Suppr超能文献

遗传和非遗传因素作为淋巴母细胞系药物表型的变量。

Heritable and non-genetic factors as variables of pharmacologic phenotypes in lymphoblastoid cell lines.

机构信息

Department of Human Genetics, University of Chicago, Chicago, IL, USA.

出版信息

Pharmacogenomics J. 2010 Dec;10(6):505-12. doi: 10.1038/tpj.2010.3. Epub 2010 Feb 9.

Abstract

Publicly available genetic and expression data on lymphoblastoid cell lines (LCLs) make them a unique resource for understanding the genetic underpinnings of pharmacological outcomes and disease. LCLs have been used for pharmacogenomic discovery and validation of clinical findings associated with drug response. However, variation in cellular growth rate, baseline Epstein-Barr virus (EBV) copy number and ATP levels can all be confounders in such studies. Our objective is to better define confounding variables that affect pharmacological end points in LCLs. To this end, we evaluated the effect of these three variables on drug-induced cytotoxicity in LCLs. The drugs evaluated included daunorubicin, etoposide, carboplatin, cisplatin, cytarabine, pemetrexed, 5'-deoxyfluorouridine, vorinostat, methotrexate, 6-mercaptopurine, and 5-fluorouracil. Baseline ATP or EBV copy number were not significantly correlated with cellular growth rate or drug-induced cytotoxicity. In contrast, cellular growth rate and drug-induced cytotoxicity were significantly, directly related for all drugs except vorinostat. Importantly, cellular growth rate is under appreciable genetic influence (h²=0.30-0.39) with five suggestive linkage regions across the genome. Not surprisingly, a percentage of SNPs that significantly associate with drug-induced cytotoxicity also associate with cellular growth rate (P ≤ 0.0001). Studies using LCLs for pharmacologic outcomes should therefore consider that a portion of the genetic variation explaining drug-induced cytotoxicity is mediated via heritable effects on growth rate.

摘要

可供公开获取的淋巴母细胞系 (LCL) 的遗传和表达数据使它们成为理解药物反应相关的药理学结果和疾病遗传基础的独特资源。LCL 已被用于药物基因组学发现和验证与药物反应相关的临床发现。然而,细胞生长速率、基线 EBV 拷贝数和 ATP 水平的差异都可能是这些研究中的混杂因素。我们的目标是更好地定义影响 LCL 中药物作用终点的混杂变量。为此,我们评估了这三个变量对 LCL 中药物诱导的细胞毒性的影响。评估的药物包括柔红霉素、依托泊苷、卡铂、顺铂、阿糖胞苷、培美曲塞、5'-去氧氟尿苷、伏立诺他、甲氨蝶呤、6-巯基嘌呤和 5-氟尿嘧啶。基线 ATP 或 EBV 拷贝数与细胞生长速率或药物诱导的细胞毒性无显著相关性。相比之下,除了伏立诺他,细胞生长速率和药物诱导的细胞毒性与所有药物均呈显著正相关。重要的是,细胞生长速率受到明显的遗传影响(h²=0.30-0.39),基因组中有五个提示性连锁区域。毫不奇怪,与药物诱导的细胞毒性显著相关的 SNP 中有一部分也与细胞生长速率相关(P≤0.0001)。因此,使用 LCL 进行药理学研究时,应考虑到解释药物诱导的细胞毒性的遗传变异的一部分是通过对生长速率的遗传影响介导的。

相似文献

1
Heritable and non-genetic factors as variables of pharmacologic phenotypes in lymphoblastoid cell lines.
Pharmacogenomics J. 2010 Dec;10(6):505-12. doi: 10.1038/tpj.2010.3. Epub 2010 Feb 9.
2
Chemotherapeutic-induced apoptosis: a phenotype for pharmacogenomics studies.
Pharmacogenet Genomics. 2011 Aug;21(8):476-88. doi: 10.1097/FPC.0b013e3283481967.
3
Host genetic variants and gene expression patterns associated with Epstein-Barr virus copy number in lymphoblastoid cell lines.
PLoS One. 2014 Oct 7;9(10):e108384. doi: 10.1371/journal.pone.0108384. eCollection 2014.
4
RNA Sequencing Analyses of Gene Expression during Epstein-Barr Virus Infection of Primary B Lymphocytes.
J Virol. 2019 Jun 14;93(13). doi: 10.1128/JVI.00226-19. Print 2019 Jul 1.
5
Lymphoblastoid cell lines in pharmacogenomic discovery and clinical translation.
Pharmacogenomics. 2012 Jan;13(1):55-70. doi: 10.2217/pgs.11.121.
6
Copy number increase of 1p36.33 and mitochondrial genome amplification in Epstein-Barr virus-transformed lymphoblastoid cell lines.
Cancer Genet Cytogenet. 2007 Mar;173(2):122-30. doi: 10.1016/j.cancergencyto.2006.10.010.
7
Copy number polymorphisms and anticancer pharmacogenomics.
Genome Biol. 2011;12(5):R46. doi: 10.1186/gb-2011-12-5-r46. Epub 2011 May 25.
8
Use of CEPH and non-CEPH lymphoblast cell lines in pharmacogenetic studies.
Pharmacogenomics. 2005 Apr;6(3):303-10. doi: 10.1517/14622416.6.3.303.
10
Human lymphoblastoid cell line panels: novel tools for assessing shared drug pathways.
Pharmacogenomics. 2010 Mar;11(3):327-40. doi: 10.2217/pgs.10.27.

引用本文的文献

3
The influence of Neanderthal alleles on cytotoxic response.
PeerJ. 2018 Oct 23;6:e5691. doi: 10.7717/peerj.5691. eCollection 2018.
4
Pharmacogenetics of Chemotherapy-Induced Cardiotoxicity.
Curr Oncol Rep. 2018 Apr 30;20(7):52. doi: 10.1007/s11912-018-0696-8.
6
Human iPSC-derived neurons and lymphoblastoid cells for personalized medicine research in neuropsychiatric disorders.
Dialogues Clin Neurosci. 2016 Sep;18(3):267-276. doi: 10.31887/DCNS.2016.18.3/dgurwitz.
7
Molecular insight into thiopurine resistance: transcriptomic signature in lymphoblastoid cell lines.
Genome Med. 2015 Apr 18;7(1):37. doi: 10.1186/s13073-015-0150-6. eCollection 2015.
8
Reprogramming LCLs to iPSCs Results in Recovery of Donor-Specific Gene Expression Signature.
PLoS Genet. 2015 May 7;11(5):e1005216. doi: 10.1371/journal.pgen.1005216. eCollection 2015 May.
9
MicroRNA biogenesis and cellular proliferation.
Transl Res. 2015 Aug;166(2):145-51. doi: 10.1016/j.trsl.2015.01.012. Epub 2015 Feb 7.
10
Population-based in vitro hazard and concentration-response assessment of chemicals: the 1000 genomes high-throughput screening study.
Environ Health Perspect. 2015 May;123(5):458-66. doi: 10.1289/ehp.1408775. Epub 2015 Jan 13.

本文引用的文献

1
Pharmacogenomic discovery using cell-based models.
Pharmacol Rev. 2009 Dec;61(4):413-29. doi: 10.1124/pr.109.001461.
2
Whole-genome approach implicates CD44 in cellular resistance to carboplatin.
Hum Genomics. 2009 Jan;3(2):128-42. doi: 10.1186/1479-7364-3-2-128.
3
Population-specific genetic variants important in susceptibility to cytarabine arabinoside cytotoxicity.
Blood. 2009 Mar 5;113(10):2145-53. doi: 10.1182/blood-2008-05-154302. Epub 2008 Dec 24.
4
Identification of genomic regions contributing to etoposide-induced cytotoxicity.
Hum Genet. 2009 Mar;125(2):173-80. doi: 10.1007/s00439-008-0607-4. Epub 2008 Dec 17.
5
Genetic analysis of human traits in vitro: drug response and gene expression in lymphoblastoid cell lines.
PLoS Genet. 2008 Nov;4(11):e1000287. doi: 10.1371/journal.pgen.1000287. Epub 2008 Nov 28.
6
Gemcitabine and cytosine arabinoside cytotoxicity: association with lymphoblastoid cell expression.
Cancer Res. 2008 Sep 1;68(17):7050-8. doi: 10.1158/0008-5472.CAN-08-0405.
7
Evaluation of genetic variation contributing to differences in gene expression between populations.
Am J Hum Genet. 2008 Mar;82(3):631-40. doi: 10.1016/j.ajhg.2007.12.015. Epub 2008 Feb 28.
8
Susceptibility loci involved in cisplatin-induced cytotoxicity and apoptosis.
Pharmacogenet Genomics. 2008 Mar;18(3):253-62. doi: 10.1097/FPC.0b013e3282f5e605.
9
A genome-wide association study of global gene expression.
Nat Genet. 2007 Oct;39(10):1202-7. doi: 10.1038/ng2109. Epub 2007 Sep 16.
10
Population genomics of human gene expression.
Nat Genet. 2007 Oct;39(10):1217-24. doi: 10.1038/ng2142. Epub 2007 Sep 16.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验