandAFaivreSde GramontARaymondE. Targeting cancer cell metabolism in pancreatic adenocarcinoma. Oncotarget (2015) 6(19):16832–47. doi: 10.18632/oncotarget.4160

  • CrossRef
  • Google Scholar

• 127

  MaxfieldFR. Plasma membrane microdomains. Curr Opin Cell Biol (2002) 14(4):483–7. doi: 10.1016/s0955-0674(02)00351-4

  • CrossRef
  • Google Scholar

• 128

  MukherjeeSMaxfieldFR. Membrane domains. Annu Rev Cell Dev Biol (2004) 20:839–66. doi: 10.1146/annurev.cellbio.20.010403.095451

  • CrossRef
  • Google Scholar

• 129

  PomorskiTHrafnsdottirSDevauxPFvan MeerG. Lipid distribution and transport across cellular membranes. Semin Cell Dev Biol (2001) 12(2):139–48. doi: 10.1006/scdb.2000.0231

  • CrossRef
  • Google Scholar

• 130

  van MeerG. Membranes in motion. EMBO Rep (2010) 11(5):331–3. doi: 10.1038/embor.2010.60

  • CrossRef
  • Google Scholar

• 131

  van MeerGVoelkerDRFeigensonGW. Membrane lipids: Where they are and how they behave. Nat Rev Mol Cell Biol (2008) 9(2):112–24. doi: 10.1038/nrm2330

  • CrossRef
  • Google Scholar

• 132

  HolthuisJCMenonAK. Lipid landscapes and pipelines in membrane homeostasis. Nature (2014) 510(7503):48–57. doi: 10.1038/nature13474

  • CrossRef
  • Google Scholar

• 133

  BaenkeFPeckBMiessHSchulzeA. Hooked on fat: The role of lipid synthesis in cancer metabolism and tumour development. Dis Model Mech (2013) 6(6):1353–63. doi: 10.1242/dmm.011338

  • CrossRef
  • Google Scholar

• 134

  SwierczynskiJHebanowskaASledzinskiT. Role of abnormal lipid metabolism in development, progression, diagnosis and therapy of pancreatic cancer. World J Gastroenterol (2014) 20(9):2279–303. doi: 10.3748/wjg.v20.i9.2279

  • CrossRef
  • Google Scholar

• 135

  MenendezJALupuR. Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis. Nat Rev Cancer (2007) 7(10):763–77. doi: 10.1038/nrc2222

  • CrossRef
  • Google Scholar

• 136

  HatzivassiliouGZhaoFBauerDEAndreadisCShawANDhanakDet al. Atp citrate lyase inhibition can suppress tumor cell growth. Cancer Cell (2005) 8(4):311–21. doi: 10.1016/j.ccr.2005.09.008

  • CrossRef
  • Google Scholar

• 137

  TadrosSShuklaSKKingRJGundaVVernucciEAbregoJet al. De novo lipid synthesis facilitates gemcitabine resistance through endoplasmic reticulum stress in pancreatic cancer. Cancer Res (2017) 77(20):5503–17. doi: 10.1158/0008-5472.CAN-16-3062

  • CrossRef
  • Google Scholar

• 138

  YangYLiuHLiZZhaoZYip-SchneiderMFanQet al. Role of fatty acid synthase in gemcitabine and radiation resistance of pancreatic cancers. Int J Biochem Mol Biol (2011) 2(1):89–98.

  • Google Scholar

• 139

  GoldsteinJLBrownMS. Regulation of the mevalonate pathway. Nature (1990) 343(6257):425–30. doi: 10.1038/343425a0

  • CrossRef
  • Google Scholar

• 140

  TakahashiMHoriMIshigamoriRMutohMImaiTNakagamaH. Fatty pancreas: A possible risk factor for pancreatic cancer in animals and humans. Cancer Sci (2018) 109(10):3013–23. doi: 10.1111/cas.13766

  • CrossRef
  • Google Scholar

• 141

  KajinamiKOzakiATajimaYYamashitaSAraiHTeramotoT. Real-world data to identify hypercholesterolemia patients on suboptimal statin therapy. J Atheroscler Thromb (2019) 26(5):408–31. doi: 10.5551/jat.46201

  • CrossRef
  • Google Scholar

• 142

  TateRZonaEDe CiccoRTrottaVUrciuoliMMorelliAet al. Simvastatin inhibits the expression of stemnessrelated genes and the metastatic invasion of human cancer cells Via destruction of the cytoskeleton. Int J Oncol (2017) 51(6):1851–9. doi: 10.3892/ijo.2017.4158

  • CrossRef
  • Google Scholar

• 143

  StineJEGuoHShengXHanXSchointuchMNGilliamTPet al. The hmg-coa reductase inhibitor, simvastatin, exhibits anti-metastatic and anti-tumorigenic effects in ovarian cancer. Oncotarget (2016) 7(1):946–60. doi: 10.18632/oncotarget.5834

  • CrossRef
  • Google Scholar

• 144

  XiaYXieYYuZXiaoHJiangGZhouXet al. The mevalonate pathway is a druggable target for vaccine adjuvant discovery. Cell (2018) 175(4):1059–73.e21. doi: 10.1016/j.cell.2018.08.070

  • CrossRef
  • Google Scholar

• 145

  MorishigeMHashimotoSOgawaETodaYKotaniHHiroseMet al. Gep100 links epidermal growth factor receptor signalling to Arf6 activation to induce breast cancer invasion. Nat Cell Biol (2008) 10(1):85–92. doi: 10.1038/ncb1672

  • CrossRef
  • Google Scholar

• 146

  MenjuTHashimotoSHashimotoAOtsukaYHandaHOgawaEet al. Engagement of overexpressed Her2 with Gep100 induces autonomous invasive activities and provides a biomarker for metastases of lung adenocarcinoma. PLoS One (2011) 6(9):e25301. doi: 10.1371/journal.pone.0025301

  • CrossRef
  • Google Scholar

• 147

  SatoHHatanakaKCHatanakaYHatakeyamaHHashimotoAMatsunoYet al. High level expression of Amap1 protein correlates with poor prognosis and survival after surgery of head and neck squamous cell carcinoma patients. Cell Communication Signaling (2014) 12(1):17. doi: 10.1186/1478-811X-12-17

  • CrossRef
  • Google Scholar

• 148

  HashimotoAOikawaTHashimotoSSuginoHYoshikawaAOtsukaYet al. P53- and mevalonate pathway-driven malignancies require Arf6 for metastasis and drug resistance. J Cell Biol (2016) 213(1):81–95. doi: 10.1083/jcb.201510002

  • CrossRef
  • Google Scholar

• 149

  HashimotoSMikamiSSuginoHYoshikawaAHashimotoAOnoderaYet al. Lysophosphatidic acid activates Arf6 to promote the mesenchymal malignancy of renal cancer. Nat Commun (2016) 7:10656. doi: 10.1038/ncomms10656

  • CrossRef
  • Google Scholar

• 150

  Freed-PastorWAMizunoHZhaoXLangerødAMoonSHRodriguez-BarruecoRet al. Mutant P53 disrupts mammary tissue architecture. Via Mevalonate Pathway Cell (2012) 148(1-2):244–58. doi: 10.1016/j.cell.2011.12.017

  • CrossRef
  • Google Scholar

• 151

  MistafaOSteniusU. Statins inhibit Akt/Pkb signaling Via P2x7 receptor in pancreatic cancer cells. Biochem Pharmacol (2009) 78(9):1115–26. doi: 10.1016/j.bcp.2009.06.016

  • CrossRef
  • Google Scholar

• 152

  MüllerCBockhornAGKlusmeierSKiehlMRoederCKalthoffHet al. Lovastatin inhibits proliferation of pancreatic cancer cell lines with mutant as well as with wild-type K-ras oncogene but has different effects on protein phosphorylation and induction of apoptosis. Int J Oncol (1998) 12(3):717–23. doi: 10.3892/ijo.12.3.717

  • CrossRef
  • Google Scholar

• 153

  UraHObaraTNishinoNTannoSOkamuraKNamikiM. Cytotoxicity of simvastatin to pancreatic adenocarcinoma cells containing mutant ras gene. Jpn J Cancer Res (1994) 85(6):633–8. doi: 10.1111/j.1349-7006.1994.tb02406.x

  • CrossRef
  • Google Scholar

• 154

  LiaoJChungYTYangALZhangMLiHZhangWet al. Atorvastatin inhibits pancreatic carcinogenesis and increases survival in lsl-Krasg12d-Lsl-Trp53r172h-Pdx1-Cre mice. Mol Carcinog (2013) 52(9):739–50. doi: 10.1002/mc.21916

