Pharmacogenomics of chemotherapeutic susceptibility and toxicity

Precise Therapy Using the Selective Endogenous Encapsidation for Cellular Delivery Vector System

Interindividual variability in drug response is a major problem in the prescription of pharmacological treatments. The therapeutic effect of drugs can be influenced by human genes. Pharmacogenomic guidelines for individualization of treatment have been validated and used for conventional dosage forms. However, drugs can often target non-specific areas and produce both desired and undesired pharmacological effects. The use of nanoparticles, liposomes, or other available forms for drug formulation could help to overcome the latter problem. Virus-like particles based on retroviruses could be a potential envelope for safe and efficient drug formulations. Human endogenous retroviruses would make it possible to overcome the host immune response and deliver drugs to the desired target. PEG10 is a promising candidate that can bind to mRNA because it is secreted like an enveloped virus-like extracellular vesicle. PEG10 is a retrotransposon-derived gene that has been domesticated. Therefore, formulations with PEG10 may have a lower immunogenicity. The use of existing knowledge can lead to the development of suitable drug formulations for the precise treatment of individual diseases.

Immunogenetic variations predict immune-related adverse events for PD-1/PD-L1 inhibitors

BACKGROUND

PD-1/PD-L1 inhibitors have brought remarkable benefits but can cause profound immune-related adverse events (irAEs). The host immunogenetic background is likely to play a role in irAE susceptibility. In this study, we aimed to identify potential immunogenetic biomarkers to predict irAEs.

METHODS

Patients with solid tumours receiving PD-1/PD-L1 blockade were recruited and followed up. Genes considered pivotal contributors to tumour-immunity and autoimmune diseases were screened out via protein-protein interaction network and Cytoscape. Consequently, thirty-nine variants in eighteen genes were genotyped using the multiplex genotyping assay. Association analysis between genetic variants and irAEs as well as irAEs-free survival was performed.

RESULTS

Four immunogenetic variants as predictive biomarkers of irAEs were identified. The C allele of Mitogen-Activated Protein Kinase 1 (MAPK1) rs3810610 (odds ratio [OR] = 1.495, 95% confidence interval [CI] = 1.093-2.044, P = 0.012) was a risk predictor while the A allele of PTPRC rs6428474 (OR = 0.717, 95% CI = 0.521-0.987, P = 0.041) was a protective factor for all-grade irAEs. The A allele of ADAD1 rs17388568 (OR = 2.599, 95% CI = 1.355-4.983, P = 0.003) increased the risk while the G allele of IL6 rs1800796 (OR = 0.425, 95% CI = 0.205-0.881, P = 0.018) protected patients from high-grade irAEs. Significant immunogenetic variants reached a similar tendency in PD-1 blockade or lung cancer subgroups. In multivariate Cox regression analysis, the MAPK1 rs3810610 was an independent factor regarding all-grade irAEs-free survival (CC versus CT or TT: hazard ratio [HR] = 0.71, 95% CI = 0.52-0.99, P = 0.042). ADAD1 rs17388568 (AA versus AG or GG: HR = 0.11, 95% CI = 0.025-0.49, P = 0.004) and IL6 rs1800796 (GG or GC versus CC: HR = 3.10, 95% CI = 1.315-7.29, P = 0.01) were independent variables for high-grade irAEs-free survival.

CONCLUSION

We first identified several immunogenetic polymorphisms associated with irAEs and irAEs-free survival in PD-1/PD-L1 blockade-treated tumour patients, and they may serve as potential predictive biomarkers.

Aspirin-Loaded Cross-Linked Lipoic Acid Nanodrug Prevents Postoperative Tumor Recurrence by Residual Cancer Cell Killing and Inflammatory Microenvironment Improvement

In addition to residual cancer cells, the surgery resection-induced hyperinflammatory microenvironment is a key factor that leads to postsurgical cancer recurrence. Herein, we developed a dual-functional nanodrug Asp@cLANVs for postsurgical recurrence inhibition by loading the classical anti-inflammatory drug aspirin (Asp) into cross-linked lipoic acid nanovesicles (cLANVs). The Asp@cLANVs can not only kill residual cancer cells at the doses comparable to common cytotoxic drugs by synergistic interaction between Asp and cLANVs, but also improve the postsurgical inflammatory microenvironment by their strongly synergistic anti-inflammation activity between Asp and cLANVs. Using mice bearing partially removed NCI-H460 tumors, we found that Asp@cLANVs gave a much lower recurrence rate (33.3%) compared with the first-line cytotoxic drug cisplatin (100%), and no mice died for at least 60 days after Asp@cLANV treatment while no mouse survived beyond day 43 in the cisplatin group. This dual-functional nanodrug constructs the first example that combines residual cancer cell killing and postoperative inflammation microenvironment improvement to suppress postsurgical cancer recurrence.

