Pharmacogenomic discovery using cell-based models

Oncogenic signaling pathways and hallmarks of cancer in Korean patients with acral melanoma

Acral melanoma (AM), a rare subtype of cutaneous melanoma, shows higher incidence in Asians, including Koreans, than in Caucasians. However, the genetic modification associated with AM in Koreans is not well known and has not been comprehensively investigated in terms of oncogenic signaling, and hallmarks of cancer. We performed whole-exome and RNA sequencing for Korean patients with AM and acquired the genetic alterations and gene expression profiles. KIT alterations (previously known to be recurrent alterations in AM) and CDK4/CCND1 copy number amplifications were identified in the patients. Genetic and transcriptomic alterations in patients with AM were functionally converge to the hallmarks of cancer and oncogenic pathways, including 'proliferative signal persistence', 'apoptotic resistance', and 'activation of invasion and metastasis', despite the heterogeneous somatic mutation profiles of Korean patients with AM. This study may provide a molecular understanding for therapeutic strategy for AM.

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.

Making Sense of Patient-Derived iPSCs, Transdifferentiated Neurons, Olfactory Neuronal Cells, and Cerebral Organoids as Models for Psychiatric Disorders

The improvement of experimental models for disorders requires a constant approximation towards the dysregulated tissue. In psychiatry, where an impairment of neuronal structure and function is assumed to play a major role in disease mechanisms and symptom development, this approximation is an ongoing process implicating various fields. These include genetic, animal, and post-mortem studies. To test hypotheses generated through these studies, in vitro models using non-neuronal cells such as fibroblasts and lymphocytes have been developed. For brain network disorders, cells with neuronal signatures would, however, represent a more adequate tissue. Considering the limited accessibility of brain tissue, research has thus turned towards neurons generated from induced pluripotent stem cells as well as directly induced neurons, cerebral organoids, and olfactory neuroepithelium. Regarding the increasing importance and amount of research using these neuronal cells, this review aims to provide an overview of all these models to make sense of the current literature. The development of each model system and its use as a model for the various psychiatric disorder categories will be laid out. Also, advantages and limitations of each model will be discussed, including a reflection on implications and future perspectives.

Melatonin effect on hypoxia inducible factor-1α and clinical response in patients with oral squamous cell carcinoma receiving neoadjuvant chemotherapy: A randomized controlled trial

CONTEXT

Chemoresistance is a major issue in patients with locally advanced oral squamous cell carcinoma (OSCC). In this study, we evaluated the effectiveness of melatonin in conjunction with neoadjuvant chemotherapy (NC) on hypoxia-inducible factor-1α (HIF-1α) expression and clinical response in locally advanced OSCC patients.

AIMS

To study the effects of melatonin on HIF-1α expression and its effect on the clinical response of patients with locally advanced OSCC.

SETTINGS AND DESIGN

A randomized controlled trial was conducted, wherein patients were recruited from several hospitals in Jakarta, Indonesia. Patients were randomized into two groups using computerized block randomization.

SUBJECTS AND METHODS

Both groups were given NC, with treatment group receiving melatonin. Outcomes measured in this study were HIF-1α expression from tissue samples and clinical response based on the RECIST 1.1 criteria. Twenty-five patients completed the study protocol and were included in the data analysis.

STATISTICAL ANALYSIS USED

Shapiro-Wilk test was used to test the data normality. For data with normal distribution, we conducted an independent t-test to compare between the two groups. Data with abnormal distribution were analyzed using Mann-Whitney U-test. The mean difference between the two groups was analyzed using Shapiro-Wilk normality test.

RESULTS

Our study showed a significant decrease in HIF-1α expression in the melatonin group compared to the placebo group (P < 0.05, relative risk 3.08). However, the degree of reduction of HIF-1α expression in the melatonin group did not differ significantly (P = 0.301).

CONCLUSIONS

Our study showed that melatonin administered at 20 mg/day could reduce the expression of HIF-1α and residual tumor percentage, but did not affect the clinical response in OSCC patients.

Response and Toxicity to Cytarabine Therapy in Leukemia and Lymphoma: From Dose Puzzle to Pharmacogenomic Biomarkers

Simple Summary

In this review, the authors propose a crosswise examination of cytarabine-related issues ranging from the spectrum of clinical activity and severe toxicities, through updated cellular pharmacology and drug formulations, to the genetic variants associated with drug-induced phenotypes. Cytarabine (cytosine arabinoside; Ara-C) in multiagent chemotherapy regimens is often used for leukemia or lymphoma treatments, as well as neoplastic meningitis. Chemotherapy regimens can induce a suboptimal clinical outcome in a fraction of patients. The individual variability in clinical response to Leukemia & Lymphoma treatments among patients appears to be associated with intracellular accumulation of Ara-CTP due to genetic variants related to metabolic enzymes. The review provides exhaustive information on the effects of Ara-C-based therapies, the adverse drug reaction will also be provided including bone pain, ocular toxicity (corneal pain, keratoconjunctivitis, and blurred vision), maculopapular rash, and occasional chest pain. Evidence for predicting the response to cytarabine-based treatments will be highlighted, pointing at their significant impact on the routine management of blood cancers.

Abstract

Cytarabine is a pyrimidine nucleoside analog, commonly used in multiagent chemotherapy regimens for the treatment of leukemia and lymphoma, as well as for neoplastic meningitis. Ara-C-based chemotherapy regimens can induce a suboptimal clinical outcome in a fraction of patients. Several studies suggest that the individual variability in clinical response to Leukemia & Lymphoma treatments among patients, underlying either Ara-C mechanism resistance or toxicity, appears to be associated with the intracellular accumulation and retention of Ara-CTP due to genetic variants related to metabolic enzymes. Herein, we reported (a) the latest Pharmacogenomics biomarkers associated with the response to cytarabine and (b) the new drug formulations with optimized pharmacokinetics. The purpose of this review is to provide readers with detailed and comprehensive information on the effects of Ara-C-based therapies, from biological to clinical practice, maintaining high the interest of both researcher and clinical hematologist. This review could help clinicians in predicting the response to cytarabine-based treatments.

Race and smoking status associated with paclitaxel drug response in patient-derived lymphoblastoid cell lines

The use of ex-vivo model systems to provide a level of forecasting for in-vivo characteristics remains an important need for cancer therapeutics. The use of lymphoblastoid cell lines (LCLs) is an attractive approach for pharmacogenomics and toxicogenomics, due to their scalability, efficiency, and cost-effectiveness. There is little data on the impact of demographic or clinical covariates on LCL response to chemotherapy. Paclitaxel sensitivity was determined in LCLs from 93 breast cancer patients from the University of North Carolina Lineberger Comprehensive Cancer Center Breast Cancer Database to test for potential associations and/or confounders in paclitaxel dose-response assays. Measures of paclitaxel cell viability were associated with patient data included treatment regimens, cancer status, demographic and environmental variables, and clinical outcomes. We used multivariate analysis of variance to identify the in-vivo variables associated with ex-vivo dose-response. In this unique dataset that includes both in-vivo and ex-vivo data from breast cancer patients, race (P = 0.0049) and smoking status (P = 0.0050) were found to be significantly associated with ex-vivo dose-response in LCLs. Racial differences in clinical dose-response have been previously described, but the smoking association has not been reported. Our results indicate that in-vivo smoking status can influence ex-vivo dose-response in LCLs, and more precise measures of covariates may allow for more precise forecasting of clinical effect. In addition, understanding the mechanism by which exposure to smoking in-vivo effects ex-vivo dose-response in LCLs may open up new avenues in the quest for better therapeutic prediction.

Effect of melatonin supplementation in combination with neoadjuvant chemotherapy to miR-210 and CD44 expression and clinical response improvement in locally advanced oral squamous cell carcinoma: a randomized controlled trial

BACKGROUND

Squamous cell carcinoma of the oral cavity (OSCC) is the sixth most common malignancy. Surgery is mainstay treatment for oral cancers. Surgery in locally advanced OSCC presents many challenges primarily because the head and neck have critical structures that can be damaged by tumor or treatment. It is thought that neoadjuvant chemotherapy (NC) in locally advanced OSCC is able to shrink tumor size. Chemoresistancy is a problem due to hypoxic microenvironment characterized by increased expression of HIF-1α. It is also regulated by miR-210 as well as increased expression of CD44 and CD133. Melatonin has a powerful antioxidant and oncostatic effects that are expected to improve tumor hypoxia and clinical response. Fifty patients with OSCC were included and randomized. miR-210 and CD44 expression were measured before and after intervention using qRT-PCR absolute quantification, and clinical response was evaluated according to RECIST 1.1 criteria. This study aims to determine the effect of melatonin in improving the clinical response of patients with locally advanced oral squamous cell carcinoma (OSCC) after neoadjuvant chemotherapy to miR-210 and CD44 expression.

RESULTS

Melatonin administration reduced miR-210 levels but not significant (p = 0.767). CD44 expression also decreased in the melatonin group compared with placebo yet was not significant (p = 0.103). There was a decrease in the expression of miR-210 and CD44 followed by a decrease in the percentage of residual tumor but not significant (p = 0.114).

CONCLUSION

In OSCC, the addition of 20-mg melatonin to neoadjuvant chemotherapy (NC) reduced the expression of miR-210 and CD44 and decreased the percentage of tumor residue; however, no statistically significant result was observed.

TRIAL REGISTRATION

This study is registered to ClinicalTrials.gov under trial registration number: NCT04137627 with date of registration on October 22, 2019-retrospectively registered, accessible from: https://clinicaltrials.gov/ct2/show/NCT04137627.

Rhythm on a chip: circadian entrainment in vitro is the next frontier in body-on-a chip technology

Organoids, bioprinted mini-tissues and body-on-a-chip technologies are poised to transform the practice of preclinical pharmacology, with a view to achieving better predictive value. We review the need for further refinement in static and dynamic biomechanical aspects of such microenvironments. Further consideration of the developments required in perfusion systems to enable delivery of an appropriate soluble microenvironment are argued. We place particular emphasis on a major deficiency in these systems, being the absence or aberrant circadian behaviour of cells used in such settings, and consider the technical challenges that are needing to be met in order to achieve rhythm-on-a-chip.

Tissue specificity of in vitro drug sensitivity

Objectives

We sought to investigate the tissue specificity of drug sensitivities in large-scale pharmacological studies and compare these associations to those found in drug clinical indications.

Materials and Methods

We leveraged the curated cell line response data from PharmacoGx and applied an enrichment algorithm on drug sensitivity values' area under the drug dose-response curves (AUCs) with and without adjustment for general level of drug sensitivity.

Results

We observed tissue specificity in 63% of tested drugs, with 8% of total interactions deemed significant (false discovery rate <0.05). By restricting the drug-tissue interactions to those with AUC > 0.2, we found that in 52% of interactions, the tissue was predictive of drug sensitivity (concordance index > 0.65). When compared with clinical indications, the observed overlap was weak (Matthew correlation coefficient, MCC = 0.0003, P > .10).

Discussion

While drugs exhibit significant tissue specificity in vitro, there is little overlap with clinical indications. This can be attributed to factors such as underlying biological differences between in vitro models and patient tumors, or the inability of tissue-specific drugs to bring additional benefits beyond gold standard treatments during clinical trials.

Conclusion

Our meta-analysis of pan-cancer drug screening datasets indicates that most tested drugs exhibit tissue-specific sensitivities in a large panel of cancer cell lines. However, the observed preclinical results do not translate to the clinical setting. Our results suggest that additional research into showing parallels between preclinical and clinical data is required to increase the translational potential of in vitro drug screening.

Population-scale genomics-Enabling precision public health

The current excitement for affordable genomics technologies and national precision medicine initiatives marks a turning point in worldwide healthcare practices. The last decade of global population sequencing efforts has defined the enormous extent of genetic variation in the human population resulting in insights into differential disease burden and response to therapy within and between populations. Population-scale pharmacogenomics helps to provide insights into the choice of optimal therapies and an opportunity to estimate, predict and minimize adverse events. Such an approach can potentially empower countries to formulate national selection and dosing policies for therapeutic agents thereby promoting public health with precision. We review the breadth and depth of worldwide population-scale sequencing efforts and its implications for the implementation of clinical pharmacogenetics toward making precision medicine a reality.

Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling

Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.

