Machine Learning-Based Gene Expression Analysis to Identify Prognostic Biomarkers in Upper Tract Urothelial Carcinoma
Machine Learning-Based Gene Expression Analysis to Identify Prognostic Biomarkers in Upper Tract Urothelial Carcinoma
B. Padullés,Ruben López-Aladid,6 Authors,Antonio Alcaraz
TLDR
By analyzing gene expression patterns in tissue samples from 17 UTUC patients who underwent surgery, machine learning tools for gene expression analysis are applied to identify biomarkers that can help predict disease progression.
Abstract
Simple Summary Upper tract urothelial carcinoma (UTUC) is a rare but aggressive cancer with limited tools to predict patient outcomes after surgery. This study applies machine learning tools for gene expression analysis to identify biomarkers that can help predict disease progression. By analyzing gene expression patterns in tissue samples from 17 UTUC patients who underwent surgery, we identified ten key prognostic genes. These findings highlight potential biomarkers for future research to improve patient care and outcomes.