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.

A resource for integrated genomic analysis of the human liver

In this study, we generated whole-transcriptome RNA-Seq from n = 192 genotyped liver samples and used these data with existing data from the GTEx Project (RNA-Seq) and previous liver eQTL (microarray) studies to create an enhanced transcriptomic sequence resource in the human liver. Analyses of genotype-expression associations show pronounced enrichment of associations with genes of drug response. The associations are primarily consistent across the two RNA-Seq datasets, with some modest variation, indicating the importance of obtaining multiple datasets to produce a robust resource. We further used an empirical Bayesian model to compare eQTL patterns in liver and an additional 20 GTEx tissues, finding that MHC genes, and especially class II genes, are enriched for liver-specific eQTL patterns. To illustrate the utility of the resource to augment GWAS analysis with small sample sizes, we developed a novel meta-analysis technique to combine several liver eQTL data sources. We also illustrate its application using a transcriptome-enhanced re-analysis of a study of neutropenia in pancreatic cancer patients. The associations of genotype with liver expression, including splice variation and its genetic associations, are made available in a searchable genome browser.

Current opinion on the pharmacogenomics of paclitaxel-induced toxicity

Introduction: Paclitaxel is a microtubule stabilizer that is currently one of the most utilized chemotherapeutic agents. Its efficacy in breast, uterine, lung and other neoplasms made its safety profile enhancement a subject of great interest. Neurotoxicity is the most common paclitaxel-associated toxicities. In addition, hypersensitivity reactions, hematological, gastrointestinal, and cardiac toxicities are all encountered.Areas covered: The current review explores paclitaxel-induced toxicities mechanisms and risk factors. Studies investigating these toxicities pharmacogenomic biomarkers are reviewed and summarized. There is a limited margin of consistency between the retrieved associations. Variants in genes related to neuro-sensitivity are the most promising candidates for future studies.Expert opinion: Genome-wide association studies highlighted multiple-candidate biomarkers relevant to neuro-sensitivity. Most of the identified paclitaxel-neurotoxicity candidate genes are derived from congenital neuropathy and diabetic-induced neurotoxicity pathways. Future studies should explore these sets of genes while considering the multifactorial nature of paclitaxel-induced neurotoxicity. In the absence of certain paclitaxel-toxicity biomarkers, future research should avoid earlier studies' caveats. Genes in paclitaxel's pharmacokinetic pathways could not provide consistent results in any of its associated toxicities. There is a need to dig deeper into toxicity-development mechanisms and personal vulnerability factors, rather than targeting only the genes suspected to affect drug exposure.

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.

Absolute Neutrophil Count after the First Chemotherapy Cycle as a Surrogate Marker for Treatment Outcomes in Patients with Neuroblastoma

Purpose

We performed this study to determine whether the degree of neutropenia after the first chemotherapy cycle can be used as a surrogate marker of individual susceptibility to chemotherapeutic agents affecting treatment outcome in patients with neuroblastoma.

Materials and Methods

The study included 313 patients who received the first cycle chemotherapy with a CEDC (cisplatin+etoposide+doxorubicin+cyclophosphamide) regimen and had absolute neutrophil count (ANC) data available. The cumulative incidences of progression and treatment-related mortality (TRM) were estimated. To identify genetic variations associated with the ANC, a genome-wide association study (GWAS) was performed.

Results

An ANC of 32.5/μL was determined as the cutoff point to categorize patients into the good and poor prognosis subgroups in terms of progression. Patients with a high nadir ANC had a higher cumulative incidence of progression than those with a low nadir ANC (p < 0.001). In multivariate analysis, high nadir ANC, age, bone marrow involvement, and unfavorable histology were poor prognostic factors. With regard to the TRM, patients with a low nadir ANC (ANC < 51.0/μL) had a higher cumulative incidence of TRM than those with a high nadir ANC (p=0.010). In GWAS, single-nucleotide polymorphisms of LPHN2 and CRHR1 were significantly associated with the nadir ANC.

