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.