Genome-wide discovery of loci influencing chemotherapy cytotoxicity

Solvent system effects on the physical and mechanical properties of electrospun Poly(ε-caprolactone) scaffolds for in vitro lung models

Mechanical properties are among the key considerations for the design and fabrication of complex tissue models and implants. In addition to the choice of material and the processing technique, the solvent system can significantly influence the mechanical properties of scaffolds. Poly(ε-caprolactone) (PCL) has been abundantly used to develop constructs, fibrous in particular, for pharmaceutical and biomedical research due to the flexibility offered by PCL-based fibrous matrices. The effect of solvent type on the morphological features of electrospun fibres has been extensively studied. Nevertheless, comprehensive studies on the impact of the solvent system on the mechanical properties of electrospun PCL fibres are lacking. This study elucidates the relationship between topographical, physical and mechanical properties of electrospun PCL fibrous meshes upon using various solvent systems. The results of the mechanical investigation highlight the significance of inter-fibre bonds on the mechanical properties of the bulk membranes and that the option of altering the solvent system composition could be considered for tuning the mechanical properties of the PCL scaffolds to serve specific biomedical application requirements. The applicability of the developed membranes as artificial ECM (Extracellular matrix) in the lung will then be investigated and compared to the commercial Polycarbonate (PC) membranes that are often used for in vitro lung models.

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

Cancer patients exhibit a broad range of inter-individual variability in response and toxicity to widely used anticancer drugs, and genetic variation is a major contributor to this variability. To identify new genes that influence the response of 44 FDA-approved anticancer drug treatments widely used to treat various types of cancer, we conducted high-throughput screening and genome-wide association mapping using 680 lymphoblastoid cell lines from the 1000 Genomes Project. The drug treatments considered in this study represent nine drug classes widely used in the treatment of cancer in addition to the paclitaxel + epirubicin combination therapy commonly used for breast cancer patients. Our genome-wide association study (GWAS) found several significant and suggestive associations. We prioritized consistent associations for functional follow-up using gene-expression analyses. The NAD(P)H quinone dehydrogenase 1 (NQO1) gene was found to be associated with the dose-response of arsenic trioxide, erlotinib, trametinib, and a combination treatment of paclitaxel + epirubicin. NQO1 has previously been shown as a biomarker of epirubicin response, but our results reveal novel associations with these additional treatments. Baseline gene expression of NQO1 was positively correlated with response for 43 of the 44 treatments surveyed. By interrogating the functional mechanisms of this association, the results demonstrate differences in both baseline and drug-exposed induction.

In the burgeoning field of personalized medicine, genetic variation is recognized as a major contributor to patients’ differential responses to drugs. Lymphoblastoid cell lines (LCLs) are a consistent and convenient representation of cells used for in vitro research. Human genome sequencing with LCLs can identify new genes that influence individuals’ drug responses, including the dose-response relationship, which describes the relationship between physiological response and the amount of exposure to a substance. In this work, we conduct high-throughput screening and genome-wide association mapping using 680 LCLs from the 1000 Genomes Project to identify new genes that influence individual response to 44 widely used anticancer drugs. We found the NQO1 gene to be associated with the dose-response of several drugs, namely arsenic trioxide, erlotinib, trametinib, and the paclitaxel + epirubicin combination, and performed follow-up analyses to better understand its functional role in drug response. Our results indicate NQO1 expression is correlated with increased drug resistance and provide some evidence that SNP rs1800566 influences drug response by altering protein activity for these four treatments. With further research, NQO1 has potential use as a therapeutic target, for example, suppressing NQO1 expression to increase sensitivity to particular drugs.

The Road so Far in Colorectal Cancer Pharmacogenomics: Are We Closer to Individualised Treatment?

In recent decades, survival rates in colorectal cancer have improved greatly due to pharmacological treatment. However, many patients end up developing adverse drug reactions that can be severe or even life threatening, and that affect their quality of life. These remain a limitation, as they may force dose reduction or treatment discontinuation, diminishing treatment efficacy. From candidate gene approaches to genome-wide analysis, pharmacogenomic knowledge has advanced greatly, yet there is still huge and unexploited potential in the use of novel technologies such as next-generation sequencing strategies. This review summarises the road of colorectal cancer pharmacogenomics so far, presents considerations and directions to be taken for further works and discusses the path towards implementation into clinical practice.

Common genetic predisposition for heart failure and cancer

Cardiovascular diseases and cancer are major causes of mortality in industrialized societies. They share common risk factors (e.g., genetics, lifestyle, age, infection, toxins, and pollution) and might also mutually promote the onset of the respective other disease. Cancer can affect cardiac function directly while antitumor therapies may have acute- and/or late-onset cardiotoxic effects. Recent studies suggest that heart failure might promote tumorigenesis and tumor progression. In both cancer and cardiovascular diseases, genetic predisposition is implicated in the disease onset and development. In this regard, genetic variants classically associated with cardiomyopathies increase the risk for toxic side effects on the cardiovascular system. Genetic variants associated with increased cancer risk are frequent in patients with peripartum cardiomyopathy complicated by cancer, pointing to a common genetic predisposition for both diseases. Common risk factors, cardiotoxic antitumor treatment, genetic variants (associated with cardiomyopathies and/or cancer), and increased cardiac stress lead us to propose the "multi-hit hypothesis" linking cancer and cardiovascular diseases. In the present review, we summarize the current knowledge on potential connecting factors between cancer and cardiovascular diseases with a major focus on the role of genetic predisposition and its implication for individual therapeutic strategies and risk assessment in the novel field of oncocardiology.

Association of Genetic Variants at TRPC6 With Chemotherapy-Related Heart Failure

Background: Our previous GWAS identified genetic variants at six novel loci that were associated with a decline in left ventricular ejection fraction (LVEF), p < 1 × 10⁻⁵ in 1,191 early breast cancer patients from the N9831 clinical trial of chemotherapy plus trastuzumab. In this study we sought replication of these loci.

Methods: We tested the top loci from the GWAS for association with chemotherapy-related heart failure (CRHF) using 26 CRHF cases from N9831 and 984 patients from the Mayo Clinic Biobank which included CRHF cases (N = 12) and control groups of patients treated with anthracycline +/– trastuzumab without HF (N = 282) and patients with HF that were never treated with anthracycline or trastuzumab (N = 690). We further examined associated loci in the context of gene expression and rare coding variants using a TWAS approach in heart left ventricle and Sanger sequencing, respectively. Doxorubicin-induced apoptosis and cardiomyopathy was modeled in human iPSC-derived cardiomyocytes and endothelial cells and a mouse model, respectively, that were pre-treated with GsMTx-4, an inhibitor of TRPC6.