Conclusion

In neuroblastoma patients, the degree of neutropenia after the first chemotherapy cycle can be used as a surrogate marker to predict an individual’s susceptibility to chemotherapeutic agents. Tailoring of treatment based on the degree of neutropenia needs to be considered.

Synergistic Chemotherapy Drug Response Is a Genetic Trait in Lymphoblastoid Cell Lines

Lymphoblastoid cell lines (LCLs) are a highly successful model for evaluating the genetic etiology of cancer drug response, but applications using this model have typically focused on single drugs. Combination therapy is quite common in modern chemotherapy treatment since drugs often work synergistically, and it is an important progression in the use of the LCL model to expand work for drug combinations. In the present work, we demonstrate that synergy occurs and can be quantified in LCLs across a range of clinically important drug combinations. Lymphoblastoid cell lines have been commonly employed in association mapping in cancer pharmacogenomics, but it is so far untested as to whether synergistic effects have a genetic etiology. Here we use cell lines from extended pedigrees to demonstrate that there is a substantial heritable component to synergistic drug response. Additionally, we perform linkage mapping in these pedigrees to identify putative regions linked to this important phenotype. This demonstration supports the premise of expanding the use of the LCL model to perform association mapping for combination therapies.

Gene Expression Profiling Analysis Reveals Putative Phytochemotherapeutic Target for Castration-Resistant Prostate Cancer

Prostate cancer is the leading cause of cancer death among men globally, with castration development resistant contributing significantly to treatment failure and death. By analyzing the differentially expressed genes between castration-induced regression nadir and castration-resistant regrowth of the prostate, we identified soluble guanylate cyclase 1 subunit alpha as biologically significant to driving castration-resistant prostate cancer. A virtual screening of the modeled protein against 242 experimentally-validated anti-prostate cancer phytochemicals revealed potential drug inhibitors. Although, the identified four non-synonymous somatic point mutations of the human soluble guanylate cyclase 1 gene could alter its form and ligand binding ability, our analysis identified compounds that could effectively inhibit the mutants together with wild-type. Of the identified phytochemicals, (8′R)-neochrome and (8′S)-neochrome derived from the Spinach (Spinacia oleracea) showed the highest binding energies against the wild and mutant proteins. Our results identified the neochromes and other phytochemicals as leads in pharmacotherapy and as nutraceuticals in management and prevention of castration-resistance prostate cancers.

Whole-body Imaging of Cell Death Provides a Systemic, Minimally Invasive, Dynamic, and Near-real Time Indicator for Chemotherapeutic Drug Toxicity

PURPOSE

Response to toxicity in chemotherapies varies considerably from tissue to tissue and from patient to patient. An ability to monitor the tissue damage done by chemotherapy may have a profound impact on treatment and prognosis allowing for a proactive management in understanding and mitigating such events. For the first time, we investigated the feasibility of using whole-body imaging to map chemotherapeutic drug-induced toxicity on an individual basis.

EXPERIMENTAL DESIGN

In a preclinical proof-of-concept, rats were treated with a single clinical dose of cyclophosphamide, methotrexate, or cisplatin. In vivo whole-body imaging data were acquired using ^99mTc-duramycin, which identifies dead and dying cells as an unambiguous marker for tissue injury in susceptible organs. Imaging results were cross-validated using quantitative ex vivo measurements and histopathology and compared with standard blood and serum panels for toxicology.

RESULTS

The in vivo whole-body imaging data detected widespread changes, where spatially heterogeneous toxic effects were identified across different tissues, within substructures of organs, as well as among different individuals. The signal changes were consistent with established toxicity profiles of these chemotherapeutic drugs. Apart from generating a map of susceptible tissues, this in vivo imaging approach was more sensitive compared with conventional blood and serum markers used in toxicology. Also, repeated imaging during the acute period after drug treatment captured different kinetics of tissue injury among susceptible organs in males and females.

