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利用大型合作组试验得出的 GWAS 数据评估乳腺癌患者接受紫杉烷类药物引起的周围神经病变(TIPN)的风险:第 2 部分-与乳腺癌患者 TIPN 风险相关的 SNP 簇的功能意义。

Leveraging GWAS data derived from a large cooperative group trial to assess the risk of taxane-induced peripheral neuropathy (TIPN) in patients being treated for breast cancer: Part 2-functional implications of a SNP cluster associated with TIPN risk in patients being treated for breast cancer.

机构信息

Yale University, School of Medicine, New Haven, CT, USA.

Harvard School of Dental Medicine, Boston, MA, USA.

出版信息

Support Care Cancer. 2023 Feb 21;31(3):178. doi: 10.1007/s00520-023-07617-6.

Abstract

INTRODUCTION

Using GWAS data derived from a large collaborative trial (ECOG-5103), we identified a cluster of 267 SNPs which predicted CIPN in treatment-naive patients as reported in Part 1 of this study. To assess the functional and pathological implications of this set, we identified collective gene signatures were and evaluated the informational value of those signatures in defining CIPN's pathogenesis.

METHODS

In Part 1, we analyzed GWAS data derived from ECOG-5103, first identifying those SNPs that were most strongly associated with CIPN using Fisher's ratio. After identifying those SNPs which differentiated CIPN-positive from CIPN-negative phenotypes, we ranked them in order of their discriminatory power to produce a cluster of SNPs which provided the highest predictive accuracy using leave-one-out cross validation (LOOCV). An uncertainty analysis was included. Using the best predictive SNP cluster, we performed gene attribution for each SNP using NCBI Phenotype Genotype Integrator and then assessed functionality by applying GeneAnalytics, Gene Set Enrichment Analysis, and PCViz.

RESULTS

Using aggregate data derived from the GWAS, we identified a 267 SNP cluster which was associated with a CIPN+ phenotype with an accuracy of 96.1%. We could attribute 173 genes to the 267 SNP cluster. Six long intergenic non-protein coding genes were excluded. Ultimately, the functional analysis was based on 138 genes. Of the 17 pathways identified by Gene Analytics (GA) software, the irinotecan pharmacokinetic pathway had the highest score. Highly matching gene ontology attributions included flavone metabolic process, flavonoid glucuronidation, xenobiotic glucuronidation, nervous system development, UDP glycosyltransferase activity, retinoic acid binding, protein kinase C binding, and glucoronosyl transferase activity. Gene Set Enrichment Analysis (GSEA) GO terms identified neuron-associated genes as most significant (p = 5.45e-10). Consistent with the GA's output, flavone, and flavonoid associated terms, glucuronidation were noted as were GO terms associated with neurogenesis.

CONCLUSION

The application of functional analyses to phenotype-associated SNP clusters provides an independent validation step in assessing the clinical meaningfulness of GWAS-derived data. Functional analyses following gene attribution of a CIPN-predictive SNP cluster identified pathways, gene ontology terms, and a network which were consistent with a neuropathic phenotype.

摘要

简介

利用来自大型合作试验(ECOG-5103)的 GWAS 数据,我们在本研究的第一部分报告了一组 267 个 SNP,这些 SNP 可预测未经治疗的患者出现 CIPN。为了评估该集合的功能和病理意义,我们确定了共同的基因特征,并评估了这些特征在定义 CIPN 发病机制方面的信息价值。

方法

在第一部分中,我们分析了来自 ECOG-5103 的 GWAS 数据,首先使用 Fisher 比确定与 CIPN 最密切相关的那些 SNP。在确定区分 CIPN 阳性和 CIPN 阴性表型的 SNP 后,我们按其区分能力对其进行排序,以生成使用留一法交叉验证(LOOCV)产生最高预测准确性的 SNP 簇。包含不确定性分析。使用最佳预测 SNP 簇,我们使用 NCBI 表型基因型整合器对每个 SNP 进行基因归因,然后使用 GeneAnalytics、基因集富集分析和 PCViz 评估功能。

结果

使用来自 GWAS 的汇总数据,我们确定了一个与 CIPN+表型相关的 267 SNP 簇,其准确性为 96.1%。我们可以将 173 个基因归因于 267 SNP 簇。排除了 6 个长的非蛋白编码基因。最终,功能分析基于 138 个基因。在 Gene Analytics(GA)软件识别的 17 条途径中,伊立替康药代动力学途径的得分最高。高度匹配的基因本体论归因包括黄酮类代谢过程、黄酮类葡萄糖醛酸化、外源物葡萄糖醛酸化、神经系统发育、UDP 糖基转移酶活性、视黄酸结合、蛋白激酶 C 结合和葡萄糖醛酸转移酶活性。基因集富集分析(GSEA)GO 术语确定与神经元相关的基因最为显著(p=5.45e-10)。与 GA 的输出一致,注意到黄酮类和类黄酮相关术语以及与神经发生相关的 GO 术语。

结论

对与表型相关的 SNP 簇进行功能分析为评估 GWAS 衍生数据的临床意义提供了一个独立的验证步骤。对 CIPN 预测 SNP 簇进行基因归因后的功能分析确定了与神经病变表型一致的途径、基因本体论术语和网络。

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