Lymphoblastoid cell lines in pharmacogenomic discovery and clinical translation

The CEPH aging cohort and biobank: a valuable collection of biological samples from exceptionally long-lived French individuals and their offspring for longevity studies

The increasing aging of the human population is currently and for the coming decades a major public health issue in many countries, requiring the implementation of global public health policies promoting healthy and successful aging. Individuals are not equal in the face of aging and some can present exceptional healthspan and/or lifespan, which are notably influenced by both genetic and environmental factors. Research and studies on human aging, healthy aging and longevity should rely in particular on cohorts of long-lived individuals, also including biological samples allowing studies on the biology of aging and longevity. In this manuscript, we provide for the first time a complete description of the CEPH (Centre d'Etude du Polymophisme Humain) Aging cohort, an exceptional cohort recruited during the 90s to 2000s, including more than 1700 French long-lived individuals (≥ 90 years old) born between 1875 and 1916 as well as for some of them their siblings and offspring. Among the participants, 1265 were centenarians, including 255 semi-supercentenarians ([105-110] years old) and 25 supercentenarians (≥ 110 years old). The available anthropometric, epidemiologic and clinical data for the cohort participants are described and especially the collection of blood-derived biological samples associated with the cohort which includes DNA, cryopreserved cells and cell lines, plasma, and serum. This biological collection from the first cohort of centenarians in the world is an inestimable resource for ongoing and future molecular, cellular, and functional studies aimed at deciphering the mechanisms of human (successful) aging and longevity.

Star allele search: a pharmacogenetic annotation database and user-friendly search tool of publicly available 1000 Genomes Project biospecimens

Here we describe a new public pharmacogenetic (PGx) annotation database of a large (n = 3,202) and diverse biospecimen collection of 1000 Genomes Project cell lines and DNAs. The database is searchable with a user friendly, web-based tool ( www.coriell.org/StarAllele/Search ). This resource leverages existing whole genome sequencing data and PharmVar annotations to characterize *alleles for each biospecimen in the collection. This new tool is designed to facilitate in vitro functional characterization of *allele haplotypes and diplotypes as well as support clinical PGx assay development, validation, and implementation.

Quartet metabolite reference materials for inter-laboratory proficiency test and data integration of metabolomics profiling

BACKGROUND

Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets.

RESULTS

As part of the Quartet Project, we establish a publicly available suite of four metabolite reference materials derived from B lymphoblastoid cell lines from a family of parents and monozygotic twin daughters. We generate comprehensive LC-MS-based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. The Quartet multi-sample-based signal-to-noise ratio enables objective assessment of the reliability of intra-batch and cross-batch metabolomics profiling in detecting intrinsic biological differences among the four groups of samples. Significant variations in the reliability of the metabolomics profiling are identified across laboratories. Importantly, ratio-based metabolomics profiling, by scaling the absolute values of a study sample relative to those of a common reference sample, enables cross-laboratory quantitative data integration. Thus, we construct the ratio-based high-confidence reference datasets between two reference samples, providing "ground truth" for inter-laboratory accuracy assessment, which enables objective evaluation of quantitative metabolomics profiling using various instruments and protocols.

CONCLUSIONS

Our study provides the community with rich resources and best practices for inter-laboratory proficiency tests and data integration, ensuring reliability of large-scale and longitudinal metabolomic studies.

Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics

BACKGROUND

Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories.

RESULTS

Here, we develop the Quartet standard as a proteome reference material with built-in truths, and distribute the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 mass spectrometry files are obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There is a wide dynamic range of proteomes spanning about 7 orders of magnitude, and the injection order has marked effects on quantitative instead of qualitative characteristics.

CONCLUSION

Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

MKX-AS1 Gene Expression Associated with Variation in Drug Response to Oxaliplatin and Clinical Outcomes in Colorectal Cancer Patients

Oxaliplatin (OXAL) is a commonly used chemotherapy for treating colorectal cancer (CRC). A recent genome wide association study (GWAS) showed that a genetic variant (rs11006706) in the lncRNA gene MKX-AS1 and partnered sense gene MKX could impact the response of genetically varied cell lines to OXAL treatment. This study found that the expression levels of MKX-AS1 and MKX in lymphocytes (LCLs) and CRC cell lines differed between the rs11006706 genotypes, indicating that this gene pair could play a role in OXAL response. Further analysis of patient survival data from the Cancer Genome Atlas (TCGA) and other sources showed that patients with high MKX-AS1 expression status had significantly worse overall survival (HR = 3.2; 95%CI = (1.17-9); p = 0.024) compared to cases with low MKX-AS1 expression status. Alternatively, high MKX expression status had significantly better overall survival (HR = 0.22; 95%CI = (0.07-0.7); p = 0.01) compared to cases with low MKX expression status. These results suggest an association between MKX-AS1 and MKX expression status that could be useful as a prognostic marker of response to OXAL and potential patient outcomes in CRC.

RYK Gene Expression Associated with Drug Response Variation of Temozolomide and Clinical Outcomes in Glioma Patients

Temozolomide (TMZ) chemotherapy is an important tool in the treatment of glioma brain tumors. However, variable patient response and chemo-resistance remain exceptionally challenging. Our previous genome-wide association study (GWAS) identified a suggestively significant association of SNP rs4470517 in the RYK (receptor-like kinase) gene with TMZ drug response. Functional validation of RYK using lymphocytes and glioma cell lines resulted in gene expression analysis indicating differences in expression status between genotypes of the cell lines and TMZ dose response. We conducted univariate and multivariate Cox regression analyses using publicly available TCGA and GEO datasets to investigate the impact of RYK gene expression status on glioma patient overall (OS) and progression-free survival (PFS). Our results indicated that in IDH mutant gliomas, RYK expression and tumor grade were significant predictors of survival. In IDH wildtype glioblastomas (GBM), MGMT status was the only significant predictor. Despite this result, we revealed a potential benefit of RYK expression in IDH wildtype GBM patients. We found that a combination of RYK expression and MGMT status could serve as an additional biomarker for improved survival. Overall, our findings suggest that RYK expression may serve as an important prognostic or predictor of TMZ response and survival for glioma patients.

