Additional file 2: of Integrated proteotranscriptomics of breast cancer reveals globally increased protein-mRNA concordance associated with subtypes and survival

Figure S1. Processing of proteome data. Figure S2. Overlap in identified proteins between our study (Tang et al.) and other proteome datasets for breast cancer. Figure S3. Proteome profiles for tumors vs. adjacent non-cancerous tissues and for tumor subtypes. Figure S4. Increased expression of proteins in breast tumors encoded by mRNAs with shortened 3′UTR. Figure S5. KEGG pathways that are significantly enriched for proteins and mRNAs that were differentially expressed between basal-like tumors and adjacent non-cancerous tissue (13 pairs). Figure S6. Robustness of the global protein-mRNA concordance estimates for breast tumors and adjacent non-cancerous tissues. Figure S7. Exclusion of extracellular matrix proteins from the proteome dataset does not significantly alter the protein-mRNA concordance calculations for tumors or non-cancerous tissues. Figure S8. Correlation between tissue protein levels and tumor grade. Figure S9. Correlation between steady-state protein and mRNA abundance (rho) in breast tumors and association with PAM50-defined molecular subtypes using the CPTAC breast cancer proteomics dataset for 77 tumor samples (Mertins et al.). Figure S10. Non-negative matrix factorization (NMF) clustering of the tumor proteome data. (PDF 2346 kb