Integrative Analysis of Gene Expression Profiles in Renal Cell Carcinoma

Abstract

Background and Objective: Renal cell carcinoma (RCC) is a heterogeneous group of kidney tumours with diverse molecular landscapes, necessitating a deeper understanding and novel biomarkers for effective diagnosis and treatment. The study aimed to elucidate specific gene expression signatures common to the sub-types and identifying hub genes that could be potential therapeutic targets in renal cell carcinoma through integrative analysis of gene expression profiles.

Materials and Methods: Renal cell carcinoma characterized by aberrant cell cycle regulation and immune evasion driven by genetic mutations, was investigated using three mRNA microarray datasets (GSE6344, GSE40435, GSE15641) from the Gene Expression Omnibus. Comprehensive bioinformatics tools including GEO2R, DAVID, STRING and Cytoscape identified differentially expressed genes and performed gene ontology and KEGG pathway enrichment analyses.

Results: Differential expression analysis uncovered 36 common DEGs, notably HADH, SCARB1 and SFRP1, involved in critical cellular functions such as renal water homeostasis, metabolic regulation and glycolysis/gluconeogenesis. These genes were enriched in cellular compartments like extracellular exosome, plasma membrane and mitochondrion, emphasizing their roles in RCC pathophysiology. Protein-protein Interaction (PPI) network analysis identified 12 hub genes (ALB, ALDOB, AQP2, G6PC, GK, HAO2, HPD, NPHS2, SCARB1, SLC12A3, SLC34A1 and UMOD) essential in metabolic reprogramming, signal transduction and ion transport, processes critical to RCC progression.

Conclusion: The study highlights the metabolic adaptations, immune evasion strategies and dysregulated signalling pathways contributing to RCC development, offering valuable insights into the molecular mechanisms underlying tumorigenesis