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BioMed Research International
Volume 2015, Article ID 878546, 10 pages
http://dx.doi.org/10.1155/2015/878546
Research Article

Identification of Gene Expression Pattern Related to Breast Cancer Survival Using Integrated TCGA Datasets and Genomic Tools

1College of Biomedical Engineering and Instrument Science, Zhejiang University, Zhouyiqing Building No. 510, Yuquan Campus, Hangzhou 310027, China
2The Children’s Hospital, Zhejiang University, Zhouyiqing Building No. 510, Yuquan Campus, Hangzhou 310003, China
3The Institute of Translational Medicine, Zhejiang University, Zhouyiqing Building No. 510, Yuquan Campus, Hangzhou 310029, China

Received 3 July 2015; Revised 14 September 2015; Accepted 28 September 2015

Academic Editor: Sílvia A. Sousa

Copyright © 2015 Zhenzhen Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

The total 201 genes that their expression levels were significantly related to shorter overall survival in breast cancer patients were listed in two excel files.

High expression with poor prognosis

Low expression with poor prognosis

Supplement Figure 1: The survival curves of related mitochondrial ribosome and cytosol ribosome genes expression pattern were given in Supplement Figure 1.

Supplement Figure 2: Four additional breast cancer gene expression datasets that were downloaded from Oncomine were plotted in Supplement Figure 2 to support that HSPA2 plays a different role in breast cancer.

Supplement Figure 3: Supplement Figure 3 gave survival curves that generated from NKI295 datasets also help us confirm the HSPA2 expression pattern in breast cancer.

  1. Supplementary Material