Author:
Li Huihuang,Hu Jiao,Zu Xiongbing,Chen Minfeng,Chen Jinbo,Zou Yihua,Deng Ruoping,Qin Gang,Li Wenze,Tang Jiansheng,Deng Dingshan,Liu Jinhui,Cheng Chunliang,Cui Yu,Ou Zhenyu
Abstract
Background: Although neoadjuvant chemotherapy (NAC) has become the standard treatment option for muscle invasive bladder carcinoma (MIBC), its application is still limited because of the lack of biomarkers for NAC prediction.Methods: We conducted a territory multicenter real-world study to summarize NAC practice in China and its associated clinicopathologic variables with NAC response. Then, we developed and validated a robust gene-based signature for accurate NAC prediction using weighted correlation network analysis (WGCNA), the least absolute shrinkage and selector operation (LASSO) algorithm, a multivariable binary logistic regression model, and immunohistochemistry (IHC).Results: In total, we collected 69 consecutive MIBC patients treated with NAC from four clinical centers. The application of NAC in the real world was relatively safe, with only two grade Ⅳ and seven grade Ⅲ AEs and no treatment-related deaths being reported. Among these patients, 16 patients gave up surgery after NAC, leaving 53 patients for further analysis. We divided them into pathological response and non-response groups and found that there were more patients with a higher grade and stage in the non-response group. Patients with a pathological response could benefit from a significant overall survival (OS) improvement. In addition, univariate and multivariate logistic analyses indicated that tumor grade and clinical T stage were both independent factors for predicting NAC response. Importantly, we developed and validated a five-gene-based risk score for extremely high predictive accuracy for NAC response.Conclusion: NAC was relatively safe and could significantly improve OS for MIBC patients in the real-world practice. Our five-gene-based risk score could guide personalized therapy and promote the application of NAC.
Subject
Genetics (clinical),Genetics,Molecular Medicine