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GST 多态性对乳腺癌患者基于蒽环类药物化疗反应和毒性的药物遗传学影响:一种多分析方法。

Pharmacogenetic influence of GST polymorphisms on anthracycline-based chemotherapy responses and toxicity in breast cancer patients: a multi-analytical approach.

机构信息

Department of Genetics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Raebareli road, Lucknow, 226 014, India.

出版信息

Mol Diagn Ther. 2013 Dec;17(6):371-9. doi: 10.1007/s40291-013-0045-4.

Abstract

BACKGROUND AND OBJECTIVE

Chemotherapeutic drug treatment outcomes are genetically determined. Polymorphisms in genes encoding phase II drug metabolizing enzyme glutathione-S-transferase (GST) can possibly predict treatment outcomes, and can be of prognostic significance in breast cancer patients. The aim of this study was to determine the role of genetic variations in GST in predicting response to, and toxicity of, anthracycline-based chemotherapy in breast cancer patients.

METHOD

Two hundred and seven patients treated with anthracycline-based chemotherapy were genotyped for GSTM1 and GSTT1 deletion polymorphisms, and GSTP1 Ile105Val (rs1695), by polymerase chain reaction (PCR)/ PCR-restriction fragment length polymorphism (RFLP). Genetic variations were correlated with tumor response to neo-adjuvant chemotherapy (NACT) in 100 patients, and with chemo-toxicity in 207 who received adjuvant chemotherapy or NACT, using Chi-square and logistic regression. Higher order gene-gene interactions with treatment outcomes were characterized by multifactor dimensionality reduction (MDR) analysis.

RESULTS

In single-locus analysis, Ile/Val and Ile/Val+Val/Val genotypes of the GSTP1 Ile105Val (rs1695) polymorphism reached statistical significance with grade 2-4 anemia (P=0.019, P=0.027). On performing gene-gene interaction analysis, GSTM1 null-GSTP1 Ile/Val was significantly associated with response to NACT (P=0.032). On evaluating higher order gene-gene interaction models by MDR analysis, GSTM1 and GSTP1 Ile105Val; GSTM1 and GSTT1; and GSTT1 and GSTP1 Ile105Val showed significant association with treatment response, grade 2-4 anemia, and dose delay/reduction due to neutropenia (P=0.046, P=0.027, P=0.026), respectively.

CONCLUSION

Multi-analytical strategies may serve as a better tool for characterization of pharmacogenetic-based breast cancer treatment outcomes.

摘要

背景与目的

化疗药物的治疗效果是由基因决定的。编码Ⅱ相药物代谢酶谷胱甘肽-S-转移酶(GST)的基因多态性可能预测治疗效果,并可能对乳腺癌患者具有预后意义。本研究旨在确定 GST 基因多态性在预测乳腺癌患者接受基于蒽环类药物化疗的反应和毒性方面的作用。

方法

采用聚合酶链反应(PCR)/PCR 限制性片段长度多态性(RFLP)方法,对 207 例接受基于蒽环类药物化疗的患者进行 GSTM1 和 GSTT1 缺失多态性及 GSTP1 Ile105Val(rs1695)的基因分型。采用卡方检验和逻辑回归分析,将遗传变异与 100 例新辅助化疗(NACT)患者的肿瘤反应相关联,与 207 例接受辅助化疗或 NACT 的患者的化疗毒性相关联。采用多因素维度缩减(MDR)分析方法,对与治疗效果相关的更高阶基因-基因相互作用进行特征描述。

结果

在单基因座分析中,GSTP1 Ile105Val(rs1695)多态性的 Ile/Val 和 Ile/Val+Val/Val 基因型与 2-4 级贫血达到统计学显著性(P=0.019,P=0.027)。在进行基因-基因相互作用分析时,GSTM1 缺失-GSTP1 Ile/Val 与 NACT 反应显著相关(P=0.032)。通过 MDR 分析评价更高阶基因-基因相互作用模型,GSTM1 和 GSTP1 Ile105Val;GSTM1 和 GSTT1;以及 GSTT1 和 GSTP1 Ile105Val 与治疗反应、2-4 级贫血以及因中性粒细胞减少而导致的剂量延迟/减少显著相关(P=0.046,P=0.027,P=0.026)。

结论

多分析策略可能是一种更好的工具,用于描述基于遗传药理学的乳腺癌治疗效果。

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