Integrated Analysis of Multi-Omics Data to Identify Prognostic Genes for Pancreatic Cancer

Pancreatic cancer (PC) is a common cause of cancer-related deaths. Current research shows that prognostic biomarkers play a key role in the treatment of PC. This study aimed to identify prognostic genes through bioinformatics research. We combined data from 175 cases of PC from the cancer genome atlas (TCGA) database with gene mutation expression, level distribution of methylation, mRNA expression, and through weighted correlation network analysis to nine hub genes. Subsequently, these genes were verified on TCGA and Gene Expression Profiling Interactive Analysis (GEPIA) platforms. Reverse transcription quantitative PCR (RT-qPCR) was performed to investigate the expression levels of 9 genes in PC cells and cancerous and 30 PC cases and corresponding adjacent tissues. CIBERSORT database analysis was conducted for hub genes. Our findings demonstrated that the 9 genes (MST1R, TMPRSS4, PTK6, KLF5, CGN, ABHD17C, MUC1, CAPN8, and B3GNT3) were prognostic biomarkers of PC identified from the top 10 genes of the 2 coexpression modules. The nine genes were then used to divide early PC cases into two subgroups with significant differences in prognosis and differences in function (digestion, extracellular cell adhesion). Further analysis revealed that the nine genes were highly expressed in PC tissues. In addition, MST1R, PTK6, ABHD17C, and CGN mRNA were expressed high in PC cells and clinical tissues. CIBERSORT analysis indicated that the expression of these genes was closely correlated with naive B cells, CD8⁺ T cells, and M0 macrophages. This suggests that these genes could play a carcinogenic role in the preservation of immune-dominant status for the tumor microenvironment. The nine key genes identified in this study could enhance our understanding of the molecular mechanisms associated with PC.