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April 24, 2026European journal of medical research0 citationsOpen Access

Prognostic model construction and mechanistic analysis of pancreatic adenocarcinoma based on RCD-related genes and immune microenvironment features

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YZY C ZhangHDHao-Xuan DuBPBo Peng

Key Points

  • To develop a prognostic model based on regulated cell death (RCD) genes and analyze integrin β4's role in the immune microenvironment of pancreatic adenocarcinoma.
  • Analyzed RNA sequencing data from TCGA and GEO for RCD-related genes.
  • Constructed a prognostic model using LASSO regression that integrates several key genes.
  • Quantified immune cell infiltration and predicted immunotherapy response using established frameworks.
  • Thirteen RCD-related genes were significantly upregulated, establishing an RCD score for prognosis.
  • Patients with the C2 subtype showed better overall survival and increased infiltration of CD8+ T cells and polarized macrophages.
  • Low-risk patients displayed higher responses to PD-L1 inhibitors, indicating the model's predictive accuracy.

Abstract

Abstract Background Regulated cell death (RCD) has been extensively implicated in the pathogenesis, progression, and immunosuppressive tumor microenvironment (TME) of pancreatic adenocarcinoma (PAAD). However, systematic investigations into the prognostic relevance of RCD-related genes in PAAD remain limited. This study aimed to construct an RCD-based prognostic model and delineate the mechanistic role of integrin β4 ( ITGB4 ) in immunosuppressive TME remodeling. Methods RNA sequencing (RNA-seq) data from PAAD specimens were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We identified differentially expressed RCD-related genes (DE-RCDs) and classified molecular subtypes via consensus clustering. Survival disparities and immune microenvironment profiles were comparatively analyzed. A prognostic model (RCD score) was developed via Least Absolute Shrinkage and Selection Operator (LASSO) penalized Cox regression, integrating ITGB4, MUC1, and ATG16L2 , and validated in independent GEO cohorts. Tumor-infiltrating immune cells were quantified using the CIBERSORT algorithm, while immunotherapy responsiveness was predicted via the Tumor Immune Dysfunction and Exclusion (TIDE) framework. ITGB4 expression and tumor-associated macrophages (TAMs) polarization states were assessed via multiplex immunofluorescence co-staining. Results Thirteen genes were significantly upregulated (adj. P 1.5). The C2 subtype exhibited superior overall survival (hazard ratio HR = 0.62, 95% confidence interval CI: 0.41–0.93; P = 0.0062), accompanied by heightened infiltration of CD8 + cytotoxic T cells and M1-polarized TAMs ( P < 0.001). The RCD score independently predicted PAAD prognosis and improved 3-year survival prediction accuracy when combined with TNM staging (misclassification rate < 5%). Low-risk patients demonstrated enhanced responsiveness to programmed death-ligand 1 (PD-L1) inhibitors (odds ratio OR = 2.17, 95% CI 1.32–3.56; P = 0.014). Immunofluorescence confirmed ITGB4 overexpression in PAAD tissues, demonstrating a robust correlation with M2-polarized TAMs (r = 0.9168, P < 0.0001). Conclusion The RCD score-based signature demonstrates robust predictive utility for PAAD outcomes. Clinically, the RCD score could serve as a complementary biomarker to CA19-9 and TNM staging, potentially enhancing early risk stratification and informing personalized immunotherapy decisions for PAAD patients. RCD-related genes orchestrate immunosuppressive TME remodeling, with ITGB4 functioning as a central regulator of tumor progression via M2-polarized TAM modulation.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69eb09ff553a5433e34b4323https://doi.org/10.1186/s40001-026-04480-z
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