Pharmacogenomic and Statistical Analysis

Genetic variants can alter response to drugs and other therapeutic interventions. The study of this phenomenon, called pharmacogenomics, is similar in many ways to other types of genetic studies but has distinct methodological and statistical considerations. Genetic variants involved in the processing of exogenous compounds exhibit great diversity and complexity, and the phenotypes studied in pharmacogenomics are also more complex than typical genetic studies. In this chapter, we review basic concepts in pharmacogenomic study designs, data generation techniques, statistical analysis approaches, and commonly used methods and briefly discuss the ultimate translation of findings to clinical care.

Extensive proteome and functional genomic profiling of variability between genetically identical human B-lymphoblastoid cells

In life-science research isogenic B-lymphoblastoid cell lines (LCLs) are widely known and preferred for their genetic stability - they are often used for studying mutations for example, where genetic stability is crucial. We have shown previously that phenotypic variability can be observed in isogenic B-lymphoblastoid cell lines. Isogenic LCLs present well-defined phenotypic differences on various levels, for example on the gene expression level or the chromatin level. Based on our investigations, the phenotypic variability of the isogenic LCLs is accompanied by certain genetic variation too. We have developed a compendium of LCL datasets that present the phenotypic and genetic variability of five isogenic LCLs from a multiomic perspective. In this paper, we present additional datasets generated with Next Generation Sequencing techniques to provide genomic and transcriptomic profiles (WGS, RNA-seq, single cell RNA-seq), protein-DNA interactions (ChIP-seq), together with mass spectrometry and flow cytometry datasets to monitor the changes in the proteome. We are sharing these datasets with the scientific community according to the FAIR principles for further investigations.

Construction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technology

Long-read sequencing technology enable better characterization of structural variants (SVs). To adapt the technology to population-scale analyses, one critical issue is to obtain sufficient amount of high-molecular-weight genomic DNA. Here, we propose utilizing activated T lymphocytes, which can be established efficiently in a biobank to stably supply high-grade genomic DNA sufficiently. We conducted nanopore sequencing of 333 individuals constituting 111 trios with high-coverage long-read sequencing data (depth 22.2x, N50 of 25.8 kb) and identified 74,201 SVs. Our trio-based analysis revealed that more than 95% of the SVs were concordant with Mendelian inheritance. We also identified SVs associated with clinical phenotypes, all of which appear to be stably transmitted from parents to offspring. Our data provide a catalog of SVs in the general Japanese population, and the applied approach using the activated T-lymphocyte resource will contribute to biobank-based human genetic studies focusing on SVs at the population scale.

Long-read sequencing on activated T-cells from a sample of 333 Japanese individuals (representing 111 parent-offspring trios) provides a useful reference dataset of structural variation in the Japanese population.

A Population-Based Human In Vitro Approach to Quantify Inter-Individual Variability in Responses to Chemical Mixtures

Human cell-based population-wide in vitro models have been proposed as a strategy to derive chemical-specific estimates of inter-individual variability; however, the utility of this approach has not yet been tested for cumulative exposures in mixtures. This study aimed to test defined mixtures and their individual components and determine whether adverse effects of the mixtures were likely to be more variable in a population than those of the individual chemicals. The in vitro model comprised 146 human lymphoblastoid cell lines from four diverse subpopulations of European and African descent. Cells were exposed, in concentration−response, to 42 chemicals from diverse classes of environmental pollutants; in addition, eight defined mixtures were prepared from these chemicals using several exposure- or hazard-based scenarios. Points of departure for cytotoxicity were derived using Bayesian concentration−response modeling and population variability was quantified in the form of a toxicodynamic variability factor (TDVF). We found that 28 chemicals and all mixtures exhibited concentration−response cytotoxicity, enabling calculation of the TDVF. The median TDVF across test substances, for both individual chemicals or defined mixtures, ranged from a default assumption (101/2) of toxicodynamic variability in human population to >10. The data also provide a proof of principle for single-variant genome-wide association mapping for toxicity of the chemicals and mixtures, although replication would be necessary due to statistical power limitations with the current sample size. This study demonstrates the feasibility of using a set of human lymphoblastoid cell lines as an in vitro model to quantify the extent of inter-individual variability in hazardous properties of both individual chemicals and mixtures. The data show that population variability of the mixtures is unlikely to exceed that of the most variable component, and that similarity in genome-wide associations among components may be used to accrue additional evidence for grouping of constituents in a mixture for cumulative assessments.

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.

Potential depression and antidepressant-response biomarkers in human lymphoblast cell lines from treatment-responsive and treatment-resistant subjects: roles of SSRIs and omega-3 polyunsaturated fatty acids

While several therapeutic strategies exist for depression, most antidepressant drugs require several weeks before reaching full biochemical efficacy and remission is not achieved in many patients. Therefore, biomarkers for depression and drug-response would help tailor treatment strategies. This study made use of banked human lymphoblast cell lines (LCLs) from normal and depressed subjects; the latter divided into remitters and non-remitters. Due to the fact that previous studies have shown effects on growth factors, cytokines, and elements of the cAMP-generating system as potential biomarkers for depression and antidepressant action, these were examined in LCLs. Initial gene and protein expression profiles for signaling cascades related to neuroendocrine and inflammatory functions differ among the three groups. Growth factor genes, including VEGFA and BDNF were significantly down-regulated in cells from depressed subjects. In addition, omega-3 polyunsaturated fatty acids (n-3 PUFAs) have been reported to act as both antidepressants and anti-inflammatories, but the mechanisms for these effects are not established. Here we showed that n-3 PUFAs and escitalopram (selective serotonin reuptake inhibitors, SSRIs) treatment increased adenylyl cyclase (AC) and BDNF gene expression in LCLs. These data are consistent with clinical observations showing that n-3 PUFA and SSRI have antidepressant affects, which may be additive. Contrary to observations made in neuronal and glial cells, n-3 PUFA treatment attenuated cAMP accumulation in LCLs. However, while lymphoblasts show paradoxical responses to neurons and glia, patient-derived lymphoblasts appear to carry potential depression biomarkers making them an important tool for studying precision medicine in depressive patients. Furthermore, these data validate usefulness of n-3 PUFAs in treatment for depression.