Results:TRPC6 5′ flanking variant rs57242572-T was significantly more frequent in cases compared to controls, p = 0.031, and rs61918162-T showed a trend for association, p = 0.065. The rs61918162 T-allele was associated with higher TRPC6 expression in the heart left ventricle. We identified a single TRPC6 rare missense variant (rs767086724, N338S, prevalence 0.0025% in GnomAD) in one of 38 patients (2.6%) with CRHF. Pre-treatment of cardiomyocytes and endothelial cells with GsMTx4 significantly reduced doxorubicin-induced apoptosis. Similarly, mice treated with GsMTx4 had significantly improved doxorubicin-induced cardiac dysfunction.

Conclusions: Genetic variants that are associated with increased TRPC6 expression in the heart and rare TRPC6 missense variants may be clinically useful as risk factors for CRHF. GsMTx-4 may be a cardioprotective agent in patients with TRPC6 risk variants. Replication of the genetic associations in larger well-characterized samples and functional studies are required.

Genetic variation in the ATP binding cassette transporter ABCC10 is associated with neutropenia for docetaxel in Japanese lung cancer patients cohort

Background

Docetaxel is a widely used cytotoxic agent for treatments of various cancers. The ATP binding cassette (ABC) transporter / multidrug resistance protein (MRP) ABCC10/MRP7, involved in transporting taxanes, has been associated with resistance to these agents. Since genetic variation in drug transporters may affect clinical outcomes, we examined whether polymorphism of ABCC10 could affect clinical responses to docetaxel.

Methods

Using 18 NSCLC cell lines and CRISPR-based genome-edited HeLa cells, we analyzed whether genetic variants of ABCC10 (rs2125739, rs9349256) affected cytotoxicity to docetaxel. Subsequently, we analyzed genetic variants [ABCC10 (rs2125739), ABCB1 (C1236T, C3435T, G2677 T/A), ABCC2 (rs12762549), and SLCO1B3 (rs11045585)] in 69 blood samples of NSCLC patients treated with docetaxel monotherapy. Clinical outcomes were evaluated between genotype groups.

Results

In the cell lines, only one genetic variant (rs2125739) was significantly associated with docetaxel cytotoxicity, and this was confirmed in the genome-edited cell line. In the 69 NSCLC patients, there were no significant differences related to rs2125739 genotype in terms of RR, PFS, or OS. However, this SNP was associated with grade 3/4 neutropenia (T/C group 60% vs. T/T group 87%; P = 0.028). Furthermore, no patient with a T/C genotype experienced febrile neutropenia.

Conclusions

Our results indicate that genetic variation in the ABCC10 gene is associated with neutropenia for docetaxel treatment.

Pharmacogenetics of Chemotherapy-Induced Cardiotoxicity

PURPOSE OF REVIEW

The goal of this review is to summarize current understanding of pharmacogenetics and pharmacogenomics in chemotherapy-induced cardiotoxicity.

RECENT FINDINGS

Most of the studies rely on in vitro cytotoxic assays. There have been several smaller scale candidate gene approaches and a handful of genome-wide studies linking genetic variation to susceptibility to chemotherapy-induced cardiotoxicity. Currently, pharmacogenomic testing of all childhood cancer patients with an indication for doxorubicin or daunorubicin therapy for RARG rs2229774, SLC28A3 rs7853758, and UGT1A6*4 rs17863783 variants is recommended. There is no recommendation regarding testing in adults. There is clear evidence pointing to the role of pharmacogenetics and pharmacogenomics in cardiotoxicity susceptibility to chemotherapeutic agents. Larger scale studies are needed to further identify susceptibility markers and to develop pharmacogenomics-based risk profiling to improve quality of life and life expectancy in cancer survivors.

Incorporating population-level genetic variability within laboratory models in toxicology: From the individual to the population

Humans respond to chemical exposures differently due to many factors, such as previous and concurrent stressors, age, sex, and genetic background. The vast majority of laboratory-based toxicology studies, however, have not considered the impact of population-level variability within dose-response relationships. The lack of data dealing with the influence of genetic diversity on the response to chemical exposure provides a difficult challenge for risk assessment as individuals within the population will display a wide-range of responses following toxicant challenge. Notably, the genetic background of individuals plays a major role in the variability seen in a population-level response to a drug or chemical and, thus, there is growing interest in including genetic diversity into laboratory-models. Here we outline several laboratory-based models that can be used to assay the influence of genetic variability on an individual's response to chemicals: 1) genetically-diverse cell lines, 2) human primary cells, 3) and genetically-diverse mouse panels. We also provide a succinct review for several seminal studies to highlight the capability, feasibility, and power of each of these models. This article is intended to highlight the need to include population-level genetic diversity into toxicological study designs via laboratory-based models with the goal to provide and supplement evidence in assessing the risk posed by chemicals to the human population. As such, incorporation of genetic variability will positively impact human-based risk assessment and provide empirical data to aid and influence decision-making processes in relation to chemical exposures.

Gene expression and linkage analysis implicate CBLB as a mediator of rituximab resistance

Elucidating resistance mechanisms for therapeutic monoclonal antibodies (MAbs) is challenging, because they are difficult to study in non-human models. We therefore developed a strategy to genetically map in vitro drug sensitivity, identifying genes that alter responsiveness to rituximab, a therapeutic anti-CD20 MAb that provides significant benefit to patients with B-cell malignancies. We discovered novel loci with genome-wide mapping analyses and functionally validated one of these genes, CBLB, which causes rituximab resistance when knocked down in lymphoma cells. This study demonstrates the utility of genome-wide mapping to discover novel biological mechanisms of potential clinical advantage.

Rationally Designed 2-in-1 Nanoparticles Can Overcome Adaptive Resistance in Cancer

The development of resistance is the major cause of mortality in cancer. Combination chemotherapy is used clinically to reduce the probability of evolution of resistance. A similar trend toward the use of combinations of drugs is also emerging in the application of cancer nanomedicine. However, should a combination of two drugs be delivered from a single nanoparticle or should they be delivered in two different nanoparticles for maximal efficacy? We explored these questions in the context of adaptive resistance, which emerges as a phenotypic response of cancer cells to chemotherapy. We studied the phenotypic dynamics of breast cancer cells under cytotoxic chemotherapeutic stress and analyzed the data using a phenomenological mathematical model. We demonstrate that cancer cells can develop adaptive resistance by entering into a predetermined transitional trajectory that leads to phenocopies of inherently chemoresistant cancer cells. Disrupting this deterministic program requires a unique combination of inhibitors and cytotoxic agents. Using two such combinations, we demonstrate that a 2-in-1 nanomedicine can induce greater antitumor efficacy by ensuring that the origins of adaptive resistance are terminated by deterministic spatially constrained delivery of both drugs to the target cells. In contrast, a combination of free-form drugs or two nanoparticles, each carrying a single payload, is less effective, arising from a stochastic distribution to cells. These findings suggest that 2-in-1 nanomedicines could emerge as an important strategy for targeting adaptive resistance, resulting in increased antitumor efficacy.