  • CrossRef
  • Google Scholar

• 155

  WiseDRThompsonCB. Glutamine addiction: A new therapeutic target in cancer. Trends Biochem Sci (2010) 35(8):427–33. doi: 10.1016/j.tibs.2010.05.003

  • CrossRef
  • Google Scholar

• 156

  HensleyCTWastiATDeBerardinisRJ. Glutamine and cancer: Cell biology, physiology, and clinical opportunities. J Clin Invest (2013) 123(9):3678–84. doi: 10.1172/JCI69600

  • CrossRef
  • Google Scholar

• 157

  SonJLyssiotisCAYingHWangXHuaSLigorioMet al. Glutamine supports pancreatic cancer growth through a kras-regulated metabolic pathway. Nature (2013) 496(7443):101–5. doi: 10.1038/nature12040

  • CrossRef
  • Google Scholar

• 158

  AltmanBJStineZEDangCV. From Krebs to clinic: Glutamine metabolism to cancer therapy. Nat Rev Cancer (2016) 16(10):619–34. doi: 10.1038/nrc.2016.71

  • CrossRef
  • Google Scholar

• 159

  DangCV. Links between metabolism and cancer. Genes Dev (2012) 26(9):877–90. doi: 10.1101/gad.189365.112

  • CrossRef
  • Google Scholar

• 160

  DeBerardinisRJChengT. Q's next: The diverse functions of glutamine in metabolism, cell biology and cancer. Oncogene (2010) 29(3):313–24. doi: 10.1038/onc.2009.358

  • CrossRef
  • Google Scholar

• 161

  SullivanLBChandelNS. Mitochondrial reactive oxygen species and cancer. Cancer Metab (2014) 2(1):17. doi: 10.1186/2049-3002-2-17

  • CrossRef
  • Google Scholar

• 162

  VasanKWernerMChandelNS. Mitochondrial metabolism as a target for cancer therapy. Cell Metab (2020) 32(3):341–52. doi: 10.1016/j.cmet.2020.06.019

  • CrossRef
  • Google Scholar

• 163

  CluntunAALukeyMJCerioneRALocasaleJW. Glutamine metabolism in cancer: Understanding the heterogeneity. Trends Cancer (2017) 3(3):169–80. doi: 10.1016/j.trecan.2017.01.005

  • CrossRef
  • Google Scholar

• 164

  MayersJRWuCClishCBKraftPTorrenceMEFiskeBPet al. Elevation of circulating branched-chain amino acids is an early event in human pancreatic adenocarcinoma development. Nat Med (2014) 20(10):1193–8. doi: 10.1038/nm.3686

  • CrossRef
  • Google Scholar

• 165

  LiJTYinMWangDWangJLeiMZZhangYet al. Bcat2-mediated bcaa catabolism is critical for development of pancreatic ductal adenocarcinoma. Nat Cell Biol (2020) 22(2):167–74. doi: 10.1038/s41556-019-0455-6

  • CrossRef
  • Google Scholar

• 166

  KairaKSunoseYArakawaKOgawaTSunagaNShimizuKet al. Prognostic significance of l-type amino-acid transporter 1 expression in surgically resected pancreatic cancer. Br J Cancer (2012) 107(4):632–8. doi: 10.1038/bjc.2012.310

  • CrossRef
  • Google Scholar

• 167

  BiancurDEPauloJAMałachowskaBQuiles Del ReyMSousaCMWangXet al. Compensatory metabolic networks in pancreatic cancers upon perturbation of glutamine metabolism. Nat Commun (2017) 8:15965. doi: 10.1038/ncomms15965

  • CrossRef
  • Google Scholar

• 168

  SeoJWChoiJLeeSYSungSYooHJKangMJet al. Autophagy is required for pdac glutamine metabolism. Sci Rep (2016) 6:37594. doi: 10.1038/srep37594

  • CrossRef
  • Google Scholar

• 169

  RecouvreuxMVMoldenhauerMRGalenkampKMOJungMJamesBZhangYet al. Glutamine depletion regulates slug to promote emt and metastasis in pancreatic cancer. J Exp Med (2020) 217(9):e20200388. doi: 10.1084/jem.20200388

  • CrossRef
  • Google Scholar

• 170

  KodamaMOshikawaKShimizuHYoshiokaSTakahashiMIzumiYet al. A shift in glutamine nitrogen metabolism contributes to the malignant progression of cancer. Nat Commun (2020) 11(1):1320. doi: 10.1038/s41467-020-15136-9

  • CrossRef
  • Google Scholar

• 171

  BiancurDEPauloJAMalachowskaBQuiles Del ReyMSousaCMWangXet al. Compensatory metabolic networks in pancreatic cancers upon perturbation of glutamine metabolism. Nat Commun (2017) 8:15965. doi: 10.1038/ncomms15965

  • CrossRef
  • Google Scholar

• 172

  BottAJShenJTonelliCZhanLSivaramNJiangYPet al. Glutamine anabolism plays a critical role in pancreatic cancer by coupling carbon and nitrogen metabolism. Cell Rep (2019) 29(5):1287–98.e6. doi: 10.1016/j.celrep.2019.09.056

  • CrossRef
  • Google Scholar

• 173

  MizushimaNLevineBCuervoAMKlionskyDJ. Autophagy fights disease through cellular self-digestion. Nature (2008) 451(7182):1069–75. doi: 10.1038/nature06639

  • CrossRef
  • Google Scholar

• 174

  KamphorstJJNofalMCommissoCHackettSRLuWGrabockaEet al. Human pancreatic cancer tumors are nutrient poor and tumor cells actively scavenge extracellular protein. Cancer Res (2015) 75(3):544–53. doi: 10.1158/0008-5472.CAN-14-2211

  • CrossRef
  • Google Scholar

• 175

  YangARajeshkumarNVWangXYabuuchiSAlexanderBMChuGCet al. Autophagy is critical for pancreatic tumor growth and progression in tumors with P53 alterations. Cancer Discov (2014) 4(8):905–13. doi: 10.1158/2159-8290.Cd-14-0362

  • CrossRef
  • Google Scholar

• 176

  RosenfeldtMTO'PreyJMortonJPNixonCMacKayGMrowinskaAet al. P53 status determines the role of autophagy in pancreatic tumour development. Nature (2013) 504(7479):296–300. doi: 10.1038/nature12865

  • CrossRef
  • Google Scholar

• 177

  KathederNSKhezriRO'FarrellFSchultzSWJainARahmanMMet al. Microenvironmental autophagy promotes tumour growth. Nature (2017) 541(7637):417–20. doi: 10.1038/nature20815

  • CrossRef
  • Google Scholar

• 178

  SousaCMBiancurDEWangXHalbrookCJShermanMHZhangLet al. Pancreatic stellate cells support tumour metabolism through autophagic alanine secretion. Nature (2016) 536(7617):479–83. doi: 10.1038/nature19084

  • CrossRef
  • Google Scholar

• 179

  Pylayeva-GuptaYLeeKEHajduCHMillerGBar-SagiD. Oncogenic kras-induced gm-csf production promotes the development of pancreatic neoplasia. Cancer Cell (2012) 21(6):836–47. doi: 10.1016/j.ccr.2012.04.024

  • CrossRef
  • Google Scholar

• 180

  BinnewiesMRobertsEWKerstenKChanVFearonDFMeradMet al. Understanding the tumor immune microenvironment (Time) for effective therapy. Nat Med (2018) 24(5):541–50. doi: 10.1038/s41591-018-0014-x

  • CrossRef
  • Google Scholar

• 181

  BearASVonderheideRHO'HaraMH. Challenges and opportunities for pancreatic cancer immunotherapy. Cancer Cell (2020) 38(6):788–802. doi: 10.1016/j.ccell.2020.08.004

  • CrossRef
  • Google Scholar

• 182

  LeinwandJMillerG. Regulation and modulation of antitumor immunity in pancreatic cancer. Nat Immunol (2020) 21(10):1152–9. doi: 10.1038/s41590-020-0761-y

  • CrossRef
  • Google Scholar

• 183

  RooneyMSShuklaSAWuCJGetzGHacohenN. Molecular and genetic properties of tumors associated with local immune cytolytic activity. Cell (2015) 160(1-2):48–61. doi: 10.1016/j.cell.2014.12.033

  • CrossRef
  • Google Scholar

• 184

  McGranahanNRosenthalRHileyCTRowanAJWatkinsTBKWilsonGAet al. Allele-specific hla loss and immune escape in lung cancer evolution. Cell (2017) 171(6):1259–71.e11. doi: 10.1016/j.cell.2017.10.001

  • CrossRef
  • Google Scholar

• 185

  RodigSJGusenleitnerDJacksonDGGjiniEGiobbie-HurderAJinCet al. Mhc proteins confer differential sensitivity to ctla-4 and pd-1 blockade in untreated metastatic melanoma. Sci Transl Med (2018) 10(450):eaar3342. doi: 10.1126/scitranslmed.aar3342

  • CrossRef
  • Google Scholar

• 186

  RyschichENötzelTHinzUAutschbachFFergusonJSimonIet al. Control of T-Cell-Mediated immune response by hla class I in human pancreatic carcinoma. Clin Cancer Res (2005) 11(2 Pt 1):498–504.

