@article{lewis_thomas_breen_peden_teferedegne_foseh_motsinger-reif_rotroff_lewis_2022, title={The AGMK1-9T7 cell model of neoplasia: Evolution of DNA copy-number aberrations and miRNA expression during transition from normal to metastatic cancer cells}, volume={17}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0275394}, abstractNote={To study neoplasia in tissue culture, cell lines representing the evolution of normal cells to tumor cells are needed. To produce such cells, we developed the AGMK1-9T7 cell line, established cell banks at 10-passage intervals, and characterized their biological properties. Here we examine the evolution of chromosomal DNA copy-number aberrations and miRNA expression in this cell line from passage 1 to the acquisition of a tumorigenic phenotype at passage 40. We demonstrated the use of a human microarray platform for DNA copy-number profiling of AGMK1-9T7 cells using knowledge of synteny to ‘recode’ data from human chromosome coordinates to those of the African green monkey. This approach revealed the accumulation of DNA copy-number gains and losses in AGMK1-9T7 cells from passage 3 to passage 40, which spans the period in which neoplastic transformation occurred. These alterations occurred in the sequences of genes regulating DNA copy-number imbalance of several genes that regulate endothelial cell angiogenesis, survival, migration, and proliferation. Regarding miRNA expression, 195 miRNAs were up- or down-regulated at passage 1 at levels that appear to be biologically relevant (i.e., log2 fold change >2.0 (q<0.05)). At passage 10, the number of up/down-regulated miRNAs fell to 63; this number increased to 93 at passage 40. Principal-component analysis grouped these miRNAs into 3 clusters; miRNAs in sub-clusters of these groups could be correlated with initiation, promotion, and progression, stages that have been described for neoplastic development. Thirty-four of the AGMK1-9T7 miRNAs have been associated with these stages in human cancer. Based on these data, we propose that the evolution of AGMK1-9T7 cells represents a detailed model of neoplasia in vitro.}, number={10}, journal={PLOS ONE}, author={Lewis, Andrew M., Jr. and Thomas, Rachael and Breen, Matthew and Peden, Keith and Teferedegne, Belete and Foseh, Gideon and Motsinger-Reif, Alison and Rotroff, Daniel and Lewis, Gladys}, year={2022}, month={Oct} }
 @article{mcdonough_warren_jack_motsinger‐reif_armstrong_bis_house_singh_el rouby_gong_et al._2021, title={Adverse Cardiovascular Outcomes and Antihypertensive Treatment: A Genome‐Wide Interaction Meta‐Analysis in the International Consortium for Antihypertensive Pharmacogenomics Studies}, volume={110}, ISSN={0009-9236 1532-6535}, url={http://dx.doi.org/10.1002/cpt.2355}, DOI={10.1002/cpt.2355}, abstractNote={We sought to identify genome‐wide variants influencing antihypertensive drug response and adverse cardiovascular outcomes, utilizing data from four randomized controlled trials in the International Consortium for Antihypertensive Pharmacogenomics Studies (ICAPS). Genome‐wide antihypertensive drug‐single nucleotide polymorphism (SNP) interaction tests for four drug classes (β‐blockers, n = 9,195; calcium channel blockers (CCBs), n = 10,511; thiazide/thiazide‐like diuretics, n = 3,516; ACE‐inhibitors/ARBs, n = 2,559) and cardiovascular outcomes (incident myocardial infarction, stroke, or death) were analyzed among patients with hypertension of European ancestry. Top SNPs from the meta‐analyses were tested for replication of cardiovascular outcomes in an independent Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) study (n = 21,267), blood pressure (BP) response in independent ICAPS studies (n = 1,552), and ethnic validation in African Americans from the Genetics of Hypertension Associated Treatment study (GenHAT; n = 5,115). One signal reached genome‐wide significance in the β‐blocker‐SNP interaction analysis (rs139945292, Interaction P = 1.56 × 10−8). rs139945292 was validated through BP response to β‐blockers, with the T‐allele associated with less BP