Grant Number:	5R01CA161608-08 Interpret this number
Primary Investigator:	Reif, David
Organization:	North Carolina State University Raleigh
Project Title:	Genetic Etiology of Cancer Drug Response
Fiscal Year:	2020

Abstract: Important progress continues to be made in the treatment of most common cancers, but therapeutic benefit remains difficult to predict and severe or fatal adverse events occur frequently. The Human Genome Project has fueled the notion that genetic information can produce effective and cost-efficient selection of therapies for individual patients, but validated genetic signatures that predict response to most chemotherapy regimens remain to be identified. Numerous genes potentially influence drug response, but current candidate-gene approaches are limited by the requirement of a priori knowledge about the genes involved and the moderate size of most clinical trials often limits the power of in vitro genome wide association studies (GWAS) for cancer pharmacogenomics discovery. In response to these limitations, we have undertaken a thorough, pharmacogenomic assessment of cytotoxic effect of the majority of FDA approved anti-cancer compounds using an ex vivo model system to determine the heritability of drug-induced cell killing to prioritize drugs for pharmacogenomic mapping. These results are an important first step, and while high heritability of a trait does not guarantee successful association mapping results, it represents an important first step and the results will be used to prioritize drugs with high heritabilities for genome-wide association mapping. In the current proposal, GWAS mapping of cytotoxic agents will be performed in a European American population, and then replication GWAS mapping will be performed in an East Asian population. In addition to discovering and validating genetic variants that predict drug response, the wealth of data collected will be used to dissect the underlying etiology of drug response traits, including assessing the relative contribution of genetic, environmental, and interaction components of variation. These results will provide crucial insight to prioritize genetic variants for follow-up in precious clinical population resources, and potentially reveal new insight into the overall etiology of drug responses.




Deep autoencoder-based behavioral pattern recognition outperforms standard statistical methods in high-dimensional zebrafish studies.
Authors: Green A.J. , Truong L. , Thunga P. , Leong C. , Hancock M. , Tanguay R.L. , Reif D.M. .
Source: Plos Computational Biology, 2024 Sep; 20(9), p. e1012423.
EPub date: 2024-09-10 00:00:00.0.
PMID: 39255309
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Deep autoencoder-based behavioral pattern recognition outperforms standard statistical methods in high-dimensional zebrafish studies.
Authors: Green A.J. , Truong L. , Thunga P. , Leong C. , Hancock M. , Tanguay R.L. , Reif D.M. .
Source: Biorxiv : The Preprint Server For Biology, 2023-09-17 00:00:00.0; , .
EPub date: 2023-09-17 00:00:00.0.
PMID: 37745446
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MKX-AS1 Gene Expression Associated with Variation in Drug Response to Oxaliplatin and Clinical Outcomes in Colorectal Cancer Patients.
Authors: Gonzalez R.D. , Small G.W. , Green A.J. , Akhtari F.S. , Motsinger-Reif A.A. , Quintanilha J.C.F. , Havener T.M. , Reif D.M. , McLeod H.L. , Wiltshire T. .
Source: Pharmaceuticals (basel, Switzerland), 2023-05-17 00:00:00.0; 16(5), .
EPub date: 2023-05-17 00:00:00.0.
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Utilizing a Population-Genetic Framework to Test for Gene-Environment Interactions between Zebrafish Behavior and Chemical Exposure.
Authors: Thunga P. , Truong L. , Rericha Y. , Du J. , Morshead M. , Tanguay R.L. , Reif D.M. .
Source: Toxics, 2022-12-09 00:00:00.0; 10(12), .
EPub date: 2022-12-09 00:00:00.0.
PMID: 36548602
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LGR5 is a conserved marker of hair follicle stem cells in multiple species and is present early and throughout follicle morphogenesis.
Authors: Polkoff K.M. , Gupta N.K. , Green A.J. , Murphy Y. , Chung J. , Gleason K.L. , Simpson S.G. , Walker D.M. , Collins B. , Piedrahita J.A. .
Source: Scientific Reports, 2022-06-01 00:00:00.0; 12(1), p. 9104.
EPub date: 2022-06-01 00:00:00.0.
PMID: 35650234
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Prediction of synergistic drug combinations using PCA-initialized deep learning.
Authors: Ma J. , Motsinger-Reif A. .