Extending the lymphoblastoid cell line model for drug combination pharmacogenomics

Combination drug therapies have become an integral part of precision oncology, and while evidence of clinical effectiveness continues to grow, the underlying mechanisms supporting synergy are poorly understood. Immortalized human lymphoblastoid cell lines (LCLs) have been proven as a particularly useful, scalable and low-cost model in pharmacogenetics research, and are suitable for elucidating the molecular mechanisms of synergistic combination therapies. In this review, we cover the advantages of LCLs in synergy pharmacogenomics and consider recent studies providing initial evidence of the utility of LCLs in synergy research. We also discuss several opportunities for LCL-based systems to address gaps in the research through the expansion of testing regimens, assessment of new drug classes and higher-order combinations, and utilization of integrated omics technologies.

Identifying genetic modulators of statin response using subject-derived lymphoblastoid cell lines

Although statins (3-hydroxy-3-methylglutaryl-CoA reductase inhibitors) have proven effective in reducing plasma low-density lipoprotein levels and risk of cardiovascular disease, their lipid lowering efficacy is highly variable among individuals. Furthermore, statin treatment carries a small but significant risk of adverse effects, most notably myopathy and new onset diabetes. Hence, identification of biomarkers for predicting patients who would most likely benefit from statin treatment without incurring increased risk of adverse effects can have a significant public health impact. In this review, we discuss the rationale for the use of subject-derived lymphoblastoid cell lines in studies of statin pharmacogenomics and describe a variety of approaches we have employed to identify novel genetic markers associated with interindividual variation in statin response.

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.

LC-MALDI-TOF ISD MS analysis is an effective, simple and rapid method of investigation for histones characterization: Application to EBV lymphoblastoid cell lines

This contribution is the result of our progressive engagement to develop and to apply a top-down liquid chromatography (LC) matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) (LC-MALDI-TOF) analysis for the histone post-translational modifications (PTMs) and variants characterization, mainly in order to provide comprehensive and fast results. The histone post-translational modifications and the differential expression of the histone variants play an essential role both in the DNA packaging mechanism in chromosomes and in the regulation of gene expression in different cellular processes, also in response to molecular agents of environmental origin. This epigenetic mechanism is widely studied in different field such as cellular differentiation, development and in the understanding of mechanisms underlying diseases. The characterization of histone PTMs has traditionally performed by antibodies-based assay, but immunological methods have significant limits, and today systems that use mass spectrometry are increasingly employed. We evaluated an in-source decay (ISD) analysis for the histone investigation on human lymphoblastoid cells, and by this approach, we were able to identify and quantify several PTMs such as the di-methylation in the lysine 20 and the acetylation in the lysine 16 in H4 and the mono-methylation, di-methylation and trimethylations at K9 of the histone H3.1. Moreover, we detected and quantified in the same H2B spectrum the prevalent H2B 1C/2E type but also the minor H2B 1D, 1M and 1B/1L/1N, 1O/2F, 1J/1K variants. In this work, we show that MALDI-ISD represents an excellent methodology to obtain global information on histone PTMs and variants from cells in culture, with rapidity and simplicity of execution. Finally, this is a useful approach to get label-free relative quantitative data of histone variants and PTMs.

Genetically regulated expression underlies cellular sensitivity to chemotherapy in diverse populations

Most cancer chemotherapeutic agents are ineffective in a subset of patients; thus, it is important to consider the role of genetic variation in drug response. Lymphoblastoid cell lines (LCLs) in 1000 Genomes Project populations of diverse ancestries are a useful model for determining how genetic factors impact the variation in cytotoxicity. In our study, LCLs from three 1000 Genomes Project populations of diverse ancestries were previously treated with increasing concentrations of eight chemotherapeutic drugs, and cell growth inhibition was measured at each dose with half-maximal inhibitory concentration (IC50) or area under the dose-response curve (AUC) as our phenotype for each drug. We conducted both genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) within and across ancestral populations. We identified four unique loci in GWAS and three genes in TWAS to be significantly associated with the chemotherapy-induced cytotoxicity within and across ancestral populations. In the etoposide TWAS, increased STARD5 predicted expression associated with decreased etoposide IC50 (P = 8.5 × 10-8). Functional studies in A549, a lung cancer cell line, revealed that knockdown of STARD5 expression resulted in the decreased sensitivity to etoposide following exposure for 72 (P = 0.033) and 96 h (P = 0.0001). By identifying loci and genes associated with cytotoxicity across ancestral populations, we strive to understand the genetic factors impacting the effectiveness of chemotherapy drugs and to contribute to the development of future cancer treatment.

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.

Childhood maltreatment and HPA axis gene expression in bipolar disorders: A gene network analysis

INTRODUCTION

Bipolar disorder (BD) is highly associated with childhood maltreatment (CM), the exposure to such early adversity being suggested to disrupt the expression of several biological pathways. This study aims at exploring associations between the mRNA levels of 9 HPA axis genes in lymphoblastoid cell lines from patients with BD according to their self-reported exposure to CM.

