Deepening the Understanding of Platelet-Derived RNA as Biomarker for Glioblastoma Through GSEA, TDEA, and Elastic Net Regularization Analysis

Abstract

Background

Glioblastoma (GBM) is the most aggressive form of primary brain cancer. Blood platelets have emerged as biomarkers where their RNA expression pattern indicates a tumor's presence. Our study aimed to characterize these patterns to identify biological processes associated with GBM and to evaluate their potential as a non-invasive biomarker.

Methods

We analyzed platelet RNA-seq expression profiles from 84 GBM patients and 319 healthy individuals using two complementary analytical approaches of Gene Set Enrichment Analysis and Threshold-based Differential Expression Analysis with Elastic Net regularization. Together, these approaches may offer complementary perspectives on biological pathways associated with GBM and the descriptive functional annotation of a predictive platelet RNA gene signature, providing insight into platelet-tumor interactions.

Results

Our GSEA broad analysis highlighted platelet-related biological processes, including coagulation, wound healing, immune regulation, and cytoskeletal organization. The Elastic Net framework additionally suggested pathways related to immune activation, cell signaling, and protein folding. Overall, these findings may suggest that platelet-derived RNA not only has potential as a non-invasive biomarker but may also provide insight into the systemic biological processes associated with the GBM tumor microenvironment.

Conclusions

Our data suggests that platelet-derived RNA may reflect biological processes associated with the GBM tumor microenvironment, where wound repair and immune-related processes may play important roles. Our findings provide a resource for further research into the mechanisms that may underlie the pathophysiology and progression of glioblastoma.