  • Google Scholar

• 187

  PommierAAnaparthyNMemosNKelleyZLGouronnecAYanRet al. Unresolved endoplasmic reticulum stress engenders immune-resistant, latent pancreatic cancer metastases. Science (2018) 360(6394):eaao4908. doi: 10.1126/science.aao4908

  • CrossRef
  • Google Scholar

• 188

  YamamotoKVenidaAYanoJBiancurDEKakiuchiMGuptaSet al. Autophagy promotes immune evasion of pancreatic cancer by degrading mhc-I. Nature (2020) 581(7806):100–5. doi: 10.1038/s41586-020-2229-5

  • CrossRef
  • Google Scholar

• 189

  BiancurDEKimmelmanAC. The plasticity of pancreatic cancer metabolism in tumor progression and therapeutic resistance. Biochim Biophys Acta Rev Cancer (2018) 1870(1):67–75. doi: 10.1016/j.bbcan.2018.04.011

  • CrossRef
  • Google Scholar

• 190

  LeeSWZhangYJungMCruzNAlasBCommissoC. Egfr-pak signaling selectively regulates glutamine deprivation-induced macropinocytosis. Dev Cell (2019) 50(3):381–92.e5. doi: 10.1016/j.devcel.2019.05.043

  • CrossRef
  • Google Scholar

• 191

  MichalopoulouEBulusuVKamphorstJJ. Metabolic scavenging by cancer cells: When the going gets tough, the tough keep eating. Br J Cancer (2016) 115(6):635–40. doi: 10.1038/bjc.2016.256

  • CrossRef
  • Google Scholar

• 192

  ZhangYCommissoC. Macropinocytosis in cancer: A complex signaling network. Trends Cancer (2019) 5(6):332–4. doi: 10.1016/j.trecan.2019.04.002

  • CrossRef
  • Google Scholar

• 193

  Bar-SagiDFeramiscoJR. Induction of membrane ruffling and fluid-phase pinocytosis in quiescent fibroblasts by ras proteins. Science (1986) 233(4768):1061–8. doi: 10.1126/science.3090687

  • CrossRef
  • Google Scholar

• 194

  Porat-ShliomNKloogYDonaldsonJG. A unique platform for h-ras signaling involving clathrin-independent endocytosis. Mol Biol Cell (2008) 19(3):765–75. doi: 10.1091/mbc.e07-08-0841

  • CrossRef
  • Google Scholar

• 195

  CommissoCDavidsonSMSoydaner-AzelogluRGParkerSJKamphorstJJHackettSet al. Macropinocytosis of protein is an amino acid supply route in ras-transformed cells. Nature (2013) 497(7451):633–7. doi: 10.1038/nature12138

  • CrossRef
  • Google Scholar

• 196

  SungSChoiJCheongH. Catabolic pathways regulated by Mtorc1 are pivotal for survival and growth of cancer cells expressing mutant ras. Oncotarget (2015) 6(38):40405–17. doi: 10.18632/oncotarget.6334

  • CrossRef
  • Google Scholar

• 197

  PalmWArakiJKingBDeMatteoRGThompsonCB. Critical role for Pi3-kinase in regulating the use of proteins as an amino acid source. Proc Natl Acad Sci U S A (2017) 114(41):E8628–36. doi: 10.1073/pnas.1712726114

  • CrossRef
  • Google Scholar

• 198

  DavidsonSMJonasOKeiblerMAHouHWLuengoAMayersJRet al. Direct evidence for cancer-Cell-Autonomous extracellular protein catabolism in pancreatic tumors. Nat Med (2017) 23(2):235–41. doi: 10.1038/nm.4256

  • CrossRef
  • Google Scholar

• 199

  MoreauKRavikumarBPuriCRubinszteinDC. Arf6 promotes autophagosome formation Via effects on phosphatidylinositol 4,5-bisphosphate and phospholipase d. J Cell Biol (2012) 196(4):483–96. doi: 10.1083/jcb.201110114

  • CrossRef
  • Google Scholar

• 200

  GeorgeAAHaydenSStantonGRBrockerhoffSE. Arf6 and the 5'phosphatase of synaptojanin 1 regulate autophagy in cone photoreceptors. Bioessays (2016) 38 Suppl 1:S119–35. doi: 10.1002/bies.201670913

  • CrossRef
  • Google Scholar

• 201

  WilliamsonCDDonaldsonJG. Arf6, Jip3, and dynein shape and mediate macropinocytosis. Mol Biol Cell (2019) 30(12):1477–89. doi: 10.1091/mbc.E19-01-0022

  • CrossRef
  • Google Scholar

• 202

  HashimotoAHandaHHataSTsutahoAYoshidaTHiranoSet al. Inhibition of mutant kras-driven overexpression of Arf6 and myc by an Eif4a inhibitor drug improves the effects of anti-Pd-1 immunotherapy for pancreatic cancer. Cell Commun Signal (2021) 19(1):54. doi: 10.1186/s12964-021-00733-y

  • CrossRef
  • Google Scholar

• 203

  GeigerRRieckmannJCWolfTBassoCFengYFuhrerTet al. L-arginine modulates T cell metabolism and enhances survival and anti-tumor activity. Cell (2016) 167(3):829–42.e13. doi: 10.1016/j.cell.2016.09.031

  • CrossRef
  • Google Scholar

• 204

  WitkiewiczAKCostantinoCLMetzRMullerAJPrendergastGCYeoCJet al. Genotyping and expression analysis of Ido2 in human pancreatic cancer: A novel, active target. J Am Coll Surg (2009) 208(5):781–7. doi: 10.1016/j.jamcollsurg.2008.12.018

  • CrossRef
  • Google Scholar

• 205

  AndersonKGStromnesIMGreenbergPD. Obstacles posed by the tumor microenvironment to T cell activity: A case for synergistic therapies. Cancer Cell (2017) 31(3):311–25. doi: 10.1016/j.ccell.2017.02.008

  • CrossRef
  • Google Scholar

• 206

  Di VirgilioFSartiACFalzoniSDe MarchiEAdinolfiE. Extracellular atp and P2 purinergic signalling in the tumour microenvironment. Nat Rev Cancer (2018) 18(10):601–18. doi: 10.1038/s41568-018-0037-0

  • CrossRef
  • Google Scholar

• 207

  ViganoSAlatzoglouDIrvingMMenetrier-CauxCCauxCRomeroPet al. Targeting adenosine in cancer immunotherapy to enhance T-cell function. Front Immunol (2019) 10:925. doi: 10.3389/fimmu.2019.00925

  • CrossRef
  • Google Scholar

• 208

  JacobsonKAGaoZG. Adenosine receptors as therapeutic targets. Nat Rev Drug Discovery (2006) 5(3):247–64. doi: 10.1038/nrd1983

  • CrossRef
  • Google Scholar

• 209

  HammamiAAllardDAllardBStaggJ. Targeting the adenosine pathway for cancer immunotherapy. Semin Immunol (2019) 42:101304. doi: 10.1016/j.smim.2019.101304

  • CrossRef
  • Google Scholar

• 210

  ColganSPEltzschigHKEckleTThompsonLF. Physiological roles for ecto-5'-Nucleotidase (Cd73). Purinergic Signal (2006) 2(2):351–60. doi: 10.1007/s11302-005-5302-5

  • CrossRef
  • Google Scholar

• 211

  OhtaASitkovskyM. Role of G-Protein-Coupled adenosine receptors in downregulation of inflammation and protection from tissue damage. Nature (2001) 414(6866):916–20. doi: 10.1038/414916a

