DNA Methylation of PI3K/AKT Pathway-Related Genes Predicts Outcome in Patients with Pancreatic Cancer: A Comprehensive Bioinformatics-Based Study

Abstract

Simple Summary Pancreatic cancer is a highly lethal malignancy. Dysregulation of epigenetic mechanisms leads to abnormal patterns of gene expression contributing to the development and progression of cancer. We explored the ability of DNA methylation of PI3K-related genes to differentiate between malignant and healthy pancreatic tissue using distinct pancreatic cancer cohorts, and found that the methylation levels of the ITGA4, SFN, ITGA2, and PIK3R1 genes are altered in tumour samples since the early stages of malignant transformation and could serve as new diagnostic tools. We also demonstrate that these alterations correlate with overall survival and recurrence-free survival of the patients suggesting that its assessment can serve as independent prognostic indicators of patients' survival with higher sensitivity and specificity than the currently implemented biomarkers. Therefore, the methylation profile of genes involved in this pathway may be an alternative method for predicting cell malignancy and help doctors' decisions on patient care. Pancreatic cancer (PCA) is one of the most lethal malignancies worldwide with a 5-year survival rate of 9\%. Despite the advances in the field, the need for an earlier detection and effective therapies is paramount. PCA high heterogeneity suggests that epigenetic alterations play a key role in tumour development. However, only few epigenetic biomarkers or therapeutic targets have been identified so far. Here we explored the potential of distinct DNA methylation signatures as biomarkers for early detection and prognosis of PCA. PI3K/AKT-related genes differentially expressed in PCA were identified using the Pancreatic Expression Database (n = 153). Methylation data from PCA patients was obtained from The Cancer Genome Atlas (n = 183), crossed with clinical data to evaluate the biomarker potential of the epigenetic signatures identified and validated in independent cohorts. The majority of selected genes presented higher expression and hypomethylation in tumour tissue. The methylation signatures of specific genes in the PI3K/AKT pathway could distinguish normal from malignant tissue at initial disease stages with AUC > 0.8, revealing their potential as PCA diagnostic tools. ITGA4, SFN, ITGA2, and PIK3R1 methylation levels could be independent prognostic indicators of patients' survival. Methylation status of SFN and PIK3R1 were also associated with disease recurrence. Our study reveals that the methylation levels of PIK3/AKT genes involved in PCA could be used to diagnose and predict patients' clinical outcome with high sensitivity and specificity. These results provide new evidence of the potential of epigenetic alterations as biomarkers for disease screening and management and highlight possible therapeutic targets.