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PubMed2026

Beta cell-derived cholecystokinin drives obesity-associated pancreatic adenocarcinoma development.

Pancreatic endocrine-exocrine crosstalk plays a key role in normal physiology and disease and can be altered by host metabolic states, such as obesity. Classically, endocrine islet beta (β) cell secretion of insulin is thought to promote the development of obesity-associated pancreatic adenocarcinoma (PDAC), an exocrine cell-derived tumor. Here, we show that β cell expression of the peptide hormone cholecystokinin (CCK) is necessary and sufficient for obesity-associated PDAC progression in mice and that CCK expression - rather than insulin - correlates strongly with enhanced tumorigenesis. Single-cell RNA-sequencing, in silico latent-space archetypal and trajectory analysis, and experimental lineage tracing in vivo reveal that obesity induces the expansion of postnatal immature β cells, which adapt to express CCK via stress-responsive JNK/cJun signaling. Finally, obesity perturbs CCK-dependent peri-islet exocrine cell transcriptional states and enhances islet-proximal tumor formation. These results define endocrine-exocrine CCK signaling as a bona fide driver of obesity-associated PDAC development and uncover avenues to target the endocrine pancreas to subvert exocrine tumorigenesis.

Animals↗

PubMed2026

MEK inhibitor-based genomically matched combinatorial targeted therapies in metastatic pancreatic adenocarcinoma with KRAS alterations.

INTRODUCTION: Pancreatic Ductal Adenocarcinoma (PDAC) is often caused by mutations in multiple genes including KRAS (activating the Ras-Raf-MEK-ERK pathway). This study evaluated the role of MEK inhibitor (MEKi)-based combinatorial targeted therapies in patients with PDAC. Methods. This is a retrospective/prospective observational, single institution study, including 29 patients with metastatic PDAC with KRAS alterations, treated with MEKi therapies between 2022-2024. RESULTS: Ten patients had KRAS G12R (34.5%), ten G12D (34.5%), and nine G12V (31%). Majority of patients received MEKi therapy as third-line and beyond (KRAS G12R/G12D/G12V 60%/50%/78%, respectively). Median overall survival from MEKi initiation for KRAS G12R/G12D/G12V was 8.2/5.1/4.7 months (P = 0.5), respectively, and median progression-free survival was 4.4/2.3/1.4 months (P = 0.11). Six (21%) patients discontinued at least one drug in the treatment combination due to toxicity. CONCLUSIONS: MEKi-based combinatorial therapies had modest disease control in patients with KRAS G12R, and minimal disease control in patients with KRAS G12D/V in the late-line setting.

KRAS↗

PubMed2025

Pharmacogenomics-based subtype decoded implications for risk stratification and immunotherapy in pancreatic adenocarcinoma.

BACKGROUND: With fatal malignant peculiarities and poor survival rate, outcomes of pancreatic adenocarcinoma (PAAD) were frustrated by non-response and even resistance to therapy due to heterogeneity across clinical patients. Nevertheless, pharmacogenomics has been developed for individualized-treatment and still maintains obscure in PAAD. METHODS: A total of 964 samples from 10 independent multi-center cohorts were enrolled in our study. With drug response data from the profiling of relative inhibition simultaneously in mixtures (PRISM) and genomics of drug sensitivity in cancer (GDSC) databases, we established and validated multidimensionally three pharmacogenomics-classified subtypes using non-negative matrix factorization (NMF) and nearest template prediction (NTP) algorithms, separately. The heterogenous biological characteristics and precision medicine strategies among subtypes were further investigated. RESULTS: Three pharmacogenomics-classified subtypes after stable and reproducible validation, distinguished in six aspects of prognosis, biological peculiarities, immune landscapes, genomic variations, immunotherapy and individualized management strategies. Subtype 2 was close to immunocompetent phenotype and projected to immunotherapy; Subtype 3 held most favorable outcomes and metabolic pathways distinctively, promising to be treated with first-line agents. Subtype 1 with worst prognosis, was anticipated to chromosome instability (CIN) phenotype and resistant to chemotherapeutic agents. In addition, ITGB6 contributed to subtype 1 resistance to 5-fluorouracil, and knockdown of ITGB6 enhanced sensitivity to 5-fluorouracil in in vitro experiments. Ultimately, appropriate clinical stratified treatments were assigned to corresponding subtypes according to pharmacogenomic transcripts. Some limitations were not taken into account, thus needs to be supported by more research. CONCLUSION: A span-new molecular subtype exploited for PAAD uncovered an insight into precise medication on ground of pharmacogenomics, and highly refined multiple clinical management strategies for specific patients.