METHODS

The sample consisted of 33 Caucasian patients with a diagnosis of BD type 1, assessed for the exposure to CM with the Childhood Trauma Questionnaire (CTQ). Quantitative RT-PCR was performed on 9 transcripts of the HPA axis genes: DGKH, FKBP5, NR3C1, SGK1, SGK2, SGK3, SKA2, STAT5A and UCN. RT-qPCR data were analyzed using the method of disjoint gene networks with SARP.compo package for R.

RESULTS

We found no associations between CTQ total score and the amount of HPA axis transcripts neither in univariate analyses, nor with network analyses. Emotional abuse (EA) was associated with a significant decreased expression of two transcripts, DGKH (p = 0.009) and NR3C1 (p = 0.04). This was confirmed by the disjoint network analysis, which showed that NR3C1 and DGKH were expressed differently from the rest of the HPA axis network in presence of emotional abuse.

DISCUSSION

This study described the expression levels of a comprehensive set of HPA axis genes according to childhood maltreatment in a sample of patients with BD type 1 and suggested that emotional abuse decreased the expression of NR3C1 and DGKH. Our results require further replication in independent larger samples.

Citalopram-induced pathways regulation and tentative treatment-outcome-predicting biomarkers in lymphoblastoid cell lines from depression patients

Antidepressant therapy is still associated with delays in symptomatic improvement and low response rates. Incomplete understanding of molecular mechanisms underlying antidepressant effects hampered the identification of objective biomarkers for antidepressant response. In this work, we studied transcriptome-wide expression followed by pathway analysis in lymphoblastoid cell lines (LCLs) derived from 17 patients documented for response to SSRI antidepressants from the Munich Antidepressant Response Signatures (MARS) study upon short-term incubation (24 and 48 h) with citalopram. Candidate transcripts were further validated with qPCR in MARS LCLs from responders (n = 33) vs. non-responders (n = 36) and afterward in an independent cohort of treatment-resistant patients (n = 20) vs. first-line responders (n = 24) from the STAR*D study. In MARS cohort we observed significant associations of GAD1 (glutamate decarboxylase 1; p = 0.045), TBC1D9 (TBC1 Domain Family Member 9; p = 0.014-0.021) and NFIB (nuclear factor I B; p = 0.015-0.025) expression with response status, remission status and improvement in depression scale, respectively. Pathway analysis of citalopram-altered gene expression indicated response-status-dependent transcriptional reactions. Whereas in clinical responders neural function pathways were primarily up- or downregulated after incubation with citalopram, deregulated pathways in non-responders LCLs mainly involved cell adhesion and immune response. Results from the STAR*D study showed a marginal association of treatment-resistant depression with NFIB (p = 0.068) but not with GAD1 (p = 0.23) and TBC1D9 (p = 0.27). Our results propose the existence of distinct pathway regulation mechanisms in responders vs. non-responders and suggest GAD1, TBC1D9, and NFIB as tentative predictors for clinical response, full remission, and improvement in depression scale, respectively, with only a weak overlap in predictors of different therapy outcome phenotypes.

Epstein-Barr virus subverts mevalonate and fatty acid pathways to promote infected B-cell proliferation and survival

Epstein-Barr virus (EBV) causes infectious mononucleosis and is associated with multiple human malignancies. EBV drives B-cell proliferation, which contributes to the pathogenesis of multiple lymphomas. Yet, knowledge of how EBV subverts host biosynthetic pathways to transform resting lymphocytes into activated lymphoblasts remains incomplete. Using a temporal proteomic dataset of EBV primary human B-cell infection, we identified that cholesterol and fatty acid biosynthetic pathways were amongst the most highly EBV induced. Epstein-Barr nuclear antigen 2 (EBNA2), sterol response element binding protein (SREBP) and MYC each had important roles in cholesterol and fatty acid pathway induction. Unexpectedly, HMG-CoA reductase inhibitor chemical epistasis experiments revealed that mevalonate pathway production of geranylgeranyl pyrophosphate (GGPP), rather than cholesterol, was necessary for EBV-driven B-cell outgrowth, perhaps because EBV upregulated the low-density lipoprotein receptor in newly infected cells for cholesterol uptake. Chemical and CRISPR genetic analyses highlighted downstream GGPP roles in EBV-infected cell small G protein Rab activation. Rab13 was highly EBV-induced in an EBNA3-dependent manner and served as a chaperone critical for latent membrane protein (LMP) 1 and 2A trafficking and target gene activation in newly infected and in lymphoblastoid B-cells. Collectively, these studies identify highlight multiple potential therapeutic targets for prevention of EBV-transformed B-cell growth and survival.

EBV, the first human tumor virus identified, persistently infects >95% of adults worldwide. Upon infection of small, resting B-lymphocytes, EBV establishes a state of viral latency, where viral oncoproteins and non-coding RNAs activate host pathways to promote rapid B-cell proliferation. EBV’s growth-transforming properties are closely linked to the pathogenesis of multiple immunoblastic lymphomas, particularly in immunosuppressed hosts. While EBV oncogenes important for B-cell transformation have been identified, knowledge remains incomplete of how these EBV factors remodel cellular metabolism, a hallmark of human cancers. Using a recently established proteomic map of EBV-mediated B-cell growth transformation, we found that EBV induces biosynthetic pathways that convert acetyl-coenzyme A (acetyl-CoA) into isoprenoids, steroids, terpenoids, cholesterol, and long-chain fatty acids. Viral nuclear antigens cooperated with EBV-activated host transcription factors to upregulate rate-limiting enzymes of these biosynthetic pathways. The isoprenoid geranylgeranyl pyrophosphate was identified as a key product of the EBV-induced mevalonate pathway. Our studies highlighted GGPP roles in Rab protein activation, and Rab13 was identified as a highly EBV-upregulated GTPase critical for LMP1 and LMP2A trafficking and signaling. These studies identify multiple EBV-induced metabolic enzymes important for B-cell transformation, including potential therapeutic targets.

