Dataset Information

Breast Cancer Proteomics - Differences in Protein Expression between Estrogen Receptor-Positive and -Negative Tumors Identified by Tandem Mass Tag Technology.

ABSTRACT: BACKGROUND: Proteomic analysis has become an effective tool in breast cancer research. In this study, we applied the new gel-free tandem mass tag (TMT) reference method for the first time in breast cancer. MATERIALS AND METHODS: Proteomic analysis was used to compare 10 estrogen receptor (ER)-positive and 10 ER-negative samples. The results of the proteomic approach were validated by Western blot, immunohistochemistry and gene expression analysis. RESULTS: 17 proteins with significant differences in expression were identified. 13 proteins were overexpressed in ER-negative tumors and 4 were overexpressed in ER-positive samples. All these proteins were characterized by relatively high cellular abundance. CONCLUSIONS: Our results demonstrate that the gel-free TMT approach allows the quantification of differences in protein expression levels. Further improvement of the sensitivity by subfractionation of the tissue should allow also the identification of low-abundance proteins and might lead to the use of this method in breast cancer research.

SUBMITTER: Ruckhaberle E

PROVIDER: S-EPMC3357159 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Breast Cancer Proteomics - Differences in Protein Expression between Estrogen Receptor-Positive and -Negative Tumors Identified by Tandem Mass Tag Technology.

Ruckhäberle Eugen E Karn Thomas T Hanker Lars L Schwarz Josef J Schulz-Knappe Peter P Kuhn Karsten K Böhm Gitte G Selzer Stefan S Erhard Neukum N Engels Knut K Holtrich Uwe U Kaufmann Manfred M Rody Achim A

Breast care (Basel, Switzerland) 20100216 1

BACKGROUND: Proteomic analysis has become an effective tool in breast cancer research. In this study, we applied the new gel-free tandem mass tag (TMT) reference method for the first time in breast cancer. MATERIALS AND METHODS: Proteomic analysis was used to compare 10 estrogen receptor (ER)-positive and 10 ER-negative samples. The results of the proteomic approach were validated by Western blot, immunohistochemistry and gene expression analysis. RESULTS: 17 proteins with significant differen ...[more]

PMID: 22619634

Similar Datasets

Project description:PURPOSE:A subset of estrogen receptor-positive (ER-positive) breast cancer (BC) contains high levels of tumor-infiltrating lymphocytes (TILs), similar to triple-negative BC (TNBC). The majority of immuno-oncology trials target TNBCs because of the greater proportion of TIL-rich TNBCs. The extent to which the immune microenvironments of immune-rich ER-positive BC and TNBC differ is unknown. PATIENTS AND METHODS:RNA sequencing data from The Cancer Genome Atlas (TCGA; n = 697 ER-positive BCs; n = 191 TNBCs) were used for discovery; microarray expression data from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC; n = 1,186 ER-positive BCs; n = 297 TNBCs) was used for validation. Patients in the top 25th percentile of a previously published total TIL metagene score distribution were considered immune rich. We compared expression of immune cell markers, immune function metagenes, and immuno-oncology therapeutic targets among immune-rich subtypes. RESULTS:Relative fractions of resting mast cells (TCGA P adj = .009; METABRIC P adj = 4.09E-15), CD8+ T cells (TCGA P adj = .015; METABRIC P adj = 0.390), and M2-like macrophages (TCGA P adj= 4.68E-05; METABRIC P adj = .435) were higher in immune-rich ER-positive BCs, but M0-like macrophages (TCGA P adj = 0.015; METABRIC P adj = .004) and M1-like macrophages (TCGA P adj = 9.39E-08; METABRIC P adj = 6.24E-11) were higher in immune-rich TNBCs. Ninety-one immune-related genes (eg, CXCL14, CSF3R, TGF-B3, LRRC32/GARP, TGFB-R2) and a transforming growth factor ? (TGF-?) response metagene were significantly overexpressed in immune-rich ER-positive BCs, whereas 41 immune-related genes (eg, IFNG, PD-L1, CTLA4, MAGEA4) were overexpressed in immune-rich TNBCs in both discovery and validation data sets. TGF-? pathway member genes correlated negatively with expression of immune activation markers (IFNG, granzyme-B, perforin) and positively with M2-like macrophages (IL4, IL10, and MMP9) and regulatory T-cell (FOXP3) markers in both subtypes. CONCLUSION:Different immunotherapy strategies may be optimal in immune-rich ER-positive BC and TNBC. Drugs targeting the TGF-? pathway and M2-like macrophages are promising strategies in immune-rich ER-positive BCs to augment antitumor immunity.

Project description:Identification of the proteins that are associated with estrogen receptor (ER) status is a first step towards better understanding of the hormone-dependent nature of breast carcinogenesis. Although a number of gene expression analyses have been conducted, protein complement has not been systematically investigated to date. Because proteins are primary targets of therapeutic drugs, in this study, we have attempted to identify proteomic signatures that demarcate ER-positive and -negative breast cancers. Using highly enriched breast tumor cells, replicate analyses from 3 ERα+ and 3 ERα- human breast tumors resulted in the identification of 2,995 unique proteins with ≥2 peptides. Among these, a number of receptor tyrosine kinases and intracellular kinases that are abundantly expressed in ERα+ and ERα- breast cancer tissues were identified. Further, label-free quantitative proteome analysis revealed that 236 proteins were differentially expressed in ERα+ and ERα- breast tumors. Among these, 141 proteins were selectively up-regulated in ERα+, and 95 proteins were selectively up-regulated in ERα- breast tumors. Comparison of differentially expressed proteins with a breast cancer database revealed 98 among these have been previously reported to be involved in breast cancer. By Gene Ontology molecular function, dehydrogenase, reductase, cytoskeletal proteins, extracellular matrix, hydrolase, and lyase categories were significantly enriched in ERα+, whereas selected calcium-binding protein, membrane traffic protein, and cytoskeletal protein were enriched in ERα- breast tumors. Biological process and pathway analysis revealed that up-regulated proteins of ERα+ were overrepresented by proteins involved in amino acid metabolism, proteasome, and fatty acid metabolism, while up-regulated proteins of ERα- were overrepresented by proteins involved in glycolysis pathway. The presence and relative abundance of 4 selected differentially abundant proteins (liprin-α1, fascin, DAP5, and β-arrestin-1) were quantified and validated by immunohistochemistry. In conclusion, unlike in vitro cell culture models, the in vivo signaling proteins and pathways that we have identified directly from human breast cancer tissues may serve as relevant therapeutic targets for the pharmacological intervention of breast cancer.

Dataset Information

Breast Cancer Proteomics - Differences in Protein Expression between Estrogen Receptor-Positive and -Negative Tumors Identified by Tandem Mass Tag Technology.

Publications

Breast Cancer Proteomics - Differences in Protein Expression between Estrogen Receptor-Positive and -Negative Tumors Identified by Tandem Mass Tag Technology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets