首页> 外文期刊>World Journal of Surgery: Official Journal of the Societe Internationale de Chirurgie, Collegium Internationale Chirurgiae Digestivae, and of the International Association of Endocrine Surgeons >Generalized Multifactor Dimensionality Reduction (GMDR) Analysis of Drug-Metabolizing Enzyme-Encoding Gene Polymorphisms may Predict Treatment Outcomes in Indian Breast Cancer Patients
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Generalized Multifactor Dimensionality Reduction (GMDR) Analysis of Drug-Metabolizing Enzyme-Encoding Gene Polymorphisms may Predict Treatment Outcomes in Indian Breast Cancer Patients

机译:药物代谢酶编码基因多态性的广义多维度降维(GMDR)分析可预测印度乳腺癌患者的治疗结果

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摘要

Prediction of response and toxicity of chemotherapy can help personalize the treatment and choose effective yet non-toxic treatment regimen for a breast cancer patient. Interplay of variations in various drug-metabolizing enzyme (DME)-encoding genes results in variable response and toxicity of chemotherapeutic drugs. Generalized multi-analytical (GMDR) approach was used to determine the influence of the combination of variants of genes encoding phase 0 (SLC22A16); phase I (CYP450, NQO1); phase II (GSTs, MTHFR, UGT2B15); and phase III (ABCB1) DMEs along with confounding factors on the response and toxicity of chemotherapeutic drugs in breast cancer patients.
机译:化学疗法的反应和毒性的预测可以帮助个性化治疗,并为乳腺癌患者选择有效而无毒的治疗方案。各种药物代谢酶(DME)编码基因中的变异相互作用会导致化学治疗药物的应答和毒性发生变化。使用广义多分析(GMDR)方法确定编码0期的基因(SLC22A16)的变体组合的影响;第一阶段(CYP450,NQO1);第二阶段(GST,MTHFR,UGT2B15);和III期(ABCB1)DME以及影响乳腺癌患者化疗药物反应和毒性的混杂因素。

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