High-efficiency genomic editing in Epstein-Barr virus-transformed lymphoblastoid B cells using a single-stranded donor oligonucleotide strategy

While human lymphoblastoid cell lines represent a valuable resource for population genetic studies, they have usually been regarded as difficult for CRISPR-mediated genomic editing because of very inefficient DNA transfection and retroviral or lentiviral transduction in these cells, which becomes a substantial problem when multiple constructs need to be co-expressed. Here we describe a protocol using a single-stranded donor oligonucleotide strategy for 'scarless' editing in lymphoblastoid cells, yielding 12/60 (20%) of clones with homology-directed recombination, when rates of <5-10% are frequently typical for many other cell types. The protocol does not require the use of lentiviruses or stable transfection, permitting lymphoblastoid cell lines to be used for CRISPR-mediated genomic targeting and screening in population genetic studies.

Single-cell RNA sequencing of a European and an African lymphoblastoid cell line

In biomedical research, lymphoblastoid cell lines (LCLs), often established by in vitro infection of resting B cells with Epstein-Barr virus, are commonly used as surrogates for peripheral blood lymphocytes. Genomic and transcriptomic information on LCLs has been used to study the impact of genetic variation on gene expression in humans. Here we present single-cell RNA sequencing (scRNA-seq) data on GM12878 and GM18502—two LCLs derived from the blood of female donors of European and African ancestry, respectively. Cells from three samples (the two LCLs and a 1:1 mixture of the two) were prepared separately using a 10x Genomics Chromium Controller and deeply sequenced. The final dataset contained 7,045 cells from GM12878, 5,189 from GM18502, and 5,820 from the mixture, offering valuable information on single-cell gene expression in highly homogenous cell populations. This dataset is a suitable reference for population differentiation in gene expression at the single-cell level. Data from the mixture provide additional valuable information facilitating the development of statistical methods for data normalization and batch effect correction.

Design Type(s)	transcription profiling design • strain comparison design
Measurement Type(s)	transcription profiling assay
Technology Type(s)	RNA sequencing
Factor Type(s)	ancestry status • sex
Sample Characteristic(s)	GM12878 cell • GM18502 cell • immortal human peripheral vein-derived B cell line cell

Machine-accessible metadata file describing the reported data (ISA-Tab format)

Extensive epigenetic and transcriptomic variability between genetically identical human B-lymphoblastoid cells with implications in pharmacogenomics research

Genotyped human B-lymphoblastoid cell lines (LCLs) are widely used models in mapping quantitative trait loci for chromatin features, gene expression, and drug response. The extent of genotype-independent functional genomic variability of the LCL model, although largely overlooked, may inform association study design. In this study, we use flow cytometry, chromatin immunoprecipitation sequencing and mRNA sequencing to study surface marker patterns, quantify genome-wide chromatin changes (H3K27ac) and transcriptome variability, respectively, among five isogenic LCLs derived from the same individual. Most of the studied LCLs were non-monoclonal and had mature B cell phenotypes. Strikingly, nearly one-fourth of active gene regulatory regions showed significantly variable H3K27ac levels, especially enhancers, among which several were classified as clustered enhancers. Large, contiguous genomic regions showed signs of coordinated activity change. Regulatory differences were mirrored by mRNA expression changes, preferentially affecting hundreds of genes involved in specialized cellular processes including immune and drug response pathways. Differential expression of DPYD, an enzyme involved in 5-fluorouracil (5-FU) catabolism, was associated with variable LCL growth inhibition mediated by 5-FU. The extent of genotype-independent functional genomic variability might highlight the need to revisit study design strategies for LCLs in pharmacogenomics.

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.

The influence of Neanderthal alleles on cytotoxic response

Various studies have shown that people of Eurasian origin contain traces of DNA inherited from interbreeding with Neanderthals. Recent studies have demonstrated that these Neanderthal variants influence a range of clinically important traits and diseases. Thus, understanding the genetic factors responsible for the variability in individual response to drug or chemical exposure is a key goal of pharmacogenomics and toxicogenomics, as dose responses are clinically and epidemiologically important traits. It is well established that ethnic and racial differences are important in dose response traits, but to our knowledge the influence of Neanderthal ancestry on response to xenobiotics is unknown. Towards this aim, we examined if Neanderthal ancestry plays a role in cytotoxic response to anti-cancer drugs and toxic environmental chemicals. We identified common Neanderthal variants in lymphoblastoid cell lines (LCLs) derived from the globally diverse 1000 Genomes Project and Caucasian cell lines from the Children's Hospital of Oakland Research Institute. We analyzed the effects of these Neanderthal alleles on cytotoxic response to 29 anti-cancer drugs and 179 environmental chemicals at varying concentrations using genome-wide data. We identified and replicated single nucleotide polymorphisms (SNPs) from these association results, including a SNP in the SNORD-113 cluster. Our results also show that the Neanderthal alleles cumulatively lead to increased sensitivity to both the anti-cancer drugs and the environmental chemicals. Our results demonstrate the influence of Neanderthal ancestry-informative markers on cytotoxic response. These results could be important in identifying biomarkers for personalized medicine or in dissecting the underlying etiology of dose response traits.