CONCLUSIONS

This novel and highly translational imaging approach shows promise in optimizing therapeutic decisions by detecting and managing drug toxicity on a personalized basis.Toxicity to normal tissues is a significant limitation in chemotherapies. This work demonstrated an in vivo imaging-based approach for characterizing toxicity-induced tissue injury in a systemic, dynamic, and near-real time fashion. This novel approach shows promise in optimizing therapeutic decisions by monitoring drug toxicity on a personalized basis.

The germline genetic component of drug sensitivity in cancer cell lines

Patients with seemingly the same tumour can respond very differently to treatment. There are strong, well-established effects of somatic mutations on drug efficacy, but there is at-most anecdotal evidence of a germline component to drug response. Here, we report a systematic survey of how inherited germline variants affect drug susceptibility in cancer cell lines. We develop a joint analysis approach that leverages both germline and somatic variants, before applying it to screening data from 993 cell lines and 265 drugs. Surprisingly, we find that the germline contribution to variation in drug susceptibility can be as large or larger than effects due to somatic mutations. Several of the associations identified have a direct relationship to the drug target. Finally, using 17-AAG response as an example, we show how germline effects in combination with transcriptomic data can be leveraged for improved patient stratification and to identify new markers for drug sensitivity.

Little is known about the contribution of germline genetic variants to cancer drug sensitivity. Here, the authors devise an approach for joint analysis of germline variants and somatic mutations, identifying substantial germline contributions to variation in drug sensitivity.

Genetic and genomic stability across lymphoblastoid cell line expansions

Objective

Lymphoblastoid cell lines are widely used in genetic and genomic studies. Previous work has characterized variant stability in transformed culture and across culture passages. Our objective was to extend this work to evaluate single nucleotide polymorphism and structural variation across cell line expansions, which are commonly used in biorepository distribution. Our study used DNA and cell lines sampled from six research participants. We assayed genome-wide genetic variants and inferred structural variants for DNA extracted from blood, from transformed cell cultures, and from three generations of expansions.

Results

Single nucleotide variation was stable between DNA and expanded cell lines (ranging from 99.90 to 99.98% concordance). Structural variation was less consistent across expansions (median 33% concordance) with a noticeable decrease in later expansions. In summary, we demonstrate consistency between SNPs assayed from whole blood DNA and LCL DNA; however, more caution should be taken in using LCL DNA to study structural variation.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3664-3) contains supplementary material, which is available to authorized users.

Principled multi-omic analysis reveals gene regulatory mechanisms of phenotype variation

Recent studies have analyzed large-scale data sets of gene expression to identify genes associated with interindividual variation in phenotypes ranging from cancer subtypes to drug sensitivity, promising new avenues of research in personalized medicine. However, gene expression data alone is limited in its ability to reveal cis-regulatory mechanisms underlying phenotypic differences. In this study, we develop a new probabilistic model, called pGENMi, that integrates multi-omic data to investigate the transcriptional regulatory mechanisms underlying interindividual variation of a specific phenotype—that of cell line response to cytotoxic treatment. In particular, pGENMi simultaneously analyzes genotype, DNA methylation, gene expression, and transcription factor (TF)-DNA binding data, along with phenotypic measurements, to identify TFs regulating the phenotype. It does so by combining statistical information about expression quantitative trait loci (eQTLs) and expression-correlated methylation marks (eQTMs) located within TF binding sites, as well as observed correlations between gene expression and phenotype variation. Application of pGENMi to data from a panel of lymphoblastoid cell lines treated with 24 drugs, in conjunction with ENCODE TF ChIP data, yielded a number of known as well as novel (TF, Drug) associations. Experimental validations by TF knockdown confirmed 41% of the predicted and tested associations, compared to a 12% confirmation rate of tested nonassociations (controls). An extensive literature survey also corroborated 62% of the predicted associations above a stringent threshold. Moreover, associations predicted only when combining eQTL and eQTM data showed higher precision compared to an eQTL-only or eQTM-only analysis using pGENMi, further demonstrating the value of multi-omic integrative analysis.

