PARP7 negatively regulates the type I interferon response in cancer cells and its inhibition triggers antitumor immunity.

PARP7 is a monoPARP that catalyzes the transfer of single units of ADP-ribose onto substrates to change their function. Here, we identify PARP7 as a negative regulator of nucleic acid sensing in tumor cells. Inhibition of PARP7 restores type I interferon (IFN) signaling responses to nucleic acids in tumor models. Restored signaling can directly inhibit cell proliferation and activate the immune system, both of which contribute to tumor regression. Oral dosing of the PARP7 small-molecule inhibitor, RBN-2397, results in complete tumor regression in a lung cancer xenograft and induces tumor-specific adaptive immune memory in an immunocompetent mouse cancer model, dependent on inducing type I IFN signaling in tumor cells. PARP7 is a therapeutic target whose inhibition induces both cancer cell-autonomous and immune stimulatory effects via enhanced IFN signaling. These data support the targeting of a monoPARP in cancer and introduce a potent and selective PARP7 inhibitor to enter clinical development.

Targeted Degradation of PARP14 Using a Heterobifunctional Small Molecule.

PARP14 is an interferon-stimulated gene that is overexpressed in multiple tumor types, influencing pro-tumor macrophage polarization as well as suppressing the antitumor inflammation response by modulating IFN-γ and IL-4 signaling. PARP14 is a 203 kDa protein that possesses a catalytic domain responsible for the transfer of mono-ADP-ribose to its substrates. PARP14 also contains three macrodomains and a WWE domain which are binding modules for mono-ADP-ribose and poly-ADP-ribose, respectively, in addition to two RNA recognition motifs. Catalytic inhibitors of PARP14 have been shown to reverse IL-4 driven pro-tumor gene expression in macrophages, however it is not clear what roles the non-enzymatic biomolecular recognition motifs play in PARP14-driven immunology and inflammation. To further understand this, we have discovered a heterobifunctional small molecule designed based on a catalytic inhibitor of PARP14 that binds in the enzyme's NAD+ -binding site and recruits cereblon to ubiquitinate it and selectively target it for degradation.

A potent and selective PARP14 inhibitor decreases protumor macrophage gene expression and elicits inflammatory responses in tumor explants.

PARP14 has been implicated by genetic knockout studies to promote protumor macrophage polarization and suppress the antitumor inflammatory response due to its role in modulating interleukin-4 (IL-4) and interferon-γ signaling pathways. Here, we describe structure-based design efforts leading to the discovery of a potent and highly selective PARP14 chemical probe. RBN012759 inhibits PARP14 with a biochemical half-maximal inhibitory concentration of 0.003 µM, exhibits >300-fold selectivity over all PARP family members, and its profile enables further study of PARP14 biology and disease association both in vitro and in vivo. Inhibition of PARP14 with RBN012759 reverses IL-4-driven protumor gene expression in macrophages and induces an inflammatory mRNA signature similar to that induced by immune checkpoint inhibitor therapy in primary human tumor explants. These data support an immune suppressive role of PARP14 in tumors and suggest potential utility of PARP14 inhibitors in the treatment of cancer.

Enabling drug discovery for the PARP protein family through the detection of mono-ADP-ribosylation.

Poly-ADP-ribose polymerases (PARPs) are a family of enzymes responsible for transferring individual or chains of ADP-ribose subunits to substrate targets as a type of post-translational modification. PARPs regulate a wide variety of important cellular processes, ranging from DNA damage repair to antiviral response. However, most research to date has focused primarily on the polyPARPs, which catalyze the formation of ADP-ribose polymer chains, while the monoPARPs, which transfer individual ADP-ribose monomers, have not been studied as thoroughly. This is partially due to the lack of robust assays to measure mono-ADP-ribosylation in the cell. In this study, the recently developed MAR/PAR antibody has been shown to detect mono-ADP-ribosylation in cells, enabling the field to investigate the function and therapeutic potential of monoPARPs. In this study, the antibody was used in conjunction with engineered cell lines that overexpress various PARPs to establish a panel of assays to evaluate the potencies of literature-reported PARP inhibitors. These assays should be generally applicable to other PARP family members for future compound screening efforts. A convenient and generalizable workflow to identify and validate PARP substrates has been established. As an initial demonstration, aryl hydrocarbon receptor was verified as a direct PARP7 substrate and other novel substrates for this enzyme were also identified and validated. This workflow takes advantage of commercially available detection reagents and conventional mass spectrometry instrumentation and methods. Ultimately, these assays and methods will help drive research in the PARP field and benefit future therapeutics development.