Humans↗

PubMed2026

Metabolism pathway-based subtyping in pancreatic adenocarcinoma: an integrated study by bulk RNA-sequence and machine learning algorithms.

BACKGROUND: Pancreatic adenocarcinoma (PAAD) is highly aggressive, and its tumor microenvironment has significant metabolic and immune microenvironment complexity and genomic instability. In this study, by integrating the metabolic pathway activity score and clinical data, we constructed a novel risk assessment model to reveal the unique biological behavior and clinical significance behind different PAAD subtypes. METHODS: In this study, the transcriptome and clinical data of TCGA and GSE57495 databases were integrated to explore the interaction between metabolic pathways. Based on unsupervised clustering analysis of pathway activity and survival prognosis, patients with PAAD were classified into metabolic subtypes with significant prognostic differences. Subsequently, we assessed the heterogeneity of these subtypes in terms of clinical outcomes, genomic characteristics, and immune microenvironment composition. Based on the differentially expressed genes (DEGs) among metabolic subtypes, a clinical prognostic risk model and nomogram were constructed, which were double-validated by GSE57495-independent cohort and GSE57495 + TCGA-PAAD combined cohort. Finally, the correlations between risk scores (RSs) and signaling pathway activity and tumor immune microenvironment characteristics were evaluated. RESULTS: Based on metabolic pathway correlation and prognostic information, 240 patients in the TCGA-PAAD and GSE57495 datasets were divided into three subgroups. There were significant differences between subgroups in gene expression, pathway activity, clinical prognosis, and immune infiltration characteristics among the subtypes. Using machine learning algorithms, an RS model was constructed from DEGs among the subgroups, with the random forest method showing the best performance. A nomogram integrating the RS and clinical indicators demonstrated excellent predictive accuracy for 1-, 3-, and 5-year survival rates, confirming the RS as an independent prognostic factor. High- and low-risk groups exhibited significant differences in immune infiltration, pathway activity, and gene mutations. Drug sensitivity analysis showed that the high-risk group was more sensitive to AZD6244, ABT737, and other drugs. CONCLUSION: This study stratified patients with PAAD into three subgroups based on metabolic pathways and prognostic information, revealing significant differences in clinical outcomes, immune characteristics, and genetic mutations. The robust RS model developed from these findings demonstrated strong predictive power for patient survival and identified promising therapeutic strategies, providing valuable insights for advancing precision medicine in PAAD.

immune microenvironment↗

PubMed2026

S100P as a Shared Biomarker in Inflammatory Bowel Disease, Colorectal Cancer, and Pancreatic Adenocarcinoma: An Integrated Transcriptomic Analysis.

