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Single Sample Expression-Anchored Mechanisms Predict Survival in Head and Neck Cancer

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  • Xinan Yang
  • Kelly Regan
  • Yong Huang
  • Qingbei Zhang
  • Jianrong Li
  • Tanguy Y Seiwert
  • Ezra E W Cohen
  • H Rosie Xing
  • Yves A Lussier

Abstract

Gene expression signatures that are predictive of therapeutic response or prognosis are increasingly useful in clinical care; however, mechanistic (and intuitive) interpretation of expression arrays remains an unmet challenge. Additionally, there is surprisingly little gene overlap among distinct clinically validated expression signatures. These “causality challenges” hinder the adoption of signatures as compared to functionally well-characterized single gene biomarkers. To increase the utility of multi-gene signatures in survival studies, we developed a novel approach to generate “personal mechanism signatures” of molecular pathways and functions from gene expression arrays. FAIME, the Functional Analysis of Individual Microarray Expression, computes mechanism scores using rank-weighted gene expression of an individual sample. By comparing head and neck squamous cell carcinoma (HNSCC) samples with non-tumor control tissues, the precision and recall of deregulated FAIME-derived mechanisms of pathways and molecular functions are comparable to those produced by conventional cohort-wide methods (e.g. GSEA). The overlap of “Oncogenic FAIME Features of HNSCC” (statistically significant and differentially regulated FAIME-derived genesets representing GO functions or KEGG pathways derived from HNSCC tissue) among three distinct HNSCC datasets (pathways:46%, p

Suggested Citation

  • Xinan Yang & Kelly Regan & Yong Huang & Qingbei Zhang & Jianrong Li & Tanguy Y Seiwert & Ezra E W Cohen & H Rosie Xing & Yves A Lussier, 2012. "Single Sample Expression-Anchored Mechanisms Predict Survival in Head and Neck Cancer," PLOS Computational Biology, Public Library of Science, vol. 8(1), pages 1-18, January.
  • Handle: RePEc:plo:pcbi00:1002350
    DOI: 10.1371/journal.pcbi.1002350
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    1. Junjie Su & Byung-Jun Yoon & Edward R Dougherty, 2009. "Accurate and Reliable Cancer Classification Based on Probabilistic Inference of Pathway Activity," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-10, December.
    2. Andrea H. Bild & Guang Yao & Jeffrey T. Chang & Quanli Wang & Anil Potti & Dawn Chasse & Mary-Beth Joshi & David Harpole & Johnathan M. Lancaster & Andrew Berchuck & John A. Olson & Jeffrey R. Marks &, 2006. "Oncogenic pathway signatures in human cancers as a guide to targeted therapies," Nature, Nature, vol. 439(7074), pages 353-357, January.
    3. Andy J. Minn & Gaorav P. Gupta & Peter M. Siegel & Paula D. Bos & Weiping Shu & Dilip D. Giri & Agnes Viale & Adam B. Olshen & William L. Gerald & Joan Massagué, 2005. "Genes that mediate breast cancer metastasis to lung," Nature, Nature, vol. 436(7050), pages 518-524, July.
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