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Issue title: Quantitative Methods for Biomarker Discovery and Validation
Article type: Research Article
Authors: He, Yudong D.; *
Affiliations: Rosetta Impharmatics LLC, A wholly owned subsidiary of Merck & Co., Inc., 401 Terry Avenue North, Seattle, WA 98109, USA | Biostatistics Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
Correspondence: [*] Corresponding author. Tel.: +1 206 802 7351; Fax: +1 206 802 6411; E-mail: yudong_he@merck.com.
Abstract: This paper discusses selected activities, issues, and challenges in recent development of analytical methods and applications in biomarker identification and validation using state-of-the-art genomic approaches. Molecular profiling via genomics, proteomics, and metabonomics has opened new windows to study disease states and biological systems. It has also provided exciting opportunities for novel applications in clinical research as well as in drug discovery and development. In the past several years, we have witnessed enormous progress resulting particularly from gene expression profiling of mRNA or transcriptomics. After a brief review on technology advances in gene expression profiling using microarrays, I mainly discuss recent developments of the genomic approaches to biomarker identification and validation in two major types of applications. The first type involves examples in cancer diagnostics and prognostics based on tumor gene expression profiling, whereas the second type involves biomarker applications in drug discovery and development. The focus will be on analytical methods and algorithms that have been developed in recent years facilitating biomarker discovery and application by leveraging genome-wide expression profiles derived from microarrays. Technical issues in experimental design, data processing, error modeling, quality control, figures of merit for performance evaluation, and meta-analysis related to biomarker discovery and application are also discussed. A case study of disease outcome prognosis for breast cancer patients based on tumor expression pattern is presented before closing remarks.
Keywords: Biomarker, genomics, expression profile, microarray, oncology, drug discovery
DOI: 10.3233/CBM-2006-23-404
Journal: Cancer Biomarkers, vol. 2, no. 3-4, pp. 103-133, 2006
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