Inflammatory bowel disease (IBD) is associated with an increased risk of colorectal cancer (CRC) and pancreatic adenocarcinoma (PAAD), yet the molecular features shared among these diseases remain incompletely understood. This study aimed to identify common genes and biological pathways associated with IBD, CRC, and PAAD through integrated transcriptomic analysis and experimental validation. Gene expression datasets for IBD, CRC, and PAAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Weighted gene co-expression network analysis and differential expression analysis were performed to identify disease-associated and shared genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (analyses were used to explore enriched biological functions and pathways. Immune cell infiltration was evaluated using Cell-type Identification by Estimating Relative Subsets of RNA Transcripts. Receiver operating characteristic analysis was performed to assess the diagnostic performance of common genes. Single-cell RNA sequencing analysis was conducted to examine the cellular distribution of S100P. In addition, the effects of S100P downregulation were evaluated in lipopolysaccharide (LPS)-stimulated colonic epithelial cells. A total of 162 disease-associated genes and four common genes were identified. Functional enrichment analyses indicated significant enrichment of immune- and inflammation-related pathways, including the interleukin-17 signaling pathway. Immune infiltration analysis revealed similar trends in several immune cell populations across IBD, CRC, and PAAD. Single-cell analysis showed elevated S100P expression in epithelial cells from all three diseases. Downregulation of S100P restored the proliferative capacity of LPS-stimulated colonic epithelial cells and reduced inflammatory cytokine expression. Integrated transcriptomic analysis identified S100P as a biomarker associated with IBD, CRC, and PAAD and highlighted shared immune-related features across these diseases.

Humans↗

PubMed2026

Casein Kinase 1 Alpha 1 Is Over-expressed in Pancreatic Adenocarcinoma Tissues and Correlates With Shorter Patient Survival.

BACKGROUND/AIM: A quarter of a century has passed since the start of the 21st century, and cancer, once considered an incurable disease, has become manageable thanks to the development of various treatments. However, pancreatic adenocarcinoma (PAAD) remains one of the deadliest cancers in the world, with over 95% of patients dying within five years. This is because the anatomical location of the pancreas makes it very difficult to detect with imaging, and symptoms often do not appear until the cancer invades the nerve plexus in its terminal stages, meaning that by the time it is diagnosed, it is often too late. Therefore, the development of prognostic markers is an urgent task. Casein kinase 1 alpha 1 (CSNK1A1) is a serine/threonine protein kinase deeply involved in Wnt signaling and the tumor suppressor mechanisms of p53. While the association between increased or decreased CSNK1A1 expression and prognosis has been reported in many types of cancer tissue, its association in PAAD is not yet fully understood. This study investigated the potential of CSNK1A1 as a prognostic marker for PAAD. MATERIALS AND METHODS: We used Gene Expression Profiling Interactive Analysis (GEPIA) and the University of Alabama Birmingham Cancer Data Analysis Portal (UALCAN) bioinformatics platforms to analyze CSNK1A1 mRNA expression, protein levels, and survival rates of patients with PAAD obtained from The Cancer Genome Atlas (TCGA) database. RESULTS: CSNK1A1 mRNA and protein levels were significantly higher in PAAD tissue compared to normal pancreatic tissue, and this increase was associated with a poor prognosis in patients with PAAD. CONCLUSION: In PAAD tissue, increased expression of CSNK1A1 mRNA and protein was observed compared to normal pancreatic tissue, and this increased expression correlated with poor patient prognosis. Therefore, CSNK1A1 is considered a promising prognostic biomarker in PAAD.

CSNK1A1↗

PubMed2026

Integrated transcriptomic and functional characterization of Claudin-1 reveals its oncogenic and immunomodulatory roles in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains among the deadliest malignancies, driven by its invasive nature and lack of effective biomarkers. Disruption of the epithelial barrier, mediated by tight junction components, is a critical yet underexplored contributor to PDAC progression. Claudins, integral regulators of tight junction integrity, display altered expression across cancers, but their prognostic and immunomodulatory roles in PDAC remain unclear. We performed an integrative analysis of 177 RNA-Seq datasets from TCGA and GTEx to characterize Claudin family alterations in PDAC. Differential expression, copy number variation, methylation, and co-expression networks were analyzed alongside clinical and survival data. Prognostic significance was assessed using Kaplan - Meier and Cox regression analyses, while immune cell infiltration was examined using deconvolution algorithms. Functional validation of Claudin-1 was conducted in Capan-1 cells using CRISPR/Cas9 knockout, followed by proliferation, wound-healing, and Western blot assays. Ten Claudin genes were significantly dysregulated, with Claudin-1 and Claudin-4 frequently amplified and associated with advanced stage and poor survival. High Claudin-1 expression correlated with reduced immune infiltration, indicating an immune-excluded phenotype characterized by immune cells retained in the tumor stroma but largely absent from the tumor parenchyma. Claudin-1 knockout markedly inhibited proliferation, migration, and EMT, evidenced by downregulation of Snail and Slug and restoration of E-cadherin expression. This integrative transcriptomic and functional study identifies Claudin-1 as a key driver of PDAC aggressiveness and immune modulation. These findings establish Claudin-1 as a promising prognostic biomarker and therapeutic target for restoring epithelial integrity and counteracting immune evasion in pancreatic cancer.

