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

Abstract

BackgroundTranscriptome analysis of breast cancer discovered distinct disease subtypes of clinical significance. However, it remains a challenge to define disease biology solely based on gene expression because tumor biology is often the result of protein function. Here, we measured global proteome and transcriptome expression in human breast tumors and adjacent non-cancerous tissue and performed an integrated proteotranscriptomic analysis.MethodsWe applied a quantitative liquid chromatography/mass spectrometry-based proteome analysis using an untargeted approach and analyzed protein extracts from 65 breast tumors and 53 adjacent non-cancerous tissues. Additional gene expression data from Affymetrix Gene Chip Human Gene ST Arrays were available for 59 tumors and 38 non-cancerous tissues in our study. We then applied an integrated analysis of the proteomic and transcriptomic data to examine relationships between them, disease characteristics, and patient survival. Findings were validated in a second dataset using proteome and transcriptome data from “The Cancer Genome Atlas” and the Clinical Proteomic Tumor Analysis Consortium.ResultsWe found that the proteome describes differences between cancerous and non-cancerous tissues that are not revealed by the transcriptome. The proteome, but not the transcriptome, revealed an activation of infection-related signal pathways in basal-like and triple-negative tumors. We also observed that proteins rather than mRNAs are increased in tumors and show that this observation could be related to shortening of the 3′ untranslated region of mRNAs in tumors. The integrated analysis of the two technologies further revealed a global increase in protein-mRNA concordance in tumors. Highly correlated protein-gene pairs were enriched in protein processing and disease metabolic pathways. The increased concordance between transcript and protein levels was additionally associated with aggressive disease, including basal-like/triple-negative tumors, and decreased patient survival. We also uncovered a strong positive association between protein-mRNA concordance and proliferation of tumors. Finally, we observed that protein expression profiles co-segregate with a Myc activation signature and separate breast tumors into two subgroups with different survival outcomes.ConclusionsOur study provides new insights into the relationship between protein and mRNA expression in breast cancer and shows that an integrated analysis of the proteome and transcriptome has the potential of uncovering novel disease characteristics.Electronic supplementary materialThe online version of this article (10.1186/s13073-018-0602-x) contains supplementary material, which is available to authorized users.

Liver- and Microbiome-derived Bile Acids Accumulate in Human Breast Tumors and Inhibit Growth and Improve Patient Survival

“…Large-scale proteome and metabolome data existed for 58 breast tumors. The mass spectrometry-based analysis of the proteome was performed as described previously (19). More details are provided in Supplementary Methods.…”

“…Together, our findings suggest that bile acids may cause a reprogramming in breast cancer biology toward a less aggressive disease and thereby improve breast cancer outcomes. meta-gene score as a marker for tissue proliferation, as described previously (19)(20)(21). This proliferation signature also contains MKI67, the transcript that encodes Ki67, a commonly used proliferation marker using IHC.…”

“…To further characterize the tumor biology associated with increased GCDC, we examined relationships of GCDC with the transcriptome and proteome. Having existing gene expression and proteome data from 61 and 58 breast tumors, respectively, in our NCI-Maryland breast cancer cohort (11,19), we initially analyzed the transcriptome differences between the 15 GCDChigh versus the 46 GCDC-low tumors. The investigation identified 73 transcripts that were significantly differentially expressed using a false discovery rate (FDR) < 5% and fold difference > 2 as stringent cutoffs ( Supplementary Table S2).…”

Integration of Online Omics-Data Resources for Cancer Research

“…between mRNA and protein levels was linked with aggressive BC, including basal-like/triple-negative BC, and decreased survival (Tang et al, 2018). Despite the relative strengths and weaknesses of post-analysis and integrated approaches, these strategies are currently being used as exploratory tools to generate a new hypothesis or to provide some mechanistic explanation of cancer phenotypes.…”

A time-resolved proteotranscriptomics atlas of the human placenta reveals pan-cancer immunomodulators

“…In almost every organism that has been examined to date, steady-state transcript abundances only partially predict protein abundance. 4 The matched LC-MS/MS and RNA-seq measurements allowed the first global analysis of protein-mRNA relationships in the human placenta cohort. Consistent with previous findings, the correlation of mRNA and protein in this study was also moderate (median Spearman correlation coefficients (SCCs) = 0.44).…”