Organoids with cancer stem cell-like properties secrete exosomes and HSP90 in a 3D nanoenvironment

Ability to form cellular aggregations such as tumorspheres and spheroids have been used as a morphological marker of malignant cancer cells and in particular cancer stem cells (CSC). However, the common definition of the types of cellular aggregation formed by cancer cells has not been available. We examined morphologies of 67 cell lines cultured on three dimensional morphology enhancing NanoCulture Plates (NCP) and classified the types of cellular aggregates that form. Among the 67 cell lines, 49 cell lines formed spheres or spheroids, 8 cell lines formed grape-like aggregation (GLA), 8 cell lines formed other types of aggregation, and 3 cell lines formed monolayer sheets. Seven GLA-forming cell lines were derived from adenocarcinoma among the 8 lines. A neuroendocrine adenocarcinoma cell line PC-3 formed asymmetric GLA with ductal structures on the NCPs and rapidly growing asymmetric tumors that metastasized to lymph nodes in immunocompromised mice. In contrast, another adenocarcinoma cell line DU-145 formed spheroids in vitro and spheroid-like tumors in vivo that did not metastasize to lymph nodes until day 50 after transplantation. Culture in the 3D nanoenvironment and in a defined stem cell medium enabled the neuroendocrine adenocarcinoma cells to form slowly growing large organoids that expressed multiple stem cell markers, neuroendocrine markers, intercellular adhesion molecules, and oncogenes in vitro. In contrast, the more commonly used 2D serum-contained environment reduced intercellular adhesion and induced mesenchymal transition and promoted rapid growth of the cells. In addition, the 3D stemness nanoenvironment promoted secretion of HSP90 and EpCAM-exosomes, a marker of CSC phenotype, from the neuroendocrine organoids. These findings indicate that the NCP-based 3D environment enables cells to form stem cell tumoroids with multipotency and model more accurately the in vivo tumor status at the levels of morphology and gene expression.

Gene and MicroRNA Perturbations of Cellular Response to Pemetrexed Implicate Biological Networks and Enable Imputation of Response in Lung Adenocarcinoma

Pemetrexed is indicated for non-small cell lung carcinoma and mesothelioma, but often has limited efficacy due to drug resistance. To probe the molecular mechanisms underlying chemotherapeutic response, we performed mRNA and microRNA (miRNA) expression profiling of pemetrexed treated and untreated lymphoblastoid cell lines (LCLs) and applied a hierarchical Bayesian method. We identified genetic variation associated with gene expression in human lung tissue for the most significant differentially expressed genes (Benjamini-Hochberg [BH] adjusted p < 0.05) using the Genotype-Tissue Expression data and found evidence for their clinical relevance using integrated molecular profiling and lung adenocarcinoma survival data from The Cancer Genome Atlas project. We identified 39 miRNAs with significant differential expression (BH adjusted p < 0.05) in LCLs. We developed a gene expression based imputation model of drug sensitivity, quantified its prediction performance, and found a significant correlation of the imputed phenotype generated from expression data with survival time in lung adenocarcinoma patients. Differentially expressed genes (MTHFD2 and SUFU) that are putative targets of differentially expressed miRNAs also showed differential perturbation in A549 fusion lung tumor cells with further replication in A549 cells. Our study suggests pemetrexed may be used in combination with agents that target miRNAs to increase its cytotoxicity.

Label-free technology and patient cells: from early drug development to precision medicine

Drug development requires physiologically more appropriate model systems and assays to increase understanding of drug action and pathological processes in individual humans. Specifically, patient-derived cells offer great opportunities as representative cellular model systems. Moreover, with novel label-free cellular assays, it is often possible to investigate complex biological processes in their native environment. Combining these two offers distinct opportunities for increasing physiological relevance. Here, we review impedance-based label-free technologies in the context of patient samples, focusing on commonly used cell types, including fibroblasts, blood components, and stem cells. Applications extend as far as tissue-on-a-chip models. Thus, applying label-free technologies to patient samples can produce highly biorelevant data and, with them, unique opportunities for drug development and precision medicine.

Global profiling of viral and cellular non-coding RNAs in Epstein-Barr virus-induced lymphoblastoid cell lines and released exosome cargos

The human EBV-transformed lymphoblastoid cell line (LCL), obtained by infecting peripheral blood monocular cells with Epstein-Barr Virus, has been extensively used for human genetic, pharmacogenomic, and immunologic studies. Recently, the role of exosomes has also been indicated as crucial in the crosstalk between EBV and the host microenvironment. Because the role that the LCL and LCL exosomal cargo might play in maintaining persistent infection, and since little is known regarding the non-coding RNAs of LCL, the aim of our work was the comprehensive characterization of this class of RNA, cellular and viral miRNAs, and cellular lncRNAs, in LCL compared with PBMC derived from the same donors. In this study, we have demonstrated, for the first time, that all the viral miRNAs expressed by LCL are also packaged in the exosomes, and we found that two miRNAs, ebv-miR-BART3 and ebv-miR-BHRF1-1, are more abundant in the exosomes, suggesting a microvescicular viral microRNA transfer. In addition, lncRNA profiling revealed that LCLs were enriched in lncRNA H19 and H19 antisense, and released these through exosomes, suggesting a leading role in the regulation of the tumor microenvironment.

Investigating Leber's hereditary optic neuropathy: Cell models and future perspectives

Leber's hereditary optic neuropathy (LHON) was the first human disease found to be associated with a mitochondrial DNA (mtDNA) point mutation. The most common LHON mutations are 11778G>A, 3460G>A or 14484T>C. The most common clinical features of LHON are optic nerve and retina atrophy. The affected tissue is not available for studies, therefore a variety of other cell types are used. However, all models face difficulties and limitations in mitochondrial disease research. The advantages and disadvantages of different cell models used to study LHON, recent advances in animal model generation and novel approaches in this field are discussed.

Precision medicine: from pharmacogenomics to pharmacoproteomics

Disease progression and drug response may vary significantly from patient to patient. Fortunately, the rapid development of high-throughput ‘omics’ technologies has allowed for the identification of potential biomarkers that may aid in the understanding of the heterogeneities in disease development and treatment outcomes. However, mechanistic gaps remain when the genome or the proteome are investigated independently in response to drug treatment. In this article, we discuss the current status of pharmacogenomics in precision medicine and highlight the needs for concordant analysis at the proteome and metabolome levels via the more recently-evolved fields of pharmacoproteomics, toxicoproteomics, and pharmacometabolomics. Integrated ‘omics’ investigations will be critical in piecing together targetable mechanisms of action for both drug development and monitoring of therapy in order to fully apply precision medicine to the clinic.