reduction (systolic BP response P = 6 × 10−4, Beta = 3.09, diastolic BP response P = 5 × 10−3, Beta = 1.53). The T‐allele was also associated with increased adverse cardiovascular risk within the β‐blocker treated patients’ subgroup (P = 2.35 × 10−4, odds ratio = 1.57, 95% confidence interval = 1.23–1.99). The locus showed nominal replication in CHARGE, and consistent directional trends in β‐blocker treated African Americans. rs139945292 is an expression quantitative trait locus for the 50 kb upstream gene NTM (neurotrimin). No SNPs attained genome‐wide significance for any other drugs classes. Top SNPs were located near CALB1 (CCB), FLJ367777 (ACE‐inhibitor), and CES5AP1 (thiazide). The NTM region is associated with increased risk for adverse cardiovascular outcomes and less BP reduction in β‐blocker treated patients. Further investigation into this region is warranted.}, number={3}, journal={Clinical Pharmacology & Therapeutics}, publisher={Wiley}, author={McDonough, Caitrin W. and Warren, Helen R. and Jack, John R. and Motsinger‐Reif, Alison A. and Armstrong, Nicole D. and Bis, Joshua C. and House, John S. and Singh, Sonal and El Rouby, Nihal M. and Gong, Yan and et al.}, year={2021}, month={Aug}, pages={723–732} }
 @article{ash_kuenemann_rotroff_motsinger-reif_fourches_2019, title={Cheminformatics approach to exploring and modeling trait-associated metabolite profiles}, volume={11}, ISSN={["1758-2946"]}, DOI={10.1186/s13321-019-0366-3}, abstractNote={Developing predictive and transparent approaches to the analysis of metabolite profiles across patient cohorts is of critical importance for understanding the events that trigger or modulate traits of interest (e.g., disease progression, drug metabolism, chemical risk assessment). However, metabolites' chemical structures are still rarely used in the statistical modeling workflows that establish these trait-metabolite relationships. Herein, we present a novel cheminformatics-based approach capable of identifying predictive, interpretable, and reproducible trait-metabolite relationships. As a proof-of-concept, we utilize a previously published case study consisting of metabolite profiles from non-small-cell lung cancer (NSCLC) adenocarcinoma patients and healthy controls. By characterizing each structurally annotated metabolite using both computed molecular descriptors and patient metabolite concentration profiles, we show that these complementary features enhance the identification and understanding of key metabolites associated with cancer. Ultimately, we built multi-metabolite classification models for assessing patients' cancer status using specific groups of metabolites identified based on high structural similarity through chemical clustering. We subsequently performed a metabolic pathway enrichment analysis to identify potential mechanistic relationships between metabolites and NSCLC adenocarcinoma. This cheminformatics-inspired approach relies on the metabolites' structural features and chemical properties to provide critical information about metabolite-trait associations. This method could ultimately facilitate biological understanding and advance research based on metabolomics data, especially with respect to the identification of novel biomarkers.}, journal={JOURNAL OF CHEMINFORMATICS}, author={Ash, Jeremy R. and Kuenemann, Melaine A. and Rotroff, Daniel and Motsinger-Reif, Alison and Fourches, Denis}, year={2019}, month={Jun} }
 @article{morieri_gao_pigeyre_shah_sjaarda_mendonca_hastings_buranasupkajorn_motsinger-reif_rotroff_et al._2018, title={Genetic Tools for Coronary Risk Assessment in Type 2 Diabetes: A Cohort Study From the ACCORD Clinical Trial}, volume={41}, ISSN={["1935-5548"]}, DOI={10.2337/dc18-0709}, abstractNote={
                  OBJECTIVE
                  We evaluated whether the increasing number of genetic loci for coronary artery disease (CAD) identified in the general population could be used to predict the risk of major CAD events (MCE) among participants with type 2 diabetes at high cardiovascular risk.
               
