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Coupling proteomics and transcriptomics in the quest of subtype-specific proteins in breast cancer
Article first published online: 25 FEB 2013
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Volume 13, Issue 7, pages 1083–1095, April 2013
How to Cite
Pavlou, M. P., Dimitromanolakis, A. and Diamandis, E. P. (2013), Coupling proteomics and transcriptomics in the quest of subtype-specific proteins in breast cancer. Proteomics, 13: 1083–1095. doi: 10.1002/pmic.201200526
- Issue published online: 5 APR 2013
- Article first published online: 25 FEB 2013
- Accepted manuscript online: 5 FEB 2013 11:57AM EST
- Manuscript Accepted: 7 JAN 2013
- Manuscript Revised: 19 DEC 2012
- Manuscript Received: 20 NOV 2012
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Figure S1. Comparison of the secretomes of the 8 breast cancer cell lines to generate subtype specific proteomic signatures. First, proteins of cell lines that belong to the same subtype were compared to identify proteins common in all the cell lines of each subtype (a). Then, the resulting protein groups were compared to identify proteins unique to each subtype. It is noteworthy that ERBB2 protein was one of the seven proteins uniquely identified in the HER2-neu amplified subtype.
Figure S2. mRNA expression of the selected genes in 51 cell lines displayed as a heatmap. Red corresponds to higher than mean expression whereas blue to lower. The color of each cell is relative to the mean value of each row and can be used to judge over/under expression.
Figure S3. Kaplan-Meier analysis for i) all breast cancer patients and ii) patients with ER+ breast cancer using the online tool GOBO. Patients with high ABAT expression have better prognosis when compared to patients with low expression. Relapse-free survival (RFS) was used as end-point.
Figure S4. Kaplan-meier analysis using relapse-free survival (RFS) as end-point and corresponding multivariate analysis using estrogen receptor (ER) status and grade as covariates for i) patients with grade II breast cancer and ii) tamoxifen-treated patients.
Table S1. Characteristics of the 8 breast cancer cell lines used in the present study.
Table S2. Optimum culture conditions for the 8 breast cancer cell lines used in the present study.
Table S3. Peptide sequence and mass-to-charge (m/z) ratio of parent and product ions targeted by SRM in the present study.
Table S4. Summary of the proteomic analysis of 8 breast cancer cell line secretomes: More than 1000 proteins were identified in the conditioned media of each cell line and more than 60% were identified with at least 2 peptides. Approximately 30% of the proteins were annotated as extracellular or cell surface based on Gene Ontology annotations.
Table S5. Ratio of means between cell lines of a specific subtype versus all others, as observed on microarray expression data (GSE12790).
Table S6. Correlation of each probe with ESR1 gene expression based on microarray data in 4 experiments with breast cancer tissues. Pearson correlation coefficient (r) and p-value of a correlation test is shown.
Table S7. Proteins identified in the mass spectrometric analysis of ER-positive and ER-negative breast cancer cytosols along with the ER+/ER- ratio based on extracted current ion intensity values. Statistical analysis was performed as described in materials and methods.
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