A Novel High-Throughput 3D Screening System for EMT Inhibitors: A Pilot Screening Discovered the EMT Inhibitory Activity of CDK2 Inhibitor SU9516

Epithelial-mesenchymal transition (EMT) is a crucial pathological event in cancer, particularly in tumor cell budding and metastasis. Therefore, control of EMT can represent a novel therapeutic strategy in cancer. Here, we introduce an innovative three-dimensional (3D) high-throughput screening (HTS) system that leads to an identification of EMT inhibitors. For the establishment of the novel 3D-HTS system, we chose NanoCulture Plates (NCP) that provided a gel-free micro-patterned scaffold for cells and were independent of other spheroid formation systems using soft-agar. In the NCP-based 3D cell culture system, A549 lung cancer cells migrated, gathered, and then formed multiple spheroids within 7 days. Live cell imaging experiments showed that an established EMT-inducer TGF-β promoted peripheral cells around the core of spheroids to acquire mesenchymal spindle shapes, loss of intercellular adhesion, and migration from the spheroids. Along with such morphological change, EMT-related gene expression signatures were altered, particularly alteration of mRNA levels of ECAD/CDH1, NCAD/CDH2, VIM and ZEB1/TCF8. These EMT-related phenotypic changes were blocked by SB431542, a TGF-βreceptor I (TGFβR1) inhibitor. Inside of the spheroids were highly hypoxic; in contrast, spheroid-derived peripheral migrating cells were normoxic, revealed by visualization and quantification using Hypoxia Probe. Thus, TGF-β-triggered EMT caused spheroid hypoplasia and loss of hypoxia. Spheroid EMT inhibitory (SEMTIN) activity of SB431542 was calculated from fluorescence intensities of the Hypoxia Probe, and then was utilized in a drug screening of EMT-inhibitory small molecule compounds. In a pilot screening, 9 of 1,330 compounds were above the thresholds of the SEMTIN activity and cell viability. Finally, two compounds SB-525334 and SU9516 showed SEMTIN activities in a dose dependent manner. SB-525334 was a known TGFβR1 inhibitor. SU9516 was a cyclin-dependent kinase 2 (CDK2) inhibitor, which we showed also had an EMT-inhibitory activity. The half maximal inhibitory concentration (IC₅₀) of SB-525334 and SU9516 were 0.31 μM and 1.21 μM, respectively, while IC₅₀ of SB431542 was 2.38 μM. Taken together, it was shown that this 3D NCP-based HTS system was useful for screening of EMT-regulatory drugs.

Lymphoblastoid Cell Lines as a Tool to Study Inter-Individual Differences in the Response to Glucose

Background

White blood cells have been shown in animal studies to play a central role in the pathogenesis of diabetic retinopathy. Lymphoblastoid cells are immortalized EBV-transformed primary B-cell leukocytes that have been extensively used as a model for conditions in which white blood cells play a primary role. The purpose of this study was to investigate whether lymphoblastoid cell lines, by retaining many of the key features of primary leukocytes, can be induced with glucose to demonstrate relevant biological responses to those found in diabetic retinopathy.

Methods

Lymphoblastoid cell lines were obtained from twenty-three human subjects. Differences between high and standard glucose conditions were assessed for expression, endothelial adhesion, and reactive oxygen species.

Results

Collectively, stimulation of the lymphoblastoid cell lines with high glucose demonstrated corresponding changes on molecular, cellular and functional levels. Lymphoblastoid cell lines up-regulated expression of a panel of genes associated with the leukocyte-mediated inflammation found in diabetic retinopathy that include: a cytokine (IL-1B fold change = 2.11, p-value = 0.02), an enzyme (PKCB fold change = 2.30, p-value = 0.01), transcription factors (NFKB-p50 fold change = 2.05, p-value = 0.01), (NFKB-p65 fold change = 2.82, p-value = 0.003), and an adhesion molecule (CD18 fold change = 2.59, 0.02). Protein expression of CD18 was also increased (p-value = 2.14x10^-5). The lymphoblastoid cell lines demonstrated increased adhesiveness to endothelial cells (p = 1.28x10^-5). Reactive oxygen species were increased (p = 2.56x10^-6). Significant inter-individual variation among the lymphoblastoid cell lines in these responses was evident (F = 18.70, p < 0.0001).

Conclusions

Exposure of lymphoblastoid cell lines derived from different human subjects to high glucose demonstrated differential and heterogeneous gene expression, adhesion, and cellular effects that recapitulated features found in the diabetic state. Lymphoblastoid cells may represent a useful tool to guide an individualized understanding of the development and potential treatment of diabetic complications like retinopathy.

Evaluation of inter-batch differences in stem-cell derived neurons

Differentiated cells retain the genetic information of the donor but the extent to which phenotypic differences between donors or batches of differentiated cells are explained by variation introduced during the differentiation process is not fully understood. In this study, we evaluated four separate batches of commercially available neurons originating from the same iPSCs to investigate whether the differentiation process used in manufacturing iPSCs to neurons affected genome-wide gene expression and modified cytosines, or neuronal sensitivity to drugs. No significant changes in gene expression, as measured by RNA-Seq, or cytosine modification levels, as measured by the Illumina 450K arrays, were observed between batches relative to changes over time. As expected, neurotoxic chemotherapeutics affected neuronal outgrowth, but no inter-batch differences were observed in sensitivity to paclitaxel, vincristine and cisplatin. As a testament to the utility of the model for studies of neuropathy, we observed that genes involved in neuropathy had relatively higher expression levels in these samples across different time points. Our results suggest that the process used to differentiate iPSCs into neurons is consistent, resulting in minimal intra-individual variability across batches. Therefore, this model is reasonable for studies of human neuropathy, druggable targets to prevent neuropathy, and other neurological diseases.

Uncertainties in human health risk assessment of environmental contaminants: A review and perspective

Addressing uncertainties in human health risk assessment is a critical issue when evaluating the effects of contaminants on public health. A range of uncertainties exist through the source-to-outcome continuum, including exposure assessment, hazard and risk characterisation. While various strategies have been applied to characterising uncertainty, classical approaches largely rely on how to maximise the available resources. Expert judgement, defaults and tools for characterising quantitative uncertainty attempt to fill the gap between data and regulation requirements. The experiences of researching 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) illustrated uncertainty sources and how to maximise available information to determine uncertainties, and thereby provide an 'adequate' protection to contaminant exposure. As regulatory requirements and recurring issues increase, the assessment of complex scenarios involving a large number of chemicals requires more sophisticated tools. Recent advances in exposure and toxicology science provide a large data set for environmental contaminants and public health. In particular, biomonitoring information, in vitro data streams and computational toxicology are the crucial factors in the NexGen risk assessment, as well as uncertainties minimisation. Although in this review we cannot yet predict how the exposure science and modern toxicology will develop in the long-term, current techniques from emerging science can be integrated to improve decision-making.