Germline polymorphisms in an enhancer of PSIP1 are associated with progression-free survival in epithelial ovarian cancer

Women with epithelial ovarian cancer (EOC) are usually treated with platinum/taxane therapy after cytoreductive surgery but there is considerable inter-individual variation in response. To identify germline single-nucleotide polymorphisms (SNPs) that contribute to variations in individual responses to chemotherapy, we carried out a multi-phase genome-wide association study (GWAS) in 1,244 women diagnosed with serous EOC who were treated with the same first-line chemotherapy, carboplatin and paclitaxel. We identified two SNPs (rs7874043 and rs72700653) in TTC39B (best P=7x10-5, HR=1.90, for rs7874043) associated with progression-free survival (PFS). Functional analyses show that both SNPs lie in a putative regulatory element (PRE) that physically interacts with the promoters of PSIP1, CCDC171 and an alternative promoter of TTC39B. The C allele of rs7874043 is associated with poor PFS and showed increased binding of the Sp1 transcription factor, which is critical for chromatin interactions with PSIP1. Silencing of PSIP1 significantly impaired DNA damage-induced Rad51 nuclear foci and reduced cell viability in ovarian cancer lines. PSIP1 (PC4 and SFRS1 Interacting Protein 1) is known to protect cells from stress-induced apoptosis, and high expression is associated with poor PFS in EOC patients. We therefore suggest that the minor allele of rs7874043 confers poor PFS by increasing PSIP1 expression.

Identification of genetic variants or genes that are associated with Homoharringtonine (HHT) response through a genome-wide association study in human lymphoblastoid cell lines (LCLs)

Homoharringtonine (HHT) has been widely used in China to treat patients with acute and chronic myeloid leukemia for decades. Since response to HHT varies among patients, our study aimed to identify biomarkers that might influence the response to HHT using a panel of various human lymphoblastoid cell lines (LCLs). Genome-wide association (GWA) analysis using single nucleotide polymorphism (SNP) and mRNA expression data was assessed for association with cytotoxicity to HHT in LCLs. Integrated analysis among SNPs, expression, AUC value was also performed to help select candidate genes for further functional characterization. Functional validation of candidate genes was performed using leukemia cell lines (U937, K562). Candidate genes were knocked down using specific siRNA and its response to HHT was assessed using MTS assay. We found that 15 expression probes were associated with HHT AUC with P < 10(-4), and 96 individual probe sets with P < 10(-3). Eighteen SNPs were associated with HHT AUC with P < 10(-5) and 281 SNPs with P < 10(-4). The integrated analysis identified 4 unique SNPs that were associated with both expression and AUC. Functional validation using siRNA knockdown in leukemia cell lines showed that knocking down CCDC88A, CTBP2, SOCS4 genes in U937 and K562 cells significantly altered HHT cytotoxicity. In summary, this study performed with LCLs can help to identify novel biomarker that might contribute to variation in response to HHT therapy.

Germline oncopharmacogenetics, a promising field in cancer therapy

Pharmacogenetics (PGx) is the study of the relationship between inter-individual genetic variation and drug responses. Germline variants of genes involved in drug metabolism, drug transport, and drug targets can affect individual response to medications. Cancer therapies are characterized by an intrinsically high toxicity; therefore, the application of pharmacogenetics to cancer patients is a particularly promising method for avoiding the use of inefficacious drugs and preventing the associated adverse effects. However, despite continuing efforts in this field, very few labels include information about germline genetic variants associated with drug responses. DPYD, TPMT, UGT1A1, G6PD, CYP2D6, and HLA are the sole loci for which the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) report specific information. This review highlights the germline PGx variants that have been approved to date for anticancer treatments, and also provides some insights about other germline variants with potential clinical applications. The continuous and rapid evolution of next-generation sequencing applications, together with the development of computational methods, should help to refine the implementation of personalized medicine. One day, clinicians may be able to prescribe the best treatment and the correct drug dosage based on each patient's genotype. This approach would improve treatment efficacy, reduce toxicity, and predict non-responders, thereby decreasing chemotherapy-associated morbidity and improving health benefits.

Identification of genetic variants associated with capecitabine-induced hand-foot syndrome through integration of patient and cell line genomic analyses

OBJECTIVE

A primary challenge in identifying replicable pharmacogenomic markers from clinical genomewide association study (GWAS) trials in oncology is the difficulty in performing a second large clinical trial with the same drugs and dosage regimen. We sought to overcome this challenge by incorporating GWAS results from cell-based studies using the same chemotherapy as a clinical cohort.

METHODS

In this study, we test whether the overlap between genetic variants identified in a preclinical study and a clinical study on capecitabine is more than expected by chance. A GWAS of capecitabine-induced cytotoxicity was performed in 164 lymphoblastoid cell lines derived from the CEU HapMap population and compared with a GWAS of hand-foot syndrome (HFS), the most frequent capecitabine-induced adverse drug reaction, in Spanish breast and colorectal cancer patients (n=160) treated with capecitabine.

RESULTS

We observed an overlap of 16 single nucleotide polymorphisms associated with capecitabine-induced cytotoxicity (P<0.001) in lymphoblastoid cell lines and HFS (P<0.05) in patients, which is a greater overlap than expected by chance (genotype-phenotype permutation empirical P=0.015). Ten tag single nucleotide polymorphisms, which cover the overlap loci, were genotyped in a second patient cohort (n=85) and one of them, rs9936750, was associated with capecitabine-induced HFS (P=0.0076).

CONCLUSION

The enrichment results imply that cellular models of capecitabine-induced cytotoxicity may capture components of the underlying polygenic architecture of related toxicities in patients.

Genomic architecture of pharmacological efficacy and adverse events

The pharmacokinetic and pharmacodynamic disciplines address pharmacological traits, including efficacy and adverse events. Pharmacogenomics studies have identified pervasive genetic effects on treatment outcomes, resulting in the development of genetic biomarkers for optimization of drug therapy. Pharmacogenomics-based tests are already being applied in clinical decision making. However, despite substantial progress in identifying the genetic etiology of pharmacological response, current biomarker panels still largely rely on single gene tests with a large portion of the genetic effects remaining to be discovered. Future research must account for the combined effects of multiple genetic variants, incorporate pathway-based approaches, explore gene-gene interactions and nonprotein coding functional genetic variants, extend studies across ancestral populations, and prioritize laboratory characterization of molecular mechanisms. Because genetic factors can play a key role in drug response, accurate biomarker tests capturing the main genetic factors determining treatment outcomes have substantial potential for improving individual clinical care.

Replication of genetic polymorphisms reported to be associated with taxane-related sensory neuropathy in patients with early breast cancer treated with Paclitaxel

PURPOSE

Associations between taxane-related sensory neuropathy (TRSN) and single-nucleotide polymorphisms (SNP) have previously been reported, but few have been replicated in large, independent validation studies. This study evaluates the association between previously investigated SNPs and TRSN, using genotype data from a study of chemotherapy-related toxicity in patients with breast cancer.

