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Identification of a 9-gene signature to enhance biochemical recurrence prediction in primary prostate cancer: A benchmarking study using ten machine learning methods and twelve patient cohorts

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机构： [1]Department of Andrology, Guangzhou First People’s Hospital, South China University of Technology, 510180, Guangzhou, Guangdong, China [2]Department of Urology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510630, China [3]Genetics, Genomics, and Bioinformatics Program, University of California, Riverside, CA, 92521, USA [4]Department of Botany and Plant Sciences, University of California, Riverside, CA, 92521, USA [5]Department of Urology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, China [6]Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, Guangzhou First People’s Hospital, South China University of Technology, 510180, Guangzhou, Guangdong, China [7]State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Taipa, 999078, Macau, China

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关键词： Prostate cancer Biochemical recurrence Radical prostatectomy Machine learning

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Prostate cancer (PCa) is a prevalent malignancy among men worldwide, and biochemical recurrence (BCR) after radical prostatectomy (RP) is a critical turning point commonly used to guide the development of treatment strategies for primary PCa. However, the clinical parameters currently in use are inadequate for precise risk stratification and informing treatment choice. To address this issue, we conducted a study that collected transcriptomic data and clinical information from 1662 primary PCa patients across 12 multicenter cohorts globally. We leveraged 101 algorithm combinations that consisted of 10 machine learning methods to develop and validate a 9-gene signature, named BCR SCR, for predicting the risk of BCR after RP. Our results demonstrated that BCR SCR generally outperformed 102 published prognostic signatures. We further established the clinical significance of these nine genes in PCa progression at the protein level through immunohistochemistry on Tissue Microarray (TMA). Moreover, our data showed that patients with higher BCR SCR tended to have higher rates of BCR and distant metastasis after radical radiotherapy. Through drug target prediction analysis, we identified nine potential therapeutic agents for patients with high BCR SCR. In conclusion, the newly developed BCR SCR has significant translational potential in accurately stratifying the risk of patients who undergo RP, monitoring treatment courses, and developing new therapies for the disease.Copyright © 2024 Elsevier B.V. All rights reserved.

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出版当年[2023]版：

大类 | 1 区

医学

小类 | 2 区肿瘤学

最新[2025]版：

大类 | 1 区

医学

小类 | 2 区肿瘤学

第一作者：

第一作者机构： [1]Department of Andrology, Guangzhou First People’s Hospital, South China University of Technology, 510180, Guangzhou, Guangdong, China [2]Department of Urology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, 510630, China

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通讯作者：

通讯机构： [1]Department of Andrology, Guangzhou First People’s Hospital, South China University of Technology, 510180, Guangzhou, Guangdong, China [6]Department of Urology, Guangdong Key Laboratory of Clinical Molecular Medicine and Diagnostics, Guangzhou First People’s Hospital, South China University of Technology, 510180, Guangzhou, Guangdong, China [7]State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Taipa, 999078, Macau, China

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