Induced Pluripotent Stem Cell Models to Enable In Vitro Models for Screening in the Central Nervous System

There is great need to develop more predictive drug discovery tools to identify new therapies to treat diseases of the central nervous system (CNS). Current nonpluripotent stem cell-based models often utilize non-CNS immortalized cell lines and do not enable the development of personalized models of disease. In this review, we discuss why in vitro models are necessary for translational research and outline the unique advantages of induced pluripotent stem cell (iPSC)-based models over those of current systems. We suggest that iPSC-based models can be patient specific and isogenic lines can be differentiated into many neural cell types for detailed comparisons. iPSC-derived cells can be combined to form small organoids, or large panels of lines can be developed that enable new forms of analysis. iPSC and embryonic stem cell-derived cells can be readily engineered to develop reporters for lineage studies or mechanism of action experiments further extending the utility of iPSC-based systems. We conclude by describing novel technologies that include strategies for the development of diversity panels, novel genomic engineering tools, new three-dimensional organoid systems, and modified high-content screens that may bring toxicology into the 21st century. The strategic integration of these technologies with the advantages of iPSC-derived cell technology, we believe, will be a paradigm shift for toxicology and drug discovery efforts.

An investigation of gene-gene interactions in dose-response studies with Bayesian nonparametrics

BACKGROUND

Best practice for statistical methodology in cell-based dose-response studies has yet to be established. We examine the ability of MANOVA to detect trait-associated genetic loci in the presence of gene-gene interactions. We present a novel Bayesian nonparametric method designed to detect such interactions.

RESULTS

MANOVA and the Bayesian nonparametric approach show good ability to detect trait-associated genetic variants under various possible genetic models. It is shown through several sets of analyses that this may be due to marginal effects being present, even if the underlying genetic model does not explicitly contain them.

CONCLUSIONS

Understanding how genetic interactions affect drug response continues to be a critical goal. MANOVA and the novel Bayesian framework present a trade-off between computational complexity and model flexibility.

Genome-wide association and pharmacological profiling of 29 anticancer agents using lymphoblastoid cell lines

AIM

Association mapping with lymphoblastoid cell lines (LCLs) is a promising approach in pharmacogenomics research, and in the current study we utilized LCLs to perform association mapping for 29 chemotherapy drugs.

MATERIALS & METHODS

Currently, we use LCLs to perform genome-wide association mapping of the cytotoxic response of 520 European-Americans to 29 different anticancer drugs; the largest LCL study to date. A novel association approach using a multivariate analysis of covariance design was employed with the software program MAGWAS, testing for differences in the dose-response profiles between genotypes without making assumptions about the response curve or the biologic mode of association. Additionally, by classifying 25 of the 29 drugs into eight families according to structural and mechanistic relationships, MAGWAS was used to test for associations that were shared across each drug family. Finally, a unique algorithm using multivariate responses and multiple linear regressions across pairs of response curves was used for unsupervised clustering of drugs.

RESULTS

Among the single-drug studies, suggestive associations were obtained for 18 loci, 12 within/near genes. Three of these, MED12L, CHN2 and MGMT, have been previously implicated in cancer pharmacogenomics. The drug family associations resulted in four additional suggestive loci (three contained within/near genes). One of these genes, HDAC4, associated with the DNA alkylating agents, shows possible clinical interactions with temozolomide. For the drug clustering analysis, 18 of 25 drugs clustered into the appropriate family.

CONCLUSION

This study demonstrates the utility of LCLs in identifying genes that have clinical importance in drug response and for assigning unclassified agents to specific drug families, and proposes new candidate genes for follow-up in a large number of chemotherapy drugs.

Predicting chemosensitivity to gemcitabine and cisplatin based on gene polymorphisms and mRNA expression in non-small-cell lung cancer cells

Aim: We used a panel of 17 non-small-cell lung cancer cell lines to investigate whether the presence of polymorphisms in the RRM1, ERCC1, ABCB1 and MTHFR genes and alterations in their mRNA expression can affect the in vitro chemosensitivity to cisplatin and gemcitabine. Materials & methods: Polymorphisms in these genes were evaluated by direct sequencing. mRNA expression levels were assessed by realtime PCR. In vitro chemosensitivity to cisplatin and gemcitabine was expressed as IC50 values, using the MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide) assay. Results: There was a significant, positive correlation between RRM1 mRNA expression and IC50 values for gemcitabine (r = 0.6533, p = 0.0045), and there was a significant, negative correlation between ABCB1 mRNA expression and IC50 values for cisplatin (r = -0.5459, p = 0.0287). When examining the association between the polymorphisms and IC50, we found that only the MTHFR 1298A>C polymorphism showed a tendency to be more chemosensitive to gemcitabine (p = 0.0440). Conclusion: These in vitro results suggest that mRNA expression levels of the RRM1 and ABCB1 genes may be useful indicators of chemosensitivity to gemcitabine and cisplatin, respectively. The MTHFR 1298A>C polymorphism was associated with gemcitabine chemosensitivity, which require further functional analysis with co-expressed genes and should be explored in prospective clinical studies to determine its potential clinical application as a predictive biomarker.

Original submitted 11 February 2014; Revision submitted 3 November 2014

Peripheral blood signature of vasodilator-responsive pulmonary arterial hypertension

BACKGROUND

Heterogeneity in response to treatment of pulmonary arterial hypertension (PAH) is a major challenge to improving outcome in this disease. Although vasodilator-responsive PAH (VR-PAH) accounts for a minority of cases, VR-PAH has a pronounced response to calcium channel blockers and better survival than vasodilator-nonresponsive PAH (VN-PAH). We hypothesized that VR-PAH has a different molecular cause from VN-PAH that can be detected in the peripheral blood.

METHODS AND RESULTS

Microarrays of cultured lymphocytes from VR-PAH and VN-PAH patients followed at Vanderbilt University were performed with quantitative polymerase chain reaction performed on peripheral blood for the 25 most different genes. We developed a decision tree to identify VR-PAH patients on the basis of the results with validation in a second VR-PAH cohort from the University of Chicago. We found broad differences in gene expression patterns on microarray analysis including cell-cell adhesion factors and cytoskeletal and rho-GTPase genes. Thirteen of 25 genes tested in whole blood were significantly different: EPDR1, DSG2, SCD5, P2RY5, MGAT5, RHOQ, UCHL1, ZNF652, RALGPS2, TPD52, MKNL1, RAPGEF2, and PIAS1. Seven decision trees were built with the use of expression levels of 2 genes as the primary genes: DSG2, a desmosomal cadherin involved in Wnt/β-catenin signaling, and RHOQ, which encodes a cytoskeletal protein involved in insulin-mediated signaling. These trees correctly identified 5 of 5 VR-PAH patients in the validation cohort.