Identification of novel circulatory microRNA signatures linked to patients with ischemic stroke

MicroRNAs (miRNAs) are involved in growth, development, and occurrence and progression of many diseases. MiRNA-mediated post-transcriptional regulation is poorly understood in vascular biology and pathology. The purpose of this is to determine circulatory miRNAs as early detectable peripheral biomarkers in patients with ischemic stroke (IS). MiRNAs expression levels were measured in IS serum samples and healthy controls using Illumina deep sequencing analysis and identified differentially expressed miRNAs. Differentially expressed miRNAs were further validated using SYBR-green-based quantitative real-time PCR (qRT-PCR) assay in postmortem IS brains, lymphoblastoid IS cell lines, oxygen and glucose deprivation/reoxygenation -treated human and mouse neuroblastoma cells, and mouse models of hypoxia and ischemia (HI)-induced stroke. A total of 4656 miRNAs were differentially expressed in IS serum samples relative to healthy controls. Out of 4656 miRNAs, 272 were found to be significantly deregulated in IS patients. Interestingly, we found several novel and previously unreported miRNAs in IS patients relative to healthy controls. Further analyses revealed that some candidate miRNAs and its target genes were involved in the regulation of the stroke. To the best of our knowledge, this is the first study identified potential novel candidate miRNAs in IS serum samples from the residents of rural West Texas. MiRNAs identified in this study could potentially be used as a biomarker and the development of novel therapeutic approaches for stroke. Further studies are necessary to better understand miRNAs-regulated stroke cellular changes.

Integration of genetic and functional genomics data to uncover chemotherapeutic induced cytotoxicity

Identifying genetic variants associated with chemotherapeutic induced toxicity is an important step towards personalized treatment of cancer patients. However, annotating and interpreting the associated genetic variants remains challenging because each associated variant is a surrogate for many other variants in the same region. The issue is further complicated when investigating patterns of associated variants with multiple drugs. In this study, we used biological knowledge to annotate and compare genetic variants associated with cellular sensitivity to mechanistically distinct chemotherapeutic drugs, including platinating agents (cisplatin, carboplatin), capecitabine, cytarabine, and paclitaxel. The most significantly associated SNPs from genome wide association studies of cellular sensitivity to each drug in lymphoblastoid cell lines derived from populations of European (CEU) and African (YRI) descent were analyzed for their enrichment in biological pathways and processes. We annotated genetic variants using higher-level biological annotations in efforts to group variants into more interpretable biological modules. Using the higher-level annotations, we observed distinct biological modules associated with cell line populations as well as classes of chemotherapeutic drugs. We also integrated genetic variants and gene expression variables to build predictive models for chemotherapeutic drug cytotoxicity and prioritized the network models based on the enrichment of DNA regulatory data. Several biological annotations, often encompassing different SNPs, were replicated in independent datasets. By using biological knowledge and DNA regulatory information, we propose a novel approach for jointly analyzing genetic variants associated with multiple chemotherapeutic drugs.

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.

Enhanced Utilization of Induced Pluripotent Stem Cell-Derived Human Intestinal Organoids Using Microengineered Chips

BACKGROUND AND AIMS

Human intestinal organoids derived from induced pluripotent stem cells have tremendous potential to elucidate the intestinal epithelium's role in health and disease, but it is difficult to directly assay these complex structures. This study sought to make this technology more amenable for study by obtaining epithelial cells from induced pluripotent stem cell-derived human intestinal organoids and incorporating them into small microengineered Chips. We then investigated if these cells within the Chip were polarized, had the 4 major intestinal epithelial subtypes, and were biologically responsive to exogenous stimuli.

METHODS

Epithelial cells were positively selected from human intestinal organoids and were incorporated into the Chip. The effect of continuous media flow was examined. Immunocytochemistry and in situ hybridization were used to demonstrate that the epithelial cells were polarized and possessed the major intestinal epithelial subtypes. To assess if the incorporated cells were biologically responsive, Western blot analysis and quantitative polymerase chain reaction were used to assess the effects of interferon (IFN)-γ, and fluorescein isothiocyanate-dextran 4 kDa permeation was used to assess the effects of IFN-γ and tumor necrosis factor-α on barrier function.

RESULTS

The optimal cell seeding density and flow rate were established. The continuous administration of flow resulted in the formation of polarized intestinal folds that contained Paneth cells, goblet cells, enterocytes, and enteroendocrine cells along with transit-amplifying and LGR5⁺ stem cells. Administration of IFN-γ for 1 hour resulted in the phosphorylation of STAT1, whereas exposure for 3 days resulted in a significant upregulation of IFN-γ related genes. Administration of IFN-γ and tumor necrosis factor-α for 3 days resulted in an increase in intestinal permeability.

CONCLUSIONS

We demonstrate that the Intestine-Chip is polarized, contains all the intestinal epithelial subtypes, and is biologically responsive to exogenous stimuli. This represents a more amenable platform to use organoid technology and will be highly applicable to personalized medicine and a wide range of gastrointestinal conditions.

Rethinking ovarian cancer genomics: where genome-wide association studies stand?

Genome-wide association studies (GWAS) allow the finding of genetic variants associated with several traits. Regarding ovarian cancer (OC), 15 GWAS have been conducted since 2009, with the discovery of 49 SNPs associated with disease susceptibility and 46 with impact in the clinical outcome of patients (p < 5.00 × 10-2). Among them, 14 variants reached the genome-wide significance (p < 5.00 × 10−8). Despite the results obtained, they should be validated in independent sets. So far, five validation studies have been conducted which could confirm the association of 12 OC susceptibility SNPs. Consequently, post-GWAS studies are crucial unravel the biological plausibility of GWAS’ findings and the allelic spectrum of OC.

Comparable impediment of cognitive function in female and male rats subsequent to daily administration of haloperidol after traumatic brain injury

Antipsychotic drugs, such as haloperidol (HAL), are prescribed in the clinic to manage traumatic brain injury (TBI)-induced agitation. While preclinical studies have consistently shown that once-daily administration of HAL hinders functional recovery after TBI in male rats, its effects in females are unknown. Hence, the objective of this study was to directly compare neurobehavioral and histological outcomes in both sexes to determine whether the reported deleterious effects of HAL extend to females. Anesthetized adult female and male rats received either a controlled cortical impact (CCI) or sham injury and then were randomly assigned to a dosing regimen of HAL (0.5mg/kg, i.p.) or vehicle (VEH; 1mL/kg, i.p.) that was initiated 24h after injury and continued once daily for 19 consecutive days. Motor function was tested using established beam-balance/walk protocols on post-operative days 1-5 and acquisition of spatial learning was assessed with a well-validated Morris water maze task on days 14-19. Cortical lesion volume was quantified at 21days. No statistical differences were revealed between the HAL and VEH-treated sham groups and thus they were pooled for each sex. HAL only impaired motor recovery in males (p<0.05), but significantly diminished spatial learning in both sexes (p<0.05). Females, regardless of treatment, exhibited smaller cortical lesions vs VEH-treated males (p<0.05). Taken together, the data show that daily HAL does not prohibit motor recovery in females, but does negatively impact cognition. These task-dependent differential effects of HAL in female vs male rats may have clinical significance as they can direct therapy.

