R. Stephanie Huang

Evaluation of Genetic Variation Contributing to Differences in Gene Expression between Populations

Gene expression is a complex quantitative trait partially regulated by genetic variation in DNA sequence. Population differences in gene expression could contribute to some of the observed differences in susceptibility to common diseases and response to drug treatments. We characterized gene expression in the full set of HapMap lymphoblastoid cell lines derived from individuals of European and African ancestry for 9156 transcript clusters (gene-level) evaluated with the Affymetrix GeneChip Human Exon 1.0 ST Array. Gene expression was found to differ significantly between these samples for 383 transcript clusters. Biological processes including ribosome biogenesis and antimicrobial humoral response were found to be enriched in these differential genes, suggesting their possible roles in contributing to the population differences at a higher level than that of mRNA expression and in response to environmental information. Genome-wide association studies for local or distant genetic variants that correlate with the differentially expressed genes enabled identification of significant associations with one or more single-nucleotide polymorphisms (SNPs), consistent with the hypothesis that genetic factors and not simply population identity or other characteristics (age of cell lines, length of culture, etc.) contribute to differences in gene expression in these samples. Our results provide a comprehensive view of the genes differentially expressed between populations and the enriched biological processes involved in these genes. We also provide an evaluation of the contributions of genetic variation and nongenetic factors to the population differences in gene expression.

Genetic Architecture of Transcript-Level Variation in Humans

We report here the results of testing the pairwise association of 12,747 transcriptional gene-expression values with more than two million single-nucleotide polymorphisms (SNPs) in samples of European (CEPH from Utah; CEU) and African (Yoruba from Ibadan; YRI) ancestry. We found 4,677 and 5,125 significant associations between expression quantitative nucleotides (eQTNs) and transcript clusters in the CEU and the YRI samples, respectively. The physical distance between an eQTN and its associated transcript cluster was referred to as the intrapair distance. An association with 4 Mb or less intrapair distance was defined as local; otherwise, it was defined as distant. The enrichment analysis of functional categories shows that genes harboring the local eQTNs are enriched in the categories related to nucleosome and chromatin assembly; the genes harboring the distant eQTNs are enriched in the categories related to transmembrane signal transduction, suggesting that these biological pathways are likely to play a significant role in regulation of gene expression. We highlight in the EPHX1 gene a deleterious nonsynonymous SNP that is distantly associated with gene expression of ORMDL3, a susceptibility gene for asthma.

Variants at 6q21 implicate PRDM1 in the etiology of therapy-induced second malignancies after Hodgkin's lymphoma.

Survivors of pediatric Hodgkins lymphoma are at risk for radiation therapy–induced second malignant neoplasms (SMNs). We identified two variants at chromosome 6q21 associated with SMNs in survivors of Hodgkins lymphoma treated with radiation therapy as children but not as adults. The variants comprise a risk locus associated with decreased basal expression of PRDM1 (encoding PR domain containing 1, with ZNF domain) and impaired induction of the PRDM1 protein after radiation exposure. These data suggest a new gene-exposure interaction that may implicate PRDM1 in the etiology of radiation therapy-induced SMNs.

Pharmacogenomic discovery using cell-based models.

Quantitative variation in response to drugs in human populations is multifactorial; genetic factors probably contribute to a significant extent. Identification of the genetic contribution to drug response typically comes from clinical observations and use of classic genetic tools. These clinical studies are limited by our inability to control environmental factors in vivo and the difficulty of manipulating the in vivo system to evaluate biological changes. Recent progress in dissecting genetic contribution to natural variation in drug response through the use of cell lines has been made and is the focus of this review. A general overview of current cell-based models used in pharmacogenomic discovery and validation is included. Discussion includes the current approach to translate findings generated from these cell-based models into the clinical arena and the use of cell lines for functional studies. Specific emphasis is given to recent advances emerging from cell line panels, including the International HapMap Project and the NCI60 cell panel. These panels provide a key resource of publicly available genotypic, expression, and phenotypic data while allowing researchers to generate their own data related to drug treatment to identify genetic variation of interest. Interindividual and interpopulation differences can be evaluated because human lymphoblastoid cell lines are available from major world populations of European, African, Chinese, and Japanese ancestry. The primary focus is recent progress in the pharmacogenomic discovery area through ex vivo models.

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

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.