CONCLUSIONS

VR-PAH and VN-PAH can be differentiated with the use of RNA expression patterns in peripheral blood. These differences may reflect different molecular causes of the 2 PAH phenotypes. This biomarker methodology may identify PAH patients who have a favorable treatment response.

A cellular genetics approach identifies gene-drug interactions and pinpoints drug toxicity pathway nodes

New approaches to toxicity testing have incorporated high-throughput screening across a broad-range of in vitro assays to identify potential key events in response to chemical or drug treatment. To date, these approaches have primarily utilized repurposed drug discovery assays. In this study, we describe an approach that combines in vitro screening with genetic approaches for the experimental identification of genes and pathways involved in chemical or drug toxicity. Primary embryonic fibroblasts isolated from 32 genetically-characterized inbred mouse strains were treated in concentration-response format with 65 compounds, including pharmaceutical drugs, environmental chemicals, and compounds with known modes-of-action. Integrated cellular responses were measured at 24 and 72 h using high-content imaging and included cell loss, membrane permeability, mitochondrial function, and apoptosis. Genetic association analysis of cross-strain differences in the cellular responses resulted in a collection of candidate loci potentially underlying the variable strain response to each chemical. As a demonstration of the approach, one candidate gene involved in rotenone sensitivity, Cybb, was experimentally validated in vitro and in vivo. Pathway analysis on the combined list of candidate loci across all chemicals identified a number of over-connected nodes that may serve as core regulatory points in toxicity pathways.

Gene expression profiling of the response to interferon beta in Epstein-Barr-transformed and primary B cells of patients with multiple sclerosis

The effects of interferon-beta (IFN-β), one of the key immunotherapies used in multiple sclerosis (MS), on peripheral blood leukocytes and T cells have been extensively studied. B cells are a less abundant leukocyte type, and accordingly less is known about the B cell-specific response to IFN-β. To identify gene expression changes and pathways induced by IFN-β in B cells, we studied the in vitro response of human Epstein Barr-transformed B cells (lymphoblast cell lines-LCLs), and validated our results in primary B cells. LCLs were derived from an MS patient repository. Whole genome expression analysis identified 115 genes that were more than two-fold differentially up-regulated following IFN-β exposure, with over 50 previously unrecognized as IFN-β response genes. Pathways analysis demonstrated that IFN-β affected LCLs in a similar manner to other cell types by activating known IFN-β canonical pathways. Additionally, IFN-β increased the expression of innate immune response genes, while down-regulating many B cell receptor pathway genes and genes involved in adaptive immune responses. Novel response genes identified herein, NEXN, DDX60L, IGFBP4, and HAPLN3, B cell receptor pathway genes, CD79B and SYK, and lymphocyte activation genes, LAG3 and IL27RA, were validated as IFN-β response genes in primary B cells. In this study new IFN-β response genes were identified in B cells, with possible implications to B cell-specific functions. The study's results emphasize the applicability of LCLs for studies of human B cell drug response. The usage of LCLs from patient-based repositories may facilitate future studies of drug response in MS and other immune-mediated disorders with a B cell component.

Application of next generation sequencing to CEPH cell lines to discover variants associated with FDA approved chemotherapeutics

BACKGROUND

The goal of this study was to perform candidate gene association with cytotoxicity of chemotherapeutics in cell line models through resequencing and discovery of rare and low frequency variants along with common variations. Here, an association study of cytotoxicity response to 30 FDA approved drugs was conducted and we applied next generation targeted sequencing technology to discover variants from 103 candidate genes in 95 lymphoblastoid cell lines from 14 CEPH pedigrees. In this article, we called variants across 95 cell lines and performed association analysis for cytotoxic response using the Family Based Association Testing method and software.

RESULTS

We called 2281 variable SNP genotypes across the 103 genes for these cell lines and identified three genes of significant association within this marker set. Specifically, ATP-binding cassette, sub-family C, member 5 (ABCC5), metallothionein 1A (MT1A) and NAD(P)H dehydrogenase quinone1 (NQO1) were significantly associated with oxaliplatin drug response. The significant SNP on NQO1 (rs1800566) has been linked with poor survival rates in patients with non-small cell lung cancer treated with cisplatin (which belongs to the same class of drugs as oxaliplatin). A SNP (rs1846692) near the 5' region of MT1A was associated with arsenic trioxide.

CONCLUSIONS

The results from this study are promising and this serves as a proof-of-principle demonstration of the use of sequencing data in the cytotoxicity models of human cell lines. With increased sample sizes, such studies will be a fast and powerful way to associate common and rare variants with drug response; while overcoming the cost and time limitations to recruit cohorts for association study.

Genetic variation in the 3'-UTR of CYP1A2, CYP2B6, CYP2D6, CYP3A4, NR1I2, and UGT2B7: potential effects on regulation by microRNA and pharmacogenomics relevance

Introduction: Pharmacogenomics research has concentrated on variation in genes coding for drug metabolizing enzymes, transporters and nuclear receptors. However, variation affecting microRNA could also play a role in drug response. This project set out to investigate potential microRNA target sites in 11 genes and the extent of variation in the 3′-UTR of six selected genes; CYP1A2, CYP2B6, CYP2D6, CYP3A4, NR1I2, and UGT2B7.

Methods: Fifteen microRNA target prediction algorithms were used to identify microRNAs predicted to regulate 11 genes. The 3′-UTR of the 6 genes which topped the list of potential microRNA targets was sequenced in 30 black South Africans. In addition, genetic variants within these genes were investigated for interference with mRNA-microRNA interactions. Potential effects of observed variants were determined using in silico prediction tools.

Results: The 11 genes coding for DMEs, transporters and nuclear receptors were predicted to be targets of microRNAs with CYP2B6, NR1I2 (PXR), CYP3A4, and CYP1A2, interacting with the most microRNAs. The majority of identified genetic variants were predicted to interfere with microRNA regulation. For example, the variant, rs1054190C in NR1I2 was predicted to result in the presence of a binding site for the microRNA miR-1250-5p, while the variant rs1054191G was predicted to result in the absence of a recognition site for miR-371b-3p, miR-4258 and miR-4707-3p. Fifteen of the seventeen, novel variants occurred within microRNA target sequences.

Conclusion: The 3′-UTR harbors variation that is likely to influence regulation of specific genes by microRNA. In silico prediction followed by functional validation could aid in decoding the contribution of variation in the 3′-UTR, to some unexplained heritability that affects drug response. Understanding the specific role of each microRNA may lead to identification of markers for targeted therapy and therefore improve personalized drug treatment.

