PO.ET07.02 · 实验与分子治疗
用于个体化癌症治疗的药物遗传学检测
Pharmacogenetic assays for personalized cancer treatment
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
药物基因组学正日益应用于医学的各个领域，用于个体化药物选择和剂量确定。然而，由于报销和实用性方面的限制，大型药物基因组学面板的成本对于某些医疗实践而言可能过于高昂。目前作为服务提供的较小型、针对癌症治疗的药物遗传学面板仅提供有限数量的基因靶点，且不包括在已发表研究中与特定抗癌药物不良反应相关的重要HLA等位基因（注意本工作不确立诊断能力）。我们评估了开发一种针对抗癌药物相关基因的靶向药物遗传学检测的可行性，该检测在常用面板未涵盖的其他关键基因靶点之外还包括HLA。给定反应混合物中单个qPCR反应的数量被称为复合水平（plex level）。标准基因分型检测设计为2重（2-plex）混合物，以单个qPCR板上每样本多个反应的阵列形式提供。提高qPCR复合水平可减少每样本所需的反应数量，从而可能降低运营成本、降低操作者错误率并改善药物遗传学检测的周转时间。我们评估了在靶向药物遗传学面板中实施最大化多重化的可行性。我们已设计50个单独的qPCR检测，并将多重混合物优化为不到8个单独的反应。我们的检测靶点包括HLA-A、HLA-B、HLA-DRB1、HLA-DQA1、UGT1A1、DPYD和CYP2C9中的单核苷酸多态性（SNP）。基于多篇发表文献，这些基因中的某些多态性与特定抗癌药物不良反应风险的增加相关。我们新的数据分析方法可从标准qPCR仪器上进行的高达9重（9-plex）的qPCR反应中推导基因分型结果。检测使用合成DNA与人类DNA样本的组合进行测试，样本来自Terasaki收藏的经充分表征的DNA样本以及Coriell资源库。我们的多重反应包括在单个反应中检测HLA和非HLA等位基因的检测，采用标准qPCR染料（即ABY、JUN等）以及FRET和长斯托克斯位移染料的组合。此类药物遗传学面板的未来开发可能有助于精准医学的进一步发展。
查看英文原文 English abstract
Pharmacogenomics is increasingly utilized in various areas of medicine for personalization of drug selection and dosing. Nevertheless, the cost of large pharmacogenomic panels may be prohibitive for some practices due to reimbursement and utility limitations. Smaller, cancer treatment-specific pharmacogenetic panels that are currently available as services provide a limited number of gene targets and do not include important HLA alleles associated in published studies with adverse effects for specific cancer drugs (note that this work does not establish diagnostic capability). We evaluated the feasibility of developing a targeted pharmacogenetic test for cancer related drugs, which includes HLA along with other critical gene targets not captured by commonly available panels. The number of individual qPCR reactions in a given reaction mix is known as the plex level. Standard genotyping assays are designed as 2-plex mixtures, which are provided as an array of multiple reactions per sample present on a single qPCR plate. Increasing the qPCR plex level reduces the number of reactions required per sample, potentially reducing operational cost, reducing operator error rates and improving turn-around time for pharmacogenetic testing. We evaluated the feasibility of implementing maximal multiplexing in our targeted pharmacogenetic panel. We have designed 50 individual qPCR assays and optimized multiplex mixes into fewer than 8 individual reactions. Our assay targets include single nucleotide polymorphisms (SNPs) in HLA-A, HLA-B, HLA-DRB1, HLA-DQA1, UGT1A1, DPYD and CYP2C9. Based on multiple publications, certain polymorphisms in these genes are associated with increased risk of adverse effects for specific cancer drugs. Our new data analysis method allows derivation of genotyping results from up to 9-plex qPCR reactions performed on a standard qPCR instrument. Assays were tested using a combination of synthetic DNAs and human DNA samples, from Terasaki collection of well-characterized DNA samples and the Coriell repository. Our multiplex reactions included assays for detection of HLA and non-HLA alleles in single reactions using a combination of standard qPCR dyes (i.e; ABY, JUN, etc.) as well as FRET and long-stoke shift dyes. Future development of such pharmacogenetic panels may contribute to further advancement in precision medicine.
利益披露 Disclosure
A. Chadha, None..
J. Law, None..
Z. Wang, None..
M. Mamroth, None..
Z. Shen, None..
K. B. Mullah, None..
A. Vlassov, None..
A. Chikova, None.