Análise transcriptômica de genes do sistema imune em diferentes subtipos de câncer de mama

• Ano de defesa: 2019
• Autor(a) principal: Omena Neta, Genilda Castro de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso embargado
• Idioma: por
• Instituição de defesa: Universidade Federal de Alagoas; Brasil; Programa de Pós-Graduação eMulticêntrico em Bioquímica e Biologia Molecular; UFAL
• Palavras-chave em Português: Neoplasias da mama; Macrófagos; Neutrófilos; Neuropeptídeos; Células receptoras sensoriais; Sobrevida; Biologia computacional; Breast neoplasms; Macrophages; Neutrophils; Neuropeptides; Sensory receptor cells; Survival; Bioinformatics; CNPQ::CIENCIAS BIOLOGICAS::BIOQUIMICA
• Link de acesso: http://www.repositorio.ufal.br/handle/riufal/6679

Breast cancer (BC) is the type of cancer with the highest incidence in women worldwide. It has four molecular subtypes (Luminal A, Luminal B, HER2 and Triple Negative / Basal) and each of them has different prognoses and needs for interventions that are efficient in the treatment and increase patient survival. In this sense, the evaluation of gene and protein expression in neoplastic breast tissues of the CM subtypes using translational bioinformatics (TB) allows a wide analysis of several databases. TB works by bringing biological knowledge that can be applied in the clinic based on genomic, proteomic, histological and clinical data of patients with CM. The objective of this work is to identify the immunological profile through gene and protein expression in the molecular subtypes of breast cancer using bioinformatics tools.The methodology used involved several computational tools that allowed data collection in databases (Genomic Cancer Atlas -TCGA, Entrez Gene of NCBI, GeneCards, Proteomic Cancer Atlas -TCPA, DAVID) and analyzes (Venn diagram, Encyclopedia of Genes and Genomes -KEGG, TCGAbiolinks, Tumor Immune Cell Estimation Resource - TIMER, Prediction of Clinical Data of Genomic Profiles - PRECOG). In the statistical analyzes, the GraphPad Prism Software version 7, the Two-Way ANOVA two-way test and the two-tailed unpaired t test were used. The analysis of the differentially expressed genes (GDEs) associated with cancer metabolic pathways, genes expressed exclusively in each subtype were identified when compared to normal breast tissue: Cd38 at basal, Erbb2 at Her2 and Esr1 and Pgr in the luminal. In the analysis of immune cells, M1 macrophages were found in the subtypes with the worst prognosis (baseline and HER2) and M2 in those with the Best prognosis (luminal A and luminal B). The genes associated with the Thelper1, Thelper2, Thelper17 and Treg responses did not quantitatively determine the type of immune response. However, the basal subtype had more genes associated with the Treg response when compared to the other subtypes. In the evaluation of cell type genes (macrophages, neutrophils, neuropeptides and neuroreceptors), genes with impact on survival were identified and some that were also associated with the presence or absence of neutrophils, such as Lrp2, Serpina1, Cxcl10 and Qrfpr, and the proteins associated with immunosuppression, such as PDL1, which were more expressed at basal when compared with the other subtypes of CM and those associated with the pathways that stimulate carcinogenesis and/or dysregulation of cell proliferation, such as IRS1 and AKT that were more expressed in the neoplasic breast tissues of the luminal and basal subtypes in relation to the other subtypes, respectively. Therefore, the genes and proteins that had an impact on survival and/or interfere by some mechanism in the recruitment of immune cells found in the tumor microenvironment can be the target of in vitro and in vivo studies that can elucidate the metabolic mechanisms. With the results of this study confirmed, these genes and proteins can be new markers of CM and enable the development of new, more effective therapies.