Integrative "omic" analysis for tamoxifen sensitivity through cell based models

It has long been observed that tamoxifen sensitivity varies among breast cancer patients. Further, ethnic differences of tamoxifen therapy between Caucasian and African American have also been reported. Since most studies have been focused on Caucasian people, we sought to comprehensively evaluate genetic variants related to tamoxifen therapy in African-derived samples. An integrative "omic" approach developed by our group was used to investigate relationships among endoxifen (an active metabolite of tamoxifen) sensitivity, SNP genotype, mRNA and microRNA expressions in 58 HapMap YRI lymphoblastoid cell lines. We identified 50 SNPs that associate with cellular sensitivity to endoxifen through their effects on 34 genes and 30 microRNA expression. Some of these findings are shared in both Caucasian and African samples, while others are unique in the African samples. Among gene/microRNA that were identified in both ethnic groups, the expression of TRAF1 is also correlated with tamoxifen sensitivity in a collection of 44 breast cancer cell lines. Further, knock-down TRAF1 and over-expression of hsa-let-7i confirmed the roles of hsa-let-7i and TRAF1 in increasing tamoxifen sensitivity in the ZR-75-1 breast cancer cell line. Our integrative omic analysis facilitated the discovery of pharmacogenomic biomarkers that potentially affect tamoxifen sensitivity.

Label-free drug discovery

Current drug discovery is dominated by label-dependent molecular approaches, which screen drugs in the context of a predefined and target-based hypothesis in vitro. Given that target-based discovery has not transformed the industry, phenotypic screen that identifies drugs based on a specific phenotype of cells, tissues, or animals has gained renewed interest. However, owing to the intrinsic complexity in drug-target interactions, there is often a significant gap between the phenotype screened and the ultimate molecular mechanism of action sought. This paper presents a label-free strategy for early drug discovery. This strategy combines label-free cell phenotypic profiling with computational approaches, and holds promise to bridge the gap by offering a kinetic and holistic representation of the functional consequences of drugs in disease relevant cells that is amenable to mechanistic deconvolution.

Chemotherapy-induced peripheral neurotoxicity and ototoxicity: new paradigms for translational genomics

In view of advances in early detection and treatment, the 5-year relative survival rate for all cancer patients combined is now approximately 66%. As a result, there are more than 13.7 million cancer survivors in the United States, with this number increasing by 2% annually. For many patients, improvements in survival have been countered by therapy-associated adverse effects that may seriously impair long-term functional status, workplace productivity, and quality of life. Approximately 20% to 40% of cancer patients given neurotoxic chemotherapy develop chemotherapy-induced peripheral neurotoxicity (CIPN), which represents one of the most common and potentially permanent nonhematologic side effects of chemotherapy. Permanent bilateral hearing loss and/or tinnitus can result from several ototoxic therapies, including cisplatin- or carboplatin-based chemotherapy. CIPN and ototoxicity represent important challenges because of the lack of means for effective prevention, mitigation, or a priori identification of high-risk patients, and few studies have applied modern genomic approaches to understand underlying mechanisms/pathways. Translational genomics, including cell-based models, now offer opportunities to make inroads for the first time to develop preventive and interventional strategies for CIPN, ototoxicity, and other treatment-related complications. This commentary provides current perspective on a successful research strategy, with a focus on cisplatin, developed by an experienced, transdisciplinary group of researchers and clinicians, representing pharmacogenomics, statistical genetics, neurology, hearing science, medical oncology, epidemiology, and cancer survivorship. Principles outlined herein are applicable to the construction of research programs in translational genomics with strong clinical relevance and highlight unprecedented opportunities to understand, prevent, and treat long-term treatment-related morbidities.

Integrating cell-based and clinical genome-wide studies to identify genetic variants contributing to treatment failure in neuroblastoma patients

High-risk neuroblastoma is an aggressive malignancy with high rates of treatment failure. We evaluated genetic variants associated with in vitro sensitivity to two derivatives of cyclophosphamide for association with clinical response in a separate replication cohort of neuroblastoma patients (n=2,709). Lymphoblastoid cell lines (LCLs) were exposed to increasing concentrations of 4-hydroperoxycyclophosphamide [4HC n=422] and phosphoramide mustard [PM n=428] to determine sensitivity. Genome-wide association studies (GWAS) were performed to identify single nucleotide polymorphisms (SNPs) associated with 4HC and PM sensitivity. SNPs consistently associated with LCL sensitivity were analyzed for associations with event-free survival in patients. Two linked SNPs, rs9908694 and rs1453560, were found to be associated with PM sensitivity in LCLs across populations and were associated with event-free survival in all patients (P=0.01) and within the high-risk subset (P=0.05). Our study highlights the value of cell-based models to identify candidate variants that may predict response to treatment in patients with cancer.

Genetic variation is the major determinant of individual differences in leukocyte endothelial adhesion

Objective

To determine the genetic contribution to leukocyte endothelial adhesion.

Methods

Leukocyte endothelial adhesion was assessed through a novel cell-based assay using human lymphoblastoid cell lines. A high-throughput screening method was developed to evaluate the inter-individual variability in leukocyte endothelial adhesion using lymphoblastoid cell lines derived from different donors. To assess heritability, ninety-two lymphoblastoid cell lines derived from twenty-three monozygotic twin pairs and twenty-three sibling pairs were compared. These lymphoblastoid cell lines were plated with the endothelial cell line EA.hy926 and labeled with Calcein AM dye. Fluorescence was assessed to determine endothelial cell adhesion to each lymphoblastoid cell line. Intra-pair similarity was determined for monozygotic twins and siblings using Pearson pairwise correlation coefficients.

Results

A leukocyte endothelial adhesion assay for lymphoblastoid cell lines was developed and optimized (CV = 8.68, Z′-factor = 0.67, SNR = 18.41). A higher adhesion correlation was found between the twins than that between the siblings. Intra-pair similarity for leukocyte endothelial adhesion in monozygotic twins was 0.60 compared to 0.25 in the siblings. The extent to which these differences are attributable to underlying genetic factors was quantified and the heritability of leukocyte endothelial adhesion was calculated to be 69.66% (p-value<0.0001).

Conclusions

There is a heritable component to leukocyte endothelial adhesion. Underlying genetic predisposition plays a significant role in inter-individual variability of leukocyte endothelial adhesion.

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.

Lymphoblastoid cell lines models of drug response: successes and lessons from this pharmacogenomic model

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.

