The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Large meta-analysis of multiple cancers reveals a common, compact and highly prognostic hypoxia metagene
Open accessAbstract
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.
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The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
Hypoxia — a key regulatory factor in tumour growth
Harris, A. L. (2002) · Nature Reviews Cancer · doi:10.1038/nrc704 · Cited by 5,177
Self-citationGene-expression profiles predict survival of patients with lung adenocarcinoma
Beer, D. G., Kardia, S. L. R., Huang, C.-C., Giordano, T. J., Levin, A. M., Misek, D. E., Lin, L., Chen, G., Gharib, T. G., Thomas, D. G., et al. (2002) · Nature Medicine · doi:10.1038/nm733 · Cited by 2,025
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Metadata
- Authors
- Buffa, F. M., Harris, A. L., West, C. M., & Miller, C. J.
- Venue
- British Journal of Cancer
- Published
- 2010-01-19
- Volume
- 102
- Issue
- 2
- Pages
- 428-435
- ISSN
- 0007-0920 (ISSN-L)
- 1532-1827
- OpenAlex
- W2084116712
- Cited by
- 556
- References
- 7
- FWCI
- 0.87
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Buffa, F. M., Harris, A. L., West, C. M., & Miller, C. J. (2010). Large meta-analysis of multiple cancers reveals a common, compact and highly prognostic hypoxia metagene. British Journal of Cancer. https://doi.org/10.1038/sj.bjc.6605450
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