  • CrossRef
  • Google Scholar

• 212

  ZhaoJSotoLMSWangHKatzMHPrakashLRKimMet al. Overexpression of Cd73 in pancreatic ductal adenocarcinoma is associated with immunosuppressive tumor microenvironment and poor survival. Pancreatology (2021) 21(5):942–9. doi: 10.1016/j.pan.2021.03.018

  • CrossRef
  • Google Scholar

• 213

  BalachandranVPŁukszaMZhaoJNMakarovVMoralJARemarkRet al. Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer. Nature (2017) 551(7681):512–6. doi: 10.1038/nature24462

  • CrossRef
  • Google Scholar

• 214

  MarabelleALeDTAsciertoPADi GiacomoAMDe Jesus-AcostaADelordJPet al. Efficacy of pembrolizumab in patients with noncolorectal high microsatellite Instability/Mismatch repair-deficient cancer: Results from the phase ii keynote-158 study. J Clin Oncol (2020) 38(1):1–10. doi: 10.1200/jco.19.02105

  • CrossRef
  • Google Scholar

• 215

  BeattyGLO'HaraMHLaceySFTorigianDANazimuddinFChenFet al. Activity of mesothelin-specific chimeric antigen receptor T cells against pancreatic carcinoma metastases in a phase 1 trial. Gastroenterology (2018) 155(1):29–32. doi: 10.1053/j.gastro.2018.03.029

  • CrossRef
  • Google Scholar

• 216

  ClarkCEHingoraniSRMickRCombsCTuvesonDAVonderheideRH. Dynamics of the immune reaction to pancreatic cancer from inception to invasion. Cancer Res (2007) 67(19):9518–27. doi: 10.1158/0008-5472.Can-07-0175

  • CrossRef
  • Google Scholar

• 217

  LeeKEBar-SagiD. Oncogenic kras suppresses inflammation-associated senescence of pancreatic ductal cells. Cancer Cell (2010) 18(5):448–58. doi: 10.1016/j.ccr.2010.10.020

  • CrossRef
  • Google Scholar

• 218

  McAllisterFBaileyJMAlsinaJNirschlCJSharmaRFanHet al. Oncogenic kras activates a hematopoietic-to-Epithelial il-17 signaling axis in preinvasive pancreatic neoplasia. Cancer Cell (2014) 25(5):621–37. doi: 10.1016/j.ccr.2014.03.014

  • CrossRef
  • Google Scholar

• 219

  CarrièreCYoungALGunnJRLongneckerDSKorcM. Acute pancreatitis markedly accelerates pancreatic cancer progression in mice expressing oncogenic kras. Biochem Biophys Res Commun (2009) 382(3):561–5. doi: 10.1016/j.bbrc.2009.03.068

  • CrossRef
  • Google Scholar

• 220

  LesinaMKurkowskiMULudesKRose-JohnSTreiberMKloppelGet al. Stat3/Socs3 activation by il-6 transsignaling promotes progression of pancreatic intraepithelial neoplasia and development of pancreatic cancer. Cancer Cell (2011) 19(4):456–69. doi: 10.1016/j.ccr.2011.03.009

  • CrossRef
  • Google Scholar

• 221

  de VisserKEEichtenACoussensLM. Paradoxical roles of the immune system during cancer development. Nat Rev Cancer (2006) 6(1):24–37. doi: 10.1038/nrc1782

  • CrossRef
  • Google Scholar

• 222

  CarstensJLCorrea de SampaioPYangDBaruaSWangHRaoAet al. Spatial computation of intratumoral T cells correlates with survival of patients with pancreatic cancer. Nat Commun (2017) 8(1):15095. doi: 10.1038/ncomms15095

  • CrossRef
  • Google Scholar

• 223

  XieDXieK. Pancreatic cancer stromal biology and therapy. Genes Dis (2015) 2(2):133–43. doi: 10.1016/j.gendis.2015.01.002

  • CrossRef
  • Google Scholar

• 224

  NeesseAAlgülHTuvesonDAGressTM. Stromal biology and therapy in pancreatic cancer: A changing paradigm. Gut (2015) 64(9):1476–84. doi: 10.1136/gutjnl-2015-309304

  • CrossRef
  • Google Scholar

• 225

  LynchMDWattFM. Fibroblast heterogeneity: Implications for human disease. J Clin Invest (2018) 128(1):26–35. doi: 10.1172/jci93555

  • CrossRef
  • Google Scholar

• 226

  RinnJLBondreCGladstoneHBBrownPOChangHY. Anatomic demarcation by positional variation in fibroblast gene expression programs. PLoS Genet (2006) 2(7):e119. doi: 10.1371/journal.pgen.0020119

  • CrossRef
  • Google Scholar

• 227

  KalluriR. The biology and function of fibroblasts in cancer. Nat Rev Cancer (2016) 16(9):582–98. doi: 10.1038/nrc.2016.73

  • CrossRef
  • Google Scholar

• 228

  ÖhlundDHandly-SantanaABiffiGElyadaEAlmeidaASPonz-SarviseMet al. Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. J Exp Med (2017) 214(3):579–96. doi: 10.1084/jem.20162024

  • CrossRef
  • Google Scholar

• 229

  Özdemir BernaCPentcheva-HoangTCarstens JulienneLZhengXWuC-CSimpson TylerRet al. Depletion of carcinoma-associated fibroblasts and fibrosis induces immunosuppression and accelerates pancreas cancer with reduced survival. Cancer Cell (2014) 25(6):719–34. doi: 10.1016/j.ccr.2014.04.005

  • CrossRef
  • Google Scholar

• 230

  ElyadaEBolisettyMLaisePFlynnWFCourtoisETBurkhartRAet al. Cross-species single-cell analysis of pancreatic ductal adenocarcinoma reveals antigen-presenting cancer-associated fibroblasts. Cancer Discovery (2019) 9(8):1102–23. doi: 10.1158/2159-8290.Cd-19-0094

  • CrossRef
  • Google Scholar

• 231

  HoseinANHuangHWangZParmarKDuWHuangJet al. Cellular heterogeneity during mouse pancreatic ductal adenocarcinoma progression at single-cell resolution. JCI Insight (2019) 5(16):e129212. doi: 10.1172/jci.insight.129212

  • CrossRef
  • Google Scholar

• 232

  QuanteMTuSPTomitaHGondaTWangSSWTakashiSet al. Bone marrow-derived myofibroblasts contribute to the mesenchymal stem cell niche and promote tumor growth. Cancer Cell (2011) 19(2):257–72. doi: 10.1016/j.ccr.2011.01.020

  • CrossRef
  • Google Scholar

• 233

  WaghrayMYalamanchiliMDziubinskiMZeinaliMErkkinenMYangHet al. Gm-csf mediates mesenchymal-epithelial cross-talk in pancreatic cancer. Cancer Discov (2016) 6(8):886–99. doi: 10.1158/2159-8290.Cd-15-0947

  • CrossRef
  • Google Scholar

• 234

  Bayne LaurenJBeatty GregoryLJhalaNClark CarolynERhim AndrewDStanger BenZet al. Tumor-derived granulocyte-macrophage colony-stimulating factor regulates myeloid inflammation and T cell immunity in pancreatic cancer. Cancer Cell (2012) 21(6):822–35. doi: 10.1016/j.ccr.2012.04.025

  • CrossRef
  • Google Scholar

• 235

  HuangHWangZZhangYPradhanRNGangulyDChandraRet al. Mesothelial cell-derived antigen-presenting cancer-associated fibroblasts induce expansion of regulatory T cells in pancreatic cancer. Cancer Cell (2022) 40(6):656–73.e7. doi: 10.1016/j.ccell.2022.04.011

  • CrossRef
  • Google Scholar

• 236

  FeigCJonesJOKramanMWellsRJDeonarineAChanDSet al. Targeting Cxcl12 from fap-expressing carcinoma-associated fibroblasts synergizes with anti-Pd-L1 immunotherapy in pancreatic cancer. Proc Natl Acad Sci USA (2013) 110(50):20212–7. doi: 10.1073/pnas.1320318110

  • CrossRef
  • Google Scholar

• 237

  KoenigAMuellerCHaselCAdlerGMenkeA. Collagen type I induces disruption of e-Cadherin-Mediated cell-cell contacts and promotes proliferation of pancreatic carcinoma cells. Cancer Res (2006) 66(9):4662–71. doi: 10.1158/0008-5472.Can-05-2804

