Proteomic landscape profiling of primary prostate cancer reveals a 16-protein panel for prognosis prediction

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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Publication Details

Journal
Cell Reports Medicine
Published
2024-08-01
DOI
https://doi.org/10.1016/j.xcrm.2024.101679
Citations
12
Primary Topic
Prostate Cancer Treatment and Research
Type
article
Field-Weighted Citation Impact
5.03

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article

Proteomic landscape profiling of primary prostate cancer reveals a 16-protein panel for prognosis prediction

Tiannan Guo, Yingrui Wang, Weigang Ge, Jun Arita et al.
12 citations
Cell Reports Medicine
Prostate Cancer Treatment and Research
5.03
article

Proteomic landscape profiling of primary prostate cancer reveals a 16-protein panel for prognosis prediction

Tiannan Guo, Yingrui Wang, Weigang Ge, Jun Arita, Jili Zhang, Lingling Huang, Haolan Yu, Zhenyang Dong, Yan Wang, Yun Zhang, Zijian Li, Linhui Wang, Rui Sun, Min Qu, Chuanliang Xu, Xu Gao, Lingling Tan, Kunpeng Ma, Wenhui Zhang, Xiaochen Sun, Xuan Ding, Mengge Lyu, Jianguo Hou, Yi Zhu, Honghan Cheng, Miaoxia He, Chenghua Yang, Bo Yang
article en
12 citations

Abstract

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.

Cell Reports MedicineVol. 5(8)
Second Military Medical University (CN), Westlake University (CN), Shanghai Institute of Nutrition and Health (CN), Changhai Hospital (CN)
Westlake University, National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, Natural Science Foundation of Zhejiang Province
Good health and well-being
Openalex Percentile: Top 4%
Prostate Cancer Treatment and Research
5.03
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