Integrative analysis to select cancer candidate biomarkers to targeted validation

Rebeca Kawahara, Gabriela V. Meirelles, Henry Heberle, Romenia R. Domingues, Daniela C. Granato, Sami Yokoo, Rafael R. Canevarolo, Flavia V. Winck, Ana Carolina P. Ribeiro, Thaís Bianca Brandão, Paulo R. Filgueiras, Karen S. P. Cruz, José Alexandre Barbuto, Ronei J. Poppi, Rosane Minghim, Guilherme P. Telles, Felipe Paiva Fonseca, Jay W. Fox, Alan R. Santos-Silva, Ricardo D. ColettaNicholas E. Sherman, Adriana F. Paes Leme

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)
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Targeted 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). Three feature 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.
Original languageEnglish
Pages (from-to)43635-43652
Number of pages18
Issue number41
Publication statusPublished - 22 Dec 2015
Externally publishedYes

Bibliographical note

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  • proteomics
  • discovery
  • targeted
  • candidate biomarker
  • integrative analysis


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