Humans↗

PubMed2022

An Exosomal miRNA Biomarker for the Detection of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains a difficult tumor to diagnose and treat. To date, PDAC lacks routine screening with no markers available for early detection. Exosomes are 40-150 nm-sized extracellular vesicles that contain DNA, RNA, and proteins. These exosomes are released by all cell types into circulation and thus can be harvested from patient body fluids, thereby facilitating a non-invasive method for PDAC detection. A bioinformatics analysis was conducted utilizing publicly available miRNA pancreatic cancer expression and genome databases. Through this analysis, we identified 18 miRNA with strong potential for PDAC detection. From this analysis, 10 (MIR31, MIR93, MIR133A1, MIR210, MIR330, MIR339, MIR425, MIR429, MIR1208, and MIR3620) were chosen due to high copy number variation as well as their potential to differentiate patients with chronic pancreatitis, neoplasms, and PDAC. These 10 were examined for their mature miRNA expression patterns, giving rise to 18 mature miRs for further analysis. Exosomal RNA from cell culture media was analyzed via RTqPCR and seven mature miRs exhibited statistical significance (miR-31-5p, miR-31-3p, miR-210-3p, miR-339-5p, miR-425-5p, miR-425-3p, and miR-429). These identified biomarkers can potentially be used for early detection of PDAC.

Humans↗

PubMed2026

Machine Learning-Based Identification of Survival-Associated CpG Biomarkers in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an exceptionally aggressive cancer with a 5-year survival rate of less than 10%, driven by late-stage diagnosis, limited treatment options, and a lack of reliable biomarkers for early detection and prognosis. In this study, we integrated DNA methylation data from TCGA and ICGC cohorts, categorizing samples based on survival time, and identified 688 differentially methylated CpG sites, along with 224 CpG biomarkers significantly associated with patient survival through statistical and machine learning-based analyses. We developed a random forest model to predict patient survival, achieving 85.2% accuracy for short-survival patients and 70.0% for long-survival patients in the validation set. External dataset validation further confirmed the model's robustness and accuracy. De novo motif analysis of genomic regions surrounding the 224 CpG biomarkers identified TWIST1 and FOXA2 as key transcriptional regulators enriched in survival-associated CpG sites, linking their activity to patient survival outcomes. Collectively, our findings highlight valuable epigenetic biomarkers and provide a predictive model to assess PDAC risk levels post-surgery, offering the potential for improved patient stratification and personalized therapeutic strategies.