Source: Biodata Mining, 2021-10-20 00:00:00.0; 14(1), p. 46.
EPub date: 2021-10-20 00:00:00.0.
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High-throughput screening and genome-wide analyses of 44 anticancer drugs in the 1000 Genomes cell lines reveals an association of the NQO1 gene with the response of multiple anticancer drugs.
Authors: Akhtari F.S. , Green A.J. , Small G.W. , Havener T.M. , House J.S. , Roell K.R. , Reif D.M. , McLeod H.L. , Wiltshire T. , Motsinger-Reif A.A. .
Source: Plos Genetics, 2021 Aug; 17(8), p. e1009732.
EPub date: 2021-08-26 00:00:00.0.
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Leveraging high-throughput screening data, deep neural networks, and conditional generative adversarial networks to advance predictive toxicology.
Authors: Green A.J. , Mohlenkamp M.J. , Das J. , Chaudhari M. , Truong L. , Tanguay R.L. , Reif D.M. .
Source: Plos Computational Biology, 2021 Jul; 17(7), p. e1009135.
EPub date: 2021-07-02 00:00:00.0.
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Extending the lymphoblastoid cell line model for drug combination pharmacogenomics.
Authors: Green A.J. , Anchang B. , Akhtari F.S. , Reif D.M. , Motsinger-Reif A. .
Source: Pharmacogenomics, 2021-05-28 00:00:00.0; , .
EPub date: 2021-05-28 00:00:00.0.
PMID: 34044623
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Uncovering Evidence for Endocrine-Disrupting Chemicals That Elicit Differential Susceptibility through Gene-Environment Interactions.
Authors: Wallis D.J. , Truong L. , La Du J. , Tanguay R.L. , Reif D.M. .
Source: Toxics, 2021-04-06 00:00:00.0; 9(4), .
EPub date: 2021-04-06 00:00:00.0.
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Development of a Pandemic Awareness STEM Outreach Curriculum: Utilizing a Computational Thinking Taxonomy Framework.
Authors: Gilchrist P.O. , Alexander A.B. , Green A.J. , Sanders F.E. , Hooker A.Q. , Reif D.M. .
Source: Education Sciences, 2021 Mar; 11(3), .
EPub date: 2021-03-09 00:00:00.0.
PMID: 34824997
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Race and smoking status associated with paclitaxel drug response in patient-derived lymphoblastoid cell lines.
Authors: Akhtari F.S. , Havener T.M. , Hertz D.L. , Ash J. , Larson A. , Carey L.A. , McLeod H.L. , Motsinger-Reif A.A. .
Source: Pharmacogenetics And Genomics, 2021-02-01 00:00:00.0; 31(2), p. 48-52.
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Children's Environmental Health: A Systems Approach for Anticipating Impacts from Chemicals.
Authors: Cohen Hubal E.A. , Reif D.M. , Slover R. , Mullikin A. , Little J.C. .
Source: International Journal Of Environmental Research And Public Health, 2020-11-11 00:00:00.0; 17(22), .
EPub date: 2020-11-11 00:00:00.0.
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Pharmacogenomics.
Authors: Roden D.M. , McLeod H.L. , Relling M.V. , Williams M.S. , Mensah G.A. , Peterson J.F. , Van Driest S.L. .
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EPub date: 2019-08-05 00:00:00.0.
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Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases.
Authors: Kosnik M.B. , Reif D.M. .
Source: Toxicology And Applied Pharmacology, 2019-07-16 00:00:00.0; 379, p. 114674.
EPub date: 2019-07-16 00:00:00.0.
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Synergistic Chemotherapy Drug Response Is a Genetic Trait in Lymphoblastoid Cell Lines.
Authors: Roell K.R. , Havener T.M. , Reif D.M. , Jack J. , McLeod H.L. , Wiltshire T. , Motsinger-Reif A.A. .
Source: Frontiers In Genetics, 2019; 10, p. 829.
EPub date: 2019-10-15 00:00:00.0.
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Gene expression and linkage analysis implicate CBLB as a mediator of rituximab resistance.
Authors: Jack J. , Small G.W. , Brown C.C. , Havener T.M. , McLeod H.L. , Motsinger-Reif A.A. , Richards K.L. .