Identification of common genetic variants that account for transcript isoform variation between human populations

In addition to the differences between populations in transcriptional and translational regulation of genes, alternative pre-mRNA splicing (AS) is also likely to play an important role in regulating gene expression and generating variation in mRNA and protein isoforms. Recently, the genetic contribution to transcript isoform variation has been reported in individuals of recent European descent. We report here results of an investigation of the differences in AS patterns between human populations. AS patterns in 176 HapMap lymphoblastoid cell lines derived from individuals of European and African ancestry were evaluated using the Affymetrix GeneChip® Human Exon 1.0 ST Array. A variety of biological processes such as response to stimulus and transcription were found to be enriched among the differentially spliced genes. The differentially spliced genes also include some involved in human diseases that have different prevalence or susceptibility between populations. The genetic contribution to the population differences in transcript isoform variation was then evaluated by a genome-wide association using the HapMap genotypic data on single nucleotide polymorphisms (SNPs). The results suggest that local and distant genetic variants account for a substantial fraction of the observed transcript isoform variation between human populations. Our findings provide new insights into the complexity of the human genome as well as the health disparities between the two populations.

Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines

We demonstrate a method for the prediction of chemotherapeutic response in patients using only before-treatment baseline tumor gene expression data. First, we fitted models for whole-genome gene expression against drug sensitivity in a large panel of cell lines, using a method that allows every gene to influence the prediction. Following data homogenization and filtering, these models were applied to baseline expression levels from primary tumor biopsies, yielding an in vivo drug sensitivity prediction. We validated this approach in three independent clinical trial datasets, and obtained predictions equally good, or better than, gene signatures derived directly from clinical data.

Population-specific genetic variants important in susceptibility to cytarabine arabinoside cytotoxicity

Cytarabine arabinoside (ara-C) is an antimetabolite used to treat hematologic malignancies. Resistance is a common reason for treatment failure with adverse side effects contributing to morbidity and mortality. Identification of genetic factors important in susceptibility to ara-C cytotoxicity may allow for individualization of treatment. We used an unbiased whole-genome approach using lymphoblastoid cell lines derived from persons of European (CEU) or African (YRI) ancestry to identify these genetic factors. We interrogated more than 2 million single nucleotide polymorphisms (SNPs) for association with susceptibility to ara-C and narrowed our focus by concentrating on SNPs that affected gene expression. We identified a unique pharmacogenetic signature consisting of 4 SNPs explaining 51% of the variability in sensitivity to ara-C among the CEU and 5 SNPs explaining 58% of the variation among the YRI. Population-specific signatures were secondary to either (1) polymorphic SNPs in one population but monomorphic in the other, or (2) significant associations of SNPs with cytotoxicity or gene expression in one population but not the other. We validated the gene expression-cytotoxicity relationship for a subset of genes in a separate group of lymphoblastoid cell lines. These unique genetic signatures comprise novel genes that can now be studied further in functional studies.

Genetic variants associated with carboplatin-induced cytotoxicity in cell lines derived from Africans

To gain a better understanding of the genetic variants associated with carboplatin-induced cytotoxicity in individuals of African descent, we present a step-wise approach integrating genotypes, gene expression, and sensitivity of HapMap cell lines to carboplatin. Cell lines derived from 30 trios of African descent (YRI) were used to develop a preclinical model to identify genetic variants and gene expression that contribute to carboplatin-induced cytotoxicity. Cytotoxicity was determined as cell growth inhibition at increasing concentrations of carboplatin for 72 h. Gene expression of 89 HapMap YRI cell lines was determined using the Affymetrix GeneChip Human Exon 1.0 ST Array. Single nucleotide polymorphism genotype and the percent survival at different treatment concentrations along with carboplatin IC50 were linked through whole genome association. A second association test was done between single nucleotide polymorphism genotype and gene expression, and linear regression was then used to capture those genes whose expression correlated to drug sensitivity phenotypes. This approach allows us to identify genetic variants that significantly associate with sensitivity to the cytotoxic effects of carboplatin through their effect on gene expression. We found a gene (GPC5) whose expression is important in all carboplatin treatment concentrations as well as many genes unique to either low (e.g., MAPK1) or high (e.g., BRAF, MYC, and BCL2L1) concentrations of drug. Our whole genome approach enables us to evaluate the contribution of genetic and gene expression variation to a wide range of cellular phenotypes. The identification of concentration specific genetic signatures allows for potential integration of pharmacokinetics, pharmacodynamics, and pharmacogenetics in tailoring chemotherapy. [Mol Cancer Ther 2008;7(9):3038–46]

Pharmacogenetics and pharmacogenomics: a bridge to individualized cancer therapy.

In the past decade, advances in pharmacogenetics and pharmacogenomics (PGx) have gradually unveiled the genetic basis of interindividual differences in drug responses. A large portion of these advances have been made in the field of anticancer therapy. Currently, the US FDA has updated the package inserts of approximately 30 anticancer agents to include PGx information. Given the complexity of this genetic information (e.g., tumor mutation and gene overexpression, chromosomal translocation and germline variations), as well as the variable level of scientific evidence, the FDA recommendation and potential action needed varies among drugs. In this review, we have highlighted some of these PGx discoveries for their scientific values and utility in improving therapeutic efficacy and reducing side effects. Furthermore, examples are also provided for the role of PGx in new anticancer drug development by revealing novel druggable targets.