A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.

Autor: Huang KB; Department of Urology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Department of Urology, Sun Yat-sen University Cancer center, Guangzhou, China.; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer center, Guangzhou, China., Gui CP; Department of Urology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China., Xu YZ; Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China., Li XS; Department of Urology, Peking University First Hospital, Institute of Urology, Peking University, National Urological Cancer Center, Beijing, China., Zhao HW; Department of Urology, Affiliated Yantai Yuhuangding Hospital, Qingdao University, Yantai, China., Cao JZ; Department of Urology, Jiangmen Hospital, Sun Yat-sen University, Jiangmen, China., Chen YH; Department of Urology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China., Pan YH; Department of Urology, The Third Affiliated Hospital of Soochow University, Changzhou, China., Liao B; Department of Pathology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China., Cao Y; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer center, Guangzhou, China.; Department of Pathology, Sun Yat-sen University Cancer center, Guangzhou, China., Zhang XK; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer center, Guangzhou, China.; Department of Pathology, Sun Yat-sen University Cancer center, Guangzhou, China., Han H; Department of Urology, Sun Yat-sen University Cancer center, Guangzhou, China.; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer center, Guangzhou, China., Zhou FJ; Department of Urology, Sun Yat-sen University Cancer center, Guangzhou, China.; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer center, Guangzhou, China., Liu RY; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer center, Guangzhou, China., Chen WF; Department of Pathology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China., Jiang ZY; Department of Pathology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China., Feng ZH; Department of Urology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China., Jiang FN; Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China., Yu YF; Department of Urology, Peking University First Hospital, Institute of Urology, Peking University, National Urological Cancer Center, Beijing, China., Xiong SW; Department of Urology, Peking University First Hospital, Institute of Urology, Peking University, National Urological Cancer Center, Beijing, China., Han GP; Department of Urology, Peking University First Hospital, Institute of Urology, Peking University, National Urological Cancer Center, Beijing, China., Tang Q; Department of Urology, Peking University First Hospital, Institute of Urology, Peking University, National Urological Cancer Center, Beijing, China., Ouyang K; Department of Urology, Affiliated Yantai Yuhuangding Hospital, Qingdao University, Yantai, China., Qu GM; Department of Pathology, Affiliated Yantai Yuhuangding Hospital, Qingdao University, Yantai, China., Wu JT; Department of Urology, Affiliated Yantai Yuhuangding Hospital, Qingdao University, Yantai, China., Cao M; Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China., Dong BJ; Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China., Huang YR; Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China., Zhang J; Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China., Li CX; School of Mathematics and Computational Science, Sun Yat-sen University, Guangzhou, China., Li PX; School of Mathematics and Computational Science, Sun Yat-sen University, Guangzhou, China., Chen W; Department of Urology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China., Zhong WD; Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China., Guo JP; Institute of Precision Medicine, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China., Liu ZP; Department of Internal Medicine and Department of Molecular Biology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX, USA., Hsieh JT; Department of Urology, University of Texas Southwestern Medical Center at Dallas, Dallas, TX, USA., Xie D; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer center, Guangzhou, China.; Department of Pathology, Sun Yat-sen University Cancer center, Guangzhou, China., Cai MY; State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer center, Guangzhou, China.; Department of Pathology, Sun Yat-sen University Cancer center, Guangzhou, China., Xue W; Department of Urology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. uroxuewei@163.com., Wei JH; Department of Urology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China. weijh23@mail.sysu.edu.cn., Luo JH; Department of Urology, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China. luojunh@mail.sysu.edu.cn.; Institute of Precision Medicine, First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China. luojunh@mail.sysu.edu.cn.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2024 Jul 23; Vol. 15 (1), pp. 6215. Date of Electronic Publication: 2024 Jul 23.
DOI: 10.1038/s41467-024-50369-y
Abstrakt: Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy.
(© 2024. The Author(s).)
Databáze: MEDLINE
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