  • CrossRef
  • Google Scholar

• 238

  StokesJBAdairSJSlack-DavisJKWaltersDMTilghmanRWHersheyEDet al. Inhibition of focal adhesion kinase by pf-562,271 inhibits the growth and metastasis of pancreatic cancer concomitant with altering the tumor microenvironment. Mol Cancer Ther (2011) 10(11):2135–45. doi: 10.1158/1535-7163.Mct-11-0261

  • CrossRef
  • Google Scholar

• 239

  JiangHHegdeSKnolhoffBLZhuYHerndonJMMeyerMAet al. Targeting focal adhesion kinase renders pancreatic cancers responsive to checkpoint immunotherapy. Nat Med (2016) 22(8):851–60. doi: 10.1038/nm.4123

  • CrossRef
  • Google Scholar

• 240

  ZhengLXueJJaffeeEMHabtezionA. Role of immune cells and immune-based therapies in pancreatitis and pancreatic ductal adenocarcinoma. Gastroenterology (2013) 144(6):1230–40. doi: 10.1053/j.gastro.2012.12.042

  • CrossRef
  • Google Scholar

• 241

  Andrén-SandbergADervenisCLowenfelsB. Etiologic links between chronic pancreatitis and pancreatic cancer. Scand J Gastroenterol (1997) 32(2):97–103. doi: 10.3109/00365529709000177

  • CrossRef
  • Google Scholar

• 242

  FukunagaAMiyamotoMChoYMurakamiSKawaradaYOshikiriTet al. Cd8+ tumor-infiltrating lymphocytes together with Cd4+ tumor-infiltrating lymphocytes and dendritic cells improve the prognosis of patients with pancreatic adenocarcinoma. Pancreas (2004) 28(1):e26–31. doi: 10.1097/00006676-200401000-00023

  • CrossRef
  • Google Scholar

• 243

  OchiANguyenAHBedrosianASMushlinHMZarbakhshSBarillaRet al. Myd88 inhibition amplifies dendritic cell capacity to promote pancreatic carcinogenesis Via Th2 cells. J Exp Med (2012) 209(9):1671–87. doi: 10.1084/jem.20111706

  • CrossRef
  • Google Scholar

• 244

  De MonteLReniMTassiEClavennaDPapaIRecaldeHet al. Intratumor T helper type 2 cell infiltrate correlates with cancer-associated fibroblast thymic stromal lymphopoietin production and reduced survival in pancreatic cancer. J Exp Med (2011) 208(3):469–78. doi: 10.1084/jem.20101876

  • CrossRef
  • Google Scholar

• 245

  HiraokaNOnozatoKKosugeTHirohashiS. Prevalence of Foxp3+ regulatory T cells increases during the progression of pancreatic ductal adenocarcinoma and its premalignant lesions. Clin Cancer Res (2006) 12(18):5423–34. doi: 10.1158/1078-0432.Ccr-06-0369

  • CrossRef
  • Google Scholar

• 246

  DeyPLiJZhangJChaurasiyaSStromAWangHet al. Oncogenic kras-driven metabolic reprogramming in pancreatic cancer cells utilizes cytokines from the tumor microenvironment. Cancer Discov (2020) 10(4):608–25. doi: 10.1158/2159-8290.Cd-19-0297

  • CrossRef
  • Google Scholar

• 247

  DaleyDZambirinisCPSeifertLAkkadNMohanNWerbaGet al. Γδ T cells support pancreatic oncogenesis by restraining Aβ T cell activation. Cell (2016) 166(6):1485–99.e15. doi: 10.1016/j.cell.2016.07.046

  • CrossRef
  • Google Scholar

• 248

  GnerlichJLMitchemJBWeirJSSankpalNVKashiwagiHBeltBAet al. Induction of Th17 cells in the tumor microenvironment improves survival in a murine model of pancreatic cancer. J Immunol (2010) 185(7):4063–71. doi: 10.4049/jimmunol.0902609

  • CrossRef
  • Google Scholar

• 249

  GundersonAJKanedaMMTsujikawaTNguyenAVAffaraNIRuffellBet al. Bruton tyrosine kinase-dependent immune cell cross-talk drives pancreas cancer. Cancer Discov (2016) 6(3):270–85. doi: 10.1158/2159-8290.Cd-15-0827

  • CrossRef
  • Google Scholar

• 250

  Pylayeva-GuptaYDasSHandlerJSHajduCHCoffreMKoralovSBet al. Il35-producing b cells promote the development of pancreatic neoplasia. Cancer Discov (2016) 6(3):247–55. doi: 10.1158/2159-8290.Cd-15-0843

  • CrossRef
  • Google Scholar

• 251

  LeeKESpataMBayneLJBuzaELDurhamACAllmanDet al. Hif1a deletion reveals pro-neoplastic function of b cells in pancreatic neoplasia. Cancer Discov (2016) 6(3):256–69. doi: 10.1158/2159-8290.Cd-15-0822

  • CrossRef
  • Google Scholar

• 252

  MirlekarBMichaudDLeeSJKrenNPHarrisCGreeneKet al. B cell-derived Il35 drives Stat3-dependent Cd8(+) T-cell exclusion in pancreatic cancer. Cancer Immunol Res (2020) 8(3):292–308. doi: 10.1158/2326-6066.Cir-19-0349

  • CrossRef
  • Google Scholar

• 253

  HuHHangJJHanTZhuoMJiaoFWangLW. The M2 phenotype of tumor-associated macrophages in the stroma confers a poor prognosis in pancreatic cancer. Tumour Biol (2016) 37(7):8657–64. doi: 10.1007/s13277-015-4741-z

  • CrossRef
  • Google Scholar

• 254

  KuraharaHShinchiHMatakiYMaemuraKNomaHKuboFet al. Significance of M2-polarized tumor-associated macrophage in pancreatic cancer. J Surg Res (2011) 167(2):e211–9. doi: 10.1016/j.jss.2009.05.026

  • CrossRef
  • Google Scholar

• 255

  DaleyDManiVRMohanNAkkadNPandianGSDBSavadkarSet al. Nlrp3 signaling drives macrophage-induced adaptive immune suppression in pancreatic carcinoma. J Exp Med (2017) 214(6):1711–24. doi: 10.1084/jem.20161707

  • CrossRef
  • Google Scholar

• 256

  DaleyDManiVRMohanNAkkadNOchiAHeindelDWet al. Dectin 1 activation on macrophages by galectin 9 promotes pancreatic carcinoma and peritumoral immune tolerance. Nat Med (2017) 23(5):556–67. doi: 10.1038/nm.4314

  • CrossRef
  • Google Scholar

• 257

  SeifertLWerbaGTiwariSGiao LyNNAlothmanSAlqunaibitDet al. The necrosome promotes pancreatic oncogenesis Via Cxcl1 and mincle-induced immune suppression. Nature (2016) 532(7598):245–9. doi: 10.1038/nature17403

  • CrossRef
  • Google Scholar

• 258

  StromnesIMBrockenbroughJSIzeradjeneKCarlsonMACuevasCSimmonsRMet al. Targeted depletion of an mdsc subset unmasks pancreatic ductal adenocarcinoma to adaptive immunity. Gut (2014) 63(11):1769–81. doi: 10.1136/gutjnl-2013-306271

  • CrossRef
  • Google Scholar

• 259

  MeyerMABaerJMKnolhoffBLNyweningTMPanniRZSuXet al. Breast and pancreatic cancer interrupt Irf8-dependent dendritic cell development to overcome immune surveillance. Nat Commun (2018) 9(1):1250. doi: 10.1038/s41467-018-03600-6

  • CrossRef
  • Google Scholar

• 260

  BarillaRMDiskinBCasoRCLeeKBMohanNButtarCet al. Specialized dendritic cells induce tumor-promoting il-10+Il-17+ Foxp3neg regulatory Cd4+ T cells in pancreatic carcinoma. Nat Commun (2019) 10(1):1424. doi: 10.1038/s41467-019-09416-2

  • CrossRef
  • Google Scholar

• 261

  KenkelJATsengWWDavidsonMGTolentinoLLChoiOBhattacharyaNet al. An immunosuppressive dendritic cell subset accumulates at secondary sites and promotes metastasis in pancreatic cancer. Cancer Res (2017) 77(15):4158–70. doi: 10.1158/0008-5472.Can-16-2212

  • CrossRef
  • Google Scholar

• 262

  JangJEHajduCHLiotCMillerGDustinMLBar-SagiD. Crosstalk between regulatory T cells and tumor-associated dendritic cells negates anti-tumor immunity in pancreatic cancer. Cell Rep (2017) 20(3):558–71. doi: 10.1016/j.celrep.2017.06.062

  • CrossRef
  • Google Scholar

• 263

  MontiPLeoneBEMarchesiFBalzanoGZerbiAScaltriniFet al. The cc chemokine mcp-1/Ccl2 in pancreatic cancer progression: Regulation of expression and potential mechanisms of antimalignant activity. Cancer Res (2003) 63(21):7451–61.