               
                  RESEARCH DESIGN AND METHODS
                  A weighted genetic risk score (GRS) derived from 204 variants representative of all the 160 CAD loci identified in the general population as of December 2017 was calculated in 5,360 and 1,931 white participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Outcome Reduction With Initial Glargine Intervention (ORIGIN) studies, respectively. The association between GRS and MCE (combining fatal CAD events, nonfatal myocardial infarction, and unstable angina) was assessed by Cox proportional hazards regression.
               
               
                  RESULTS
                  The GRS was associated with MCE risk in both ACCORD and ORIGIN (hazard ratio [HR] per SD 1.27, 95% CI 1.18–1.37, P = 4 × 10−10, and HR per SD 1.35, 95% CI 1.16–1.58, P = 2 × 10−4, respectively). This association was independent from interventions tested in the trials and persisted, though attenuated, after adjustment for classic cardiovascular risk predictors. Adding the GRS to clinical predictors improved incident MCE risk classification (relative integrated discrimination improvement +8%, P = 7 × 10−4). The performance of this GRS was superior to that of GRS based on the smaller number of CAD loci available in previous years.
               
               
                  CONCLUSIONS
                  When combined into a GRS, CAD loci identified in the general population are associated with CAD also in type 2 diabetes. This GRS provides a significant improvement in the ability to correctly predict future MCE, which may increase further with the discovery of new CAD loci.
               }, number={11}, journal={DIABETES CARE}, author={Morieri, Mario Luca and Gao, He and Pigeyre, Marie and Shah, Hetal S. and Sjaarda, Jennifer and Mendonca, Christine and Hastings, Timothy and Buranasupkajorn, Patinut and Motsinger-Reif, Alison A. and Rotroff, Daniel M. and et al.}, year={2018}, month={Nov}, pages={2404–2413} }
 @article{shahin_gong_frye_rotroff_beitelshees_baillie_chapman_gums_turner_boerwinkle_et al._2018, title={Sphingolipid Metabolic Pathway Impacts Thiazide Diuretics Blood Pressure Response: Insights From Genomics, Metabolomics, and Lipidomics}, volume={7}, ISSN={["2047-9980"]}, DOI={10.1161/jaha.117.006656}, abstractNote={
            Background
            
              Although hydrochlorothiazide (
              HCTZ
              ) is a well‐established first‐line antihypertensive in the United States, <50% of
              HCTZ
              treated patients achieve blood pressure (
              BP
              ) control. Thus, identifying biomarkers that could predict the
              BP
              response to
              HCTZ
              is critically important. In this study, we utilized metabolomics, genomics, and lipidomics to identify novel pathways and biomarkers associated with
              HCTZ BP
              response.
            
          
          
            Methods and Results
            
              First, we conducted a pathway analysis for 13 metabolites we recently identified to be significantly associated with
              HCTZ BP
              response. From this analysis, we found the sphingolipid metabolic pathway as the most significant pathway (
              P
              =5.8E‐05). Testing 78 variants, within 14 genes involved in the sphingolipid metabolic canonical pathway, with the
              BP
              response to
              HCTZ
              identified variant rs6078905, within the
              
                SPTLC
                3
              
              gene, as a novel biomarker significantly associated with the
              BP
              response to
              HCTZ
              in whites (n=228). We found that rs6078905 C‐allele carriers had a better
              BP
              response to
              HCTZ
              versus noncarriers (∆
              SBP
              /∆
              DBP
              : −11.4/−6.9 versus −6.8/−3.5 mm Hg; ∆
              SBP
              P
              =6.7E‐04; ∆
              DBP
              P
              =4.8E‐04). Additionally, in blacks (n=148), we found genetic signals in the
              
                SPTLC
                3
              
              genomic region significantly associated with the
              BP
              response to
              HCTZ
              (
              P
              <0.05). Last, we observed that rs6078905 significantly affects the baseline level of 4 sphingomyelins (N24:2, N24:3, N16:1, and N22:1; false discovery rate <0.05), from which N24:2 sphingomyelin has a significant correlation with both
              HCTZ DBP
              ‐response (
              r
              =−0.42;
              P
              =7E‐03) and
              SBP
              ‐response (
              r
              =−0.36;
              P
              =2E‐02).
            
          
          
            Conclusions
            
              This study provides insight into potential pharmacometabolomic and genetic mechanisms underlying
              HCTZ BP
              response and suggests that
              
                SPTLC
                3
              
              is a potential determinant of the
              BP
              response to
              HCTZ
              .
            
          
          
            Clinical Trial Registration
            
              URL
              :
              http://www.clinicaltrials.gov
              . Unique identifier:
              NCT
              00246519.
            
