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Genoproteomic mining of urothelial cancer suggests {gamma}-glutamyl hydrolase and diazepam-binding inhibitor as putative urinary markers of outcome after chemotherapy.

ABSTRACT: Urinary biomarkers for the detection of bladder cancer have been developed, but no similar markers exist for prediction of clinical outcomes after receiving chemotherapy. Here we evaluate an approach that combines genomic, proteomic, and therapeutic outcome datasets to identify novel putative urinary biomarkers of clinical outcome after neoadjuvant methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC). Using this method, we identified gamma-glutamyl hydrolase (GGH), emmprin, survivin, and diazepam-binding inhibitor (DBI). Interestingly, GGH is a protein associated with methotrexate resistance, whereas emmprin, survivin, and DBI had been previously identified as predictors of outcome after platinum-containing chemotherapeutic regimens when assessed on tumor tissue. Using disease-free survival as a marker for clinical outcome, we evaluated the ability of GGH, emmprin, survivin, and DBI expression in tumor tissue to stratify 27 patients treated with neoadjuvant MVAC. DBI (P = 0.046) but not GGH (P = 0.190), emmprin (P = 0.066), or survivin (P = 0.393) successfully stratified patients. When GGH was used with DBI the significance of stratification improved (P = 0.024), whereas the addition of survivin or emmprin to this latter two-gene model reduced its significance (P = 0.036 and P = 0.040, respectively). Although these predictive results were obtained on tumor tissues, the presence of GGH and DBI in urine serves as a rationale for developing them as urinary markers of clinical outcomes for patients treated with neoadjuvant MVAC.

SUBMITTER: Pollard C

PROVIDER: S-EPMC2774049 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature

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Genoproteomic mining of urothelial cancer suggests {gamma}-glutamyl hydrolase and diazepam-binding inhibitor as putative urinary markers of outcome after chemotherapy.

Pollard Courtney C Nitz Matt M Baras Alex A Williams Paul P Moskaluk Christopher C Theodorescu Dan D

The American journal of pathology 20091008 5

Urinary biomarkers for the detection of bladder cancer have been developed, but no similar markers exist for prediction of clinical outcomes after receiving chemotherapy. Here we evaluate an approach that combines genomic, proteomic, and therapeutic outcome datasets to identify novel putative urinary biomarkers of clinical outcome after neoadjuvant methotrexate, vinblastine, doxorubicin, and cisplatin (MVAC). Using this method, we identified gamma-glutamyl hydrolase (GGH), emmprin, survivin, and ...[more]

PMID: 19815704

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Project description:The role of glutathione (GSH) in eukaryotic cells is well known. The biosynthesis of this γ-glutamine tripeptide is well studied. However, other γ-glutamyl peptides were found in various sources, and the pathways of their formation were not always clear. The aim of the present study was to determine whether Saccharomyces cerevisiae can produce γ-glutamyl tripeptides other than GSH and to identify the pathways associated with the formation of these peptides. The tripeptide γ-Glu-Val-Gly (γ-EVG) was used as a model. Wild-type yeast cells were shown to produce this peptide during cultivation in minimal synthetic medium. Two different biosynthetic pathways for this peptide were identified. The first pathway consisted of two steps. In the first step, γ-Glu-Val (γ-EV) was produced from glutamate and valine by the glutamate-cysteine ligase (GCL) Gsh1p or by the transfer of the γ-glutamyl group from GSH to valine by the γ-glutamyltransferase (GGT) Ecm38p or by the (Dug2p-Dug3p)2 complex. In the next step, γ-EV was combined with glycine by the glutathione synthetase (GS) Gsh2p. The second pathway consisted of transfer of the γ-glutamyl residue from GSH to the dipeptide Val-Gly (VG). This reaction was carried out mainly by the (Dug2p-Dug3p)2 complex, whereas the GGT Ecm38p did not participate in this reaction. The contribution of each of these two pathways to the intracellular pool of γ-EVG was dependent on cultivation conditions. In this work, we also found that Dug1p, previously identified as a Cys-Gly dipeptidase, played an essential role in the hydrolysis of the dipeptide VG in yeast cells. It was also demonstrated that γ-EV and γ-EVG could be effectively imported from the medium and that γ-EVG was imported by Opt1p, known to be a GSH importer. Our results demonstrated that γ-glutamyl peptides, particularly γ-EVG, are produced in yeast as products of several physiologically important reactions and are therefore natural components of yeast cells.

Project description:BackgroundMetabolic reprogramming is a feature of cancer. However, colon cancer subtypes based on the glycolysis‒cholesterol synthesis axis have not been identified, and little is known about connections between metabolic features and the tumor microenvironment.MethodsData for 430 colon cancer cases were extracted from The Cancer Genome Atlas, including transcriptome data, clinical information, and survival outcomes. Glycolysis and cholesterol synthesis-related gene sets were obtained from the Molecular Signatures Database for a gene set variation analysis. The relationship between the genomic landscape and immune landscape were investigated among four metabolic subtypes. Hub genes were determined. The clinical significance of candidate hub gene was evaluated in 264 clinical samples and potential functions were validated in vitro and in vivo.ResultsColon cancer cases were clustered into four metabolic subtypes: quiescent, glycolytic, cholesterogenic, and mixed. The metabolic subtypes differed with respect to the immune score, stromal score, and estimate score using the ESTIMATE algorithm, cancer-immunity cycle, immunomodulator signatures, and signatures of immunotherapy responses. Patients in the cholesterogenic group had better survival outcomes than those for other subtypes, especially glycolytic. The glycolytic subtype was related to unfavorable clinical characteristics, including high mutation rates in TTN, APC, and TP53, high mutation burden, vascular invasion, right colon cancer, and low-frequency microsatellite instability. GGH, CACNG4, MME, SLC30A2, CKMT2, SYN3, and SLC22A31 were identified as differentially expressed both in glycolytic-cholesterogenic subgroups as well as between colon cancers and healthy samples, and were involved in glycolysis‒cholesterol synthesis. GGH was upregulated in colon cancer; its high expression was correlated with CD4+ T cell infiltration and longer overall survival and it was identified as a favorable independent prognostic factor. The overexpression of GGH in colon cancer-derived cell lines (SW48 and SW480) inhibited PKM, GLUT1, and LDHA expression and decreased the extracellular lactate content and intracellular ATP level. The opposite effects were obtained by GGH silencing. The phenotype associated with GGH was also validated in a xenograft nude mouse model.ConclusionsOur results provide insight into the connection between metabolism and the tumor microenvironment in colon cancer and provides preliminary evidence for the role of GGH, providing a basis for subsequent studies.

Dataset Information

Genoproteomic mining of urothelial cancer suggests {gamma}-glutamyl hydrolase and diazepam-binding inhibitor as putative urinary markers of outcome after chemotherapy.

Publications

Genoproteomic mining of urothelial cancer suggests {gamma}-glutamyl hydrolase and diazepam-binding inhibitor as putative urinary markers of outcome after chemotherapy.

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