Source: The Pharmacogenomics Journal, 2018-05-22 00:00:00.0; 18(3), p. 467-473.
EPub date: 2017-12-05 00:00:00.0.
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Gene set analysis methods: a systematic comparison.
Authors: Mathur R. , Rotroff D. , Ma J. , Shojaie A. , Motsinger-Reif A. .
Source: Biodata Mining, 2018; 11, p. 8.
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The influence of Neanderthal alleles on cytotoxic response.
Authors: Akhtari F.S. , Havener T.M. , Fukudo M. , Jack J.R. , McLeod H.L. , Wiltshire T. , Motsinger-Reif A.A. .
Source: Peerj, 2018; 6, p. e5691.
EPub date: 2018-10-23 00:00:00.0.
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An Introduction to Terminology and Methodology of Chemical Synergy-Perspectives from Across Disciplines.
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Source: Frontiers In Pharmacology, 2017; 8, p. 158.
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Discordance Of Somatic Mutations Between Asian And Caucasian Patient Populations With Gastric Cancer
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Authors: Alvarellos M.L. , McDonagh E.M. , Patel S. , McLeod H.L. , Altman R.B. , Klein T.E. .
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Authors: Mason N.T. , Bell G.C. , Quilitz R.E. , Greene J.N. , McLeod H.L. .
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Source: Cancer, 2015-04-01 00:00:00.0; 121(7), p. 1025-31.
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An Investigation Of Gene-gene Interactions In Dose-response Studies With Bayesian Nonparametrics
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Authors: Marsh S. , King C.R. , Van Booven D.J. , Revollo J.Y. , Gilman R.H. , McLeod H.L. .
Source: Pharmacogenomics, 2015; 16(5), p. 441-8.
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Evaluating The Role Of Admixture In Cancer Therapy Via In Vitro Drug Response And Multivariate Genome-wide Associations
Authors: Jack J. , Havener T.M. , McLeod H.L. , Motsinger-Reif A.A. , Foster M. .
Source: Pharmacogenomics, 2015; 16(13), p. 1451-63.
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Beyond Ic50 S: Towards Robust Statistical Methods For In Vitro Association Studies
Authors: Beam A. , Motsinger-Reif A. .
Source: Journal Of Pharmacogenomics & Pharmacoproteomics, 2014-03-01 00:00:00.0; 5(1), p. 1000121.
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Genome-wide Association And Pharmacological Profiling Of 29 Anticancer Agents Using Lymphoblastoid Cell Lines
Authors: Brown C.C. , Havener T.M. , Medina M.W. , Jack J.R. , Krauss R.M. , McLeod H.L. , Motsinger-Reif A.A. .
Source: Pharmacogenomics, 2014 Feb; 15(2), p. 137-46.
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Application Of Next Generation Sequencing To Ceph Cell Lines To Discover Variants Associated With Fda Approved Chemotherapeutics
Authors: Hariani G.D. , Lam E.T. , Lam E.J. , Havener T. , Kwok P.Y. , McLeod H.L. , Wagner M.J. , Motsinger-Reif A.A. .
Source: Bmc Research Notes, 2014; 7, p. 360.
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Authors: Che R. , Jack J.R. , Motsinger-Reif A.A. , Brown C.C. .
Source: Biodata Mining, 2014; 7, p. 9.
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Lymphoblastoid Cell Lines Models Of Drug Response: Successes And Lessons From This Pharmacogenomic Model
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Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction.
Authors: Dai H. , Charnigo R.J. , Becker M.L. , Leeder J.S. , Motsinger-Reif A.A. .
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Source: Genetic Epidemiology, 2012 Dec; 36(8), p. 890-4.
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Source: Molecular Cancer Therapeutics, 2011 Oct; 10(10), p. 1839-45.
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Pharmacogenomic Characterization Of Us Fda-approved Cytotoxic Drugs
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Source: Pharmacogenomics, 2011 Oct; 12(10), p. 1407-15.
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Source: Plos One, 2011; 6(5), p. e17561.
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Optimization Of Nonlinear Dose- And Concentration-response Models Utilizing Evolutionary Computation
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Source: Dose-response : A Publication Of International Hormesis Society, 2011; 9(3), p. 387-409.
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Authors: Brown C. , Havener T.M. , Everitt L. , McLeod H. , Motsinger-Reif A.A. .
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