Pathogenic mutation profiling in matched PBMC and PDAC samples reveals gene specific and sample type dependent differences in pancreatic cancer patients

Abstract

Introduction: Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest solid tumors, largely due to late diagnosis and limited molecular stratification strategies. In our previous work, we analyzed transcriptomic profiles of PDAC tissue and PBMCs to characterize immune and oncogenic pathway activity (AHR, PD1/PDL1). To complement this, we performed targeted pathogenic mutation analysis, aiming to distinguish germline and somatic events in matched samples from PDAC patients. Aims & Methods: Targeted sequencing data from six PDAC patients were analyzed using RStudio. Each patient provided matched PDAC tissue and PBMC samples. Mutations were filtered to include only pathogenic or likely pathogenic variants, which were then plotted across genes and individuals. Sample-type–specific differences and recurrence patterns were visualized using a bubble plot format. Results: Mutations were detected in several high-impact genes, including ATM, BRCA1/2, TP53, MSH2, MSH6, PALB2, and APC. PBMCs showed elevated mutation frequency in ATM and BRCA1, suggesting possible germline background or systemic genomic instability. Tumor-specific mutations, such as in TP53 and MUC16, were mostly restricted to PDAC tissue. Some genes (e.g., PALB2, MSH6) appeared across both compartments but varied per patient. This individual variability may reflect clonal hematopoiesis or subclonal tumor heterogeneity. Conclusion: Pathogenic mutation profiles differ significantly between PBMC and PDAC compartments, with certain genes showing tissue specificity. These findings build on our transcriptomic analysis and highlight the value of integrating DNA- and RNA-level data to understand patient-specific molecular features. Combined profiling may support bio-marker development, improve patient stratification, and guide personalized treatment decisions.