TCL1A Single-Nucleotide Polymorphisms and Estrogen-Mediated Toll-Like Receptor-MYD88-Dependent Nuclear Factor-κB Activation: Single-Nucleotide Polymorphism- and Selective Estrogen Receptor Modulator-Dependent Modification of Inflammation and Immune Response

In a previous genome-wide association study (GWAS) for musculoskeletal adverse events during aromatase inhibitor therapy for breast cancer, we reported that single nucleotide polymorphisms (SNPs) near the TCL1A gene were associated with this adverse drug reaction. Functional genomic studies showed that TCL1A expression was induced by estradiol, but only in cells with the variant sequence for the top GWAS SNP (rs11849538), a SNP that created a functional estrogen response element. In addition, TCL1A genotype influenced the downstream expression of a series of cytokines and chemokines and had a striking effect on nuclear factor κB (NF-κB) transcriptional activity. Furthermore, this SNP-dependent regulation could be reversed by selective ER modulators (SERMs). The present study was designed to pursue mechanisms underlying TCL1A SNP-mediated, estrogen-dependent NF-κB activation. Functional genomic studies were performed using a panel of 300 lymphoblastoid cell lines for which we had generated genome-wide SNP and gene expression data. It is known that toll-like receptors (TLRs) can regulate NF-κB signaling by a process that requires the adaptor protein MYD88. We found that TLR2, TLR7, TLR9, and TLR10 expression, as well as that of MYD88, could be modulated by TCL1A in a SNP and estrogen-dependent fashion and that these effects were reversed in the presence of SERMs. Furthermore, MYD88 inhibition blocked the TCL1A SNP and estrogen-dependent NF-κB activation, as well as protein-protein interaction between TCL1A and MYD88. These observations greatly expand the range of pathways influenced by TCL1A genotype and raise the possibility that this estrogen- and SNP-dependent regulation might be altered pharmacologically by SERMs.

Genetic Variants Contributing to Colistin Cytotoxicity: Identification of TGIF1 and HOXD10 Using a Population Genomics Approach

Colistin sulfate (polymixin E) is an antibiotic prescribed with increasing frequency for severe Gram-negative bacterial infections. As nephrotoxicity is a common side effect, the discovery of pharmacogenomic markers associated with toxicity would benefit the utility of this drug. Our objective was to identify genetic markers of colistin cytotoxicity that were also associated with expression of key proteins using an unbiased, whole genome approach and further evaluate the functional significance in renal cell lines. To this end, we employed International HapMap lymphoblastoid cell lines (LCLs) of Yoruban ancestry with known genetic information to perform a genome-wide association study (GWAS) with cellular sensitivity to colistin. Further association studies revealed that single nucleotide polymorphisms (SNPs) associated with gene expression and protein expression were significantly enriched in SNPs associated with cytotoxicity (p ≤ 0.001 for gene and p = 0.015 for protein expression). The most highly associated SNP, chr18:3417240 (p = 6.49 × 10⁻⁸), was nominally a cis-expression quantitative trait locus (eQTL) of the gene TGIF1 (transforming growth factor β (TGFβ)-induced factor-1; p = 0.021) and was associated with expression of the protein HOXD10 (homeobox protein D10; p = 7.17 × 10⁻⁵). To demonstrate functional relevance in a murine colistin nephrotoxicity model, HOXD10 immunohistochemistry revealed upregulated protein expression independent of mRNA expression in response to colistin administration. Knockdown of TGIF1 resulted in decreased protein expression of HOXD10 and increased resistance to colistin cytotoxicity. Furthermore, knockdown of HOXD10 in renal cells also resulted in increased resistance to colistin cytotoxicity, supporting the physiological relevance of the initial genomic associations.

Gene expression and proliferation biomarkers for antidepressant treatment resistance

The neurotrophic hypothesis of depression suggests an association between effects on neuroplasticity and clinical response to antidepressant drug therapy. We studied individual variability in antidepressant drug effects on cell proliferation in lymphoblastoid cell lines (LCLs) from n=25 therapy-resistant patients versus n=25 first-line therapy responders from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Furthermore, the variability in gene expression of genes associated with cell proliferation was analyzed for tentative candidate genes for prediction of individual LCL donor's treatment response. Cell proliferation was quantified by EdU (5-ethynyl-2'-deoxyuridine) assays after 21-day incubation of LCLs with fluoxetine (0.5 ng μl-1) and citalopram (0.3 ng μl-1) as developed and described earlier. Gene expression of a panel of candidate genes derived from genome-wide expression analyses of antidepressant effects on cell proliferation of LCLs from the Munich Antidepressant Response Signature (MARS) study was analyzed by real-time PCR. Significant differences in in vitro cell proliferation effects were detected between the group of LCLs from first-line therapy responders and LCLs from treatment-resistant patients. Gene expression analysis of the candidate gene panel revealed and confirmed influence of the candidate genes ABCB1, FZD7 and WNT2B on antidepressant drug resistance. The potential of these genes as tentative biomarkers for antidepressant drug resistance was confirmed. In vitro cell proliferation testing may serve as functional biomarker for individual neuroplasticity effects of antidepressants.

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.

