Pharmacogenomic Discovery Using Cell-Based Models

Welsh, Marleen M.; Mangravite, Lara M.; Medina, Marisa W.; Tantisira, Kelan G.; Zhang, Wei; Huang, R. Stephanie; McLeod, Howard L.; Dolan, M. Eileen

doi:10.1124/pr.109.001461

Cited by 107 publications

(114 citation statements)

References 160 publications

(192 reference statements)

Supporting

Mentioning

112

Contrasting

Order By: Relevance

“…Using HapMap cell lines, several groups have identified genetic predictors of susceptibility to drug phenotypes including drug-induced cytotoxicity (1). As has been observed for most GWASs, SNPs within exons of obvious candidate genes, considered "smoking gun mutations," are not rising to the top of these analyses.…”

mentioning

confidence: 93%

“…Early pharmacogenetic discoveries were based on observations in clinical populations and were limited to phenotypes for which a single candidate gene variant had a large effect on drug activity (1). These types of studies have met with variable success and face inherent limitations because variation in response to most clinically administered drugs is likely to be dependent on the combined contribution of multiple genetic variations with moderate or small independent effects.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Chemotherapeutic drug susceptibility associated SNPs are enriched in expression quantitative trait loci

Gamazon¹,

Huang

Cox

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

108

109

View full text Add to dashboard Cite

Pharmacogenomics has employed candidate gene studies and, more recently, genome-wide association studies (GWAS) in efforts to identify loci associated with drug response and/or toxicity. The advantage of GWAS is the simultaneous, unbiased testing of millions of SNPs; the challenge is that functional information is absent for the vast majority of loci that are implicated. In the present study, we systematically evaluated SNPs associated with chemotherapeutic agent-induced cytotoxicity for six different anticancer agents and evaluated whether these SNPs were disproportionately likely to be within a functional class such as coding (consisting of missense, nonsense, or frameshift polymorphisms), noncoding (such as 3′UTRs or splice sites), or expression quantitative trait loci (eQTLs; indicating that a SNP genotype is associated with the transcript abundance level of a gene). We found that the chemotherapeutic drug susceptibility-associated SNPs are more likely to be eQTLs, and, in fact, more likely to be associated with the transcriptional expression level of multiple genes (n ≥ 10) as potential master regulators, than a random set of SNPs in the genome, conditional on minor allele frequency. Furthermore, we observed that this enrichment compared with random expectation is not present for other traditionally important coding and noncoding SNP functional categories. This research therefore has significant implications as a general approach for the identification of genetic predictors of drug response and provides important insights into the likely function of SNPs identified in GWAS analysis of pharmacologic studies.genome-wide association study | pharmacogenomics

show abstract

mentioning

confidence: 93%

mentioning

confidence: 99%

Chemotherapeutic drug susceptibility associated SNPs are enriched in expression quantitative trait loci

Gamazon¹,

Huang

Cox

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

108

109

View full text Add to dashboard Cite

show abstract

“…The public availability of these data reduces the cost of genetic mapping to only the cost of the drug response phenotyping. Welsh and colleagues provide a more detailed review of these and other resources in their 2009 review [10]. While many of the resources have evolved since this earlier review, the resources themselves are still commonly used.…”

Section: Advantages and Disadvantages Of The Lcl Model Advantagesmentioning

confidence: 99%

“…In addition to the large numbers of chemicals/drugs that can be tested, LCLs are also available from large populations of individuals. Clinical trials usually consist of hundreds of mostly unrelated individuals, LCLs allow for as many cell lines as experimentally and economically feasible while allowing for heritability estimations and association mapping from family-based study designs [10,14].…”

Section: Advantages and Disadvantages Of The Lcl Model Advantagesmentioning

confidence: 99%

Leveraging Lymphoblastoid Cell Lines for Drug Response Modeling

Motsinger‐Reif¹,

Rotroff²

2015

J Data Mining Genomics Proteomics

View full text Add to dashboard Cite

Lymphoblastoid cell lines (LCL) are becoming popular tools for modeling drug response. LCLs, and other in vitro assays, offer the ability to test many drugs, doses, and biological samples relatively quickly and inexpensively. In addition, a unique advantage to LCLs is that they are available from a large cohort of individuals, providing the capability to test for genetic variability on a scale not readily available in other in vitro systems. Since oftentimes the genotype data is publically available, the experimental costs can be limited to the cost of the drug response phenotyping. Here we describe several advantages and limitations of LCLs. In addition we review several important aspects of LCL experimental design and statistical analysis. Lastly, we present an example of LCLs being successfully used to identify candidate single nucleotide polymorphisms and genes for variability in response to a chemotherapeutic used to treat chronic myeloid leukemia. Journal of

show abstract

“…Additional limitations may include not recapitulating the appropriate in vivo disease phenotypes or not expressing appropriate cell-specific metabolic enzymes for drug metabolic studies (eg, lack of cytochrome P450 family). For additional considerations for cell-based models, readers are referred to this comprehensive review on cell-based models for pharmacogenomic discovery [11].…”

mentioning

confidence: 99%

Induced Pluripotent Stem Cell Models to Enable In Vitro Models for Screening in the Central Nervous System

Hunsberger

Efthymiou

Malik

et al. 2015

Stem Cells and Development

View full text Add to dashboard Cite

There is great need to develop more predictive drug discovery tools to identify new therapies to treat diseases of the central nervous system (CNS). Current nonpluripotent stem cell-based models often utilize non-CNS immortalized cell lines and do not enable the development of personalized models of disease. In this review, we discuss why in vitro models are necessary for translational research and outline the unique advantages of induced pluripotent stem cell (iPSC)-based models over those of current systems. We suggest that iPSC-based models can be patient specific and isogenic lines can be differentiated into many neural cell types for detailed comparisons. iPSC-derived cells can be combined to form small organoids, or large panels of lines can be developed that enable new forms of analysis. iPSC and embryonic stem cell-derived cells can be readily engineered to develop reporters for lineage studies or mechanism of action experiments further extending the utility of iPSC-based systems. We conclude by describing novel technologies that include strategies for the development of diversity panels, novel genomic engineering tools, new three-dimensional organoid systems, and modified high-content screens that may bring toxicology into the 21st century. The strategic integration of these technologies with the advantages of iPSC-derived cell technology, we believe, will be a paradigm shift for toxicology and drug discovery efforts.Disease Modeling D iseases of the central nervous system (CNS) affect a large number of people, but therapeutic intervention is hampered by the lack of useful models for many of these diseases. Current research on human subjects, particularly for drug discovery for CNS diseases, is severely (and appropriately) limited by ethical guidelines. Therefore, surrogate models are needed that share important anatomical, physiological, and genetic features to advance new treatments and therapies for CNS diseases [1].Developing rapid and effective therapies for CNS diseases requires the availability of in vitro models that accurately recapitulate disease phenotypes and predict patient treatment response. A proper model must be both sensitive and predictive while reflecting both normal and disease processes. Equally important, these models should enable the investigation of genetic and environmental risk factors contributing to diseases in a rapid and economical way. Currently used models often do not reflect a typical human response [2-4], despite efforts underway to better characterize these models and increase their preclinical value in predicting safety and efficacy in the clinic [5,6]. Therefore, there is a great need to develop disease-and patient-specific models from cells directly affected in CNS disorders. These cellbased models, we envision, could either replace or supplement current animal models and enable the efficient translation of basic research into the clinical setting. Limitations with current CNS modelsCurrently, drug discovery relies on the use of animalbased or cell-based models, ...

show abstract

Pharmacogenomic Discovery Using Cell-Based Models

Cited by 107 publications

References 160 publications

Chemotherapeutic drug susceptibility associated SNPs are enriched in expression quantitative trait loci

Chemotherapeutic drug susceptibility associated SNPs are enriched in expression quantitative trait loci

Leveraging Lymphoblastoid Cell Lines for Drug Response Modeling

Induced Pluripotent Stem Cell Models to Enable In Vitro Models for Screening in the Central Nervous System

Contact Info

Product

Resources

About