  • Google Scholar

• 264

  ZhangAQianYYeZChenHXieHZhouLet al. Cancer-associated fibroblasts promote M2 polarization of macrophages in pancreatic ductal adenocarcinoma. Cancer Med (2017) 6(2):463–70. doi: 10.1002/cam4.993

  • CrossRef
  • Google Scholar

• 265

  LiJByrneKTYanFYamazoeTChenZBaslanTet al. Tumor cell-intrinsic factors underlie heterogeneity of immune cell infiltration and response to immunotherapy. Immunity (2018) 49(1):178–93.e7. doi: 10.1016/j.immuni.2018.06.006

  • CrossRef
  • Google Scholar

• 266

  WiddisonALKaranjiaNDReberHA. Routes of spread of pathogens into the pancreas in a feline model of acute pancreatitis. Gut (1994) 35(9):1306–10. doi: 10.1136/gut.35.9.1306

  • CrossRef
  • Google Scholar

• 267

  GellerLTBarzily-RokniMDaninoTJonasOHShentalNNejmanDet al. Potential role of intratumor bacteria in mediating tumor resistance to the chemotherapeutic drug gemcitabine. Science (2017) 357(6356):1156–60. doi: 10.1126/science.aah5043

  • CrossRef
  • Google Scholar

• 268

  PushalkarSHundeyinMDaleyDZambirinisCPKurzEMishraAet al. The pancreatic cancer microbiome promotes oncogenesis by induction of innate and adaptive immune suppression. Cancer Discov (2018) 8(4):403–16. doi: 10.1158/2159-8290.Cd-17-1134

  • CrossRef
  • Google Scholar

• 269

  RiquelmeEZhangYZhangLMontielMZoltanMDongWet al. Tumor microbiome diversity and composition influence pancreatic cancer outcomes. Cell (2019) 178(4):795–806.e12. doi: 10.1016/j.cell.2019.07.008

  • CrossRef
  • Google Scholar

• 270

  SethiVKurtomSTariqueMLavaniaSMalchiodiZHellmundLet al. Gut microbiota promotes tumor growth in mice by modulating immune response. Gastroenterology (2018) 155(1):33–7.e6. doi: 10.1053/j.gastro.2018.04.001

  • CrossRef
  • Google Scholar

• 271

  GaldieroMRMaroneGMantovaniA. Cancer inflammation and cytokines. Cold Spring Harb Perspect Biol (2018) 10(8):a028662. doi: 10.1101/cshperspect.a028662

  • CrossRef
  • Google Scholar

• 272

  GretenFRGrivennikovSI. Inflammation and cancer: Triggers, mechanisms, and consequences. Immunity (2019) 51(1):27–41. doi: 10.1016/j.immuni.2019.06.025

  • CrossRef
  • Google Scholar

• 273

  ShalapourSKarinM. Pas de deux: Control of anti-tumor immunity by cancer-associated inflammation. Immunity (2019) 51(1):15–26. doi: 10.1016/j.immuni.2019.06.021

  • CrossRef
  • Google Scholar

• 274

  BriukhovetskaDDorrJEndresSLibbyPDinarelloCAKoboldS. Interleukins in cancer: From biology to therapy. Nat Rev Cancer (2021) 21(8):481–99. doi: 10.1038/s41568-021-00363-z

  • CrossRef
  • Google Scholar

• 275

  NietoMAHuangRYJacksonRAThieryJP. Emt: 2016. Cell (2016) 166(1):21–45. doi: 10.1016/j.cell.2016.06.028

  • CrossRef
  • Google Scholar

• 276

  SchwanhäusserBBusseDLiNDittmarGSchuchhardtJWolfJet al. Global quantification of mammalian gene expression control. Nature (2011) 473(7347):337–42. doi: 10.1038/nature10098

  • CrossRef
  • Google Scholar

• 277

  VogelCMarcotteEM. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet (2012) 13(4):227–32. doi: 10.1038/nrg3185

  • CrossRef
  • Google Scholar

• 278

  VogelCde Sousa AbreuRKoDLeS-YShapiroBABurnsSCet al. Sequence signatures and mrna concentration can explain two-thirds of protein abundance variation in a human cell line. Mol Syst Biol (2010) 6(1):400. doi: 10.1038/msb.2010.59

  • CrossRef
  • Google Scholar

• 279

  LiuYBeyerAAebersoldR. On the dependency of cellular protein levels on mrna abundance. Cell (2016) 165(3):535–50. doi: 10.1016/j.cell.2016.03.014

  • CrossRef
  • Google Scholar

• 280

  ZhangBWangJWangXZhuJLiuQShiZet al. Proteogenomic characterization of human colon and rectal cancer. Nature (2014) 513(7518):382–7. doi: 10.1038/nature13438

  • CrossRef
  • Google Scholar

• 281

  MurtaghJJMowattMRLeeCMLeeFJMishimaKNashTEet al. Guanine nucleotide-binding proteins in the intestinal parasite giardia lamblia. isolation of a gene encoding an approximately 20-kda adp-ribosylation factor. J Biol Chem (1992) 267(14):9654–62. doi: 10.1016/s0021-9258(19)50140-5

  • CrossRef
  • Google Scholar

• 282

  LiYKellyWGLogsdonJMJr.SchurkoAMHarfeBDHill-HarfeKLet al. Functional genomic analysis of the adp-ribosylation factor family of gtpases: Phylogeny among diverse eukaryotes and function in c. Elegans FASEB J (2004) 18(15):1834–50. doi: 10.1096/fj.04-2273com

  • CrossRef
  • Google Scholar

• 283

  AdamRD. Biology of giardia lamblia. Clin Microbiol Rev (2001) 14(3):447–75. doi: 10.1128/cmr.14.3.447-475.2001

  • CrossRef
  • Google Scholar

• 284

  TsuchiyaMPriceSRTsaiSCMossJVaughanM. Molecular identification of adp-ribosylation factor mrnas and their expression in mammalian cells. J Biol Chem (1991) 266(5):2772–7. doi: 10.1016/s0021-9258(18)49913-9

  • CrossRef
  • Google Scholar

• 285

  Volpicelli-DaleyLALiYZhangCJKahnRA. Isoform-selective effects of the depletion of adp-ribosylation factors 1-5 on membrane traffic. Mol Biol Cell (2005) 16(10):4495–508. doi: 10.1091/mbc.e04-12-1042

  • CrossRef
  • Google Scholar

• 286

  SabeHOnoderaYMazakiYHashimotoS. Arfgap family proteins in cell adhesion, migration and tumor invasion. Curr Opin Cell Biol (2006) 18(5):558–64. doi: 10.1016/j.ceb.2006.08.002

  • CrossRef
  • Google Scholar

• 287

  DonaldsonJG. Multiple roles for Arf6: Sorting, structuring, and signaling at the plasma membrane. J Biol Chem (2003) 278(43):41573–6. doi: 10.1074/jbc.R300026200

  • CrossRef
  • Google Scholar

• 288

  D'Souza-SchoreyCChavrierP. Arf proteins: Roles in membrane traffic and beyond. Nat Rev Mol Cell Biol (2006) 7(5):347–58. doi: 10.1038/nrm1910

  • CrossRef
  • Google Scholar

• 289

  KondoAHashimotoSYanoHNagayamaKMazakiYSabeH. A new paxillin-binding protein, Pag3/Papalpha/Kiaa0400, bearing an adp-ribosylation factor gtpase-activating protein activity, is involved in paxillin recruitment to focal adhesions and cell migration. Mol Biol Cell (2000) 11(4):1315–27. doi: 10.1091/mbc.11.4.1315

  • CrossRef
  • Google Scholar

• 290

  HashimotoSHashimotoAYamadaAKojimaCYamamotoHTsutsumiTet al. A novel mode of action of an arfgap, Amap2/Pag3/Papa lpha, in Arf6 function. J Biol Chem (2004) 279(36):37677–84. doi: 10.1074/jbc.M404196200

  • CrossRef
  • Google Scholar

• 291

  HashimotoSHashimotoAYamadaAOnoderaYSabeH. Assays and properties of the arfgaps, Amap1 and Amap2, in Arf6 function. Methods Enzymol (2005) 404:216–31. doi: 10.1016/s0076-6879(05)04021-8