          }, number={1}, journal={JOURNAL OF THE AMERICAN HEART ASSOCIATION}, author={Shahin, Mohamed H. and Gong, Yan and Frye, Reginald F. and Rotroff, Daniel M. and Beitelshees, Amber L. and Baillie, Rebecca A. and Chapman, Arlene B. and Gums, John G. and Turner, Stephen T. and Boerwinkle, Eric and et al.}, year={2018}, month={Jan} }
 @article{teferedegne_rotroff_macauley_foseh_lewis_motsinger-rief_lewis_2017, title={Assessment of potential miRNA biomarkers of VERO-cell tumorigenicity in a new line (AGMK1-9T7) of African green monkey kidney cells}, volume={35}, ISSN={["1873-2518"]}, DOI={10.1016/j.vaccine.2017.04.004}, abstractNote={Patterns of microRNA expression appear to delineate the process of spontaneous neoplastic development-transformation (SPNDT) occurring in the African green monkey kidney (AGMK) VERO cell line (Teferedegne et al., 2010). Analysis of microarray data identified 6 microRNAs whose high-level of expression peaked when the World Health Organization 10-87 VERO cells became tumorigenic at passage (p) 190. Six miRNAs were identified as potential biomarkers for the expression of the VERO-cell tumorigenic phenotype (Teferedegne et al., 2014). However, the question remained whether these miRNA biomarkers are specific for VERO cells or can be generalizable to other cells originating from African green monkey kidneys. To examine miRNA expression patterns in AGMK cells at lower passage levels and to re-examine the identified miRNAs as biomarkers associated with tumorigenic phenotype of VERO cells in another independently-derived line, we established a new line of African green monkey kidney cells (AGMK1-9T7) by serially passaging kidney cells from another AGM. The AGMK1-9T7 cells became tumorigenic in nude mice at p40. Evaluation of miRNA expression at intervals from p1 to p40 revealed similarities between the evolution of miRNA expression during SPNDT in the AGMK1-9T7 cells and the 10-87 VERO cells. Four of the 6 potential biomarker miRNAs (miR-376a, miR-654-3p, miR-543, miR-134) in our earlier reports were detected by microarray in the AGMK1-9T7 cells; RT-qPCR analysis detected all 6 miRNAs. All 6 of these miRNAs have been associated with human tumors. Detection of the same miRNAs associated with the tumorigenic p40 AGMK1-9T7 cells and tumorigenic 10-87 VERO cells confirmed our proposal that these miRNA represent biomarkers for the tumor-forming ability of AGMK/VERO cells. The similarities of expression of miRNAs in different AGMK cell lines that were established 50years apart suggest that the process of SPNDT in these non-human primate cells in tissue culture is based upon similar genetic and epigenetic mechanisms.}, number={41}, journal={VACCINE}, author={Teferedegne, Belete and Rotroff, Daniel M. and Macauley, Juliete and Foseh, Gideon and Lewis, Gladys and Motsinger-Rief, Alison and Lewis, Andrew M., Jr.}, year={2017}, month={Oct}, pages={5503–5509} }
 @article{marvel_rotroff_wagner_buse_havener_mcleod_motsinger-reif_2017, title={Common and rare genetic markers of lipid variation in subjects with type 2 diabetes from the ACCORD clinical trial}, volume={5}, journal={PeerJ}, author={Marvel, S. W. and Rotroff, D. M. and Wagner, M. J. and Buse, J. B. and Havener, T. M. and McLeod, H. L. and Motsinger-Reif, A. A.}, year={2017} }
 @article{rotroff_marvel_jack_havener_doria_shah_mychaleckyi_mcleod_buse_wagner_et al._2017, title={Common genetic variants in neurobeachin (nbea) are associated with metformin drug response in individuals with type 2 diabetes in the accord clinical trial}, volume={101}, number={S1}, journal={Clinical Pharmacology & Therapeutics}, author={Rotroff, D. M. and Marvel, S. W. and Jack, J. R. and Havener, T. M. and Doria, A. and Shah, H. S. and Mychaleckyi, J. C. and McLeod, H. L. and Buse, J. B. and Wagner, M. J. and et al.}, year={2017}, pages={S9–9} }
 @article{st john-williams_blach_toledo_rotroff_kim_klavins_baillie_han_mahmoudiandehkordi_jack_et al._2017, title={Data descriptor: Targeted metabolomics and medication classification data from participants in the ADNI1 cohort}, volume={4}, journal={Scientific Data}, author={St John-Williams, L. and Blach, C. and Toledo, J. B. and Rotroff, D. M. and Kim, S. and Klavins, K. and Baillie, R. and Han, X. L. and Mahmoudiandehkordi, S. and Jack, J. and et al.}, year={2017} }
 @article{toledo_arnold_kastenmuller_chang_baillie_han_thambisetty_tenenbaum_suhre_thompson_et al._2017, title={Metabolic network failures in Alzheimer's disease: A biochemical road map}, volume={13}, number={9}, journal={Alzheimers & Dementia}, author={Toledo, J. B. and Arnold, M. and Kastenmuller, G. and Chang, R. and Baillie, R. A. and Han, X. L. and Thambisetty, M. and Tenenbaum, J. D. and Suhre, K. and Thompson, J. W. and et al.}, year={2017}, pages={965–984} }
