Adaptive phenotype drives resistance to androgen deprivation therapy in prostate cancer

Autor: Adriana Amaro, Roberta Venè, Matteo Capaia, Cecilia Balbi, Paola Barboro, Elvira Inglese, Andrea Petretto, Ilaria Granata, Marina Piccirillo, Nicoletta Ferrari, Francesco Boccardo, Mario Rosario Guarracino, Antonella Brizzolara, Martina Morini, Simonetta Astigiano
Rok vydání: 2017
Předmět:
Male
0301 basic medicine
Bicalutamide
lcsh:Medicine
Androgen deprivation therapy
Biology
urologic and male genital diseases
Target therapy
Biochemistry
03 medical and health sciences
Prostate cancer
0302 clinical medicine
Cell Line
Tumor
Bioinformatic analysis
LNCaP
medicine
Humans
Epigenetics
Phosphorylation
lcsh:QH573-671
Molecular Biology
Castration-resistant prostate cancer
lcsh:Cytology
Cell growth
Research
Stress response
lcsh:R
Drug resistance
Cancer
Cell Biology
medicine.disease
Adaptation
Physiological
3. Good health
Gene Expression Regulation
Neoplastic
Androgen receptor
Prostatic Neoplasms
Castration-Resistant
Treatment Outcome
030104 developmental biology
Drug Resistance
Neoplasm
Receptors
Androgen
030220 oncology & carcinogenesis
Androgens
Cancer research
Signal Transduction
medicine.drug
Zdroj: Cell Communication and Signaling, Vol 15, Iss 1, Pp 1-14 (2017)
Cell communication and signaling (2017).
info:cnr-pdr/source/autori:Nicoletta Ferrari, Ilaria Granata, Matteo Capaia, Marina Piccirillo, Mario Rosario Guarracino, Roberta Venè, Antonella Brizzolara, Andrea Petretto, Elvira Inglese, Martina Morini, Simonetta Astigiano, Adriana Agnese Amaro, Francesco Boccardo, Cecilia Balbi, Paola Barboro/titolo:Adaptive phenotype drives resistance to androgen deprivation therapy in prostate cancer/doi:/rivista:Cell communication and signaling/anno:2017/pagina_da:/pagina_a:/intervallo_pagine:/volume
Cell Communication and Signaling : CCS
ISSN: 1478-811X
Popis: Background Prostate cancer (PCa), the second most common cancer affecting men worldwide, shows a broad spectrum of biological and clinical behaviour representing the epiphenomenon of an extreme heterogeneity. Androgen deprivation therapy is the mainstay of treatment for advanced forms but after few years the majority of patients progress to castration-resistant prostate cancer (CRPC), a lethal form that poses considerable therapeutic challenges. Methods Western blotting, immunocytochemistry, invasion and reporter assays, and in vivo studies were performed to characterize androgen resistant sublines phenotype in comparison to the parental cell line LNCaP. RNA microarray, mass spectrometry, integrative transcriptomic and proteomic differential analysis coupled with GeneOntology and multivariate analyses were applied to identify deregulated genes and proteins involved in CRPC evolution. Results Treating the androgen-responsive LNCaP cell line for over a year with 10 μM bicalutamide both in the presence and absence of 0.1 nM 5-α-dihydrotestosterone (DHT) we obtained two cell sublines, designated PDB and MDB respectively, presenting several analogies with CRPC. Molecular and functional analyses of PDB and MDB, compared to the parental cell line, showed that both resistant cell lines were PSA low/negative with comparable levels of nuclear androgen receptor devoid of activity due to altered phosphorylation; cell growth and survival were dependent on AKT and p38MAPK activation and PARP-1 overexpression; their malignant phenotype increased both in vitro and in vivo. Performing bioinformatic analyses we highlighted biological processes related to environmental and stress adaptation supporting cell survival and growth. We identified 15 proteins that could direct androgen-resistance acquisition. Eleven out of these 15 proteins were closely related to biological processes involved in PCa progression. Conclusions Our models suggest that environmental factors and epigenetic modulation can activate processes of phenotypic adaptation driving drug-resistance. The identified key proteins of these adaptive phenotypes could be eligible targets for innovative therapies as well as molecules of prognostic and predictive value. Electronic supplementary material The online version of this article (10.1186/s12964-017-0206-x) contains supplementary material, which is available to authorized users.
Databáze: OpenAIRE
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