  • CrossRef
  • Google Scholar

• 292

  IsmailSAVetterIRSotBWittinghoferA. The structure of an arf-arfgap complex reveals a Ca2+ regulatory mechanism. Cell (2010) 141(5):812–21. doi: 10.1016/j.cell.2010.03.051

  • CrossRef
  • Google Scholar

• 293

  OnoderaYHashimotoSHashimotoAMorishigeMMazakiYYamadaAet al. Expression of Amap1, an arfgap, provides novel targets to inhibit breast cancer invasive activities. EMBO J (2005) 24(5):963–73. doi: 10.1038/sj.emboj.7600588

  • CrossRef
  • Google Scholar

• 294

  OnoderaYNamJ-MHashimotoANormanJCShiratoHHashimotoSet al. Rab5c promotes Amap1–Prkd2 complex formation to enhance B1 integrin recycling in egf-induced cancer invasion. J Cell Biol (2012) 197(7):983–96. doi: 10.1083/jcb.201201065

  • CrossRef
  • Google Scholar

• 295

  HiranoMHashimotoSYonemuraSSabeHAizawaS. Epb41l5 functions to post-transcriptionally regulate cadherin and integrin during epithelial-mesenchymal transition. J Cell Biol (2008) 182(6):1217–30. doi: 10.1083/jcb.200712086

  • CrossRef
  • Google Scholar

• 296

  HashimotoAHashimotoSSuginoHYoshikawaAOnoderaYHandaHet al. Zeb1 induces Epb41l5 in the cancer mesenchymal program that drives Arf6-based invasion, metastasis and drug resistance. Oncogenesis (2016) 5(9):e259–e. doi: 10.1038/oncsis.2016.60

  • CrossRef
  • Google Scholar

• 297

  SabeHHashimotoSMorishigeMOgawaEHashimotoANamJ-Met al. The egfr-Gep100-Arf6-Amap1 signaling pathway specific to breast cancer invasion and metastasis(†). Traffic (Copenhagen Denmark) (2009) 10(8):982–93. doi: 10.1111/j.1600-0854.2009.00917.x

  • CrossRef
  • Google Scholar

• 298

  RubioCAWeisburdBHolderfieldMAriasCFangEDeRisiJLet al. Transcriptome-wide characterization of the Eif4a signature highlights plasticity in translation regulation. Genome Biol (2014) 15(10):476. doi: 10.1186/s13059-014-0476-1

  • CrossRef
  • Google Scholar

• 299

  WolfeALSinghKZhongYDrewePRajasekharVKSanghviVRet al. Rna G-quadruplexes cause Eif4a-dependent oncogene translation in cancer. Nature (2014) 513(7516):65–70. doi: 10.1038/nature13485

  • CrossRef
  • Google Scholar

• 300

  HsiehACLiuYEdlindMPIngoliaNTJanesMRSherAet al. The translational landscape of mtor signalling steers cancer initiation and metastasis. Nature (2012) 485(7396):55–61. doi: 10.1038/nature10912

  • CrossRef
  • Google Scholar

• 301

  ThoreenCCChantranupongLKeysHRWangTGrayNSSabatiniDM. A unifying model for Mtorc1-mediated regulation of mrna translation. Nature (2012) 485(7396):109–13. doi: 10.1038/nature11083

  • CrossRef
  • Google Scholar

• 302

  KawanishiNBacaYXiuJAraiHBattaglinFJayachandranPet al. Association of high gene expression levels of Arf6 with the immune microenvironment and prediction of poor outcomes. J Clin Oncol (2021) 39(15_suppl):3092. doi: 10.1200/JCO.2021.39.15_suppl.3092

  • CrossRef
  • Google Scholar

• 303

  HorikawaMSabeHOnoderaY. Dual roles of Amap1 in the transcriptional regulation and intracellular trafficking of carbonic anhydrase ix. Transl Oncol (2022) 15(1):101258. doi: 10.1016/j.tranon.2021.101258

  • CrossRef
  • Google Scholar

• 304

  MasudaKRipleyBNishimuraRMinoTTakeuchiOShioiGet al. Arid5a controls il-6 mrna stability, which contributes to elevation of il-6 level in vivo. Proc Natl Acad Sci USA (2013) 110(23):9409–14. doi: 10.1073/pnas.1307419110

  • CrossRef
  • Google Scholar

• 305

  NyatiKKZamanMMSharmaPKishimotoT. Arid5a, an rna-binding protein in immune regulation: Rna stability, inflammation, and autoimmunity. Trends Immunol (2020) 41(3):255–68. doi: 10.1016/j.it.2020.01.004

  • CrossRef
  • Google Scholar

• 306

  SaitoYKagamiSSanayamaYIkedaKSutoAKashiwakumaDet al. At-Rich-Interactive domain-containing protein 5a functions as a negative regulator of retinoic acid receptor-related orphan nuclear receptor Γt-induced Th17 cell differentiation. Arthritis Rheumatol (2014) 66(5):1185–94. doi: 10.1002/art.38324

  • CrossRef
  • Google Scholar

• 307

  AmatyaNChildsEECruzJAAggorFEYGargAVBermanAJet al. Il-17 integrates multiple self-reinforcing, feed-forward mechanisms through the rna binding protein Arid5a. Sci Signal (2018) 11(551):eaat4617. doi: 10.1126/scisignal.aat4617

  • CrossRef
  • Google Scholar

• 308

  ZamanMMMasudaKNyatiKKDubeyPKRipleyBWangKet al. Arid5a exacerbates ifn-Γ-Mediated septic shock by stabilizing T-bet mrna. Proc Natl Acad Sci U S A (2016) 113(41):11543–8. doi: 10.1073/pnas.1613307113

  • CrossRef
  • Google Scholar

• 309

  MasudaKRipleyBNyatiKKDubeyPKZamanMMHaniehHet al. Arid5a regulates naive Cd4+ T cell fate through selective stabilization of Stat3 mrna. J Exp Med (2016) 213(4):605–19. doi: 10.1084/jem.20151289

  • CrossRef
  • Google Scholar

• 310

  HaniehHMasudaKMetwallyHChaliseJPMohamedMNyatiKKet al. Arid5a stabilizes Ox40 mrna in murine Cd4(+) T cells by recognizing a stem-loop structure in its 3'utr. Eur J Immunol (2018) 48(4):593–604. doi: 10.1002/eji.201747109

  • CrossRef
  • Google Scholar

• 311

  NyatiKKMasudaKZamanMMDubeyPKMillrineDChaliseJPet al. Tlr4-induced nf-Kb and mapk signaling regulate the il-6 mrna stabilizing protein Arid5a. Nucleic Acids Res (2017) 45(5):2687–703. doi: 10.1093/nar/gkx064

  • CrossRef
  • Google Scholar

• 312

  ZmoraNBashiardesSLevyMElinavE. The role of the immune system in metabolic health and disease. Cell Metab (2017) 25(3):506–21. doi: 10.1016/j.cmet.2017.02.006

  • CrossRef
  • Google Scholar

• 313

  ArgilésJMBusquetsSStemmlerBLópez-SorianoFJ. Cancer cachexia: Understanding the molecular basis. Nat Rev Cancer (2014) 14(11):754–62. doi: 10.1038/nrc3829

  • CrossRef
  • Google Scholar

• 314

  ScottHRMcMillanDCCrillyAMcArdleCSMilroyR. The relationship between weight loss and interleukin 6 in non-Small-Cell lung cancer. Br J Cancer (1996) 73(12):1560–2. doi: 10.1038/bjc.1996.294

  • CrossRef
  • Google Scholar

• 315

  MosesAGWMaingayJSangsterKFearonKCHRossJA. Pro-inflammatory cytokine release by peripheral blood mononuclear cells from patients with advanced pancreatic cancer: Relationship to acute phase response and survival. Oncol Rep (2009) 21(4):1091–5. doi: 10.3892/or_00000328

  • CrossRef
  • Google Scholar

• 316

  EbrahimiBTuckerSLLiDAbbruzzeseJLKurzrockR. Cytokines in pancreatic carcinoma: Correlation with phenotypic characteristics and prognosis. Cancer (2004) 101(12):2727–36. doi: 10.1002/cncr.20672

  • CrossRef
  • Google Scholar

• 317

  MartignoniMEKunzePHildebrandtWKünzliBBerberatPGieseTet al. Role of mononuclear cells and inflammatory cytokines in pancreatic cancer-related cachexia. Clin Cancer Res (2005) 11(16):5802–8. doi: 10.1158/1078-0432.Ccr-05-0185