 @article{nguyen_reuter_gaikwad_rotroff_kucera_motsinger-reif_smith_nieman_rubinow_kaddurah-daouk_et al._2017, title={The steroid metabolome in women with premenstrual dysphoric disorder during GnRH agonist-induced ovarian suppression: Effects of estradiol and progesterone addback}, volume={7}, journal={Translational Psychiatry}, author={Nguyen, T. V. and Reuter, J. M. and Gaikwad, N. W. and Rotroff, D. M. and Kucera, H. R. and Motsinger-Reif, A. and Smith, C. P. and Nieman, L. K. and Rubinow, D. R. and Kaddurah-Daouk, R. and et al.}, year={2017} }
 @article{gillis_rotroff_mesa_yao_chen_carulli_yoder_walko_teer_mcleod_2017, title={Tumor exome sequencing and copy number alterations reveal potential predictors of intrinsic resistance to multi-targeted tyrosine kinase inhibitors}, volume={8}, number={70}, journal={Oncotarget}, author={Gillis, N. K. and Rotroff, D. M. and Mesa, T. E. and Yao, J. Q. and Chen, Z. H. and Carulli, M. A. and Yoder, S. J. and Walko, C. M. and Teer, J. K. and McLeod, H. L.}, year={2017}, pages={115114–115127} }
 @article{shahin_gong_mcdonough_rotroff_beitelshees_garrett_gums_motsinger-reif_chapman_turner_et al._2016, title={A genetic response score for hydrochlorothiazide use insights from genomics and metabolomics integration}, volume={68}, number={3}, journal={Hypertension}, author={Shahin, M. H. and Gong, Y. and McDonough, C. W. and Rotroff, D. M. and Beitelshees, A. L. and Garrett, T. J. and Gums, J. G. and Motsinger-Reif, A. and Chapman, A. B. and Turner, S. T. and et al.}, year={2016}, pages={621-} }
 @article{irvin_rotroff_aslibekyan_zhi_hidalgo_motsinger-reif_marvel_srinivasasainagendra_claas_buse_et al._2016, title={A genome-wide study of lipid response to fenofibrate in Caucasians: A combined analysis of the GOLDN and ACCORD studies}, volume={26}, number={7}, journal={Pharmacogenetics and Genomics}, author={Irvin, M. R. and Rotroff, D. M. and Aslibekyan, S. and Zhi, D. G. and Hidalgo, B. and Motsinger-Reif, A. and Marvel, S. and Srinivasasainagendra, V. and Claas, S. A. and Buse, J. B. and et al.}, year={2016}, pages={324–333} }
 @article{judson_houck_martin_richard_knudsen_shah_little_wambaugh_setzer_kothya_et al._2016, title={Analysis of the effects of cell stress and cytotoxicity on in vitro assay activity across a diverse chemical and assay space}, volume={152}, number={2}, journal={Toxicological Sciences}, author={Judson, R. and Houck, K. and Martin, M. and Richard, A. M. and Knudsen, T. B. and Shah, I. and Little, S. and Wambaugh, J. and Setzer, R. W. and Kothya, P. and et al.}, year={2016}, pages={323–339} }
 @article{roode_rotroff_richards_moore_motsinger-reif_okamura_mizuno_tsujimoto_suter_breen_2016, title={Comprehensive genomic characterization of five canine lymphoid tumor cell lines}, volume={12}, journal={BMC Veterinary Research}, author={Roode, S. C. and Rotroff, D. and Richards, K. L. and Moore, P. and Motsinger-Reif, A. and Okamura, Y. and Mizuno, T. and Tsujimoto, H. and Suter, S. E. and Breen, M.}, year={2016} }
 @misc{rotroff_motsinger-reif_2016, title={Embracing integrative multiomics approaches}, journal={International Journal of Genomics}, author={Rotroff, D. M. and Motsinger-Reif, A. A.}, year={2016} }
 @article{graham_rotroff_marvel_buse_havener_wilson_wagner_motsinger-reif_2016, title={Incorporating concomitant medications into genome-wide analyses for the study of complex disease and drug response}, volume={7}, journal={Frontiers in Genetics}, author={Graham, H. T. and Rotroff, D. M. and Marvel, S. W. and Buse, J. B. and Havener, T. M. and Wilson, A. G. and Wagner, M. J. and Motsinger-Reif, A. A.}, year={2016} }
 @article{rotroff_joubert_marvel_haberg_wu_nilsen_ueland_nystad_london_motsinger-reif_2016, title={Maternal smoking impacts key biological pathways in newborns through epigenetic modification in Utero}, volume={17}, journal={BMC Genomics}, author={Rotroff, D. M. and Joubert, B. R. and Marvel, S. W. and Haberg, S. E. and Wu, M. C. and Nilsen, R. M. and Ueland, P. M. and Nystad, W. and London, S. J. and Motsinger-Reif, A.}, year={2016} }
 @article{rotroff_corum_motsinger-reif_fiehn_bottrel_drevets_singh_salvadore_kaddurah-daouk_2016, title={Metabolomic signatures of drug response phenotypes for ketamine and esketamine in subjects with refractory major depressive disorder: New mechanistic insights for rapid acting antidepressants}, volume={6}, journal={Translational Psychiatry}, author={Rotroff, D. M. and Corum, D. G. and Motsinger-Reif, A. and Fiehn, O. and Bottrel, N. and Drevets, W. C. and Singh, J. and Salvadore, G. and Kaddurah-Daouk, R.}, year={2016} }
