KRT13-expressing epithelial cell population predicts better response to chemotherapy and immunotherapy in bladder cancer: Comprehensive evidences based on BCa database. (May 2023)

• Record Type: Journal Article
• Authors: Yu, Donghu; Chen, Chen; Sun, Le; Wu, Shaojie; Tang, Xiaoyu; Mei, Liye; Lei, Cheng; Wang, Du; Wang, Xinghuan; Cheng, Liang; Li, Sheng
• Is Part Of: Computers in biology and medicine. Volume 158(2023)
• Publication Date: 2023-05
• Subjects: Bladder cancer -- Prediction ability -- Artificial neural network; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2023.106795
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: Neoadjuvant chemotherapy (NAC) prior to surgery and immune checkpoint therapy (ICT) has revolutionized bladder cancer (BCa) treatment. Patients likely to benefit from these therapies need to be accurately stratified; however, this remains a major clinical challenge. In the present study, single-cell RNA sequencing was used to evaluate the predictive ability of an epithelial cell population highly expressing keratin 13 (KRT13) to assess therapeutic response in BCa. The presence of KRT13-enriched tumors indicated favorable outcomes after NAC and superior response to ICT in patients with BCa. Furthermore, KRT13 population characteristics appeared to be closely related to changes in the immune microenvironment in the vicinity of this cell population. We constructed a prognostic model using an artificial neural network based on the gene signatures in the KRT13 population; the model demonstrated strong robustness and superiority. Additionally, a user-friendly and open-access web application named BCa database was developed for researchers to study BCa by mining the connective map database. Highlights: KRT13-expressing epithelial cell population was identified. Novel molecular mechanism affecting ICB therapy outcomes was demonstrated. Prognostic model using neural network was constructed. A user-friendly and open-access web application named BCa database was developed.