  • CrossRef
  • Google Scholar

• 318

  NishimotoNKanakuraYAozasaKJohkohTNakamuraMNakanoSet al. Humanized anti–Interleukin-6 receptor antibody treatment of multicentric castleman disease. Blood (2005) 106(8):2627–32. doi: 10.1182/blood-2004-12-4602

  • CrossRef
  • Google Scholar

• 319

  WalleniusVWalleniusKAhrénBRudlingMCarlstenHDicksonSLet al. Interleukin-6-Deficient mice develop mature-onset obesity. Nat Med (2002) 8(1):75–9. doi: 10.1038/nm0102-75

  • CrossRef
  • Google Scholar

• 320

  MaYGaoMSunHLiuD. Interleukin-6 gene transfer reverses body weight gain and fatty liver in obese mice. Biochim Biophys Acta (2015) 1852(5):1001–11. doi: 10.1016/j.bbadis.2015.01.017

  • CrossRef
  • Google Scholar

• 321

  ChaliseJPHashimotoSParajuliGKangSSinghSKGemechuYet al. Feedback regulation of Arid5a and ppar-Γ2 maintains adipose tissue homeostasis. Proc Natl Acad Sci USA (2019) 116(30):15128–33. doi: 10.1073/pnas.1906712116

  • CrossRef
  • Google Scholar

• 322

  ParajuliGTekgucMWingJBHashimotoAOkuzakiDHirataTet al. Arid5a promotes immune evasion by augmenting tryptophan metabolism and chemokine expression. Cancer Immunol Res (2021) 9(8):862–76. doi: 10.1158/2326-6066.Cir-21-0014

  • CrossRef
  • Google Scholar

• 323

  VegliaFSansevieroEGabrilovichDI. Myeloid-derived suppressor cells in the era of increasing myeloid cell diversity. Nat Rev Immunol (2021) 21(8):485–98. doi: 10.1038/s41577-020-00490-y

  • CrossRef
  • Google Scholar

• 324

  SakaguchiSMikamiNWingJBTanakaAIchiyamaKOhkuraN. Regulatory T cells and human disease. Annu Rev Immunol (2020) 38:541–66. doi: 10.1146/annurev-immunol-042718-041717

  • CrossRef
  • Google Scholar

• 325

  EdingerALThompsonCB. Antigen-presenting cells control T cell proliferation by regulating amino acid availability. Proc Natl Acad Sci U S A (2002) 99(3):1107–9. doi: 10.1073/pnas.042707999

  • CrossRef
  • Google Scholar

• 326

  MunnDHShafizadehEAttwoodJTBondarevIPashineAMellorAL. Inhibition of T cell proliferation by macrophage tryptophan catabolism. J Exp Med (1999) 189(9):1363–72. doi: 10.1084/jem.189.9.1363

  • CrossRef
  • Google Scholar

• 327

  MezrichJDFechnerJHZhangXJohnsonBPBurlinghamWJBradfieldCA. An interaction between kynurenine and the aryl hydrocarbon receptor can generate regulatory T cells. J Immunol (2010) 185(6):3190–8. doi: 10.4049/jimmunol.0903670

  • CrossRef
  • Google Scholar

• 328

  NguyenNTKimuraANakahamaTChinenIMasudaKNoharaKet al. Aryl hydrocarbon receptor negatively regulates dendritic cell immunogenicity Via a kynurenine-dependent mechanism. Proc Natl Acad Sci USA (2010) 107(46):19961–6. doi: 10.1073/pnas.1014465107

  • CrossRef
  • Google Scholar

• 329

  NeamahWHSinghNPAlghetaaHAbdullaOAChatterjeeSBusbeePBet al. Ahr activation leads to massive mobilization of myeloid-derived suppressor cells with immunosuppressive activity through regulation of Cxcr2 and microrna mir-150-5p and mir-543-3p that target anti-inflammatory genes. J Immunol (2019) 203(7):1830–44. doi: 10.4049/jimmunol.1900291

  • CrossRef
  • Google Scholar

• 330

  FeinMRHeX-YAlmeidaASBružasEPommierAYanRet al. Cancer cell Ccr2 orchestrates suppression of the adaptive immune response. J Exp Med (2020) 217(10):e20181551. doi: 10.1084/jem.20181551

  • CrossRef
  • Google Scholar

• 331

  HuangBPanPYLiQSatoAILevyDEBrombergJet al. Gr-1+Cd115+ immature myeloid suppressor cells mediate the development of tumor-induced T regulatory cells and T-cell anergy in tumor-bearing host. Cancer Res (2006) 66(2):1123–31. doi: 10.1158/0008-5472.Can-05-1299

  • CrossRef
  • Google Scholar

• 332

  HuangBLeiZZhaoJGongWLiuJChenZet al. Ccl2/Ccr2 pathway mediates recruitment of myeloid suppressor cells to cancers. Cancer Lett (2007) 252(1):86–92. doi: 10.1016/j.canlet.2006.12.012

  • CrossRef
  • Google Scholar

• 333

  LiBHGarstkaMALiZF. Chemokines and their receptors promoting the recruitment of myeloid-derived suppressor cells into the tumor. Mol Immunol (2020) 117:201–15. doi: 10.1016/j.molimm.2019.11.014

  • CrossRef
  • Google Scholar

• 334

  MitsunagaSIkedaMShimizuSOhnoIFuruseJInagakiMet al. Serum levels of il-6 and il-1β can predict the efficacy of gemcitabine in patients with advanced pancreatic cancer. Br J Cancer (2013) 108(10):2063–9. doi: 10.1038/bjc.2013.174

  • CrossRef
  • Google Scholar

• 335

  DenleySMJamiesonNBMcCallPOienKAMortonJPCarterCRet al. Activation of the il-6r/Jak/Stat pathway is associated with a poor outcome in resected pancreatic ductal adenocarcinoma. J Gastrointest Surg (2013) 17(5):887–98. doi: 10.1007/s11605-013-2168-7

  • CrossRef
  • Google Scholar

• 336

  HuangCYangGJiangTZhuGLiHQiuZ. The effects and mechanisms of blockage of Stat3 signaling pathway on il-6 inducing emt in human pancreatic cancer cells in vitro. Neoplasma (2011) 58(5):396–405. doi: 10.4149/neo_2011_05_396

  • CrossRef
  • Google Scholar

• 337

  FukudaAWangSCJPtMAEFLiouAGEKet al. Stat3 and Mmp7 contribute to pancreatic ductal adenocarcinoma initiation and progression. Cancer Cell (2011) 19(4):441–55. doi: 10.1016/j.ccr.2011.03.002

  • CrossRef
  • Google Scholar

• 338

  KangRLouxTTangDSchapiroNEVernonPLiveseyKMet al. The expression of the receptor for advanced glycation endproducts (Rage) is permissive for early pancreatic neoplasia. Proc Natl Acad Sci U S A (2012) 109(18):7031–6. doi: 10.1073/pnas.1113865109

  • CrossRef
  • Google Scholar

• 339

  FlintTRJanowitzTConnellCMRobertsEWDentonAECollAPet al. Tumor-induced il-6 reprograms host metabolism to suppress anti-tumor immunity. Cell Metab (2016) 24(5):672–84. doi: 10.1016/j.cmet.2016.10.010

  • CrossRef
  • Google Scholar

• 340

  KishimotoTKangS. Il-6 revisited: From rheumatoid arthritis to car T cell therapy and covid-19. Annu Rev Immunol (2022) 40:323–48. doi: 10.1146/annurev-immunol-101220-023458

  • CrossRef
  • Google Scholar

• 341

  JonesSAJenkinsBJ. Recent insights into targeting the il-6 cytokine family in inflammatory diseases and cancer. Nat Rev Immunol (2018) 18(12):773–89. doi: 10.1038/s41577-018-0066-7

  • CrossRef
  • Google Scholar

• 342

  HiranoT. Il-6 in inflammation, autoimmunity and cancer. Int Immunol (2021) 33(3):127–48. doi: 10.1093/intimm/dxaa078

  • CrossRef
  • Google Scholar

• 343

  HashimotoSHashimotoAMuromotoRKitaiYOritaniKMatsudaT. Central roles of Stat3-mediated signals in onset and development of cancers: Tumorigenesis and immunosurveillance. Cells (2022) 11(16):2618. doi: 10.3390/cells11162618

  • CrossRef
  • Google Scholar