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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Lambrechts, D., Wauters, E., Boeckx, B., Aibar, S., Nittner, D., Burton, O., Bassez, A., Decaluwé, H., Pircher, A., Van den Eynde, K., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0096-5 · Cited by 1,648
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Jin, M.-Z., & Jin, W.-L. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-00280-x · Cited by 1,262
Hypoxia and hypoxia-inducible factors: master regulators of metastasis
Lu, X., & Kang, Y. (2010) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-10-1360 · Cited by 723
Molecular landmarks of tumor hypoxia across cancer types
Bhandari, V., Hoey, C., Liu, L. Y., Lalonde, E., Ray, J., Livingstone, J., Lesurf, R., Shiah, Y.-J., Vujcic, T., Huang, X., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0318-2 · Cited by 678
Tumour hypoxia causes DNA hypermethylation by reducing TET activity
Thienpont, B., Steinbacher, J., Zhao, H., D’Anna, F., Kuchnio, A., Ploumakis, A., Ghesquière, B., Van Dyck, L., Boeckx, B., Schoonjans, L., et al. (2016) · Nature · doi:10.1038/nature19081 · Cited by 635
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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