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Integrative multi-omics and drug-response characterization of patient-derived prostate cancer primary cells.


ABSTRACT: Prostate cancer (PCa) is the second most prevalent malignancy in males across the world. A greater knowledge of the relationship between protein abundance and drug responses would benefit precision treatment for PCa. Herein, we establish 35 Chinese PCa primary cell models to capture specific characteristics among PCa patients, including gene mutations, mRNA/protein/surface protein distributions, and pharmaceutical responses. The multi-omics analyses identify Anterior Gradient 2 (AGR2) as a pre-operative prognostic biomarker in PCa. Through the drug library screening, we describe crizotinib as a selective compound for malignant PCa primary cells. We further perform the pharmacoproteome analysis and identify 14,372 significant protein-drug correlations. Surprisingly, the diminished AGR2 enhances the inhibition activity of crizotinib via ALK/c-MET-AKT axis activation which is validated by PC3 and xenograft model. Our integrated multi-omics approach yields a comprehensive understanding of PCa biomarkers and pharmacological responses, allowing for more precise diagnosis and therapies.

SUBMITTER: Wang Z 

PROVIDER: S-EPMC10149505 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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Integrative multi-omics and drug-response characterization of patient-derived prostate cancer primary cells.

Wang Ziruoyu Z   Li Yanan Y   Zhao Wensi W   Jiang Shuai S   Huang Yuqi Y   Hou Jun J   Zhang Xuelu X   Zhai Zhaoyu Z   Yang Chen C   Wang Jiaqi J   Zhu Jiying J   Pan Jianbo J   Jiang Wei W   Li Zengxia Z   Ye Mingliang M   Tan Minjia M   Jiang Haowen H   Dang Yongjun Y  

Signal transduction and targeted therapy 20230501 1


Prostate cancer (PCa) is the second most prevalent malignancy in males across the world. A greater knowledge of the relationship between protein abundance and drug responses would benefit precision treatment for PCa. Herein, we establish 35 Chinese PCa primary cell models to capture specific characteristics among PCa patients, including gene mutations, mRNA/protein/surface protein distributions, and pharmaceutical responses. The multi-omics analyses identify Anterior Gradient 2 (AGR2) as a pre-o  ...[more]

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