Large meta-analysis of multiple cancers reveals a common, compact and highly prognostic hypoxia metagene

• Published in: British journal of cancer Vol. 102; no. 2; pp. 428 - 435
• Main Authors: Buffa, F M, Harris, A L, West, C M, Miller, C J
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.01.2010; Nature Publishing Group
• Subjects: 631/208/191/2018; 692/1807/244; 692/53/2422; 692/699/67; Biological and medical sciences; Biomedical and Life Sciences; Biomedicine; Breast Neoplasms - genetics; Breast Neoplasms - physiopathology; Cancer Research; Connectivity; Datasets; Drug Resistance; Epidemiology; Gene Expression; Gene Expression Regulation; Genetics and Genomics; Head and Neck Neoplasms - genetics; Head and Neck Neoplasms - physiopathology; Humans; Hypotheses; Hypoxia; Medical research; Medical sciences; Meta-analysis; Metagenome; Models, Biological; Molecular Medicine; Neighborhoods; Oncology; Prognosis; Seeds; Tumors; United Kingdom > UK; meta-analysis; hypoxia; gene expression; distant relapse; Oxygen; Relapse; Cancerology; Prognosis; Hypoxia; Malignant tumor; Gene expression; Cancer; Metaanalysis
• ISSN: 0007-0920; 1532-1827
• DOI: 10.1038/sj.bjc.6605450

Background: There is a need to develop robust and clinically applicable gene expression signatures. Hypoxia is a key factor promoting solid tumour progression and resistance to therapy; a hypoxia signature has the potential to be not only prognostic but also to predict benefit from particular interventions. Methods: An approach for deriving signatures that combine knowledge of gene function and analysis of in vivo co-expression patterns was used to define a common hypoxia signature from three head and neck and five breast cancer studies. Previously validated hypoxia-regulated genes (seeds) were used to generate hypoxia co-expression cancer networks. Results: A common hypoxia signature, or metagene, was derived by selecting genes that were consistently co-expressed with the hypoxia seeds in multiple cancers. This was highly enriched for hypoxia-regulated pathways, and prognostic in multivariate analyses. Genes with the highest connectivity were also the most prognostic, and a reduced metagene consisting of a small number of top-ranked genes, including VEGFA , SLC2A1 and PGAM1 , outperformed both a larger signature and reported signatures in independent data sets of head and neck, breast and lung cancers. Conclusion: Combined knowledge of multiple genes' function from in vitro experiments together with meta-analysis of multiple cancers can deliver compact and robust signatures suitable for clinical application.