The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
microRNA-Associated Progression Pathways and Potential Therapeutic Targets Identified by Integrated mRNA and microRNA Expression Profiling in Breast Cancer
Abstract
microRNA expression profiling plays an emerging role in cancer classification and identification of therapeutic strategies. In this study, we have evaluated the benefits of a joint microRNA–mRNA analysis in breast cancer. Matched mRNA and microRNA global expression profiling was conducted in a well-annotated cohort of 207 cases with complete 10-year follow-up. Penalized Cox regression including microRNA expression, mRNA expression, and clinical covariates was used to identify microRNAs associated with distant relapse-free survival (DRFS) that provide independent prognostic information, and are not simply surrogates of previously identified prognostic covariates. Penalized regression was chosen to prevent overfitting. Furthermore, microRNA–mRNA relationships were explored by global expression analysis, and exploited to validate results in several published cohorts (n = 592 with DRFS, n = 1,050 with recurrence-free survival). Four microRNAs were independently associated with DRFS in estrogen receptor (ER)-positive (3 novel and 1 known; miR-128a) and 6 in ER-negative (5 novel and 1 known; miR-210) cases. Of the latter, miR-342, -27b, and -150 were prognostic also in triple receptor-negative tumors. Coordinated expression of predicted target genes and prognostic microRNAs strengthened these results, most significantly for miR-210, -128a, and -27b, whose targets were prognostic in meta-analysis of several cohorts. In addition, miR-210 and -128a showed coordinated expression with their cognate pri-microRNAs, which were themselves prognostic in independent cohorts. Our integrated microRNA–mRNA global profiling approach has identified microRNAs independently associated with prognosis in breast cancer. Furthermore, it has validated known and predicted microRNA–target interactions, and elucidated their association with key pathways that could represent novel therapeutic targets. Cancer Res; 71(17); 5635–45. ©2011 AACR.
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Chan, S. Y., Zhang, Y.-Y., Hemann, C., Mahoney, C. E., Zweier, J. L., & Loscalzo, J. (2009) · Cell Metabolism · doi:10.1016/j.cmet.2009.08.015 · Cited by 702 · cited 1×
“ISCU plays an important role in mitochondrial respiration and DNA repair (28, 29).”
BackgroundSprouty, an intracellular inhibitor of Ras signaling
Casci, T., Vinós, J., & Freeman, M. (1999) · Cell · doi:10.1016/s0092-8674(00)80576-0 · Cited by 467
Favaro, E., Ramachandran, A., McCormick, R., Gee, H., Blancher, C., Crosby, M., Devlin, C., Blick, C., Buffa, F., Li, J.-L., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010345 · Cited by 324
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Cited by
MicroRNA profiling: approaches and considerations
Pritchard, C. C., Cheng, H. H., & Tewari, M. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3198 · Cited by 1,765
Chou, J., Lin, J. H., Brenot, A., Kim, J.-W., Provot, S., & Werb, Z. (2013) · Nature Cell Biology · doi:10.1038/ncb2672 · Cited by 373
Smith, A. L., Iwanaga, R., Drasin, D. J., Micalizzi, D. S., Vartuli, R. L., Tan, A.-C., & Ford, H. L. (2012) · Oncogene · doi:10.1038/onc.2012.11 · Cited by 293
Age-specific changes in intrinsic breast cancer subtypes: a focus on older women
Jenkins, E. O., Deal, A. M., Anders, C. K., Prat, A., Perou, C. M., Carey, L. A., & Muss, H. B. (2014) · The Oncologist · doi:10.1634/theoncologist.2014-0184 · Cited by 165
Volinia, S., & Croce, C. M. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1304977110 · Cited by 149
Metadata
- Authors
- Buffa, F. M., Camps, C., Winchester, L., Snell, C. E., Gee, H. E., Sheldon, H., Taylor, M., Harris, A. L., & Ragoussis, J.
- Venue
- Cancer Research
- Published
- 2011-08-30
- Volume
- 71
- Issue
- 17
- Pages
- 5635-5645
- ISSN
- 0008-5472 (ISSN-L)
- 1538-7445
- OpenAlex
- W2110237047
- Cited by
- 308
- References
- 3
- FWCI
- 11.78
- Type
- journal article
- Language
- en
- Open access
- closed
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- Buffa, F. M., Camps, C., Winchester, L., Snell, C. E., Gee, H. E., Sheldon, H., Taylor, M., Harris, A. L., & Ragoussis, J. (2011). microRNA-Associated Progression Pathways and Potential Therapeutic Targets Identified by Integrated mRNA and microRNA Expression Profiling in Breast Cancer. Cancer Research. https://doi.org/10.1158/0008-5472.can-11-0489
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