Reciprocal Changes in miRNA Expression with Pigmentation and Decreased Proliferation Induced in Mouse B16F1 Melanoma Cells by L-Tyrosine and 5-Bromo-2'-Deoxyuridine.

Background: Many microRNAs have been identified as critical mediators in the progression of melanoma through its regulation of genes involved in different cellular processes such as melanogenesis, cell cycle control, and senescence. However, microRNAs' concurrent participation in syngeneic mouse B16F1 melanoma cells simultaneously induced decreased proliferation and differential pigmentation by exposure to 5-Brd-2'-dU (5'Bromo-2-deoxyuridine) and L-Tyr (L-Tyrosine) respectively, is poorly understood. Aim: To evaluate changes in the expression of microRNAs and identify which miRNAs in-network may contribute to the functional bases of phenotypes of differential pigmentation and reduction of proliferation in B16F1 melanoma cells exposed to 5-Brd-2'-dU and L-Tyr. Methods: Small RNAseq evaluation of the expression profiles of miRNAs in B16F1 melanoma cells exposed to 5-Brd-2'-dU (2.5 µg/mL) and L-Tyr (5 mM), as well as the expression by qRT-PCR of some molecular targets related to melanogenesis, cell cycle, and senescence. By bioinformatic analysis, we constructed network models of regulation and co-expression of microRNAs. Results: We confirmed that stimulation or repression of melanogenesis with L-Tyr or 5-Brd-2'-dU, respectively, generated changes in melanin concentration, reduction in proliferation, and changes in expression of microRNAs 470-3p, 470-5p, 30d-5p, 129-5p, 148b-3p, 27b-3p, and 211-5p, which presented patterns of coordinated and reciprocal co-expression, related to changes in melanogenesis through their putative targets Mitf, Tyr and Tyrp1, and control of cell cycle and senescence: Cyclin D1, Cdk2, Cdk4, p21, and p27. Conclusions: These findings provide insights into the molecular biology of melanoma of the way miRNAs are coordinated and reciprocal expression that may operate in a network as molecular bases for understanding changes in pigmentation and decreased proliferation induced in B16F1 melanoma cells exposed to L-Tyr and 5-Brd-2'-dU.

Joint Transcriptomic Analysis of Lung Cancer and Other Lung Diseases.

Background: Epidemiological and clinical evidence points cancer comorbidity with pulmonary chronic disease. The acquisition of some hallmarks of cancer by cells affected with lung pathologies as a cell adaptive mechanism to a shear stress, suggests that could be associated with the establishment of tumoral processes. Objective: To propose a bioinformatic pipeline for the identification of all deregulated genes and the transcriptional regulators (TFs) that are coexpressed during lung cancer establishment, and therefore could be important for the acquisition of the hallmarks of cancer. Methods: Ten microarray datasets (six of lung cancer, four of lung diseases) comparing normal and diseases-related lung tissue were selected to identify hub differentiated expressed genes (DEGs) in common between lung pathologies and lung cancer, along with transcriptional regulators through the utilization of specialized libraries from R language. DAVID bioinformatics tool for gene enrichment analyses was used to identify genes with experimental evidence associated to tumoral processes and signaling pathways. Coexpression networks of DEGs and TFs in lung cancer establishment were created with Coexnet library, and a survival analysis of the main hub genes was made. Results: Two hundred ten DEGs were identified in common between lung cancer and other lung diseases related to the acquisition of tumoral characteristics, which are coexpressed in a lung cancer network with TFs, suggesting that could be related to the establishment of the tumoral pathology in lung. The comparison of the coexpression networks of lung cancer and other lung diseases allowed the identification of common connectivity patterns (CCPs) with DEGs and TFs correlated to important tumoral processes and signaling pathways, that haven´t been studied to experimentally validate their role in the early stages of lung cancer. Some of the TFs identified showed a correlation between its expression levels and the survival of lung cancer patients. Conclusion: Our findings indicate that lung diseases share genes with lung cancer which are coexpressed in lung cancer, and might be able to explain the epidemiological observations that point to direct and inverse comorbid associations between some chronic lung diseases and lung cancer and represent a complex transcriptomic scenario.