Dataset Information

MRP2 and GSTP1 polymorphisms and chemotherapy response in advanced non-small cell lung cancer.

ABSTRACT:

Purpose

The level of drug metabolism and drug transport is correlated with the sensitivity of cancer cells towards platinum-based chemotherapy. We hypothesize that genetic polymorphisms in metabolising enzymes gene GSTP1 (glutathione S-transferase P1), and MRP2 (multidrug resistance-associated protein 2) (ABCC2), which result in inter-individual differences in metabolism and drug disposition, may predict clinical response to platinum agents in advanced non-small cell lung cancer (NSCLC) patients.

Methods

Totally 113 patients with advanced NSCLC were routinely treated with platinum-based chemotherapy, and clinical response was evaluated after four cycles. MRP2 C-24T (-24C>T), MRP2 Val417Ile (1249G>A), MRP2 Ile1324Ile (3972C>T), and GSTP1 Ile105Val (342A>G) genotype were determined by gene-chip method (a 3-D (three dimensions) polyacrylamide gel-based DNA microarray method) using DNA samples isolated from peripheral blood collected before treatment. Pearson Chi-square test and Fisher's exact test were performed to measure the differences of the chemotherapeutic efficacy among variant genotype. The odds ratios and 95% confidence intervals were computed by logistic regression.

Results

The C-->T change of MRP2 C-24T and the A-->G change of GSTP1 Ile105Val polymorphism significantly increased platinum-based chemotherapy response.

Conclusion

The polymorphic status of MRP2 C-24T and GSTP1 Ile105Val might be the predictive markers for the treatment response of advanced NSCLC patients. The DNA microarray-based method is accurate, high throughput and inexpensive, suitable for single-nucleotide polymorphism genotyping in a large number of individuals.

SUBMITTER: Sun N

PROVIDER: S-EPMC2797421 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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Publications

MRP2 and GSTP1 polymorphisms and chemotherapy response in advanced non-small cell lung cancer.

Sun Ning N Sun Xinchen X Chen Baoan B Cheng Hongyan H Feng Jifeng J Cheng Lu L Lu Zuhong Z

Cancer chemotherapy and pharmacology 20090701 3

<h4>Purpose</h4>The level of drug metabolism and drug transport is correlated with the sensitivity of cancer cells towards platinum-based chemotherapy. We hypothesize that genetic polymorphisms in metabolising enzymes gene GSTP1 (glutathione S-transferase P1), and MRP2 (multidrug resistance-associated protein 2) (ABCC2), which result in inter-individual differences in metabolism and drug disposition, may predict clinical response to platinum agents in advanced non-small cell lung cancer (NSCLC) ...[more]

PMID: 19568750

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Project description:We developed a computational platform including machine learning and a mechanistic mathematical model to find the optimal protocol for administration of platinum-doublet chemotherapy in a palliative setting. The platform has been applied to advanced metastatic non-small cell lung cancer (NSCLC). The 42 NSCLC patients treated with palliative intent at Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, were collected from a retrospective cohort of patients diagnosed in 2004-2014. Patients were followed-up, for three years. Clinical data collected include complete information about the clinical course of the patients including treatment schedule, response according to RECIST classification, and survival. The core of the platform is the mathematical model, in the form of a system of ordinary differential equations, describing dynamics of platinum-sensitive and platinum-resistant cancer cells and interactions reflecting competition for space and resources. The model is simulated stochastically by sampling the parameter values from a joint probability distribution function. The machine learning model is applied to calibrate the mathematical model and to fit it to the overall survival curve. The model simulations faithfully reproduce the clinical cohort at three levels long-term response (OS), the initial response (according to RECIST criteria), and the relationship between the number of chemotherapy cycles and time between two consecutive chemotherapy cycles. In addition, we investigated the relationship between initial and long-term response. We showed that those two variables do not correlate which means that we cannot predict patient survival solely based on the initial response. We also tested several chemotherapy schedules to find the best one for patients treated with palliative intent. We found that the optimal treatment schedule depends, among others, on the strength of competition among various subclones in a tumor. The computational platform developed allows optimizing chemotherapy protocols, within admissible limits of toxicity, for palliative treatment of metastatic NSCLC. The simplicity of the method allows its application to chemotherapy optimization in different cancers.

Dataset Information

MRP2 and GSTP1 polymorphisms and chemotherapy response in advanced non-small cell lung cancer.

Purpose

Methods

Results

Conclusion

Publications

MRP2 and GSTP1 polymorphisms and chemotherapy response in advanced non-small cell lung cancer.

Similar Datasets

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