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Molecular oncology · 2025

Adverse prognosis gene expression patterns in metastatic castration-resistant prostate cancer.

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Sharifi Marina N, Feng Eric, Rydzewski Nicholas R, Taylor Amy K, Sperger Jamie M, Shi Yue, Helzer Kyle T, Bootsma Matthew L, Carreno Viridiana, Chang Alex H, Nunamaker Luke A, Blitzer Grace C, Shang Tianfu Andy, Subramanian Aishwarya, Bjartell Anders, Josefsson Andreas, Wikström Pernilla, Feng Emily, Kohli Manish, Yang Rendong, Dehm Scott M, Small Eric J, Aggarwal Rahul, Quigley David A, Lang Joshua M, Zhao Shuang G, Sjöström Martin

Аннотация

Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease. Several studies have identified transcriptional subtypes of mCRPC, but comprehensive analysis of prognostic gene expression pathways has been limited. Therefore, we aggregated a cohort of 1012 mCRPC tissue samples from 769 patients and investigated the association of gene expression-based pathways with clinical outcomes and intrapatient and intratumor heterogeneity. Survival data were obtained for 272 patients. Pathway-level enrichment was evaluated using gene set variation analysis. scRNA-seq datasets from mCRPC tissue biopsies and circulating tumor cells were used to investigate heterogeneity of adverse pathways. We identified five pathway clusters: (a) Immune response/WNT/TGF-beta signaling, (b) AR signaling/luminal signatures, (c) mTOR signaling and glycolysis, (d) cell proliferation, and (e) neuroendocrine differentiation. Proliferation, AR signaling loss, and glycolysis/mTOR signaling were independently prognostic. Adverse prognostic pathway scores decreased on treatment with AR signaling inhibitors, but not at progression, suggesting failure to permanently target these pathways. scRNA-seq datasets from mCRPC tissue biopsies and circulating tumor cells were used to investigate heterogeneity of adverse pathways. Our results suggest loss of AR signaling, high proliferation, and a glycolytic phenotype as adverse prognostic pathways in mCRPC that could be used in conjunction with clinical factors to prognosticate for treatment decisions.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты