Dataset Information

Analysis of Human Breast Tumors by Integrated Proteotranscriptomics

ABSTRACT: We generated large-scale proteome data for 65 human breast tumors and 53 paired adjacent non-cancerous tissue and performed an integrated proteotranscriptomic characterization. To our best knowledge, the study is one of the largest quantitative proteomic study of human breast tissues, including the analysis of 118 tissue samples from 65 patients with long-term survival outcomes. Our data show that protein expression describes a tumor biology that is only partly captured by the transcriptome, with mRNA abundance incompletely predicting protein abundance in tumors, and even less so in non-cancerous tissue. Furthermore, the tumor proteome described disease pathways and subgroups that were only partially captured by the tumor transcriptome.

INSTRUMENT(S): LTQ Orbitrap

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Breast

SUBMITTER: wei tang

LAB HEAD: Wei Tang

PROVIDER: PXD005692 | Pride | 2018-12-04

REPOSITORIES: Pride

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Publications

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

Tang Wei W Zhou Ming M Dorsey Tiffany H TH Prieto DaRue A DA Wang Xin W XW Ruppin Eytan E Veenstra Timothy D TD Ambs Stefan S

Genome medicine 20181203 1

<h4>Background</h4>Transcriptome 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.<h4>Methods</h4>We applied a quantitative liqui ...[more]

PMID: 30501643

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Project description:Current prognostic factors are insufficient for precise risk-discrimination in breast cancer patients with low grade breast tumors, which, in disagreement with theoretical prognosis, occasionally form early lymph node metastasis. To identify markers for this group of patients, we employed iTRAQ-2DLC-MS/MS proteomics to 24 lymph node positive and 24 lymph node negative grade 1 luminal A primary breast tumors. Another group of 48 high-grade tumors (luminal B, triple negative, Her-2 subtypes) was also analyzed to investigate marker specificity for grade 1 luminal A tumors. From the total of 4405 proteins identified (FDR<5%), the top 65 differentially expressed together with 30 previously identified and control markers were analyzed also at transcript level. Increased levels of carboxypeptidase B1 (CPB1), PDZ and LIM domain protein 2 (PDLIM2) and ring finger protein 25 (RNF25) were associated specifically with lymph node positive grade 1 tumors, whereas stathmin 1 (STMN1) and thymosin beta 10 (TMSB10) associated with aggressive tumor phenotype also in high grade tumors at both protein and transcript level. For CPB1, these differences were also observed by immunohistochemical analysis on tissue microarrays. Upregulation of putative biomarkers in lymph node positive (vs. negative) luminal A tumors was validated by gene expression analysis of an independent published dataset (N=343) for CPB1 (p=0.00155), PDLIM2 (p=0.02027) and RELA (p=0.00015). Moreover, statistically significant connections with patient survival were identified in another public dataset (N=1678). Our findings indicate unique pro-metastatic mechanisms in grade 1 tumors that can include up-regulation of CPB1, activation of NF-κB pathway and changes in cell survival and cytoskeleton. These putative biomarkers have potential to identify the specific minor sub-population of breast cancer patients with low grade tumors who are at higher than expected risk of recurrence and who would benefit from more intensive follow-up and may require more personalized therapy.

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