Utility of patient-derived lymphoblastoid cell lines as an ex vivo capecitabine sensitivity prediction model for breast cancer patients

Capecitabine is commonly used in treating breast cancer; however, therapeutic response varies among patients and there is no clinically validated model to predict individual outcomes. Here, we investigated whether drug sensitivity quantified in ex vivo patients' blood-derived cell lines can predict response to capecitabine in vivo. Lymphoblastoid cell lines (LCLs) were established from a cohort of metastatic breast cancer patients (n = 53) who were prospectively monitored during treatment with single agent capecitabine at 2000 mg/m²/day. LCLs were treated with increasing concentrations of 5′-DFUR, a major capecitabine metabolite, to assess patients' ex vivo sensitivity to this drug. Subsequently, ex vivo phenotype was compared to observed patient disease response and drug induced-toxicities. We acquired an independent cohort of breast cancer cell lines and LCLs derived from the same donors from ATCC, compared their sensitivity to 5′-DFUR. As seen in the patient population, we observed large inter-individual variability in response to 5′-DFUR treatment in patient-derived LCLs. Patients whose LCLs were more sensitive to 5′-DFUR had a significantly longer median progression free survival (9-month vs 6-month, log rank p-value = 0.017). In addition, this significant positive correlation for 5′-DFUR sensitivity was replicated in an independent cohort of 8 breast cancer cell lines and LCLs derived from the same donor. Our data suggests that at least a portion of the individual sensitivity to capecitabine is shared between germline tissue and tumor tissue. It also supports the utility of patient-derived LCLs as a predictive model for capecitabine treatment efficacy in breast cancer patients.

Natural variation in a single amino acid substitution underlies physiological responses to topoisomerase II poisons

Many chemotherapeutic drugs are differentially effective from one patient to the next. Understanding the causes of this variability is a critical step towards the development of personalized treatments and improvements to existing medications. Here, we investigate sensitivity to a group of anti-neoplastic drugs that target topoisomerase II using the model organism Caenorhabditis elegans. We show that wild strains of C. elegans vary in their sensitivity to these drugs, and we use an unbiased genetic approach to demonstrate that this natural variation is explained by a methionine-to-glutamine substitution in topoisomerase II (TOP-2). The presence of a non-polar methionine at this residue increases hydrophobic interactions between TOP-2 and its poison etoposide, as compared to a polar glutamine. We hypothesize that this stabilizing interaction results in increased genomic instability in strains that contain a methionine residue. The residue affected by this substitution is conserved from yeast to humans and is one of the few differences between the two human topoisomerase II isoforms (methionine in hTOPIIα and glutamine in hTOPIIβ). We go on to show that this amino acid difference between the two human topoisomerase isoforms influences cytotoxicity of topoisomerase II poisons in human cell lines. These results explain why hTOPIIα and hTOPIIβ are differentially affected by various poisons and demonstrate the utility of C. elegans in understanding the genetics of drug responses.

The severe cytotoxic effects associated with anti-neoplastic treatment regimens make it difficult to assess the contributions of genetic variation on treatment responses in clinical settings. Therefore, we leveraged genetic diversity present in the metazoan model nematode Caenorhabditis elegans to identify genetic variants that contribute to differential susceptibility to a broadly administered class of anti-neoplastic compounds that poison the activity of topoisomerase II enzymes. We show that wild C. elegans isolates contain either glutamine or methionine at a highly conserved residue of the topoisomerase II (TOP-2) protein and that this substitution is predictive of animal responses to the topoisomerase II poisons etoposide, teniposide, dactinomycin, and XK469. Interestingly, the two human versions of this protein, hTOPIIα and hTOPIIβ, contain a methionine or glutamine at the corresponding residue, respectively. We show that this difference between the two human topoisomerase II isoforms contributes to the differential cytotoxicity induced by these drugs. Taken together, our results highlight the power of studying the effects of natural genetic variation on drug responses in a model organism and propose methods to develop new drugs that have increased affinity for the desired hTOPIIα isoform expressed in tumor cells.

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.