DNA methylation↗

PubMed2024

Development of a Fit-For-Purpose Multi-Marker Panel for Early Diagnosis of Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) suffers from a lack of an effective diagnostic method, which hampers improvement in patient survival. Carbohydrate antigen 19-9 (CA19-9) is the only FDA-approved blood biomarker for PDAC, yet its clinical utility is limited due to suboptimal performance. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a burgeoning technology in clinical proteomics for the discovery, verification, and validation of novel biomarkers. A plethora of protein biomarker candidates for PDAC have been identified using LC-MS, yet few has successfully transitioned into clinical practice. This translational standstill is owed partly to insufficient considerations of practical needs and perspectives of clinical implementation during biomarker development pipelines, such as demonstrating the analytical robustness of proposed biomarkers which is critical for transitioning from research-grade to clinical-grade assays. Moreover, the throughput and cost-effectiveness of proposed assays ought to be considered concomitantly from the early phases of the biomarker pipelines for enhancing widespread adoption in clinical settings. Here, we developed a fit-for-purpose multi-marker panel for PDAC diagnosis by consolidating analytically robust biomarkers as well as employing a relatively simple LC-MS protocol. In the discovery phase, we comprehensively surveyed putative PDAC biomarkers from both in-house data and prior studies. In the verification phase, we developed a multiple-reaction monitoring (MRM)-MS-based proteomic assay using surrogate peptides that passed stringent analytical validation tests. We adopted a high-throughput protocol including a short gradient (<10 min) and simple sample preparation (no depletion or enrichment steps). Additionally, we developed our assay using serum samples, which are usually the preferred biospecimen in clinical settings. We developed predictive models based on our final panel of 12 protein biomarkers combined with CA19-9, which showed improved diagnostic performance compared to using CA19-9 alone in discriminating PDAC from non-PDAC controls including healthy individuals and patients with benign pancreatic diseases. A large-scale clinical validation is underway to demonstrate the clinical validity of our novel panel.

Humans↗

PubMed2026

Decoding spatiotemporal fibrotic and cellular immunosuppression of therapeutic T cells in live pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDA) is profoundly immunosuppressive. To help define this behavior, we present integrated experimental and computational frameworks to elucidate therapeutic T cell dynamics. Through the development of TME-CARTographer (TME-CART), a computational pipeline integrating high-dimensional data, graph theory, behavior analysis, and deep learning (DL), we present quantitative insights on 4D T cell-TME interactions in live PDA tumors. Mapping physical immunosuppression demonstrates that collagen fiber architectures direct migration while concomitantly limiting off-axis movement, creating immune exclusion zones. Expanding these findings, we establish that the collagen matrix harbors and spatially organizes immunosuppressive myeloid cells to serve as cooperative co-modulators of T cell behaviors, including migration, sampling, repulsion, and sequestration. Consistent with these findings, DL defines both linear and nonlinear collagen matrix and cellular neighborhood interactions as drivers of T cell behavior. The TME-CART DL framework also accurately predicts shifts in immunosuppression following depletion of myeloid cells. Overall, we identify synergistic barriers impeding anti-tumor T cell behaviors and present TME-CART as a discovery platform for interpreting complex 4D data to enhance the understanding and design of immunotherapies.

Journal Article↗

PubMed2025

Machine Learning-Based Identification of Survival-Associated CpG Biomarkers in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an exceptionally aggressive cancer with a 5-year survival rate of less than 10%, driven by late-stage diagnosis, limited treatment options, and a lack of reliable biomarkers for early detection and prognosis. In this study, we integrated DNA methylation data from TCGA and ICGC cohorts, categorizing samples based on survival time, and identified 684 differentially methylated CpG sites, along with 224 CpG biomarkers significantly associated with patient survival through statistical and machine learning-based analyses. We developed a random forest model to predict patient survival, achieving 85.2% accuracy for short-survival patients and 70.0% for long-survival patients in the validation set. External dataset validation further confirmed the model's robustness and accuracy. De novo motif analysis of genomic regions surrounding the 224 CpG biomarkers identified TWIST1 and FOXA2 as key transcriptional regulators enriched in survival-associated CpG sites, linking their activity to patient survival outcomes. Collectively, our findings highlight valuable epigenetic biomarkers and provide a predictive model to assess PDAC risk levels post-surgery, offering the potential for improved patient stratification and personalized therapeutic strategies.

