Decoding Prognostic Markers: Bioinformatics Insights into PIH1D1 and p53 in Children’s Brain Cancer

Abstract

AbstractGenetic alterations in normal brain cells lead to the development of brain tumors (BT). The incidence of newly diagnosed cases is on the rise over time. Understanding the molecular biology of pediatric brain tumors is crucial for advancing novel therapeutic approaches to prevent or effectively manage this disease. The R2TP complex, a conserved co-chaperone from yeast to mammals, including RUVBL1, RUVBL2, PIH1D1, and RPAP3 in humans, plays a crucial role in the assembly and maturation of various multi-subunit complexes. This study evaluates the expression of PIH1D1 and p53 in pediatric brain cancers using The Cancer Genome Atlas (TCGA) data through the UALCAN platform—a novel, user-friendly resource for cancer OMICS data analysis.Our analysis revealed elevated expression levels of PIH1D1 in pediatric brain tumors across all age groups compared to normal tissues, suggesting its potential as an early detection marker and a prognostic indicator. Additionally, P53 emerged as a promising target for brain tumor treatment, warranting exploration for age-specific applications. The Venn Diagram analysis further delineated key genes within the PIH1D1 and P53 networks, providing insights into the genetic landscape of childhood brain cancer.Despite these findings, the study has limitations, primarily relying on bioinformatics databases. Future research will incorporate clinical tissues and cell lines in in vivo and in vitro experiments to unravel the mechanistic roles of PIH1D1 and p53 in brain tumors. This comprehensive approach bridges bioinformatics and clinical exploration, contributing to a holistic understanding of pediatric brain cancer molecular biology and paving the way for targeted therapeutic interventions.