EXPERIMENTAL DESIGN

We investigated 73 SNPs in 50 genes for their contribution to TRSN risk, using genotype data from 1,303 European patients. TRSN was assessed using National Cancer Institute common toxicity criteria for adverse events classification. Unconditional logistic regression evaluated the association between each SNP and TRSN risk (primary analysis). Cox regression analysis assessed the association between each SNP and cumulative taxane dose causing the first reported moderate/severe TRSN (secondary analysis). The admixture likelihood (AML) test, which considers all SNPs with a prior probability of association with TRSN together, tested the hypothesis that certain SNPs are truly associated.

RESULTS

The AML test provided strong evidence for the association of some SNPs with TRSN (P = 0.023). The two most significantly associated SNPs were rs3213619(ABCB1) [OR = 0.47; 95% confidence interval (CI), 0.28-0.79; P = 0.004] and rs9501929(TUBB2A) (OR = 1.80; 95% CI, 1.20-2.72; P = 0.005). A further 9 SNPs were significant at P-value ≤ 0.05.

CONCLUSION

This is currently the largest study investigating SNPs associated with TRSN. We found strong evidence that SNPs within genes in taxane pharmacokinetic and pharmacodynamic pathways contribute to TRSN risk. However, a large proportion of the inter-individual variability in TRSN remains unexplained. Further validated results from GWAS will help to identify new pathways, genes, and SNPs involved in TRSN susceptibility.

ATHENA: the analysis tool for heritable and environmental network associations

MOTIVATION

Advancements in high-throughput technology have allowed researchers to examine the genetic etiology of complex human traits in a robust fashion. Although genome-wide association studies have identified many novel variants associated with hundreds of traits, a large proportion of the estimated trait heritability remains unexplained. One hypothesis is that the commonly used statistical techniques and study designs are not robust to the complex etiology that may underlie these human traits. This etiology could include non-linear gene × gene or gene × environment interactions. Additionally, other levels of biological regulation may play a large role in trait variability.

RESULTS

To address the need for computational tools that can explore enormous datasets to detect complex susceptibility models, we have developed a software package called the Analysis Tool for Heritable and Environmental Network Associations (ATHENA). ATHENA combines various variable filtering methods with machine learning techniques to analyze high-throughput categorical (i.e. single nucleotide polymorphisms) and quantitative (i.e. gene expression levels) predictor variables to generate multivariable models that predict either a categorical (i.e. disease status) or quantitative (i.e. cholesterol levels) outcomes. The goal of this article is to demonstrate the utility of ATHENA using simulated and biological datasets that consist of both single nucleotide polymorphisms and gene expression variables to identify complex prediction models. Importantly, this method is flexible and can be expanded to include other types of high-throughput data (i.e. RNA-seq data and biomarker measurements).

AVAILABILITY

ATHENA is freely available for download. The software, user manual and tutorial can be downloaded from http://ritchielab.psu.edu/ritchielab/software.

Modular network construction using eQTL data: an analysis of computational costs and benefits

Background: In this paper, we consider analytic methods for the integrated analysis of genomic DNA variation and mRNA expression (also named as eQTL data), to discover genetic networks that are associated with a complex trait of interest. Our focus is the systematic evaluation of the trade-off between network size and network search efficiency in the construction of these networks.

Results: We developed a modular approach to network construction, building from smaller networks to larger ones, thereby reducing the search space while including more variables in the analysis. The goal is achieving a lower computational cost while maintaining high confidence in the resulting networks. As demonstrated in our simulation results, networks built in this way have low node/edge false discovery rate (FDR) and high edge sensitivity comparing to greedy search. We further demonstrate our method in a data set of cellular responses to two chemotherapeutic agents: docetaxel and 5-fluorouracil (5-FU), and identify biologically plausible networks that might describe resistances to these drugs.

Conclusion: In this study, we suggest that guided comprehensive searches for parsimonious networks should be considered as an alternative to greedy network searches.

Capecitabine–docetaxel combination treatment

Metastatic breast cancer develops in approximately 50% of women diagnosed with breast cancer. The optimal treatment for patients with metastatic breast cancer has yet to be defined, owing to the heterogeneity of this group and the available agents. Patients with metastatic breast cancer often receive single-agent treatment in sequence as it is unclear whether combination therapy with cytotoxic drugs offers an overall disease-free survival benefit and single agents may offer less toxicity. The advantages of combination cytotoxic therapies have included higher response rates. However, such trials have not stratified on rapidity of disease progression or on tumor bulk. In previous studies, docetaxel is one of the few cytotoxic agents to demonstrate a survival benefit in anthracycline-resistant patients and thus it has become a vital component of cytotoxic therapy. Capecitabine is also an important oral drug and has demonstrated activity in patients pretreated with anthracyclines and taxanes. Recent preclinical and clinical trials of this combination have demonstrated an increased time to tumor progression and overall survival benefit. Paclitaxel combined with gemcitabine has been compared with docetaxel plus capecitabine, with similar response rates and survival benefits. As patients on these trials have not received uniform crossover to the other active agent, whether or not the combination therapy offers an advantage for the entire cohort of metastatic patients or may be indicated for specific subgroups remains uncertain. Combination treatments may be preferable to sequential therapy for patients requiring urgent reduction in their tumor burden. Combinations of cytotoxic agents in combination with biological agents are currently being defined.

Beyond IC50s: Towards Robust Statistical Methods for in vitro Association Studies

Cell line cytotoxicity assays have become increasingly popular approaches for genetic and genomic studies of differential cytotoxic response. There are an increasing number of success stories, but relatively little evaluation of the statistical approaches used in such studies. In the vast majority of these studies, concentration response is summarized using curve-fitting approaches, and then summary measure(s) are used as the phenotype in subsequent genetic association studies. The curve is usually summarized by a single parameter such as the curve's inflection point (e.g. the EC/IC₅₀). Such modeling makes major assumptions and has statistical limitations that should be considered. In the current review, we discuss the limitations of the EC/IC₅₀ as a phenotype in association studies, and highlight some potential limitations with a simulation experiment. Finally, we discuss some alternative analysis approaches that have been shown to be more robust.

Implications of genome-wide association studies in cancer therapeutics

Genome wide association studies (GWAS) provide an agnostic approach to identifying potential genetic variants associated with disease susceptibility, prognosis of survival and/or predictive of drug response. Although these techniques are costly and interpretation of study results is challenging, they do allow for a more unbiased interrogation of the entire genome, resulting in the discovery of novel genes and understanding of novel biological associations. This review will focus on the implications of GWAS in cancer therapy, in particular germ-line mutations, including findings from major GWAS which have identified predictive genetic loci for clinical outcome and/or toxicity. Lessons and challenges in cancer GWAS are also discussed, including the need for functional analysis and replication, as well as future perspectives for biological and clinical utility. Given the large heterogeneity in response to cancer therapeutics, novel methods of identifying mechanisms and biology of variable drug response and ultimately treatment individualization will be indispensable.

