THAIS BIANCA BRANDAO
Projetos de Pesquisa
Unidades Organizacionais
Instituto do Câncer do Estado de São Paulo, Hospital das Clínicas, Faculdade de Medicina
2 resultados
Resultados de Busca
Agora exibindo 1 - 2 de 2
article 15 Citação(ões) na Scopus Integrative analysis to select cancer candidate biomarkers to targeted validation(2015) KAWAHARA, Rebeca; MEIRELLES, Gabriela V.; HEBERLE, Henry; DOMINGUES, Romenia R.; GRANATO, Daniela C.; YOKOO, Sami; CANEVAROLO, Rafael R.; WINCK, FlaviaV.; RIBEIRO, Ana Carolina P.; BRANDAO, Thais Bianca; FILGUEIRAS, Paulo R.; CRUZ, Karen S. P.; BARBUTO, Jose Alexandre; POPPI, Ronei J.; MINGHIM, Rosane; TELLES, Guilherme P.; FONSECA, Felipe Paiva; FOX, Jay W.; SANTOS-SILVA, Alan R.; COLETTA, Ricardo D.; SHERMAN, Nicholas E.; LEME, Adriana F. PaesTargeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Threeyfeature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS.- Insights into immune responses in oral cancer through proteomic analysis of saliva and salivary extracellular vesicles(2015) WINCK, Flavia V.; RIBEIRO, Ana Carolina Prado; DOMINGUES, Romenia Ramos; LING, Liu Yi; RIANO-PACHON, Diego Mauricio; RIVERA, Cesar; BRANDAO, Thais Bianca; GOUVEA, Adriele Ferreira; SANTOS-SILVA, Alan Roger; COLETTA, Ricardo D.; LEME, Adriana F. PaesThe development and progression of oral cavity squamous cell carcinoma (OSCC) involves complex cellular mechanisms that contribute to the low five-year survival rate of approximately 20% among diagnosed patients. However, the biological processes essential to tumor progression are not completely understood. Therefore, detecting alterations in the salivary proteome may assist in elucidating the cellular mechanisms modulated in OSCC and improve the clinical prognosis of the disease. The proteome of whole saliva and salivary extracellular vesicles (EVs) from patients with OSCC and healthy individuals were analyzed by LC-MS/MS and label-free protein quantification. Proteome data analysis was performed using statistical, machine learning and feature selection methods with additional functional annotation. Biological processes related to immune responses, peptidase inhibitor activity, iron coordination and protease binding were overrepresented in the group of differentially expressed proteins. Proteins related to the inflammatory system, transport of metals and cellular growth and proliferation were identified in the proteome of salivary EVs. The proteomics data were robust and could classify OSCC with 90% accuracy. The saliva proteome analysis revealed that immune processes are related to the presence of OSCC and indicate that proteomics data can contribute to determining OSCC prognosis.