Open Access Highly Accessed Research article

EGFR associated expression profiles vary with breast tumor subtype

Katherine A Hoadley123, Victor J Weigman234, Cheng Fan23, Lynda R Sawyer5, Xiaping He23, Melissa A Troester6, Carolyn I Sartor37, Thais Rieger-House8, Philip S Bernard8, Lisa A Carey5 and Charles M Perou1239*

Author Affiliations

1 Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

2 Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

3 Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

4 Department of Biology, Program of in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

5 Division of Hematology/Oncology, Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

6 Department of Public Health – Biostatistics and Epidemiology Concentration, University of Massachusetts Amherst, Amherst, MA, USA

7 Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

8 Huntsman Cancer Institute and Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA

9 Department of Pathology & Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

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BMC Genomics 2007, 8:258  doi:10.1186/1471-2164-8-258

Published: 31 July 2007

Additional files

Additional file 1:

Gefitinib and carboplatin combinations in breast cancer-derived cell lines. Cells were treated for 72 h with constant ratios of the IC50 doses for both gefitinib and carboplatin. Combination Index (CI) values below one are synergistic, equal to one are additive, and greater than one are antagonistic.

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Additional file 2:

Full cluster diagram for the gene expression patterns of SUM102 cells treated with gefitinib or cetuximab.

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Additional file 3:

Full cluster diagram for the in vivo EGFR-activation profiles clustered on the UNC tumor data set.

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Additional file 4:

Genes from Cluster #1–3. Genes identified from the 500 SUM102 genes clustered on the UNC tumor dataset.

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Additional file 5:

Clinical data associated with each tumor sample.

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