Single sample expression-anchored mechanisms predict survival in head and neck cancer

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 cl...

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Published in:PLoS computational biology 2012-01, Vol.8 (1), p.e1002350-e1002350
Main Authors: Yang, Xinan, Regan, Kelly, Huang, Yong, Zhang, Qingbei, Li, Jianrong, Seiwert, Tanguy Y, Cohen, Ezra E W, Xing, H Rosie, Lussier, Yves A
Format: Article
Language:English
Subjects:
Apoptosis
Biology
Biomarkers
Carcinoma, Squamous Cell - genetics
Carcinoma, Squamous Cell - metabolism
Carcinoma, Squamous Cell - mortality
Cohort Studies
Development and progression
DNA replication
Gene expression
Gene Expression Profiling
Genetic aspects
Genomics
Head & neck cancer
Head and neck cancer
Head and Neck Neoplasms - genetics
Head and Neck Neoplasms - metabolism
Head and Neck Neoplasms - mortality
Humans
Lasers
Medical research
Medicine
Patient outcomes
Patients
Physiological aspects
Principal components analysis
ROC Curve
Statistical methods
Studies
Tumor proteins
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Summary: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
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1002350