Institutional implementation of clinical tumor profiling on an unselected cancer population.

BACKGROUND. Comprehensive genomic profiling of a patient's cancer can be used to diagnose, monitor, and recommend treatment. Clinical implementation of tumor profiling in an enterprise-wide, unselected cancer patient population has yet to be reported. METHODS. We deployed a hybrid-capture and massively parallel sequencing assay (OncoPanel) for all adult and pediatric patients at our combined cancer centers. Results were categorized by pathologists based on actionability. We report the results for the first 3,727 patients tested. RESULTS. Our cohort consists of cancer patients unrestricted by disease site or stage. Across all consented patients, half had sufficient and available (>20% tumor) material for profiling; once specimens were received in the laboratory for pathology review, 73% were scored as adequate for genomic testing. When sufficient DNA was obtained, OncoPanel yielded a result in 96% of cases. 73% of patients harbored an actionable or informative alteration; only 19% of these represented a current standard of care for therapeutic stratification. The findings recapitulate those of previous studies of common cancers but also identify alterations, including in AXL and EGFR, associated with response to targeted therapies. In rare cancers, potentially actionable alterations suggest the utility of a "cancer-agnostic" approach in genomic profiling. Retrospective analyses uncovered contextual genomic features that may inform therapeutic response and examples where diagnoses revised by genomic profiling markedly changed clinical management. CONCLUSIONS. Broad sequencing-based testing deployed across an unselected cancer cohort is feasible. Genomic results may alter management in diverse scenarios; however, additional barriers must be overcome to enable precision cancer medicine on a large scale. FUNDING. This work was supported by DFCI, BWH, and the National Cancer Institute (5R33CA155554 and 5K23CA157631).

Discordant Haplotype Sequencing Identifies Functional Variants at the 2q33 Breast Cancer Risk Locus.

The findings from genome-wide association studies hold enormous potential for novel insight into disease mechanisms. A major challenge in the field is to map these low-risk association signals to their underlying functional sequence variants (FSV). Simple sequence study designs are insufficient, as the vast numbers of statistically comparable variants and a limited knowledge of noncoding regulatory elements complicate prioritization. Furthermore, large sample sizes are typically required for adequate power to identify the initial association signals. One important question is whether similar sample sizes need to be sequenced to identify the FSVs. Here, we present a proof-of-principle example of an extreme discordant design to map FSVs within the 2q33 low-risk breast cancer locus. Our approach employed DNA sequencing of a small number of discordant haplotypes to efficiently identify candidate FSVs. Our results were consistent with those from a 2,000-fold larger, traditional imputation-based fine-mapping study. To prioritize further, we used expression-quantitative trait locus analysis of RNA sequencing from breast tissues, gene regulation annotations from the ENCODE consortium, and functional assays for differential enhancer activities. Notably, we implicate three regulatory variants at 2q33 that target CASP8 (rs3769823, rs3769821 in CASP8, and rs10197246 in ALS2CR12) as functionally relevant. We conclude that nested discordant haplotype sequencing is a promising approach to aid mapping of low-risk association loci. The ability to include more efficient sequencing designs into mapping efforts presents an opportunity for the field to capitalize on the potential of association loci and accelerate translation of association signals to their underlying FSVs. Cancer Res; 76(7); 1916-25. ©2016 AACR.

