Glutathione, GlutathioneS-Transferase α and π, and Aldehyde Dehydrogenase Content in Relationship to Drug Resistance in Ovarian Cancer

Berno, Tamara; Hengstler, Jan G.; Dietrich, Britta; Henrich, Michael; Steinberg, Pablo; Weikel, W.; Meinert, Rolf; Kaina, Bernd; Oesch, Franz; Knapstein, P.

doi:10.1006/gyno.1996.4593

Cited by 46 publications

(37 citation statements)

References 18 publications

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“…Some of these enzymes (e.g., dihydropyrimidine dehydrogenase and thymidine phosphorylase) that regulate in pyrimidine metabolism have already been shown to play a prognostic role in ovarian cancer (26). Tanner et al have shown that aldehyde dehydrogenase is increased in low stage ovarian carcinomas compared with high-stage tumors (27). Nicholson-Guthrie et al have described increased g-aminobutyric acid levels in ovarian cancer patients (28).…”

Section: Discussionmentioning

confidence: 99%

Mass Spectrometry–Based Metabolic Profiling Reveals Different Metabolite Patterns in Invasive Ovarian Carcinomas and Ovarian Borderline Tumors

et al. 2006

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Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. We have used a metabolite profiling approach to test the hypothesis that quantitative signatures of primary metabolites can be used to characterize molecular changes in ovarian tumor tissues. Sixty-six invasive ovarian carcinomas and nine borderline tumors of the ovary were analyzed by gas chromatography/time-of-flight mass spectrometry (GC-TOF MS) using a novel contamination-free injector system. After automated mass spectral deconvolution, 291 metabolites were detected, of which 114 (39.1%) were annotated as known compounds. By t test statistics with P < 0.01, 51 metabolites were significantly different between borderline tumors and carcinomas, with a false discovery rate of 7.8%, estimated with repeated permutation analysis. Principal component analysis (PCA) revealed four principal components that were significantly different between both groups, with the highest significance found for the second component (P = 0.00000009). PCA as well as additional supervised predictive models allowed a separation of 88% of the borderline tumors from the carcinomas. Our study shows for the first time that large-scale metabolic profiling using GC-TOF MS is suitable for analysis of fresh frozen human tumor samples, and that there is a consistent and significant change in primary metabolism of ovarian tumors, which can be detected using multivariate statistical approaches. We conclude that metabolomics is a promising high-throughput, automated approach in addition to functional genomics and proteomics for analyses of molecular changes in malignant tumors. (Cancer Res 2006; 66(22): 10795-804)

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Section: Discussionmentioning

confidence: 99%

Mass Spectrometry–Based Metabolic Profiling Reveals Different Metabolite Patterns in Invasive Ovarian Carcinomas and Ovarian Borderline Tumors

et al. 2006

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“…In Table 3, we summarized published studies in which GSTP1-1 was determined in ovarian cancer tissue and related to the clinical outcomes of patients with EOC. Some researchers found a relationship between overexpression of GSTP1-1 in malignant ovarian tissue and poor prognosis or bad response to chemotherapy (8)(9)(10)(11)(12)(13), whereas others could not detect such an association (14)(15)(16)(17)(18)(19)(20)(21). These conflicting results might be explained by differences in techniques used to quantify GSTP1-1 (Table 3).…”

Section: Discussionmentioning

confidence: 99%

GSTP1-1 in Ovarian Cyst Fluid and Disease Outcome of Patients With Ovarian Cancer

Kolwijck

Zusterzeel

Roelofs

et al. 2009

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Detoxification enzymes, especially glutathione S-transferase P1-1 (GSTP1-1), have been implicated in resistance to platinum-based chemotherapy. We studied GSTP1-1 levels in ovarian cyst fluid (oCF), obtained during surgery before chemotherapy, of patients with epithelial ovarian cancer and clinical outcomes were correlated. GSTP1-1 was determined by ELISA in oCF of 56 patients with epithelial ovarian cancer and 109 noncancer controls (21 borderline and 88 benign ovarian tumors). Differences in median GSTP1-1 between clinicopathologic subgroups were studied using Mann-Whitney U and Kruskal Wallis tests. Differences in disease-free (DFS) and overall survival (OS) between groups were analyzed by applying Kaplan-Meyer estimates and log-rank tests. Univariate and multivariate analysis were done using Cox proportional hazard model. Significantly higher levels of GSTP1-1 were found in the oCF of malignant (median, 383; range, 10-32,695 ng/mL) compared with benign (median, 20; range, 0-1,128 ng/mL) ovarian tumors (P < 0.01). Significantly higher GSTP1-1 levels were found in patients with advanced International Federation of Gynaecologists and Obstetricians stage (P = 0.01), high-grade tumors (P = 0.44), and/or high levels of preoperative CA 125 (P = 0.01). Of patients who received chemotherapy (stage, ≥Ic; n = 30), high GSTP1-1 levels were significantly associated with a poor DFS and OS (log-rank P = 0.047 and P = 0.033, respectively). International Federation of Gynaecologists and Obstetricians stage was the only independent predictor for DFS. GSTP1-1 was the only independent predictor for OS. (Cancer Epidemiol Biomarkers Prev 2009;18(8):2176-81)

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“…This might be related to therapy efficacy, since expression of GST A1 in cell lines is associated with an increase in resistance to carboplatin and cyclophosphamide [33]. Increased expression of GST A1 in tumour tissue would mean enhanced inactivation of anticancer drugs that could result in treatment failure.…”

Section: Discussionmentioning

confidence: 99%

Drug metabolism-related genes as potential biomarkers: analysis of expression in normal and tumour breast tissue

Martínez

Kennedy

Doolan

et al. 2007

Breast Cancer Res Treat

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The complex role of drug metabolism-related enzymes and their possible influence in cancer development, treatment and outcome has not yet been completely elucidated. There is evidence that these enzymes can activate certain environmental procarcinogens to more toxic derivatives and thus a role has been proposed for them in carcinogenesis. The fact that they can also inactivate a number of chemotherapeutic drugs has raised the possibility of these enzymes influencing the sensitivity of tumour cells to anticancer agents. In this report, we analyse the expression of drug metabolism-related genes within a whole genome microarray study of 104 breast cancer and 17 normal breast specimens. Kaplan-Meier survival curves, Chi-squared, and Cox Regression analyses were used to identify associations between expression of gene transcripts and patients' clinicopathological and survival data. Our results show that several of these genes are significantly expressed in both normal and tumour tissue; in many cases, expression is altered in the tumour specimens as compared to normal breast tissue. Moreover, expression of ARNT2 and GST A1 was correlated with prognosis. Kaplan-Meier analysis showed expression of ARNT2 mRNA to correlate significantly with favourable disease outcome for patients, in terms of both their disease-free survival (P = 0.0094) and overall survival (P = 0.0018) times from diagnosis, while detection of GST A1 mRNA correlated with shortened disease-free survival (P = 0.0131) and overall survival (P = 0.0028). Multivariate analysis indicated GST A1 expression to be an independent prognostic factor for overall survival (P = 0.045). Our results suggest a possible use of ARNT2 and GST A1 as prognostic breast cancer biomarkers.

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Glutathione, GlutathioneS-Transferase α and π, and Aldehyde Dehydrogenase Content in Relationship to Drug Resistance in Ovarian Cancer

Cited by 46 publications

References 18 publications

Mass Spectrometry–Based Metabolic Profiling Reveals Different Metabolite Patterns in Invasive Ovarian Carcinomas and Ovarian Borderline Tumors

Mass Spectrometry–Based Metabolic Profiling Reveals Different Metabolite Patterns in Invasive Ovarian Carcinomas and Ovarian Borderline Tumors

GSTP1-1 in Ovarian Cyst Fluid and Disease Outcome of Patients With Ovarian Cancer

Drug metabolism-related genes as potential biomarkers: analysis of expression in normal and tumour breast tissue

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