Statin-induced changes in gene expression in EBV-transformed and native B-cells

Human lymphoblastoid cell lines (LCLs), generated through Epstein-Barr Virus (EBV) transformation of B-lymphocytes (B-cells), are a commonly used model system for identifying genetic influences on human diseases and on drug responses. We have previously used LCLs to examine the cellular effects of genetic variants that modulate the efficacy of statins, the most prescribed class of cholesterol-lowering drugs used for the prevention and treatment of cardiovascular disease. However, statin-induced gene expression differences observed in LCLs may be influenced by their transformation, and thus differ from those observed in native B-cells. To assess this possibility, we prepared LCLs and purified B-cells from the same donors, and compared mRNA profiles after 24 h incubation with simvastatin (2 µm) or sham buffer. Genes involved in cholesterol metabolism were similarly regulated between the two cell types under both the statin and sham-treated conditions, and the statin-induced changes were significantly correlated. Genes whose expression differed between the native and transformed cells were primarily implicated in cell cycle, apoptosis and alternative splicing. We found that ChIP-seq signals for MYC and EBNA2 (an EBV transcriptional co-activator) were significantly enriched in the promoters of genes up-regulated in the LCLs compared with the B-cells, and could be involved in the regulation of cell cycle and alternative splicing. Taken together, the results support the use of LCLs for the study of statin effects on cholesterol metabolism, but suggest that drug effects on cell cycle, apoptosis and alternative splicing may be affected by EBV transformation. This dataset is now uploaded to GEO at the accession number GSE51444.

Integrative genomics: quantifying significance of phenotype-genotype relationships from multiple sources of high-throughput data

Given recent advances in the generation of high-throughput data such as whole-genome genetic variation and transcriptome expression, it is critical to come up with novel methods to integrate these heterogeneous datasets and to assess the significance of identified phenotype-genotype relationships. Recent studies show that genome-wide association findings are likely to fall in loci with gene regulatory effects such as expression quantitative trait loci (eQTLs), demonstrating the utility of such integrative approaches. When genotype and gene expression data are available on the same individuals, we and others developed methods wherein top phenotype-associated genetic variants are prioritized if they are associated, as eQTLs, with gene expression traits that are themselves associated with the phenotype. Yet there has been no method to determine an overall p-value for the findings that arise specifically from the integrative nature of the approach. We propose a computationally feasible permutation method that accounts for the assimilative nature of the method and the correlation structure among gene expression traits and among genotypes. We apply the method to data from a study of cellular sensitivity to etoposide, one of the most widely used chemotherapeutic drugs. To our knowledge, this study is the first statistically sound quantification of the overall significance of the genotype-phenotype relationships resulting from applying an integrative approach. This method can be easily extended to cases in which gene expression data are replaced by other molecular phenotypes of interest, e.g., microRNA or proteomic data. This study has important implications for studies seeking to expand on genetic association studies by the use of omics data. Finally, we provide an R code to compute the empirical false discovery rate when p-values for the observed and simulated phenotypes are available.

Genetic and epigenetic variants contributing to clofarabine cytotoxicity

2-chloro-2-fluoro-deoxy-9-D-arabinofuranosyladenine (Clofarabine), a purine nucleoside analog, is used in the treatment of hematologic malignancies and as induction therapy for stem cell transplantation. The discovery of pharmacogenomic markers associated with chemotherapeutic efficacy and toxicity would greatly benefit the utility of this drug. Our objective was to identify genetic and epigenetic variants associated with clofarabine toxicity using an unbiased, whole genome approach. To this end, we employed International HapMap lymphoblastoid cell lines (190 LCLs) of European (CEU) or African (YRI) ancestry with known genetic information to evaluate cellular sensitivity to clofarabine. We measured modified cytosine levels to ascertain the contribution of genetic and epigenetic factors influencing clofarabine-mediated cytotoxicity. Association studies revealed 182 single nucleotide polymorphisms (SNPs) and 143 modified cytosines associated with cytotoxicity in both populations at the threshold P ≤ 0.0001. Correlation between cytotoxicity and baseline gene expression revealed 234 genes at P ≤ 3.98 × 10(-6). Six genes were implicated as: (i) their expression was directly correlated to cytotoxicity, (ii) they had a targeting SNP associated with cytotoxicity, and (iii) they had local modified cytosines associated with gene expression and cytotoxicity. We identified a set of three SNPs and three CpG sites targeting these six genes explaining 43.1% of the observed variation in phenotype. siRNA knockdown of the top three genes (SETBP1, BAG3, KLHL6) in LCLs revealed altered susceptibility to clofarabine, confirming relevance. As clofarabine's toxicity profile includes acute kidney injury, we examined the effect of siRNA knockdown in HEK293 cells. siSETBP1 led to a significant change in HEK293 cell susceptibility to clofarabine.

Addressing human variability in next-generation human health risk assessments of environmental chemicals

BACKGROUND

Characterizing variability in the extent and nature of responses to environmental exposures is a critical aspect of human health risk assessment.

OBJECTIVE

Our goal was to explore how next-generation human health risk assessments may better characterize variability in the context of the conceptual framework for the source-to-outcome continuum.

METHODS

This review was informed by a National Research Council workshop titled "Biological Factors that Underlie Individual Susceptibility to Environmental Stressors and Their Implications for Decision-Making." We considered current experimental and in silico approaches, and emerging data streams (such as genetically defined human cells lines, genetically diverse rodent models, human omic profiling, and genome-wide association studies) that are providing new types of information and models relevant for assessing interindividual variability for application to human health risk assessments of environmental chemicals.

DISCUSSION

One challenge for characterizing variability is the wide range of sources of inherent biological variability (e.g., genetic and epigenetic variants) among individuals. A second challenge is that each particular pair of health outcomes and chemical exposures involves combinations of these sources, which may be further compounded by extrinsic factors (e.g., diet, psychosocial stressors, other exogenous chemical exposures). A third challenge is that different decision contexts present distinct needs regarding the identification-and extent of characterization-of interindividual variability in the human population.

CONCLUSIONS

Despite these inherent challenges, opportunities exist to incorporate evidence from emerging data streams for addressing interindividual variability in a range of decision-making contexts.

SCAN: a systems biology approach to pharmacogenomic discovery

Genome-wide association (GWA) studies have identified thousands of genetic variants that contribute to disease and pharmacologic traits. More recently, high-throughput sequencing studies promise to provide a more complete catalog of genetic variants with roles in human phenotypic variation. Yet, characterizing the influence of functional variants on genes, RNAs, proteins, and ultimately disease or pharmacologic traits is a critical challenge for a vast majority of the implicated susceptibility loci. Here we describe SCAN, a bioinformatics resource we have developed to elucidate the functional consequences of genetic variants identified by genome-wide scans. In particular, this public resource implements a systems biology approach to pharmacogenomic discovery.

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.