Journal Article↗

PubMed2026

Extravascular coagulation stabilizes pro-fibrotic stromal states via tumor-intrinsic PAR1 signaling in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) exhibits a desmoplastic stroma with context-dependent tumor-restraining and tumor-promoting functions, highlighting the need to selectively reprogram stromal states. Extravascular coagulation is a prominent feature of the PDAC tumor microenvironment, yet whether it functions as an upstream regulator of fibrotic stromal states, rather than merely a byproduct of tumor-associated vascular dysfunction, has remained unclear. Here, we identify extravascular coagulation as a tumor-amplified regulatory module that stabilizes pro-fibrotic stromal states via tumor-intrinsic protease-activated receptor-1 (PAR1) signaling. To interrogate this axis mechanistically, we integrated human tumor bioinformatics with microphysiological tumor-stroma (MPTS) models that reconstruct tumor-stroma interactions under controlled coagulation exposure, followed by cross-scale validation in vivo. Analysis of The Cancer Genome Atlas (TCGA) revealed heterogeneous F2R (PAR1) expression across tumors, with elevated expression associated with fibrotic transcriptional programs and reduced survival. Consistently, thrombin induced coordinated pro-fibrotic programs in tumor cells and cancer-associated fibroblasts (CAFs), which were recapitulated in MPTS where tumor-intrinsic PAR1 was required for amplification of extracellular matrix deposition and CAF activation. Mechanistically, PAR1 signaling amplified tumor-stroma communication, in part through induction of TGF-β1-dependent pathways, establishing a reinforcing feedback loop that stabilizes fibrotic remodeling. Pharmacologic inhibition of PAR1 selectively suppressed the fibrotic transcriptional program within myofibroblastic CAFs while reducing the abundance of other CAF subtypes, reprogramming stromal states and attenuating tumor progression across MPTS and in vivo models. These findings establish a coagulation-PAR1 axis as an upstream organizer of PDAC stromal architecture and identify pharmacologic PAR1 inhibition as a mechanistically grounded strategy for selectively reprogramming the tumor-promoting stroma.

Journal Article↗

PubMed2026

GFER Represents a Target for Dual Disruption of Redox Homeostasis and Reactivation of the Immune Response in Pancreatic Adenocarcinoma.

UNLABELLED: Both metabolic dysregulation and the immunosuppressive tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC) contribute to the recalcitrance of this lethal disease to treatment. Accordingly, we aimed to identify and characterize a target that elicits an anticancer response through both disrupting cancer cell redox homeostasis and increasing the immunogenicity of PDAC. First, mitochondrial metabolic dependencies in PDAC were identified by using a CRISPR-Cas9 screening system with a custom single-guide RNA library. Functional validation analyses revealed GFER, a mitochondrial FAD-dependent sulfhydryl oxidase, as an essential regulator of tumor growth. In vitro and in vivo methodologies demonstrated that GFER depletion perturbed redox homeostasis and stimulated tumor immunogenicity, including sensitization to immune checkpoint blockade. In patient-derived xenograft models of PDAC, the growth-inhibitory response induced by GFER depletion was mediated by an altered oxidative balance that released damaged mitochondrial DNA into the cytoplasm of tumor cells, leading to the activation of the cGAS-STING pathway and expression of type I IFNs. This effect was recapitulated in a mouse immunocompetent syngeneic PDAC model, in which GFER depletion suppressed tumor growth and promoted T-cell infiltration to enhance tumor-killing effects. Consequently, GFER depletion significantly increased the antitumor efficacy of immune checkpoint blockade. Overall, these findings identify GFER as a critical node for both mitochondrial redox homeostasis and immunomodulation in PDAC and reveal a therapeutic opportunity for sensitizing PDAC to immune checkpoint blockade. SIGNIFICANCE: GFER is essential for mitochondrial redox balance and suppressing tumor immunogenicity in pancreatic tumors, with the combination of GFER inhibition with immune checkpoint blockade resulting in a strong antitumor response.

Animals↗

PubMed2026

RNF43 Mutations Are Associated With the Classical Molecular Subtype, Vigorous Antitumor Immune Responses, and Prolonged Survival in Pancreatic Adenocarcinoma.