 @article{rotroff_oki_liang_yee_stocker_corum_meisner_fiehn_motsinger-reif_giacomini_et al._2016, title={Pharmacometabolomic assessment of metformin in non-diabetic, African Americans}, volume={7}, journal={Frontiers in Pharmacology}, author={Rotroff, D. M. and Oki, N. O. and Liang, X. M. and Yee, S. W. and Stocker, S. L. and Corum, D. G. and Meisner, M. and Fiehn, O. and Motsinger-Reif, A. A. and Giacomini, K. M. and et al.}, year={2016} }
 @article{zhou_yee_seiser_leeuwen_tavendalel_bennett_groves_coleman_heijden_beulens_et al._2016, title={Variation in the glucose transporter gene SLC2A2 is associated with glycemic response to metformin}, volume={48}, number={9}, journal={Nature Genetics}, author={Zhou, K. X. and Yee, S. W. and Seiser, E. L. and Leeuwen, N. and Tavendalel, R. and Bennett, A. J. and Groves, C. J. and Coleman, R. L. and Heijden, A. A. and Beulens, J. W. and et al.}, year={2016}, pages={1055-} }
 @article{roode_rotroff_avery_suter_bienzle_schiffman_motsinger-reif_breen_2015, title={Genome-wide assessment of recurrent genomic imbalances in canine leukemia identifies evolutionarily conserved regions for subtype differentiation}, volume={23}, ISSN={0967-3849 1573-6849}, url={http://dx.doi.org/10.1007/s10577-015-9475-7}, DOI={10.1007/s10577-015-9475-7}, abstractNote={Leukemia in dogs is a heterogeneous disease with survival ranging from days to years, depending on the subtype. Strides have been made in both human and canine leukemia to improve classification and understanding of pathogenesis through immunophenotyping, yet classification and choosing appropriate therapy remains challenging. In this study, we assessed 123 cases of canine leukemia (28 ALLs, 24 AMLs, 25 B-CLLs, and 46 T-CLLs) using high-resolution oligonucleotide array comparative genomic hybridization (oaCGH) to detect DNA copy number alterations (CNAs). For the first time, such data were used to identify recurrent CNAs and inclusive genes that may be potential drivers of subtype-specific pathogenesis. We performed predictive modeling to identify CNAs that could reliably differentiate acute subtypes (ALL vs. AML) and chronic subtypes (B-CLL vs. T-CLL) and used this model to differentiate cases with up to 83.3 and 95.8 % precision, respectively, based on CNAs at only one to three genomic regions. In addition, CGH datasets for canine and human leukemia were compared to reveal evolutionarily conserved copy number changes between species, including the shared gain of HSA 21q in ALL and ∼25 Mb of shared gain of HSA 12 and loss of HSA 13q14 in CLL. These findings support the use of canine leukemia as a relevant in vivo model for human leukemia and justify the need to further explore the conserved genomic regions of interest for their clinical impact.}, number={4}, journal={Chromosome Research}, publisher={Springer Science and Business Media LLC}, author={Roode, Sarah C. and Rotroff, Daniel and Avery, Anne C. and Suter, Steven E. and Bienzle, Dorothee and Schiffman, Joshua D. and Motsinger-Reif, Alison and Breen, Matthew}, year={2015}, month={Jun}, pages={681–708} }
 @article{judson_magpantay_chickarmane_haskell_tania_taylor_xia_huang_rotroff_filer_et al._2015, title={Integrated model of chemical perturbations of a biological pathway using 18 in vitro high-throughput screening assays for the estrogen receptor}, volume={148}, number={1}, journal={Toxicological Sciences}, author={Judson, R. S. and Magpantay, F. M. and Chickarmane, V. and Haskell, C. and Tania, N. and Taylor, J. and Xia, M. H. and Huang, R. L. and Rotroff, D. M. and Filer, D. L. and et al.}, year={2015}, pages={137–154} }
 @article{thomas_borst_rotroff_motsinger-reif_lindblad-toh_modiano_breen_2014, title={Genomic profiling reveals extensive heterogeneity in somatic DNA copy number aberrations of canine hemangiosarcoma}, volume={22}, ISSN={["1573-6849"]}, DOI={10.1007/s10577-014-9406-z}, abstractNote={Canine hemangiosarcoma is a highly aggressive vascular neoplasm associated with extensive clinical and anatomical heterogeneity and a grave prognosis. Comprehensive molecular characterization of hemangiosarcoma may identify novel therapeutic targets and advanced clinical management strategies, but there are no published reports of tumor-associated genome instability and disrupted gene dosage in this cancer. We performed genome-wide