Diffuse large B-cell lymphoma patient-derived xenograft models capture the molecular and biological heterogeneity of the disease.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease defined by transcriptional classifications, specific signaling and survival pathways, and multiple low-frequency genetic alterations. Preclinical model systems that capture the genetic and functional heterogeneity of DLBCL are urgently needed. Here, we generated and characterized a panel of large B-cell lymphoma (LBCL) patient-derived xenograft (PDX) models, including 8 that reflect the immunophenotypic, transcriptional, genetic, and functional heterogeneity of primary DLBCL and 1 that is a plasmablastic lymphoma. All LBCL PDX models were subjected to whole-transcriptome sequencing to classify cell of origin and consensus clustering classification (CCC) subtypes. Mutations and chromosomal rearrangements were evaluated by whole-exome sequencing with an extended bait set. Six of the 8 DLBCL models were activated B-cell (ABC)-type tumors that exhibited ABC-associated mutations such as MYD88, CD79B, CARD11, and PIM1. The remaining 2 DLBCL models were germinal B-cell type, with characteristic alterations of GNA13, CREBBP, and EZH2, and chromosomal translocations involving IgH and either BCL2 or MYC Only 25% of the DLBCL PDX models harbored inactivating TP53 mutations, whereas 75% exhibited copy number alterations of TP53 or its upstream modifier, CDKN2A, consistent with the reported incidence and type of p53 pathway alterations in primary DLBCL. By CCC criteria, 6 of 8 DLBCL PDX models were B-cell receptor (BCR)-type tumors that exhibited selective surface immunoglobulin expression and sensitivity to entospletinib, a recently developed spleen tyrosine kinase inhibitor. In summary, we have established and characterized faithful PDX models of DLBCL and demonstrated their usefulness in functional analyses of proximal BCR pathway inhibition.

Metformin pharmacogenomics: a genome-wide association study to identify genetic and epigenetic biomarkers involved in metformin anticancer response using human lymphoblastoid cell lines.

Metformin is currently considered as a promising anticancer agent in addition to its anti-diabetic effect. To better individualize metformin therapy and explore novel molecular mechanisms in cancer treatment, we conducted a pharmacogenomic study using 266 lymphoblastoid cell lines (LCLs). Metformin cytotoxicity assay was performed using the MTS assay. Genome-wide association (GWA) analyses were performed in LCLs using 1.3 million SNPs, 485k DNA methylation probes, 54k mRNA expression probe sets, and metformin cytotoxicity (IC50s). Top candidate genes were functionally validated using siRNA screening, followed by MTS assay in breast cancer cell lines. Further study of one top candidate, STUB1, was performed to elucidate the mechanisms by which STUB1 might contribute to metformin action. GWA analyses in LCLs identified 198 mRNA expression probe sets, 12 SNP loci, and 5 DNA methylation loci associated with metformin IC50 with P-values <10−4 or <10−5. Integrated SNP/methylation loci-expression-IC50 analyses found 3 SNP loci or 5 DNA methylation loci associated with metformin IC50 through trans-regulation of expression of 11 or 26 genes with P-value <10−4. Functional validation of top 61 candidate genes in 4 IPA networks indicated down regulation of 14 genes significantly altered metformin sensitivity in two breast cancer cell lines. Mechanistic studies revealed that the E3 ubiquitin ligase, STUB1, could influence metformin response by facilitating proteasome-mediated degradation of cyclin A. GWAS using a genomic data-enriched LCL model system, together with functional and mechanistic studies using cancer cell lines, help us to identify novel genetic and epigenetic biomarkers involved in metformin anticancer response.

Targetable genetic features of primary testicular and primary central nervous system lymphomas.

Primary central nervous system lymphomas (PCNSLs) and primary testicular lymphomas (PTLs) are extranodal large B-cell lymphomas (LBCLs) with inferior responses to current empiric treatment regimens. To identify targetable genetic features of PCNSL and PTL, we characterized their recurrent somatic mutations, chromosomal rearrangements, copy number alterations (CNAs), and associated driver genes, and compared these comprehensive genetic signatures to those of diffuse LBCL and primary mediastinal large B-cell lymphoma (PMBL). These studies identify unique combinations of genetic alterations in discrete LBCL subtypes and subtype-selective bases for targeted therapy. PCNSLs and PTLs frequently exhibit genomic instability, and near-uniform, often biallelic, CDKN2A loss with rare TP53 mutations. PCNSLs and PTLs also use multiple genetic mechanisms to target key genes and pathways and exhibit near-uniform oncogenic Toll-like receptor signaling as a result of MYD88 mutation and/or NFKBIZ amplification, frequent concurrent B-cell receptor pathway activation, and deregulation of BCL6. Of great interest, PCNSLs and PTLs also have frequent 9p24.1/PD-L1/PD-L2 CNAs and additional translocations of these loci, structural bases of immune evasion that are shared with PMBL.

Myeloid neoplasm demonstrating a STAT5B-RARA rearrangement and genetic alterations associated with all-trans retinoic acid resistance identified by a custom next-generation sequencing assay.

We describe the case of a patient presenting with several weeks of symptoms related to pancytopenia associated with a maturation arrest at the late promyelocyte/early myelocyte stage of granulocyte differentiation. A diagnosis of acute promyelocytic leukemia was considered, but the morphologic features were atypical for this entity and conventional tests for the presence of a PML-RARA fusion gene were negative. Additional analysis using a custom next-generation sequencing assay revealed a rearrangement producing a STAT5B-RARA fusion gene, which was confirmed by reverse transcription polymerase chain reaction (RT-PCR) and supplementary cytogenetic studies, allowing the diagnosis of a morphologically atypical form of acute promyelocytic leukemia to be made. Analysis of the sequencing data permitted characterization of both chromosomal breakpoints and revealed two additional alterations, a small deletion in RARA exon 9 and a RARA R276W substitution, that have been linked to resistance to all-trans retinoic acid. This case highlights how next-generation sequencing can augment currently standard testing to establish diagnoses in difficult cases, and in doing so help guide selection of therapy.

BreaKmer: detection of structural variation in targeted massively parallel sequencing data using kmers.

Genomic structural variation (SV), a common hallmark of cancer, has important predictive and therapeutic implications. However, accurately detecting SV using high-throughput sequencing data remains challenging, especially for 'targeted' resequencing efforts. This is critically important in the clinical setting where targeted resequencing is frequently being applied to rapidly assess clinically actionable mutations in tumor biopsies in a cost-effective manner. We present BreaKmer, a novel approach that uses a 'kmer' strategy to assemble misaligned sequence reads for predicting insertions, deletions, inversions, tandem duplications and translocations at base-pair resolution in targeted resequencing data. Variants are predicted by realigning an assembled consensus sequence created from sequence reads that were abnormally aligned to the reference genome. Using targeted resequencing data from tumor specimens with orthogonally validated SV, non-tumor samples and whole-genome sequencing data, BreaKmer had a 97.4% overall sensitivity for known events and predicted 17 positively validated, novel variants. Relative to four publically available algorithms, BreaKmer detected SV with increased sensitivity and limited calls in non-tumor samples, key features for variant analysis of tumor specimens in both the clinical and research settings.

Diverse cell stresses induce unique patterns of tRNA up- and down-regulation: tRNA-seq for quantifying changes in tRNA copy number.

Emerging evidence points to roles for tRNA modifications and tRNA abundance in cellular stress responses. While isolated instances of stress-induced tRNA degradation have been reported, we sought to assess the effects of stress on tRNA levels at a systems level. To this end, we developed a next-generation sequencing method that exploits the paucity of ribonucleoside modifications at the 3'-end of tRNAs to quantify changes in all cellular tRNA molecules. Application of this tRNA-seq method to Saccharomyces cerevisiae identified all 76 expressed unique tRNA species out of 295 coded in the yeast genome, including all isoacceptor variants, with highly precise relative (fold-change) quantification of tRNAs. In studies of stress-induced changes in tRNA levels, we found that oxidation (H2O2) and alkylation (methylmethane sulfonate, MMS) stresses induced nearly identical patterns of up- and down-regulation for 58 tRNAs. However, 18 tRNAs showed opposing changes for the stresses, which parallels our observation of signature reprogramming of tRNA modifications caused by H2O2 and MMS. Further, stress-induced degradation was limited to only a small proportion of a few tRNA species. With tRNA-seq applicable to any organism, these results suggest that translational control of stress response involves a contribution from tRNA abundance.