RNF43 mutations were correlated with microsatellite status in colorectal cancer and with fewer and later recurrences in pancreatic ductal adenocarcinoma (PDAC). Here, we undertake a detailed assessment of RNF43 mutations in PDAC. A total of 313 PDACs (308 microsatellite stable [MSS] and 5 microsatellite-instable [MSI] cases) underwent next-generation sequencing (Oncomine Tumor Mutation Load assay; Thermo Fisher). Spatial analyses (NanoString) classified PDACs according to their transcriptomic and proteomic immune signaling. Fluorescent imaging was used to define spatial compartments (tumor: pancytokeratin+/CD45- and leukocytes: pancytokeratin-/CD45+). Each of 20 PDACs with RNF43 mutations (RNF43mut) and without RNF43 mutations (RNF43wt) underwent multiplex immunofluorescence analysis to determine immune status. A total of 153 PDACs (22 RNF43mut and 131 RNF43wt cases) underwent bulk RNA sequencing to assign into molecular subtypes. Overall, 24 RNF43 mutations were identified (22 MSS PDACs and 2 MSI PDACs). The incidence of RNF43 mutations in MSS PDACs (7.1%) was consistent with The Cancer Genome Atlas (6.7%). However, RNF43 mutations were more frequent among MSI PDACs (40%). Additionally, RNF43mut had differential frequencies of other mutations (including Wnt pathway genes), higher tumor mutational burden values (5.5 mut/mb vs 1.67 mut/mb; P < .01), and significantly longer overall survival (47 vs 18 months; P < .0001) than RNF43wt. Moreover, RNF43mut exhibited significantly higher densities of CD8+ T lymphocytes, dendritic cells, and B lymphocytes (P < .001) and an upregulation of ITGAX, CD11c, CD8, and HLA-DR compared with RNF43wt. Patients with RNF43mut PDACs were more often of the classical molecular subtype (20/22, 90.9%). RNF43mut PDACs showed high tumor mutational burden values, suggesting increased neoantigen load coupled with an abundance of antigen-presenting immune cells and an upregulation of immune determinants promoting antigen presentation. All this contributes to stronger antitumor immune responses and improved clinical outcomes.

Humans↗

PubMed2026

Development and Validation of a Prognostic Signature Based on Transcription Factors Associated with Endoplasmic Reticulum Stress in Pancreatic Adenocarcinoma.

BACKGROUND: Endoplasmic reticulum stress (ER stress) plays a crucial role in influencing the malignant behaviors of various tumors. Targeting the expression or degradation of transcription factors (TFs) offers a promising avenue for cancer treatment. However, a detailed understanding of how ER stress affects TF function and their interactions remains limited. This study aims to develop a prognostic model and identify TFs associated with ER stress in pancreatic ductal adenocarcinoma (PDAC). METHODS: We obtained gene expression profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA). To develop a prognostic signature, we performed several analyses, including unsupervised clustering, enrichment analysis, immune infiltration assessment, as well as univariate, LASSO, and multivariate Cox regression analyses. Four transcription factors-STAT1, IRF6, NRF1, and RXRA-were incorporated into a risk model, which was subsequently validated using the GSE dataset. Additionally, we examined IRF6 through quantitative PCR, western blotting, flow cytometry, and immunohistochemistry in vitro using pancreatic cancer cell lines and a tissue microarray. RESULTS: The high-risk group identified by the model exhibited significant associations with immune cell infiltration and poorer survival outcomes, though there was no significant correlation with tumor purity (p = 0.19). Furthermore, IRF6 downregulation in vitro was found to inhibit pancreatic cancer cell proliferation and promote apoptosis. IRF6 depletion also increased the expression of key molecules involved in ER stress at both the transcriptional and translational levels. Immunohistochemical analysis revealed marked differences in IRF6 expression between tumor and adjacent non-tumor tissues (59.29±29.88 vs. 95.22±40.80, p<0.001). CONCLUSION: This study provides evidence that the constructed risk model can effectively predict prognosis in PDAC patients. Transcription factors related to ER stress, such as IRF6, show promise as both prognostic biomarkers and potential therapeutic targets for PDAC.