Genetic analysis of innate immunity in Behcet's disease identifies an association with IL-37 and IL-18RAP

Interleukin-1 (IL-1) and the IL-1 receptor (IL-1R) family play an important role in the pathogenesis of inflammatory diseases. This study aimed to investigate the association between single nucleotide polymorphisms (SNP) of IL-1 and IL-1R family genes with Vogt-Koyanagi-Harada (VKH) and Behcet’s disease (BD) in Han Chinese. The case-control study was divided into two stages and included 419 VKH cases, 1063 BD cases and 1872 healthy controls. The MassARRAY platform (Sequenom), iPLEX Gold Assay and TaqMan SNP assays were used to score genotypes of 24 SNPs. The expression of IL-37 and IL-18Rap was measured by ELISA and real-time PCR in genotyped healthy individuals. A significantly lower frequency of the AG genotype, and a higher frequency of the GG genotype and G allele of IL-37/rs3811047 were observed in BD as compared to controls. AA genotype and A allele frequency of IL-18RAP/rs2058660 was significantly decreased in BD as compared to controls. Functional studies performed in healthy controls showed that rs3811047 AG genotype carriers had a higher IL-37 gene expression in peripheral blood mononuclear cells (PBMCs) than GG carriers. GG carriers showed a higher cytokine expression as compared to AG carriers. No association was detected between the tested SNPs and VKH.

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.

Identifying Predictors of Taxane-Induced Peripheral Neuropathy Using Mass Spectrometry-Based Proteomics Technology

Major advances in early detection and therapy have significantly increased the survival of breast cancer patients. Unfortunately, most cancer therapies are known to carry a substantial risk of adverse long-term treatment-related effects. Little is known about patient susceptibility to severe side effects after chemotherapy. Chemotherapy-induced peripheral neuropathy (CIPN) is a common side effect of taxanes. Recent advances in genome-wide genotyping and sequencing technologies have supported the discoveries of a number of pharmacogenetic markers that predict response to chemotherapy. However, effectively implementing these pharmacogenetic markers in the clinic remains a major challenge. On the other hand, recent advances in proteomic technologies incorporating mass spectrometry (MS) for biomarker discovery show great promise to provide clinically relevant protein biomarkers. In this study, we evaluated the association between protein content in serum exosomes and severity of CIPN. Women with early stage breast cancer receiving adjuvant taxane chemotherapy were assessed with the FACT-Ntx score and serum was collected before and after the taxane treatment. Based on the change in FACT-Ntx score from baseline to 12 month follow-up, we separated patients into two groups: those who had no change (Group 1, N = 9) and those who had a ≥20% worsening (Group 1, N = 8). MS-based proteomics technology was used to identify proteins present in serum exosomes to determine potential biomarkers. Mann-Whitney-Wilcoxon analysis was applied and maximum FDR was controlled at 20%. From the serum exosomes derived from this cohort, we identified over 700 proteins known to be in different subcellular locations and have different functions. Statistical analysis revealed a 12-protein signature that resulted in a distinct separation between baseline serum samples of both groups (q<0.2) suggesting that the baseline samples can predict subsequent neurotoxicity. These toxicity-associated biomarkers can be further validated in larger retrospective cohorts for their utility in identifying patients at high risk for CIPN.

Genetic markers for toxicity of adjuvant oxaliplatin and fluoropyrimidines in the phase III TOSCA trial in high-risk colon cancer patients

We investigated 17 polymorphisms in 11 genes (TS, MTHFR, ERCC1, XRCC1, XRCC3, XPD, GSTT1, GSTP1, GSTM1, ABCC1, ABCC2) for their association with the toxicity of fluoropyrimidines and oxaliplatin in colorectal cancer patients enrolled in a prospective randomized trial of adjuvant chemotherapy. The TOSCA Italian adjuvant trial was conducted in high-risk stage II–III colorectal cancer patients treated with 6 or 3 months of either FOLFOX-4 or XELOX adjuvant chemotherapy. In the concomitant ancillary pharmacogenetic study, the primary endpoint was the association of polymorphisms with grade 3–4 CTCAE toxicity events (grade 2–4 for neurotoxicity). In 517 analyzed patients, grade ≥ 3 neutropenia and grade ≥ 2 neurotoxicity events occurred in 150 (29%) and in 132 patients (24.8%), respectively. Diarrhea grade ≥ 3 events occurred in 34 (6.5%) patients. None of the studied polymorphisms showed clinically relevant association with toxicity. Hopefully, genome-wide association studies will identify new and more promising genetic variants to be tested in future studies.