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.

Delivering systems pharmacogenomics towards precision medicine through mathematics

The latest developments of pharmacology in the post-genomic era foster the emergence of new biomarkers that represent the future of drug targets. To identify these biomarkers, we need a major shift from traditional genomic analyses alone, moving the focus towards systems approaches to elucidating genetic variation in biochemical pathways of drug response. Is there any general model that can accelerate this shift via a merger of systems biology and pharmacogenomics? Here we describe a statistical framework for mapping dynamic genes that affect drug response by incorporating its pharmacokinetic and pharmacodynamic pathways. This framework is expanded to shed light on the mechanistic and therapeutic differences of drug response based on pharmacogenetic information, coupled with genomic, proteomic and metabolic data, allowing novel therapeutic targets and genetic biomarkers to be characterized and utilized for drug discovery.

Genetic basis for the increased expression of vacuolar H+ translocating ATPase genes upon imatinib treatment in human lymphoblastoid cells

PURPOSE

The role of v-ATPases in cancer biology is being increasingly recognized. Yeast studies indicate that the tyrosine kinase inhibitor imatinib may interact with the v-ATPase genes and alter the course of cancer progression. Data from humans in this regard are lacking.

METHODS

We constructed 55 lymphoblastoid cell lines from pedigreed, cancer-free human subjects and treated them with IC20 concentration of imatinib mesylate. Using these cell lines, we (i) estimated the heritability and differential expression of 19 genes encoding several subunits of the v-ATPase protein in response to imatinib treatment; (ii) estimated the genetic similarity among these genes; and (iii) conducted a high-density scan to find cis-regulating genetic variation associated with differential expression of these genes.

RESULTS

We found that the imatinib response of the genes encoding v-ATPase subunits is significantly heritable and can be clustered to identify novel drug targets in imatinib therapy. Further, five of these genes were significantly cis-regulated and together represented nearly half-log fold change in response to imatinib (p = 0.0107) that was homogenous (p = 0.2598).

CONCLUSIONS

Our results proffer support to the growing view that personalized regimens using proton pump inhibitors or v-ATPase inhibitors may improve outcomes of imatinib therapy in various cancers.

Allele-specific behavior of molecular networks: understanding small-molecule drug response in yeast

The study of systems genetics is changing the way the genetic and molecular basis of phenotypic variation, such as disease susceptibility and drug response, is being analyzed. Moreover, systems genetics aids in the translation of insights from systems biology into genetics. The use of systems genetics enables greater attention to be focused on the potential impact of genetic perturbations on the molecular states of networks that in turn affects complex traits. In this study, we developed models to detect allele-specific perturbations on interactions, in which a genetic locus with alternative alleles exerted a differing influence on an interaction. We utilized the models to investigate the dynamic behavior of an integrated molecular network undergoing genetic perturbations in yeast. Our results revealed the complexity of regulatory relationships between genetic loci and networks, in which different genetic loci perturb specific network modules. In addition, significant within-module functional coherence was found. We then used the network perturbation model to elucidate the underlying molecular mechanisms of individual differences in response to 100 diverse small molecule drugs. As a result, we identified sub-networks in the integrated network that responded to variations in DNA associated with response to diverse compounds and were significantly enriched for known drug targets. Literature mining results provided strong independent evidence for the effectiveness of these genetic perturbing networks in the elucidation of small-molecule responses in yeast.

Multivariate methods and software for association mapping in dose-response genome-wide association studies

BACKGROUND

The large sample sizes, freedom of ethical restrictions and ease of repeated measurements make cytotoxicity assays of immortalized lymphoblastoid cell lines a powerful new in vitro method in pharmacogenomics research. However, previous studies may have over-simplified the complex differences in dose-response profiles between genotypes, resulting in a loss of power.

METHODS

The current study investigates four previously studied methods, plus one new method based on a multivariate analysis of variance (MANOVA) design. A simulation study was performed using differences in cancer drug response between genotypes for biologically meaningful loci. These loci also showed significance in separate genome-wide association studies. This manuscript builds upon a previous study, where differences in dose-response curves between genotypes were constructed using the hill slope equation.

CONCLUSION

Overall, MANOVA was found to be the most powerful method for detecting real signals, and was also the most robust method for detection using alternatives generated with the previous simulation study. This method is also attractive because test statistics follow their expected distributions under the null hypothesis for both simulated and real data. The success of this method inspired the creation of the software program MAGWAS. MAGWAS is a computationally efficient, user-friendly, open source software tool that works on most platforms and performs GWASs for individuals having multivariate responses using standard file formats.

Integration of cell line and clinical trial genome-wide analyses supports a polygenic architecture of Paclitaxel-induced sensory peripheral neuropathy

PURPOSE

We sought to show the relevance of a lymphoblastoid cell line (LCL) model in the discovery of clinically relevant genetic variants affecting chemotherapeutic response by comparing LCL genome-wide association study (GWAS) results to clinical GWAS results.

EXPERIMENTAL DESIGN

A GWAS of paclitaxel-induced cytotoxicity was conducted in 247 LCLs from the HapMap Project and compared with a GWAS of sensory peripheral neuropathy in patients with breast cancer (n = 855) treated with paclitaxel in the Cancer and Leukemia Group B (CALGB) 40101 trial. Significant enrichment was assessed by permutation resampling analysis.

RESULTS

We observed an enrichment of LCL cytotoxicity-associated single-nucleotide polymorphisms (SNP) in the sensory peripheral neuropathy-associated SNPs from the clinical trial with concordant allelic directions of effect (empirical P = 0.007). Of the 24 SNPs that overlap between the clinical trial (P < 0.05) and the preclinical cytotoxicity study (P < 0.001), 19 of them are expression quantitative trait loci (eQTL), which is a significant enrichment of this functional class (empirical P = 0.0447). One of these eQTLs is located in RFX2, which encodes a member of the DNA-binding regulatory factor X family. Decreased expression of this gene by siRNA resulted in increased sensitivity of Neuroscreen-1(NS-1; rat pheochromocytoma) cells to paclitaxel as measured by reduced neurite outgrowth and increased cytotoxicity, functionally validating the involvement of RFX2 in nerve cell response to paclitaxel.

CONCLUSIONS

The enrichment results and functional example imply that cellular models of chemotherapeutic toxicity may capture components of the underlying polygenic architecture of related traits in patients.

