Genes Co-Expressed with Influence Clinical Outcomes in Cancer Patients: TCGA Data Analysis.

ERβ has been assigned a tumor suppressor role in many cancer types. However, as conflicting findings emerge, ERβ's tissue-specific expression and functional role have remained elusive. There remains a notable gap in compact and comprehensive analyses of mRNA expression levels across diverse tumor types coupled with an exploration of its potential gene network. In this study, we aim to address these gaps by presenting a comprehensive analysis of transcriptomic data. We distinguished cancer types with significant changes in expression levels compared to corresponding healthy tissue and concluded that influences patient survival. Gene Set Enrichment Analysis (GSEA) distinguished molecular pathways affected by , including oxidative phosphorylation and epithelial-mesenchymal transition. Finally, we investigated genes displaying similar expression patterns as in tumor tissues, identifying potential co-expressed genes that may exert a synergistic effect on clinical outcomes, with significant results, including the expression of , , , and . Collectively, our results highlight the significant influence of mRNA expression on the transcriptomic landscape and the overall metabolism of cancerous cells across various tumor types.