Computational discovery of transcription factors associated with drug response

This study integrates gene expression, genotype and drug response data in lymphoblastoid cell lines with transcription factor (TF)-binding sites from ENCODE (Encyclopedia of Genomic Elements) in a novel methodology that elucidates regulatory contexts associated with cytotoxicity. The method, GENMi (Gene Expression iN the Middle), postulates that single-nucleotide polymorphisms within TF-binding sites putatively modulate its regulatory activity, and the resulting variation in gene expression leads to variation in drug response. Analysis of 161 TFs and 24 treatments revealed 334 significantly associated TF-treatment pairs. Investigation of 20 selected pairs yielded literature support for 13 of these associations, often from studies where perturbation of the TF expression changes drug response. Experimental validation of significant GENMi associations in taxanes and anthracyclines across two triple-negative breast cancer cell lines corroborates our findings. The method is shown to be more sensitive than an alternative, genome-wide association study-based approach that does not use gene expression. These results demonstrate the utility of GENMi in identifying TFs that influence drug response and provide a number of candidates for further testing.

Modeling neurological diseases with induced pluripotent cells reprogrammed from immortalized lymphoblastoid cell lines

Patient-specific induced pluripotent stem cells (iPSCs) facilitate understanding of the etiology of diseases, discovery of new drugs and development of novel therapeutic interventions. A frequently used starting source of cells for generating iPSCs has been dermal fibroblasts (DFs) isolated from skin biopsies. However, there are also numerous repositories containing lymphoblastoid B-cell lines (LCLs) generated from a variety of patients. To date, this rich bioresource of LCLs has been underused for generating iPSCs, and its use would greatly expand the range of targeted diseases that could be studied by using patient-specific iPSCs. However, it remains unclear whether patient’s LCL-derived iPSCs (LiPSCs) can function as a disease model. Therefore, we generated Parkinson’s disease patient-specific LiPSCs and evaluated their utility as tools for modeling neurological diseases. We established iPSCs from two LCL clones, which were derived from a healthy donor and a patient carrying PARK2 mutations, by using existing non-integrating episomal protocols. Whole genome sequencing (WGS) and comparative genomic hybridization (CGH) analyses showed that the appearance of somatic variations in the genomes of the iPSCs did not vary substantially according to the original cell types (LCLs, T-cells and fibroblasts). Furthermore, LiPSCs could be differentiated into functional neurons by using the direct neurosphere conversion method (dNS method), and they showed several Parkinson’s disease phenotypes that were similar to those of DF-iPSCs. These data indicate that the global LCL repositories can be used as a resource for generating iPSCs and disease models. Thus, LCLs are the powerful tools for generating iPSCs and modeling neurological diseases.

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.

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.

Lithium-responsive genes and gene networks in bipolar disorder patient-derived lymphoblastoid cell lines

Lithium (Li) is the mainstay mood stabilizer for the treatment of bipolar disorder (BD), although its mode of action is not yet fully understood nor is it effective in every patient. We sought to elucidate the mechanism of action of Li and to identify surrogate outcome markers that can be used to better understand its therapeutic effects in BD patients classified as good (responders) and poor responders (nonresponders) to Li treatment. To accomplish these goals, RNA-sequencing gene expression profiles of lymphoblastoid cell lines (LCLs) were compared between BD Li responders and nonresponders with healthy controls before and after treatment. Several Li-responsive gene coexpression networks were discovered indicating widespread effects of Li on diverse cellular signaling systems including apoptosis and defense response pathways, protein processing and response to endoplasmic reticulum stress. Individual gene markers were also identified, differing in response to Li between BD responders and nonresponders, involved in processes of cell cycle and nucleotide excision repair that may explain part of the heterogeneity in clinical response to treatment. Results further indicated a Li gene expression signature similar to that observed with clonidine treatment, an α2-adrenoceptor agonist. These findings provide a detailed mechanism of Li in LCLs and highlight putative surrogate outcome markers that may permit for advanced treatment decisions to be made and for facilitating recovery in BD patients.

Transcriptomic variation of pharmacogenes in multiple human tissues and lymphoblastoid cell lines

Variation in the expression level and activity of genes involved in drug disposition and action (‘pharmacogenes') can affect drug response and toxicity, especially when in tissues of pharmacological importance. Previous studies have relied primarily on microarrays to understand gene expression differences, or have focused on a single tissue or small number of samples. The goal of this study was to use RNA-sequencing (RNA-seq) to determine the expression levels and alternative splicing of 389 Pharmacogenomics Research Network pharmacogenes across four tissues (liver, kidney, heart and adipose) and lymphoblastoid cell lines, which are used widely in pharmacogenomics studies. Analysis of RNA-seq data from 139 different individuals across the 5 tissues (20–45 individuals per tissue type) revealed substantial variation in both expression levels and splicing across samples and tissue types. Comparison with GTEx data yielded a consistent picture. This in-depth exploration also revealed 183 splicing events in pharmacogenes that were previously not annotated. Overall, this study serves as a rich resource for the research community to inform biomarker and drug discovery and use.

Genome-wide microarray analysis of gene expression profiling in major depression and antidepressant therapy

Major depressive disorder (MDD) is a serious health concern worldwide. Currently there are no predictive tests for the effectiveness of any particular antidepressant in an individual patient. Thus, doctors must prescribe antidepressants based on educated guesses. With the recent advent of scientific research, genome-wide gene expression microarray studies are widely utilized to analyze hundreds of thousands of biomarkers by high-throughput technologies. In addition to the candidate-gene approach, the genome-wide approach has recently been employed to investigate the determinants of MDD as well as antidepressant response to therapy. In this review, we mainly focused on gene expression studies with genome-wide approaches using RNA derived from peripheral blood cells. Furthermore, we reviewed their limitations and future directions with respect to the genome-wide gene expression profiling in MDD pathogenesis as well as in antidepressant therapy.

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.