Multiplexed DNA repair assays for multiple lesions and multiple doses via transcription inhibition and transcriptional mutagenesis.

The capacity to repair different types of DNA damage varies among individuals, making them more or less susceptible to the detrimental health consequences of damage exposures. Current methods for measuring DNA repair capacity (DRC) are relatively labor intensive, often indirect, and usually limited to a single repair pathway. Here, we describe a fluorescence-based multiplex flow-cytometric host cell reactivation assay (FM-HCR) that measures the ability of human cells to repair plasmid reporters, each bearing a different type of DNA damage or different doses of the same type of DNA damage. FM-HCR simultaneously measures repair capacity in any four of the following pathways: nucleotide excision repair, mismatch repair, base excision repair, nonhomologous end joining, homologous recombination, and methylguanine methyltransferase. We show that FM-HCR can measure interindividual DRC differences in a panel of 24 cell lines derived from genetically diverse, apparently healthy individuals, and we show that FM-HCR may be used to identify inhibitors or enhancers of DRC. We further develop a next-generation sequencing-based HCR assay (HCR-Seq) that detects rare transcriptional mutagenesis events due to lesion bypass by RNA polymerase, providing an added dimension to DRC measurements. FM-HCR and HCR-Seq provide powerful tools for exploring relationships among global DRC, disease susceptibility, and optimal treatment.

Discovery of genetic biomarkers contributing to variation in drug response of cytidine analogues using human lymphoblastoid cell lines.

BACKGROUND: Two cytidine analogues, gemcitabine and cytosine arabinoside (AraC), are widely used in the treatment of a variety of cancers with a large individual variation in response. To identify potential genetic biomarkers associated with response to these two drugs, we used a human lymphoblastoid cell line (LCL) model system with extensive genomic data, including 1.3 million SNPs and 54,000 basal expression probesets to perform genome-wide association studies (GWAS) with gemcitabine and AraC IC50 values. RESULTS: We identified 11 and 27 SNP loci significantly associated with gemcitabine and AraC IC50 values, respectively. Eleven candidate genes were functionally validated using siRNA knockdown approach in multiple cancer cell lines. We also characterized the potential mechanisms of genes by determining their influence on the activity of 10 cancer-related signaling pathways using reporter gene assays. Most SNPs regulated gene expression in a trans manner, except 7 SNPs in the PIGB gene that were significantly associated with both the expression of PIGB and gemcitabine cytotoxicity. CONCLUSION: These results suggest that genetic variation might contribute to drug response via either cis- or trans- regulation of gene expression. GWAS analysis followed by functional pharmacogenomics studies might help identify novel biomarkers contributing to variation in response to these two drugs and enhance our understanding of underlying mechanisms of drug action.

Host plant peptides elicit a transcriptional response to control the Sinorhizobium meliloti cell cycle during symbiosis.

The α-proteobacterium Sinorhizobium meliloti establishes a chronic intracellular infection during the symbiosis with its legume hosts. Within specialized host cells, S. meliloti differentiates into highly polyploid, enlarged nitrogen-fixing bacteroids. This differentiation is driven by host cells through the production of defensin-like peptides called "nodule-specific cysteine-rich" (NCR) peptides. Recent research has shown that synthesized NCR peptides exhibit antimicrobial activity at high concentrations but cause bacterial endoreduplication at sublethal concentrations. We leveraged synchronized S. meliloti populations to determine how treatment with a sublethal NCR peptide affects the cell cycle and physiology of bacteria at the molecular level. We found that at sublethal levels a representative NCR peptide specifically blocks cell division and antagonizes Z-ring function. Gene-expression profiling revealed that the cell division block was produced, in part, through the substantial transcriptional response elicited by sublethal NCR treatment that affected ∼15% of the genome. Expression of critical cell-cycle regulators, including ctrA, and cell division genes, including genes required for Z-ring function, were greatly attenuated in NCR-treated cells. In addition, our experiments identified important symbiosis functions and stress responses that are induced by sublethal levels of NCR peptides and other antimicrobial peptides. Several of these stress-response pathways also are found in related α-proteobacterial pathogens and might be used by S. meliloti to sense host cues during infection. Our data suggest a model in which, in addition to provoking stress responses, NCR peptides target intracellular regulatory pathways to drive S. meliloti endoreduplication and differentiation during symbiosis.