microarray-based somatic DNA copy number profiling of 75 primary intra-abdominal hemangiosarcomas from five popular dog breeds that are highly predisposed to this disease. The cohort exhibited limited global genomic instability, compared to other canine sarcomas studied to date, and DNA copy number aberrations (CNAs) were predominantly of low amplitude. Recurrent imbalances of several key cancer-associated genes were evident; however, the global penetrance of any single CNA was low and no distinct hallmark aberrations were evident. Copy number gains of dog chromosomes 13, 24, and 31, and loss of chromosome 16, were the most recurrent CNAs involving large chromosome regions, but their relative distribution within and between cases suggests they most likely represent passenger aberrations. CNAs involving CDKN2A, VEGFA, and the SKI oncogene were identified as potential driver aberrations of hemangiosarcoma development, highlighting potential targets for therapeutic modulation. CNA profiles were broadly conserved between the five breeds, although subregional variation was evident, including a near twofold lower incidence of VEGFA gain in Golden Retrievers versus other breeds (22 versus 40 %). These observations support prior transcriptional studies suggesting that the clinical heterogeneity of this cancer may reflect the existence of multiple, molecularly distinct subtypes of canine hemangiosarcoma.}, number={3}, journal={CHROMOSOME RESEARCH}, author={Thomas, Rachael and Borst, Luke and Rotroff, Daniel and Motsinger-Reif, Alison and Lindblad-Toh, Kerstin and Modiano, Jaime F. and Breen, Matthew}, year={2014}, month={Sep}, pages={305–319} }
 @article{jack_rotroff_motsinger-reif_2014, title={Lymphoblastoid Cell Lines Models of Drug Response: Successes and Lessons from this Pharmacogenomic Model}, volume={14}, ISSN={["1875-5666"]}, DOI={10.2174/1566524014666140811113946}, abstractNote={A new standard for medicine is emerging that aims to improve individual drug responses through studying associations with genetic variations. This field, pharmacogenomics, is undergoing a rapid expansion due to a variety of technological advancements that are enabling higher throughput with reductions in cost. Here we review the advantages, limitations, and opportunities for using lymphoblastoid cell lines (LCL) as a model system for human pharmacogenomic studies. There are a wide range of publicly available resources with genome-wide data available for LCLs from both related and unrelated populations, removing the cost of genotyping the data for drug response studies. Furthermore, in contrast to human clinical trials or in vivo model systems, with high-throughput in vitro screening technologies, pharmacogenomics studies can easily be scaled to accommodate large sample sizes. An important component to leveraging genome-wide data in LCL models is association mapping. Several methods are discussed herein, and include multivariate concentration response modeling, issues with multiple testing, and successful examples of the 'triangle model' to identify candidate variants. Once candidate gene variants have been determined, their biological roles can be elucidated using pathway analyses and functionally confirmed using siRNA knockdown experiments. The wealth of genomics data being produced using related and unrelated populations is creating many exciting opportunities leading to new insights into the genetic contribution and heritability of drug response.}, number={7}, journal={CURRENT MOLECULAR MEDICINE}, author={Jack, J. and Rotroff, D. and Motsinger-Reif, A.}, year={2014}, pages={833–840} }
 @article{rotroff_jack_campbell_clark_motsinger-reif_2014, title={PGxClean: a quality control GUI for the Affymetrix DMET chip and other candidate gene studies with non-biallelic alleles}, volume={7}, journal={Biodata Mining}, author={Rotroff, D. and Jack, J. and Campbell, N. and Clark, S. and Motsinger-Reif, A. A.}, year={2014} }
