Next Article in Journal
Contribution of mTOR and PTEN to Radioresistance in Sporadic and NF2-Associated Vestibular Schwannomas: A Microarray and Pathway Analysis
Previous Article in Journal
Triple-Negative Primary Breast Tumors Induce Supportive Premetastatic Changes in the Extracellular Matrix and Soluble Components of the Lung Microenvironment
Open AccessArticle

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)

1
Institute of Oncology Research (IOR), Università della Svizzera italiana (USI), 6500 Bellinzona, Switzerland
2
Swiss Institute of Bioinformatics (SIB), 1015 Lausanne, Switzerland
3
Laboratory of Cancer Genomics, Fondazione Edo ed Elvo Tempia Valenta, 13900 Biella, Italy
4
Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, 00133 Rome, Italy
5
Molecular Oncology Unit, CIEMAT, 28040 Madrid, Spain
6
Biomedicine Research Institute, Hospital 12 octubre, 28040 Madrid, Spain
7
Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28040 Madrid, Spain
8
Department of Oncology, Faculty of Biology and Medicine, University of Lausanne, 1011 Lausanne, Switzerland
*
Authors to whom correspondence should be addressed.
Cancers 2020, 12(1), 176; https://doi.org/10.3390/cancers12010176
Received: 10 December 2019 / Revised: 28 December 2019 / Accepted: 6 January 2020 / Published: 10 January 2020
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. View Full-Text
Keywords: prostate cancer; tumor classification; predictive biomarkers; gene signature; gene classifier prostate cancer; tumor classification; predictive biomarkers; gene signature; gene classifier
Show Figures

Figure 1

MDPI and ACS Style

Mapelli, S.N.; Albino, D.; Mello-Grand, M.; Shinde, D.; Scimeca, M.; Bonfiglio, R.; Bonanno, E.; Chiorino, G.; Garcia-Escudero, R.; Catapano, C.V.; Carbone, G.M. 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 2020, 12, 176.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop