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Chicago Ridge, IL, United States

Njiaju U.O.,University of Chicago | Gamazon E.R.,Section of Genetic Medicine | Gorsic L.K.,University of Chicago | Delaney S.M.,University of Chicago | And 3 more authors.
Pharmacogenetics and Genomics | Year: 2012

Objective: The clinical use of paclitaxel is limited by variable responses and the potential for significant toxicity. To date, studies of associations between variants in candidate genes and paclitaxel effects have yielded conflicting results. We aimed to evaluate the relationships between global gene expression and paclitaxel sensitivity. Methods: We utilized well-genotyped lymphoblastoid cell lines derived from the International HapMap Project to evaluate the relationships between cellular susceptibility to paclitaxel and global gene expression. Cells were exposed to varying concentrations of paclitaxel to evaluate paclitaxel-induced cytotoxicity and apoptosis. Among the top genes, we identified solute carrier (SLC) genes associated with paclitaxel sensitivity and narrowed down the list to those that had single nucleotide polymorphisms associated with both the expression level of the SLC gene and also with paclitaxel sensitivity. We performed an independent validation in an independent set of cell lines and also conducted functional studies using RNA interference. Results: Of all genes associated with paclitaxel-induced cytotoxicity at P less than 0.05 (1713 genes), there was a significant enrichment in SLC genes (31 genes). A subset of SLC genes, namely SLC31A2, SLC43A1, SLC35A5, and SLC41A2, was associated with paclitaxel sensitivity and had regulating single nucleotide polymorphisms that were also associated with paclitaxel-induced cytotoxicity. Multivariate modeling demonstrated that those four SLC genes together explained 20% of the observed variability in paclitaxel susceptibility. Using RNA interference, we demonstrated increased paclitaxel susceptibility with knockdown of three SLC genes, SLC31A2, SLC35A5, and SLC41A2. Conclusion: Our findings are novel and lend further support to the role of transporters, specifically solute carriers, in mediating cellular susceptibility to paclitaxel. © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins. Source

Trubetskoy V.,Section of Genetic Medicine | Rodriguez A.,University of Chicago | Dave U.,University of Chicago | Campbell N.,Vanderbilt University | And 7 more authors.
Bioinformatics | Year: 2015

Motivation: The development of cost-effective next-generation sequencing methods has spurred the development of high-throughput bioinformatics tools for detection of sequence variation. With many disparate variant-calling algorithms available, investigators must ask, 'Which method is best for my data?' Machine learning research has shown that so-called ensemble methods that combine the output of multiple models can dramatically improve classifier performance. Here we describe a novel variant-calling approach based on an ensemble of variant-calling algorithms, which we term the Consensus Genotyper for Exome Sequencing (CGES). CGES uses a two-stage voting scheme among four algorithm implementations. While our ensemble method can accept variants generated by any variant-calling algorithm, we used GATK2.8, SAMtools, FreeBayes and Atlas-SNP2 in building CGES because of their performance, widespread adoption and diverse but complementary algorithms. Results: We apply CGES to 132 samples sequenced at the Hudson Alpha Institute for Biotechnology (HAIB, Huntsville, AL) using the Nimblegen Exome Capture and Illumina sequencing technology. Our sample set consisted of 40 complete trios, two families of four, one parent-child duo and two unrelated individuals. CGES yielded the fewest total variant calls (NCGES=139897), the highest Ts/Tv ratio (3.02), the lowest Mendelian error rate across all genotypes (0.028%), the highest rediscovery rate from the Exome Variant Server (EVS; 89.3%) and 1000 Genomes (1KG; 84.1%) and the highest positive predictive value (PPV; 96.1%) for a random sample of previously validated de novo variants. We describe these and other quality control (QC) metrics from consensus data and explain how the CGES pipeline can be used to generate call sets of varying quality stringency, including consensus calls present across all four algorithms, calls that are consistent across any three out of four algorithms, calls that are consistent across any two out of four algorithms or a more liberal set of all calls made by any algorithm. © The Author 2014. Published by Oxford University Press. All rights reserved. Source

LaCroix B.,University of Chicago | Gamazon E.R.,Section of Genetic Medicine | Lenkala D.,University of Chicago | Im H.K.,Section of Genetic Medicine | And 5 more authors.
BMC Genomics | Year: 2014

Background: Using genome-wide genetic, gene expression, and microRNA expression (miRNA) data, we developed an integrative approach to investigate the genetic and epigenetic basis of chemotherapeutic sensitivity.Results: Through a sequential multi-stage framework, we identified genes and miRNAs whose expression correlated with platinum sensitivity, mapped these to genomic loci as quantitative trait loci (QTLs), and evaluated the associations between these QTLs and platinum sensitivity. A permutation analysis showed that top findings from our approach have a much lower false discovery rate compared to those from a traditional GWAS of drug sensitivity. Our approach identified five SNPs associated with 10 miRNAs and the expression level of 15 genes, all of which were associated with carboplatin sensitivity. Of particular interest was one SNP (rs11138019), which was associated with the expression of both miR-30d and the gene ABCD2, which were themselves correlated with both carboplatin and cisplatin drug-specific phenotype in the HapMap samples. Functional study found that knocking down ABCD2 in vitro led to increased apoptosis in ovarian cancer cell line SKOV3 after cisplatin treatment. Over-expression of miR-30d in vitro caused a decrease in ABCD2 expression, suggesting a functional relationship between the two.Conclusions: We developed an integrative approach to the investigation of the genetic and epigenetic basis of human complex traits. Our approach outperformed standard GWAS and provided hints at potential biological function. The relationships between ABCD2 and miR-30d, and ABCD2 and platin sensitivity were experimentally validated, suggesting a functional role of ABCD2 and miR-30d in sensitivity to platinating agents. © 2014 LaCroix et al.; licensee BioMed Central Ltd. Source

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