 @article{zang_rotroff_judson_2013, title={Binary Classification of a Large Collection of Environmental Chemicals from Estrogen Receptor Assays by Quantitative Structure-Activity Relationship and Machine Learning Methods}, volume={53}, ISSN={["1549-960X"]}, DOI={10.1021/ci400527b}, abstractNote={There are thousands of environmental chemicals subject to regulatory decisions for endocrine disrupting potential. The ToxCast and Tox21 programs have tested ∼8200 chemicals in a broad screening panel of in vitro high-throughput screening (HTS) assays for estrogen receptor (ER) agonist and antagonist activity. The present work uses this large data set to develop in silico quantitative structure-activity relationship (QSAR) models using machine learning (ML) methods and a novel approach to manage the imbalanced data distribution. Training compounds from the ToxCast project were categorized as active or inactive (binding or nonbinding) classes based on a composite ER Interaction Score derived from a collection of 13 ER in vitro assays. A total of 1537 chemicals from ToxCast were used to derive and optimize the binary classification models while 5073 additional chemicals from the Tox21 project, evaluated in 2 of the 13 in vitro assays, were used to externally validate the model performance. In order to handle the imbalanced distribution of active and inactive chemicals, we developed a cluster-selection strategy to minimize information loss and increase predictive performance and compared this strategy to three currently popular techniques: cost-sensitive learning, oversampling of the minority class, and undersampling of the majority class. QSAR classification models were built to relate the molecular structures of chemicals to their ER activities using linear discriminant analysis (LDA), classification and regression trees (CART), and support vector machines (SVM) with 51 molecular descriptors from QikProp and 4328 bits of structural fingerprints as explanatory variables. A random forest (RF) feature selection method was employed to extract the structural features most relevant to the ER activity. The best model was obtained using SVM in combination with a subset of descriptors identified from a large set via the RF algorithm, which recognized the active and inactive compounds at the accuracies of 76.1% and 82.8% with a total accuracy of 81.6% on the internal test set and 70.8% on the external test set. These results demonstrate that a combination of high-quality experimental data and ML methods can lead to robust models that achieve excellent predictive accuracy, which are potentially useful for facilitating the virtual screening of chemicals for environmental risk assessment.}, number={12}, journal={JOURNAL OF CHEMICAL INFORMATION AND MODELING}, author={Zang, Qingda and Rotroff, Daniel M. and Judson, Richard S.}, year={2013}, month={Dec}, pages={3244–3261} }
 @article{rotroff_thomas_breen_motsinger-reif_2013, title={Naturally occuring canine cancers: powerful models for stimulating pharmacogenomic advancement in human medicine}, volume={14}, ISSN={["1744-8042"]}, DOI={10.2217/pgs.13.178}, abstractNote={An estimated 1.6 million new cases of cancer were diagnosed in the USA in 2012 [101]. The pharmaceutical industry is working furiously to develop new efficacious chemotherapeutics; however, the vast majority of compounds that show anticancer activity in preclinical studies fail during subsequent human clinical trials, hindering progress in patient care and further increasing costs for drug development [1–3]. Modern cancer research places a heavy emphasis on murine models for investigating cancer etiology and for driving the development of new therapies. Mice represent excellent models for studying cancer due to their short lifespans, ease of maintenance and opportunities for genetic manipulation [4]. While their attributes have led to numerous fundamental advances in identifying novel therapies, several important limitations exist. Murine models of cancer are generally induced by genetic engineering, or by subcutaneous xenografts. The limitations and advantages of various methods of inducing neoplasms in mice are well reviewed elsewhere [4,5]. Induced murine neoplasms are developed in a short period of time and they lack heterogeneity in the tumor cell population, the microenvironment and the stroma, all of which are inconsistent with most human cancers. Furthermore, human cancers typically display increased genomic instability compared with their induced murine counterparts, which limits their utility as tools for pharmacogenomics [6]. Many of these limitations may be addressed by using the domestic dog as a complementary model system. Canines share our environment and develop many age-related diseases with similar pathologies to humans. Perhaps most importantly, dogs exhibit a wide variety of spontaneous cancers that share extensive clinicopathologic features with those of human patients, offering a unique opportunity for comparative analysis of}, number={16}, journal={PHARMACOGENOMICS}, author={Rotroff, Daniel M. and Thomas, Rachael and Breen, Matthew and Motsinger-Reif, Alison A.}, year={2013}, month={Dec}, pages={1929–1931} }