Glutathione S-transferase P1 (GSTP1) directly influences platinum drug chemosensitivity in ovarian tumour cell lines.

BACKGROUND: Chemotherapy response in ovarian cancer patients is frequently compromised by drug resistance, possibly due to altered drug metabolism. Platinum drugs are metabolised by glutathione S-transferase P1 (GSTP1), which is abundantly, but variably expressed in ovarian tumours. We have created novel ovarian tumour cell line models to investigate the extent to which differential GSTP1 expression influences chemosensitivity. METHODS: Glutathione S-transferase P1 was stably deleted in A2780 and expression significantly reduced in cisplatin-resistant A2780DPP cells using Mission shRNA constructs, and MTT assays used to compare chemosensitivity to chemotherapy drugs used to treat ovarian cancer. Differentially expressed genes in GSTP1 knockdown cells were identified by Illumina HT-12 expression arrays and qRT-PCR analysis, and altered pathways predicted by MetaCore (GeneGo) analysis. Cell cycle changes were assessed by FACS analysis of PI-labelled cells and invasion and migration compared in quantitative Boyden chamber-based assays. RESULTS: Glutathione S-transferase P1 knockdown selectively influenced cisplatin and carboplatin chemosensitivity (2.3- and 4.83-fold change in IC50, respectively). Cell cycle progression was unaffected, but cell invasion and migration was significantly reduced. We identified several novel GSTP1 target genes and candidate platinum chemotherapy response biomarkers. CONCLUSIONS: Glutathione S-transferase P1 has an important role in cisplatin and carboplatin metabolism in ovarian cancer cells. Inter-tumour differences in GSTP1 expression may therefore influence response to platinum-based chemotherapy in ovarian cancer patients.

Cofactor infections and HIV epidemics in developing countries: implications for treatment.

This article shows that the burden of certain tropical disease infections, after controlling for other factors, is positively correlated with HIV prevalence. Using cross-national data and multivariate linear regression analysis, we investigate the determinants of HIV prevalence in low- and middle-income countries. We begin with social and economic variables used in other cross-national studies and then incorporate data on parasitic and infectious diseases endemic in poor populations, which are found to be strongly and significantly correlated with--and are potent predictors of--HIV prevalence. The paper concludes by arguing that treating tropical diseases may be a cost-effective add-on to HIV-prevention and -treatment programs, thus slowing the spread of HIV in disease-burdened populations.