Global analysis of cell cycle gene expression of the legume symbiont Sinorhizobium meliloti.

In α-proteobacteria, strict regulation of cell cycle progression is necessary for the specific cellular differentiation required for adaptation to diverse environmental niches. The symbiotic lifestyle of Sinorhizobium meliloti requires a drastic cellular differentiation that includes genome amplification. To achieve polyploidy, the S. meliloti cell cycle program must be altered to uncouple DNA replication from cell division. In the α-proteobacterium Caulobacter crescentus, cell cycle-regulated transcription plays an important role in the control of cell cycle progression but this has not been demonstrated in other α-proteobacteria. Here we describe a robust method for synchronizing cell growth that enabled global analysis of S. meliloti cell cycle-regulated gene expression. This analysis identified 462 genes with cell cycle-regulated transcripts, including several key cell cycle regulators, and genes involved in motility, attachment, and cell division. Only 28% of the 462 S. meliloti cell cycle-regulated genes were also transcriptionally cell cycle-regulated in C. crescentus. Furthermore, CtrA- and DnaA-binding motif analysis revealed little overlap between the cell cycle-dependent regulons of CtrA and DnaA in S. meliloti and C. crescentus. The predicted S. meliloti cell cycle regulon of CtrA, but not that of DnaA, was strongly conserved in more closely related α-proteobacteria with similar ecological niches as S. meliloti, suggesting that the CtrA cell cycle regulatory network may control functions of central importance to the specific lifestyles of α-proteobacteria.

Arsenic exposure perturbs the gut microbiome and its metabolic profile in mice: an integrated metagenomics and metabolomics analysis.

BACKGROUND: The human intestine is host to an enormously complex, diverse, and vast microbial community-the gut microbiota. The gut microbiome plays a profound role in metabolic processing, energy production, immune and cognitive development, epithelial homeostasis, and so forth. However, the composition and diversity of the gut microbiome can be readily affected by external factors, which raises the possibility that exposure to toxic environmental chemicals leads to gut microbiome alteration, or dysbiosis. Arsenic exposure affects large human populations worldwide and has been linked to a number of diseases, including cancer, diabetes, and cardiovascular disorders. OBJECTIVES: We investigated the impact of arsenic exposure on the gut microbiome composition and its metabolic profiles. METHODS: We used an integrated approach combining 16S rRNA gene sequencing and mass spectrometry-based metabolomics profiling to examine the functional impact of arsenic exposure on the gut microbiome. RESULTS: 16S rRNA gene sequencing revealed that arsenic significantly perturbed the gut microbiome composition in C57BL/6 mice after exposure to 10 ppm arsenic for 4 weeks in drinking water. Moreover, metabolomics profiling revealed a concurrent effect, with a number of gut microflora-related metabolites being perturbed in multiple biological matrices. CONCLUSIONS: Arsenic exposure not only alters the gut microbiome community at the abundance level but also substantially disturbs its metabolic profiles at the function level. These findings may provide novel insights regarding perturbations of the gut microbiome and its functions as a potential new mechanism by which arsenic exposure leads to or exacerbates human diseases. CITATION: Lu K, Abo RP, Schlieper KA, Graffam ME, Levine S, Wishnok JS, Swenberg JA, Tannenbaum SR, Fox JG. 2014. Arsenic exposure perturbs the gut microbiome and its metabolic profile in mice: an integrated metagenomics and metabolomics analysis. Environ Health Perspect 122:284-291; http://dx.doi.org/10.1289/ehp.1307429.

Integrative gene set analysis: application to platinum pharmacogenomics.