Tissue-specific selection of optimal reference genes for expression analysis of anti-cancer drug-related genes in tumor samples using quantitative real-time RT-PCR

Gene transcription analysis in clinical tumor samples can help with diagnosis, prognosis, and treatment of cancers. We aimed to identify the optimal reference genes for reliable expression analysis in various tumor samples by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Using a one-step TaqMan-based qRT-PCR, 5 commonly used reference genes (ACTB, GAPDH, RPLPO, GUSB, and TFRC) and 10 anticancer drug-related genes (TYMS, RRM1, TUBB3, STMN1, TOP2A, EGFR, VEGFR2, HER2, ERCC1, and BRCA1) were analyzed in 327 tissue samples from lung, rectal, colon, gastric, esophageal, and breast tumors. According to the expression stability assessments obtained by using three programs (geNorm, NormFinder, and BestKeeper) and a comprehensive ranking method, the optimal reference genes for lung, gastric, esophageal, and breast tumors were RPLPO, GAPDH, ACTB, and ACTB, respectively. For rectal tumors, a combination of the 3 most stable genes (GUSB, ACTB, and RPLPO) was suitable for qRT-PCR, whereas for colon tumors, a combination of the 4 most stable genes (GAPDH, ACTB, GUSB, and RPLPO) was optimal for qRT-PCR. Based on the expression data of target genes normalized against selected reference genes, the principal component analysis revealed 4 expression patterns in 6 different tissues. One pattern was observed in gastric, rectal, and colon tumor tissues, which are gastrointestinal tumors. Expressions in the breast, lung, and esophageal tissues were separately represented as one pattern. Our results could facilitate the practice of personalized cancer medicine based on the gene expression profile of the patients.

Chemotherapy pro-drug activation by biocatalytic virus-like nanoparticles containing cytochrome P450

This work shows, for the first time, the encapsulation of a highly relevant protein in the biomedical field into virus-like particles (VLPs). A bacterial CYP variant was effectively encapsulated in VLPs constituted of coat protein from cowpea chlorotic mottle virus (CCMV). The catalytic VLPs are able to transform the chemotherapeutic pro-drug, tamoxifen, and the emerging pro-drug resveratrol. The chemical nature of the products was identified, confirming similar active products than those obtained with human CYP. The enzymatic VLPs remain stable after the catalytic reaction. The potential use of these biocatalytic nanoparticles as targeted CYP carriers for the activation of chemotherapy drugs is discussed.

A functional variant of pre-miRNA-196a2 confers risk for Behcet's disease but not for Vogt-Koyanagi-Harada syndrome or AAU in ankylosing spondylitis

This study aimed to investigate the predisposition of common pre-miRNA SNPs with Behcet's disease (BD), Vogt-Koyanagi-Harada (VKH) syndrome and acute anterior uveitis (AAU) associated with ankylosing spondylitis (AS). A two-stage association study was carried out in 859 BD, 400 VKH syndrome, 209 AAU(+)AS(+) patients and 1,685 controls all belonging to a Chinese Han population. Genotyping, the expression of miR-196a and Bach1 (the target gene of miR-196a), cell proliferation, cytokine production were examined by PCR-RFLP, real-time PCR, CCK8 and ELISA. In the first stage study, the results showed significantly increased frequencies of the miR-196a2/rs11614913 TT genotype and T allele in BD patients (adjusted P(c) = 0.024, OR = 1.63; adjusted P(c) = 5.4 × 10(-3), OR = 1.45, respectively). However, no significant association of the tested SNPs with VKH and AAU(+)AS(+) patients was observed. The second stage and combined studies confirmed the association of rs11614913 with BD (TT genotype: adjusted P(c) = 6×10(-5), OR = 1.53; T allele: adjusted P(c) = 8×10(-6), OR = 1.35; CC genotype: adjusted P(c) = 0.024, OR = 0.68). A stratified analysis showed an association of the rs11614913 TT genotype and T allele with the arthritis subgroup of BD (P(c) = 5.3 × 10(-3), OR = 1.89; P(c) = 0.015, OR = 1.56, respectively). Functional experiments showed a decreased miR-196a expression, an increased Bach1 expression and an increased production of IL-1β and MCP-1 in TT cases compared to CC cases (P = 0.023, P = 0.0073, P = 0.012, P = 0.002, respectively). This study shows that a functional variant of miR-196a2 confers risk for BD but not for VKH syndrome or AAU(+)AS(+) by modulating the miR-196a gene expression and by regulating pro-inflammatory IL-1β and MCP-1 production.