Environment and bladder cancer: molecular analysis by interaction networks

// Andrea Polo 1 , Anna Crispo 1 , Pellegrino Cerino 2 , Luca Falzone 3 , Saverio Candido 3 , Aldo Giudice 1 , Giuseppina De Petro 4 , Gennaro Ciliberto 5 , Maurizio Montella 1 , Alfredo Budillon 6 and Susan Costantini 6 1 Epidemiology Unit, Istituto Nazionale Tumori “Fondazione G. Pascale”, IRCCS, Napoli, Italia 2 Istituto Zooprofilattico Sperimentale del Mezzogiorno (IZSM), Napoli, Italia 3 Department of Biomedical and Biotechnological Sciences, Section of General and Clinical Pathology and Oncology – Translational Oncology and Functional Genomics Laboratory, University of Catania, Catania, Italy 4 Dipartimento di Medicina Molecolare e Traslazionale, Universita di Brescia, Brescia, Italia 5 Scientific Directorate, Istituto Nazionale Tumori “Regina Elena”, IRCCS, Roma, Italia 6 Experimental Pharmacology Unit, Istituto Nazionale Tumori “Fondazione G. Pascale”, IRCCS, Napoli, Italia Correspondence to: Alfredo Budillon, email: a.budillon@istitutotumori.na.it Susan Costantini, email: s.costantini@istitutotumori.na.it Keywords: bladder cancer, network analysis, environmental exposure, arsenicals Received: March 16, 2017 Accepted: April 12, 2017 Published: May 26, 2017 ABSTRACT Bladder cancer (BC) is the 9th most common cancer worldwide, and the 6th most common cancer in men. Its development is linked to chronic inflammation, genetic susceptibility, smoking, occupational exposures and environmental pollutants. Aim of this work was to identify a sub-network of genes/proteins modulated by environmental or arsenic exposure in BC by computational network approaches. Our studies evidenced the presence of HUB nodes both in “BC and environment” and “BC and arsenicals” networks. These HUB nodes resulted to be correlated to circadian genes and targeted by some miRNAs already reported as involved in BC, thus suggesting how they play an important role in BC development due to environmental or arsenic exposure. Through data-mining analysis related to putative effect of the identified HUB nodes on survival we identified genes/proteins and their mutations on which it will be useful to focus further experimental studies related to the evaluation of their expression in biological matrices and to their utility as biomarkers of BC development.