Humans↗

PubMed2026

Impact of Tumor Genomic Profile on Adjuvant Chemotherapy Efficacy in Resected Pancreatic Adenocarcinoma: Results From the PRODIGE-24/CCTG PA6 Study.

PURPOSE: Modified fluorouracil, leucovorin, irinotecan, and oxaliplatin (mFOLFIRINOX/mFFX) is the standard adjuvant chemotherapy for resected pancreatic ductal adenocarcinoma (PDAC), offering survival benefits over gemcitabine (GEM). However, the contribution of molecular biomarkers to treatment selection remains unclear. Here, we characterize the molecular landscape of tumors from the PRODIGE-24/CCTG PA6 trial and assess the clinical impact of genomic alterations and molecular subtypes. PATIENTS AND METHODS: Tumor DNA sequencing was successfully performed in 317/350 tumors (168 mFFX; 149 GEM), complemented by transcriptomic subtyping using the PurIST classifier. Mutational status of four key PDAC driver genes and 24 homologous recombination repair (HRR)-associated genes was analyzed, alongside single-base substitution (SBS) mutational signatures. Primary and secondary end points were disease-free survival (DFS) and cancer-specific survival (CSS), respectively. RESULTS: In the mFFX group, the PurIST subtype was prognostic, with classical tumors showing superior DFS compared with basal-like tumors (stratified hazard ratio [sHR], 0.48 [95% CI, 0.31 to 0.77]). Among KRAS-mutated patients, mFFX significantly improved DFS compared with GEM (sHR, 0.60 [95% CI, 0.45 to 0.79]; P < .001), while no benefit was observed in KRAS wild-type tumors (interaction test, Pint. = 0.010). HRR and BRCA status were not predictive (Pint. = .568 and Pint. = .785, respectively). The benefit of mFFX was consistent across SBS-positive and SBS-negative subgroups. CONCLUSION: Overall, these results do not support a change in current adjuvant treatment strategies. mFFX remains the standard adjuvant regimen in PDAC, and the observed lack of benefit in KRAS wild-type tumors should be considered hypothesis-generating and warrants further investigation.

Humans↗

PubMed2026

Plasma Proteomic Profiling Identifies Candidate Biomarkers for Pancreatic Ductal Adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy that is often diagnosed after curative treatment is no longer feasible. Existing biomarkers, particularly CA19-9, have limited sensitivity and specificity. Plasma proteins that capture tumor-associated biological alterations may therefore provide useful signals for earlier detection. METHODS: Plasma samples from 99 patients with PDAC and 30 healthy controls were analyzed using data-independent acquisition (DIA) proteomics. Differentially expressed proteins were identified using predefined statistical thresholds and further examined by functional enrichment analysis. Selected candidate biomarkers were validated by ELISA in an independent subset. RESULTS: Among 565 quantified plasma proteins, 52 were differentially expressed between PDAC and controls. These proteins were enriched in extracellular processes, cholesterol metabolism, complement and coagulation cascades, and pancreatic secretion pathways. ELISA validation confirmed higher plasma levels of Cathepsin S, CTRB2, MARCO, PIGR, PRDX6, REG1A, Trypsin-2, and PEP-FAP in patients with PDAC compared with healthy controls. ROC analyses showed moderate-to-good discriminatory performance for several candidates, and the MARCO + PEP-FAP model improved classification compared with either marker alone. CONCLUSION: These findings reveal circulating proteins linked to key PDAC-related biological processes and identify eight candidates for further evaluation in multi-protein diagnostic panels. Larger validation studies incorporating clinically relevant disease control groups are warranted to determine their diagnostic specificity and clinical utility.

Humans↗