Pharmacogenomics of chemotherapeutic susceptibility and toxicity

The goal of personalized medicine is to tailor a patient's treatment strategy on the basis of his or her unique genetic make-up. The field of oncology is beginning to incorporate many of the strategies of personalized medicine, especially within the realm of pharmacogenomics, which is the study of how inter-individual genetic variation determines drug response or toxicity. A main objective of pharmacogenomics is to facilitate physician decision-making regarding optimal drug selection, dose and treatment duration on a patient-by-patient basis. Recent advances in genome-wide genotyping and sequencing technologies have supported the discoveries of a number of pharmacogenetic markers that predict response to chemotherapy. However, effectively implementing these pharmacogenetic markers in the clinic remains a major challenge. This review focuses on the contribution of germline genetic variation to chemotherapeutic toxicity and response, and discusses the utility of genome-wide association studies and use of lymphoblastoid cell lines (LCLs) in pharmacogenomic studies. Furthermore, we highlight several recent examples of genetic variants associated with chemotherapeutic toxicity or response in both patient cohorts and LCLs, and discuss the challenges and future directions of pharmacogenomic discovery for cancer treatment.

Cancer pharmacogenomics: strategies and challenges

Genetic variation influences the response of an individual to drug treatments. Understanding this variation has the potential to make therapy safer and more effective by determining selection and dosing of drugs for an individual patient. In the context of cancer, tumours may have specific disease-defining mutations, but a patient's germline genetic variation will also affect drug response (both efficacy and toxicity), and here we focus on how to study this variation. Advances in sequencing technologies, statistical genetics analysis methods and clinical trial designs have shown promise for the discovery of variants associated with drug response. We discuss the application of germline genetics analysis methods to cancer pharmacogenomics with a focus on the special considerations for study design.

A genome-wide association analysis of temozolomide response using lymphoblastoid cell lines shows a clinically relevant association with MGMT

OBJECTIVE

Recently, lymphoblastoid cell lines (LCLs) have emerged as an innovative model system for mapping gene variants that predict the dose response to chemotherapy drugs.

METHODS

In the current study, this strategy was expanded to the in-vitro genome-wide association approach, using 516 LCLs derived from a White cohort to assess the cytotoxic response to temozolomide.

RESULTS

Genome-wide association analysis using ∼2.1 million quality-controlled single-nucleotide polymorphisms (SNPs) identified a statistically significant association (P<10(-8)) with SNPs in the O(6)-methylguanine-DNA methyltransferase (MGMT) gene. We also show that the primary SNP in this region is significantly associated with the differential gene expression of MGMT (P<10(-26)) in LCLs and differential methylation in glioblastoma samples from The Cancer Genome Atlas.

CONCLUSION

The previously documented clinical and functional relationships between MGMT and temozolomide response highlight the potential of well-powered genome-wide association studies of the LCL model system to identify meaningful genetic associations.

Genetic association with overall survival of taxane-treated lung cancer patients - a genome-wide association study in human lymphoblastoid cell lines followed by a clinical association study

Background

Taxane is one of the first line treatments of lung cancer. In order to identify novel single nucleotide polymorphisms (SNPs) that might contribute to taxane response, we performed a genome-wide association study (GWAS) for two taxanes, paclitaxel and docetaxel, using 276 lymphoblastoid cell lines (LCLs), followed by genotyping of top candidate SNPs in 874 lung cancer patient samples treated with paclitaxel.

Methods

GWAS was performed using 1.3 million SNPs and taxane cytotoxicity IC50 values for 276 LCLs. The association of selected SNPs with overall survival in 76 small or 798 non-small cell lung cancer (SCLC, NSCLC) patients were analyzed by Cox regression model, followed by integrated SNP-microRNA-expression association analysis in LCLs and siRNA screening of candidate genes in SCLC (H196) and NSCLC (A549) cell lines.

Results

147 and 180 SNPs were associated with paclitaxel or docetaxel IC50s with p-values <10^-4 in the LCLs, respectively. Genotyping of 153 candidate SNPs in 874 lung cancer patient samples identified 8 SNPs (p-value < 0.05) associated with either SCLC or NSCLC patient overall survival. Knockdown of PIP4K2A, CCT5, CMBL, EXO1, KMO and OPN3, genes within 200 kb up-/downstream of the 3 SNPs that were associated with SCLC overall survival (rs1778335, rs2662411 and rs7519667), significantly desensitized H196 to paclitaxel. SNPs rs2662411 and rs1778335 were associated with mRNA expression of CMBL or PIP4K2A through microRNA (miRNA) hsa-miR-584 or hsa-miR-1468.

Conclusions

GWAS in an LCL model system, joined with clinical translational and functional studies, might help us identify genetic variations associated with overall survival of lung cancer patients treated paclitaxel.

Association of differential gene expression with imatinib mesylate and omacetaxine mepesuccinate toxicity in lymphoblastoid cell lines

BACKGROUND

Imatinib mesylate is currently the drug of choice to treat chronic myeloid leukemia. However, patient resistance and cytotoxicity make secondary lines of treatment, such as omacetaxine mepesuccinate, a necessity. Given that drug cytotoxicity represents a major problem during treatment, it is essential to understand the biological pathways affected to better predict poor drug response and prioritize a treatment regime.

METHODS

We conducted cell viability and gene expression assays to determine heritability and gene expression changes associated with imatinib and omacetaxine treatment of 55 non-cancerous lymphoblastoid cell lines, derived from 17 pedigrees. In total, 48,803 transcripts derived from Illumina Human WG-6 BeadChips were analyzed for each sample using SOLAR, whilst correcting for kinship structure.

RESULTS

Cytotoxicity within cell lines was highly heritable following imatinib treatment (h2 = 0.60-0.73), but not omacetaxine treatment. Cell lines treated with an IC20 dose of imatinib or omacetaxine showed differential gene expression for 956 (1.96%) and 3,892 transcripts (7.97%), respectively; 395 of these (0.8%) were significantly influenced by both imatinib and omacetaxine treatment. k-means clustering and DAVID functional annotation showed expression changes in genes related to kinase binding and vacuole-related functions following imatinib treatment, whilst expression changes in genes related to cell division and apoptosis were evident following treatment with omacetaxine. The enrichment scores for these ontologies were very high (mostly >10).

CONCLUSIONS

Induction of gene expression changes related to different pathways following imatinib and omacetaxine treatment suggests that the cytotoxicity of such drugs may be differentially tolerated by individuals based on their genetic background.

Lymphoblastoid cell lines in pharmacogenomic discovery and clinical translation

The ability to predict how an individual patient will respond to a particular treatment is the ambitious goal of personalized medicine. The genetic make up of an individual has been shown to play a role in drug response. For pharmacogenomic studies, human lymphoblastoid cell lines (LCLs) comprise a useful model system for identifying genetic variants associated with pharmacologic phenotypes. The availability of extensive genotype data for many panels of LCLs derived from individuals of diverse ancestry allows for the study of genetic variants contributing to interethnic and interindividual variation in susceptibility to drugs. Many genome-wide association studies for drug-induced phenotypes have been performed in LCLs, often incorporating gene-expression data. LCLs are also being used in follow-up studies to clinical findings to determine how an associated variant functions to affect phenotype. This review describes the most recent pharmacogenomic findings made in LCLs, including the translation of some findings to clinical cohorts.

