Combined bulk and single-cell transcriptomic analysis reveals cell-type-specific inflammatory crosstalk in pancreatic cancer.

Objectives: This study aims to elucidate the complex molecular and cellular landscape of pancreatic ductal adenocarcinoma (PDAC) by identifying key regulatory non-coding RNAs (ncRNAs), hub protein-coding genes, and Intercellular communication pathways that may serve as prognostic biomarkers and therapeutic targets.

Background: Pancreatic cancer remains one of the deadliest malignancies worldwide, characterized by late diagnosis, limited treatment response, and poor prognosis. Among its histological subtypes, PDAC accounts for over 80% of cases and is defined by a highly fibrotic and immunosuppressive tumor microenvironment (TME).

Methods: We performed a comprehensive bioinformatics analysis integrating multiple transcriptomic datasets from the NCBI Gene Expression Omnibus (GEO), including mRNA, miRNA, lncRNA, and circRNA profiles from PDAC and adjacent normal tissues. Differential expression analysis was conducted using GEO2R, followed by functional enrichment via DAVID. Hub genes were identified from protein-protein interaction (PPI) networks constructed using STRING and validated using GEPIA2. A competing endogenous RNA (ceRNA) network was developed to investigate regulatory ncRNA-mRNA axes. To refine these findings, single-cell RNA-seq (scRNA-seq) data were analyzed to resolve the cellular origin of hub genes and ncRNAs, and CellChat was employed to model intercellular communication within the TME.

Results: We identified several dysregulated genes and ncRNAs implicated in key oncogenic pathways, including ECM remodeling, inflammation, and immune evasion. The ceRNA network highlighted functional interactions between circRNAs, lncRNAs, and miRNAs regulating key hub genes. Single-cell analysis revealed cell-type-specific expression of hub genes-e.g., FN1 and COL11A1 in fibroblasts, CXCL8 in macrophages, and ITGA3 in ductal cells-and uncovered a macrophage-endothelial CXCL8-ACKR1 signaling axis potentially driving tumor-associated angiogenesis. Moreover, correlations with immune cell infiltration and drug sensitivity further underscored the translational relevance of the identified molecular targets.

Conclusion: Our analysis combining bulk and single-cell transcriptomics provides a multi-scale view of PDAC pathogenesis. The findings highlight the interplay between ncRNAs, hub genes, and cellular crosstalk in shaping the tumor ecosystem and suggest novel targets for precision therapeutic intervention and biomarker development.