Impact of bioinformatic procedures in the development and translation of high-throughput molecular classifiers in oncology.

Published

Journal Article (Review)

The progressive introduction of high-throughput molecular techniques in the clinic allows for the extensive and systematic exploration of multiple biologic layers of tumors. Molecular profiles and classifiers generated from these assays represent the foundation of what the National Academy describes as the future of "precision medicine". However, the analysis of such complex data requires the implementation of sophisticated bioinformatic and statistical procedures. It is critical that oncology practitioners be aware of the advantages and limitations of the methods used to generate classifiers to usher them into the clinic. This article uses publicly available expression data from patients with non-small cell lung cancer to first illustrate the challenges of experimental design and preprocessing of data before clinical application and highlights the challenges of high-dimensional statistical analysis. It provides a roadmap for the translation of such classifiers to clinical practice and makes key recommendations for good practice.

Full Text

Duke Authors

Cited Authors

  • Ferté, C; Trister, AD; Huang, E; Bot, BM; Guinney, J; Commo, F; Sieberts, S; André, F; Besse, B; Soria, J-C; Friend, SH

Published Date

  • August 15, 2013

Published In

Volume / Issue

  • 19 / 16

Start / End Page

  • 4315 - 4325

PubMed ID

  • 23780890

Pubmed Central ID

  • 23780890

International Standard Serial Number (ISSN)

  • 1078-0432

Digital Object Identifier (DOI)

  • 10.1158/1078-0432.CCR-12-3937

Language

  • eng

Conference Location

  • United States