| 論文作者 |
Sun, R; Jun, A; Yu, HL; Wang, Y; He, MX; Tan, LL; Cheng, HH; Zhang, JL; Wang, YR; Sun, XC; Lyu, M; Qu, M; Huang, LL; Li, ZJ; Zhang, WH; Ma, KP; Dong, ZY; Ge, WG; Zhang, Y; Ding, X; Ying, B; Hou, JG; Xu, CL; Wang, LH; Zhu, Y; Guo, TN; Gao, X; Yang, CH |
| 摘要 |
Prostate cancer (PCa) is the most common malignant tumor in men. Currently, there are few prognosis indicators for predicting PCa outcomes and guiding treatments. Here, we perform comprehensive proteomic profiling of 918 tissue specimens from 306 Chinese patients with PCa using data-independent acquisition mass spectrometry (DIA-MS). We identify over 10,000 proteins and define three molecular subtypes of PCa with significant clinical and proteomic differences. We develop a 16-protein panel that effectively predicts biochemical recurrence (BCR) for patients with PCa, which is validated in six published datasets and one additional 99-biopsy-sample cohort by targeted proteomics. Interestingly, this 16-protein panel effectively predicts BCR across different International Society of Urological Pathology (ISUP) grades and pathological stages and outperforms the D'Amico risk classification system in BCR prediction. Furthermore, double knockout of NUDT5 and SEPTIN8, two components from the 16-protein panel, significantly suppresses the PCa cells to proliferate, invade, and migrate, suggesting the combination of NUDT5 and SEPTIN8 may provide new approaches for PCa treatment. |
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