Establishment & characterization of lymphoblastoid cell lines from patients with multiple primary neoplasms in the upper aero-digestive tract & healthy individuals

BACKGROUND & OBJECTIVES

A major drawback for genetic studies as well as long-term genotype-phenotype correlation studies in cancer is lack of representative human cell lines providing a continuous source of basic biomolecules and a system to carry out various experimental investigations. This can be overcome to some extent by establishing lymphoblastoid cell lines (LCLs) by infecting peripheral blood lymphocytes with Epstein Barr virus (EBV) which is known to immortalize human resting B cells in vitro giving rise to actively proliferating B-lymphoblastoid cell lines. The present study involves preparation and characterization of LCLs generated from patients with multiple primary neoplasms (MPN) of upper aero-digestive tract (UADT).

METHODS

Thirty seven LCLs were established from UADT MPN patients and healthy age, sex and habit matched controls using EBV crude stock. Characterization was done with respect to expression of CD-19 (Pan B-cell marker), CD3 (T cell specific marker), CD56 (NK-cell specific marker), cell morphology, ploidy analysis, genotype and gene expression comparison with the parent lymphocytes.

RESULTS

LCLs showed rosette morphology with doubling time of approximately 24 h. Ploidy analysis showed diploid DNA content which was maintained for at least 30 population doublings. When compared with parent lymphocytes there appeared no change at genetic and gene expression level.

INTERPRETATION & CONCLUSIONS

Our results show that lymphoblastoid cell lines are a good surrogate of isolated lymphocytes bearing their close resemblance at genetic and phenotypic level to parent lymphocytes and are a valuable resource for understanding genotype-phenotype interactions.

Pharmacogenomic characterization of US FDA-approved cytotoxic drugs

AIMS

Individualization of cancer chemotherapy based on the patient's genetic makeup holds promise for reducing side effects and improving efficacy. However, the relative contribution of genetics to drug response is unknown.

MATERIALS & METHODS

In this study, we investigated the cytotoxic effect of 29 commonly prescribed chemotherapeutic agents from diverse drug classes on 125 lymphoblastoid cell lines derived from 14 extended families.

RESULTS

The results of this systematic study highlight the variable role that genetics plays in response to cytotoxic drugs, ranging from a heritability of <0.15 for gemcitabine to >0.60 for epirubicin.

CONCLUSION

Putative quantitative trait loci for cytotoxic response were identified, as well as drug class-specific signatures, which could indicate possible shared genetic mechanisms. In addition to the identification of putative quantitative trait locis, the results of this study inform the prioritization of chemotherapeutic drugs with a sizable genetic response component for future investigation.

Lymphoblastoid Cell lines: a Continuous in Vitro Source of Cells to Study Carcinogen Sensitivity and DNA Repair

Obtaining a continuous source of normal cells or DNA from a single individual has always been a rate limiting step in biomedical research. Availability of Lymphoblastoid cell lines (LCLs) as a surrogate for isolated or cryopreserved peripheral blood lymphocytes has substantially accelerated the process of biological investigations. LCLs can be established by in vitro infection of resting B cells from peripheral blood with Epstein Barr Virus (EBV) resulting in a continuous source, bearing negligible genetic and phenotypic alterations. Being a spontaneous replicating source, LCLs fulfil the requirement of constant supply of starting material for variety of assays, sparing the need of re-sampling. There is a reason to believe that LCLs are in close resemblance with the parent lymphocytes based on the ample supporting observations from a variety of studies showing significant level of correlation at molecular and functional level. LCLs, which carry the complete set of germ line genetic material, have been instrumental in general as a source of biomolecules and a system to carry out various immunological and epidemiological studies. Furthermore, in recent times their utility for analysing the whole human genome has extensively been documented. This proves the usefulness of LCLs in various genetic and functional studies. There are a few contradictory reports that have questioned the employment of LCLs as parent surrogate. Regardless of some inherent limitations LCLs are increasingly being considered as an important resource for genetic and functional research.

A comparison of association methods for cytotoxicity mapping in pharmacogenomics

Cytotoxicity assays of immortalized lymphoblastoid cell lines (LCLs) represent a promising new in vitro approach in pharmacogenomics research. However, previous studies employing LCLs in gene mapping have used simple association methods, which may not adequately capture the true differences in non-linear response profiles between genotypes. Two common approaches summarize each dose-response curve with either the IC50 or the slope parameter estimates from a hill slope fit and treat these estimates as the response in a linear model. The current study investigates these two methods, as well as four novel methods, and compares their power to detect differences between the response profiles of genotypes under a variety of different alternatives. The four novel methods include two methods that summarize each dose-response by its area under the curve, one method based off of an analysis of variance (ANOVA) design, and one method that compares hill slope fits for all individuals of each genotype. The power of each method was found to depend not only on the choice of alternative, but also on the choice for the set of dosages used in cytotoxicity measurements. The ANOVA-based method was found to be the most robust across alternatives and dosage sets for power in detecting differences between genotypes.

Genomic profiling in CEPH cell lines distinguishes between the camptothecins and indenoisoquinolines

We have attempted to use a familial genetics strategy to study mechanisms of topoisomerase 1 (Top1) inhibition. Investigations have steadily been chipping away at the pathways involved in cellular response following Top1 inhibition for more than 20 years. Our system-wide approach, which phenotypes a collection of genotyped human cell lines for sensitivity to compounds and interrogates all genes and molecular pathways simultaneously. Previously, we characterized the in vitro sensitivity of 15 families of Centre d'Etude Polymorphisme Humain (CEPH) cell lines (n = 142) to 9 camptothecin analogues. Linkage analysis revealed a pattern of 7 quantitative trait loci (QTL) shared by all of the camptothecins. To identify which, if any, QTLs are related to the general mechanism of Top1 inhibition or should be considered camptothecin specific, we characterized the in vitro sensitivity of the same panel of CEPH cell lines to the indenisoquinolones, a structurally distinct class of Top1 inhibitors. Four QTLs on chromosomes 1, 5, 11, and 16 were shared by both the camptothecins and the indenoisoquinolines and are considered associated with the general mechanism of Top1 inhibition. The remaining 3 QTLs (chromosomes 6 and 20) are considered specific to camptothecin-induced cytotoxicity. Finally, 8 QTLs were identified, which were unique to the indenoisoquinolines.

Genome-wide meta-analysis identifies variants associated with platinating agent susceptibility across populations

Platinating agents are used in the treatment of many cancers, yet they can induce toxicities and resistance that limit their utility. Using previously published and additional world population panels of diverse ancestry totaling 608 lymphoblastoid cell lines (LCLs), we performed meta-analyses of over 3 million SNPs for both carboplatin- and cisplatin-induced cytotoxicity. The most significant SNP in the carboplatin meta-analysis is located in an intron of NBAS (p = 5.1 × 10⁻⁷). The most significant SNP in the cisplatin meta-analysis is upstream of KRT16P2 (p = 5.8 × 10⁻⁷). We also show that cisplatin-susceptibility SNPs are enriched for carboplatin-susceptibility SNPs. Most of the variants that associate with platinum-induced cytotoxicity are polymorphic across multiple world populations; therefore, they could be tested in follow-up studies in diverse clinical populations. Seven genes previously implicated in platinating agent response, including BCL2, GSTM1, GSTT1, ERCC2, and ERCC6 were also implicated in our meta-analyses.

