In this study, we extracted prostate cell-specific gene sets (metagenes) to define the epithelial differentiation status of prostate cancers and, using a deconvolution-based strategy, interrogated thousands of primary and metastatic tumors in public gene profiling datasets. We identified a subgroup of primary prostate tumors with low luminal epithelial enrichment (LumElow). LumElow tumors were associated with higher Gleason score and mutational burden, reduced relapse-free and overall survival, and were more likely to progress to castration-resistant prostate cancer (CRPC). Using discriminant function analysis, we generate a predictive 10-gene classifier for clinical implementation. This mini-classifier predicted with high accuracy the luminal status in both primary tumors and CRPCs. Immunohistochemistry for COL4A1, a low-luminal marker, sustained the association of attenuated luminal phenotype with metastatic disease. We found also an association of LumE score with tumor phenotype in genetically engineered mouse models (GEMMs) of prostate cancer. Notably, the metagene approach led to the discovery of drugs that could revert the low luminal status in prostate cell lines and mouse models. This study describes a novel tool to dissect the intrinsic heterogeneity of prostate tumors and provide predictive information on clinical outcome and treatment response in experimental and clinical samples.

Mapelli, S.n., Albino, D., Mello-Grand, M., Shinde, D., Scimeca, M., Bonfiglio, R., et al. (2020). A novel prostate cell type-specific gene signature to interrogate prostate tumor differentiation status and monitor therapeutic response (Running title: Phenotypic classification of prostate tumors). CANCERS, 12(1) [10.3390/cancers12010176].

A novel prostate cell type-specific gene signature to interrogate prostate tumor differentiation status and monitor therapeutic response (Running title: Phenotypic classification of prostate tumors)

Scimeca M.;Bonfiglio R.;Bonanno E.;
2020-01-01

Abstract

In this study, we extracted prostate cell-specific gene sets (metagenes) to define the epithelial differentiation status of prostate cancers and, using a deconvolution-based strategy, interrogated thousands of primary and metastatic tumors in public gene profiling datasets. We identified a subgroup of primary prostate tumors with low luminal epithelial enrichment (LumElow). LumElow tumors were associated with higher Gleason score and mutational burden, reduced relapse-free and overall survival, and were more likely to progress to castration-resistant prostate cancer (CRPC). Using discriminant function analysis, we generate a predictive 10-gene classifier for clinical implementation. This mini-classifier predicted with high accuracy the luminal status in both primary tumors and CRPCs. Immunohistochemistry for COL4A1, a low-luminal marker, sustained the association of attenuated luminal phenotype with metastatic disease. We found also an association of LumE score with tumor phenotype in genetically engineered mouse models (GEMMs) of prostate cancer. Notably, the metagene approach led to the discovery of drugs that could revert the low luminal status in prostate cell lines and mouse models. This study describes a novel tool to dissect the intrinsic heterogeneity of prostate tumors and provide predictive information on clinical outcome and treatment response in experimental and clinical samples.
2020
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore MED/08 - ANATOMIA PATOLOGICA
English
gene classifier; gene signature; predictive biomarkers; prostate cancer; tumor classification
Mapelli, S.n., Albino, D., Mello-Grand, M., Shinde, D., Scimeca, M., Bonfiglio, R., et al. (2020). A novel prostate cell type-specific gene signature to interrogate prostate tumor differentiation status and monitor therapeutic response (Running title: Phenotypic classification of prostate tumors). CANCERS, 12(1) [10.3390/cancers12010176].
Mapelli, Sn; Albino, D; Mello-Grand, M; Shinde, D; Scimeca, M; Bonfiglio, R; Bonanno, E; Chiorino, G; Garcia-Escudero, R; Catapano, Cv; Carbone, Gm
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/231126
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