Gene signature for response prediction to immunotherapy and prognostic markers in metastatic urothelial carcinoma.

ABSTRACT: To date, immune checkpoint inhibitors (ICIs) have emerged as a leading treatment for metastatic cancer, significantly improving patient survival while causing relatively few side effects. However, the objective response rate for ICIs remains low approximately 30% in urothelial carcinoma (UC), underscoring the urgent need for predictive response biomarkers. Several state-of-the-art signatures have been revealed in top-tier journals, highlighting the importance of this field. As the number of genes (~20,000) far exceeds the sample sizes of typical training sets (generally ≤ 300), we first developed feature selection procedures to reduce the number of features to a few hundred. We then trained multiple machine learning classifiers using the selected genes and the IMvigor210 dataset, which inc

SUBMITTER: Langfelder P 

PROVIDER: S-EPMC12675356 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature