Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UNIPROT:P80404 (GABA transaminase)
 786 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Breast-cancer subtypes present with distinct clinical characteristics. Therefore, characterization of subtype-specific proteins may augment the development of targeted therapies and prognostic biomarkers. To address this issue, MS-based secretome analysis of eight breast cancer cell lines, corresponding to the three main breast cancer subtypes was performed. More than 5200 non-redundant proteins were identified with 23, four, and four proteins identified uniquely in basal, HER2-neu-amplified, and luminal breast cancer cells, respectively. An in silico mRNA analysis using publicly available breast cancer tissue microarray data was carried out as a preliminary verification step. In particular, the expression profiles of 15 out of 28 proteins included in the microarray (from a total of 31 in our subtype-specific signature) showed significant correlation with estrogen receptor (ER) expression. A MS-based analysis of breast cancer tissues was undertaken to verify the results at the proteome level. Eighteen out of 31 proteins were quantified in the proteomes of ER-positive and ER-negative breast cancer tissues. Survival analysis using microarray data was performed to examine the prognostic potential of these selected candidates. Three proteins correlated with ER status at both mRNA and protein levels: ABAT, PDZK1, and PTX3, with the former showing significant prognostic potential.
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PMID:Coupling proteomics and transcriptomics in the quest of subtype-specific proteins in breast cancer. 2338 93

Mass spectrometry and nuclear magnetic resonance-based metabolomics have been developed into mature technologies that can be utilized to analyze hundreds of biological samples in a high-throughput manner. Over the past few years, both technologies were utilized to analyze large cohorts of fresh frozen breast cancer tissues. Metabolite biomarkers were shown to separate breast cancer tissues from normal breast tissues with high sensitivity and specificity. Furthermore, the metabolome differed between hormone receptor positive (HR+) and hormone receptor negative (HR-) breast cancer, but was unchanged in HER2+ tumors compared to HER2- tumors. New metabolism-related biomarkers were discovered including the 4-aminobutyrate aminotransferase ABAT, where low mRNA expression led to an accumulation of beta-alanine and shortened relapse-free survival. The glutamate-to-glutamine ratio (GGR) represents another new biomarker that was increased in 88 % of HR- tumors and 56 % of HR+ tumors compared to normal breast tissues. The GGR might help to stratify patients for the treatment with specific glutaminase inhibitors that were recently developed and are currently being tested in phase I clinical studies. Surprisingly, 2-hydroxyglutarate (2-HG), initially found to accumulate in isocitrate dehydrogenase (IDH) mutated gliomas and leukemias and described as an oncometabolite, was detected to be drastically increased in several breast carcinomas in the absence of IDH mutations. In summary, metabolomics analysis of breast cancer tissues is a reliable method and has produced many new biological insights that may impact breast cancer diagnostics and treatment over the coming years.
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PMID:Tissue-Based Metabolomics to Analyze the Breast Cancer Metabolome. 2755 38