Chemotherapeutic-induced apoptosis: a phenotype for pharmacogenomics studies

AIM

To determine whether cellular apoptosis is a suitable phenotypic trait for pharmacogenomics studies by evaluating caspase 3/7-mediated activity in lymphoblastoid cell lines after treatment with six chemotherapeutic agents: 5'-deoxyfluorouridine, pemetrexed, cytarabine, paclitaxel, carboplatin, and cisplatin.

MATERIALS AND METHODS

Using monozygotic twin pair and sibling pair lymphoblastoid cell lines, we identified conditions for measurement of caspase 3/7 activity in lymphoblastoid cell lines. Genome-wide association studies were performed with over 2 million single nucleotide polymorphisms (SNPs) and cisplatin-induced apoptosis in HapMap CEU cell lines (n=77).

RESULTS

Although treatment with 5'-deoxyfluorouridine and pemetrexed for up to 24 h resulted in low levels of apoptosis or interindividual variation in caspase-dependent cell death; paclitaxel, cisplatin, carboplatin, and cytarabine treatment for 24 h resulted in 9.4-fold, 9.1-fold, 7.0-fold, and 6.0-fold increases in apoptosis relative to control, respectively. There was a weak correlation between caspase activity and cytotoxicity (r(2)=0.03-0.29) demonstrating that cytotoxicity and apoptosis are two distinct phenotypes that may produce independent genetic associations. Estimated heritability (h(2)) for apoptosis was 0.57 and 0.29 for cytarabine (5 and 40 μmol/l, respectively), 0.22 for paclitaxel (12.5 nmol/l), and 0.34 for cisplatin (5 μmol/l). In the genome-wide association study using the HapMap CEU panel, we identified a significant enrichment of cisplatin-induced cytotoxicity SNPs within the significant cisplatin-induced apoptosis SNPs and an enrichment of expression quantitative trait loci (eQTL). Among these eQTLs, we identified several eQTLs with known function related to apoptosis and/or cytotoxicity.

CONCLUSION

Our study identifies apoptosis as a phenotype for pharmacogenomic studies in lymphoblastoid cell lines after treatment with paclitaxel, cisplatin, carboplatin, and cytarabine that may have utility for discovering biomarkers to predict response to certain chemotherapeutics.

Genome-wide local ancestry approach identifies genes and variants associated with chemotherapeutic susceptibility in African Americans

Chemotherapeutic agents are used in the treatment of many cancers, yet variable resistance and toxicities among individuals limit successful outcomes. Several studies have indicated outcome differences associated with ancestry among patients with various cancer types. Using both traditional SNP-based and newly developed gene-based genome-wide approaches, we investigated the genetics of chemotherapeutic susceptibility in lymphoblastoid cell lines derived from 83 African Americans, a population for which there is a disparity in the number of genome-wide studies performed. To account for population structure in this admixed population, we incorporated local ancestry information into our association model. We tested over 2 million SNPs and identified 325, 176, 240, and 190 SNPs that were suggestively associated with cytarabine-, 5'-deoxyfluorouridine (5'-DFUR)-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-4)). Importantly, some of these variants are found only in populations of African descent. We also show that cisplatin-susceptibility SNPs are enriched for carboplatin-susceptibility SNPs. Using a gene-based genome-wide association approach, we identified 26, 11, 20, and 41 suggestive candidate genes for association with cytarabine-, 5'-DFUR-, carboplatin-, and cisplatin-induced cytotoxicity, respectively (p≤10(-3)). Fourteen of these genes showed evidence of association with their respective chemotherapeutic phenotypes in the Yoruba from Ibadan, Nigeria (p<0.05), including TP53I11, COPS5 and GAS8, which are known to be involved in tumorigenesis. Although our results require further study, we have identified variants and genes associated with chemotherapeutic susceptibility in African Americans by using an approach that incorporates local ancestry information.

Ex-Vivo Modeling for Heritability Assessment and Genetic Mapping in Pharmacogenomics

The investigation of genetic factors that determine differential drug response is a key goal of pharmacogenomics (PGX), and relies on the often-untested assumption that differential response is heritable. While limitations in traditional study design often prohibit heritability (h²) estimates in PGX, new approaches may allow such estimates. We demonstrate an ex vivo model system to determine the h² of drug-induced cell killing and performed genome-wide analysis for gene mapping. The cytotoxic effect of 29 diverse chemotherapeutic agents on lymphoblastoid cell lines (LCLs) derived from family- and population-based cohorts was investigated. We used a high throughput format to determine cytotoxicity of the drugs on LCLs and developed a new evolutionary computation approach to fit response curves for each individual. Variance components analysis determined the h² for each drug response and a wide range of values was observed across drugs. Genome-wide analysis was performed using new analytical approaches. These results lay the groundwork for future studies to uncover genes influencing chemotherapeutic response and demonstrate a new computational framework for performing such analysis.

Identification and replication of loci involved in camptothecin-induced cytotoxicity using CEPH pedigrees

To date, the Centre d'Etude Polymorphism Humain (CEPH) cell line model has only been used as a pharmacogenomic tool to evaluate which genes are responsible for the disparity in response to a single drug. The purpose of this study was demonstrate the model's ability to establish a specific pattern of quantitative trait loci (QTL) related to a shared mechanism for multiple structurally related drugs, the camptothecins, which are Topoisomerase 1 inhibitors. A simultaneous screen of six camptothecin analogues for in vitro sensitivity in the CEPH cell lines resulted in cytotoxicity profiles and orders of potency which were in agreement with the literature. For all camptothecins studied, heritability estimates for cytotoxic response averaged 23.1 ± 2.6%. Nonparametric linkage analysis was used to identify a relationship between genetic markers and response to the camptothecins. Ten QTLs on chromosomes 1, 3, 5, 6, 11, 12, 16 and 20 were identified as shared by all six camptothecin analogues. In a separate validation experiment, nine of the ten QTLs were replicated at the significant and suggestive levels using three additional camptothecin analogues. To further refine this list of QTLs, another validation study was undertaken and seven of the nine QTLs were independently replicated for all nine camptothecin analogues. This is the first study using the CEPH cell lines that demonstrates that a specific pattern of QTLs could be established for a class of drugs which share a mechanism of action. Moreover, it is the first study to report replication of linkage results for drug-induced cytotoxicity using this model. The QTLs, which have been identified as shared by all camptothecins and replicated across multiple datasets, are of considerable interest; they harbor genes related to the shared mechanism of action for the camptothecins, which are responsible for variation in response.