Methylation-to-Expression Feature Models of Breast Cancer Accurately Predict Overall Survival, Distant-Recurrence Free Survival, and Pathologic Complete Response in Multiple Cohorts-Reference-Cited by-同舟云学术

Methylation-to-Expression Feature Models of Breast Cancer Accurately Predict Overall Survival, Distant-Recurrence Free Survival, and Pathologic Complete Response in Multiple Cohorts

Published:2018-03-26 Issue:1 Volume:8 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Thompson Jeffrey A.,Christensen Brock C.,Marsit Carmen J.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://www.nature.com/articles/s41598-018-23494-0.pdf

Reference38 articles.

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2. Weinstein, J. N. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet 45, 1113–1120, https://doi.org/10.1038/ng.2764 (2013).

3. Zhang, J. J. et al. International Cancer Genome Consortium Data Portal-a one-stop shop for cancer genomics data. Database-Oxford https://doi.org/10.1093/database/bar026 (2011).

4. Edgar, R., Domrachev, M. & Lash, A. E. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res 30, 207–210, https://doi.org/10.1093/nar/30.1.207 (2002).

5. Parker, J. S. et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 27, 1160–1167, https://doi.org/10.1200/JCO.2008.18.1370 (2009).

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