Short communication: PDF OnlyRace and smoking status associated with paclitaxel drug response in patient-derived lymphoblastoid cell linesAkhtari, Farida S.a,,b; Havener, Tammy M.c; Hertz, Daniel L.d; Ash, Jeremyb; Larson, Alexandrab; Carey, Lisa A.e; McLeod, Howard L.f,,g; Motsinger-Reif, Alison A.g,,hAuthor Information aDepartment of Biological Sciences bBioinformatics Research Center, North Carolina State University, Raleigh cPharmacotherapy and Experimental Therapeutics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina dDepartment of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, Michigan eDivision of Hematology/Oncology, University of North Carolina, Chapel Hill, North Carolina fUniversity of South Florida Taneja College of Pharmacy, Tampa, Florida gCenter for Pharmacogenomics and Individualized Therapy, University of North Carolina at Chapel Hill, Chapel Hill hBiostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Durham, North Carolina, USA Received 2 March 2020 Accepted 22 June 2020 Supplemental Digital Content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website, www.pharmacogeneticsandgenomics.com. Correspondence to Alison Motsinger-Reif, PhD, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, 111 TW Alexander Drive, Durham, NC 27709, USA, Tel: +984 287 3705; e-mail: firstname.lastname@example.org Pharmacogenetics and Genomics: September 15, 2020 - Volume Publish Ahead of Print - Issue - doi: 10.1097/FPC.0000000000000419 Buy SDC PAP Metrics Abstract The use of ex-vivo model systems to provide a level of forecasting for in-vivo characteristics remains an important need for cancer therapeutics. The use of lymphoblastoid cell lines (LCLs) is an attractive approach for pharmacogenomics and toxicogenomics, due to their scalability, efficiency, and cost-effectiveness. There is little data on the impact of demographic or clinical covariates on LCL response to chemotherapy. Paclitaxel sensitivity was determined in LCLs from 93 breast cancer patients from the University of North Carolina Lineberger Comprehensive Cancer Center Breast Cancer Database to test for potential associations and/or confounders in paclitaxel dose-response assays. Measures of paclitaxel cell viability were associated with patient data included treatment regimens, cancer status, demographic and environmental variables, and clinical outcomes. We used multivariate analysis of variance to identify the in-vivo variables associated with ex-vivo dose-response. In this unique dataset that includes both in-vivo and ex-vivo data from breast cancer patients, race (P = 0.0049) and smoking status (P = 0.0050) were found to be significantly associated with ex-vivo dose-response in LCLs. Racial differences in clinical dose-response have been previously described, but the smoking association has not been reported. Our results indicate that in-vivo smoking status can influence ex-vivo dose-response in LCLs, and more precise measures of covariates may allow for more precise forecasting of clinical effect. In addition, understanding the mechanism by which exposure to smoking in-vivo effects ex-vivo dose-response in LCLs may open up new avenues in the quest for better therapeutic prediction. Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.