Integrative genomics has the potential to uncover relevant loci, as clinical outcome and response to chemotherapies are most likely not due to a single gene (or data type) but rather a complex relationship involving genetic variation, mRNA, DNA methylation, and copy number variation. In addition to this complexity, many complex phenotypes are thought to be controlled by the interplay of multiple genes within the same molecular pathway or gene set (GS). To address these two challenges, we propose an integrative gene set analysis approach and apply this strategy to a cisplatin (CDDP) pharmacogenomics study involving lymphoblastoid cell lines for which genome-wide SNP and mRNA expression data was collected. Application of the integrative GS analysis implicated the role of the RNA binding and cytoskeletal part GSs. The genes LMNB1 and CENPF, within the cytoskeletal part GS, were functionally validated with siRNA knockdown experiments, where the knockdown of LMNB1 and CENPF resulted in CDDP resistance in multiple cancer cell lines. This study demonstrates the utility of an integrative GS analysis strategy for detecting novel genes associated with response to cancer therapies, moving closer to tailored therapy decisions for cancer patients.

Gut microbiome perturbations induced by bacterial infection affect arsenic biotransformation.

Exposure to arsenic affects large human populations worldwide and has been associated with a long list of human diseases, including skin, bladder, lung, and liver cancers, diabetes, and cardiovascular disorders. In addition, there are large individual differences in susceptibility to arsenic-induced diseases, which are frequently associated with different patterns of arsenic metabolism. Several underlying mechanisms, such as genetic polymorphisms and epigenetics, have been proposed, as these factors closely impact the individuals' capacity to metabolize arsenic. In this context, the role of the gut microbiome in directly metabolizing arsenic and triggering systemic responses in diverse organs raises the possibility that perturbations of the gut microbial communities affect the spectrum of metabolized arsenic species and subsequent toxicological effects. In this study, we used an animal model with an altered gut microbiome induced by bacterial infection, 16S rRNA gene sequencing, and inductively coupled plasma mass spectrometry-based arsenic speciation to examine the effect of gut microbiome perturbations on the biotransformation of arsenic. Metagenomics sequencing revealed that bacterial infection significantly perturbed the gut microbiome composition in C57BL/6 mice, which in turn resulted in altered spectra of arsenic metabolites in urine, with inorganic arsenic species and methylated and thiolated arsenic being perturbed. These data clearly illustrated that gut microbiome phenotypes significantly affected arsenic metabolic reactions, including reduction, methylation, and thiolation. These findings improve our understanding of how infectious diseases and environmental exposure interact and may also provide novel insight regarding the gut microbiome composition as a new risk factor of individual susceptibility to environmental chemicals.

Genome-wide association study for biomarker identification of Rapamycin and Everolimus using a lymphoblastoid cell line system.

The mammalian target of rapamycin (mTOR) inhibitors, a set of promising potential anti-cancer agents, has shown response variability among individuals. This study aimed to identify novel biomarkers and mechanisms that might influence the response to Rapamycin and Everolimus. Genome-wide association (GWA) analyses involving single nucleotide polymorphisms (SNPs), mRNA, and microRNAs microarray data were assessed for association with area under the cytotoxicity dose response curve (AUC) of two mTOR inhibitors in 272 human lymphoblastoid cell lines (LCLs). Integrated analysis among SNPs, expression data, microRNA data and AUC values were also performed to help select candidate genes for further functional characterization. Functional validation of candidate genes using siRNA screening in multiple cell lines followed by MTS assays for the two mTOR inhibitors were performed. We found that 16 expression probe sets (genes) that overlapped between the two drugs were associated with AUC values of two mTOR inhibitors. One hundred and twenty seven and one hundred SNPs had P < 10(-4), while 8 and 10 SNPs had P < 10(-5) with Rapamycin and Everolimus AUC, respectively. Functional studies indicated that 13 genes significantly altered cell sensitivity to either one or both drugs in at least one cell line. Additionally, one microRNA, miR-10a, was significantly associated with AUC values for both drugs and was shown to repress expression of genes that were associated with AUC and desensitize cells to both drugs. In summary, this study identified genes and a microRNA that might contribute to response to mTOR inhibitors.