Single nucleotide polymorphism patterns associated with a cancer resistant phenotype.

BACKGROUND AND AIMS: In this study ten mouse strains representing ~90% of genetic diversity in laboratory mice (B6C3F1/J, C57BL/6J, C3H/HeJ, A/J, NOD.B1oSnH2/J, NZO/HILtJ, 129S1/SvImJ, WSB/EiJ, PWK/PhJ, CAST/EiJ) were examined to identify the mouse strain with the lowest incidence of cancer. The unique single polymorphisms (SNPs) associated with this low cancer incidence are reported. METHODS: Evaluations of cancer incidence in the 10 mouse strains were based on gross and microscopic diagnosis of tumors. Single nucleotide polymorphisms (SNPs) in the coding regions of the genome were derived from the respective mouse strains located in the Sanger mouse sequencing database and the B6C3F1/N genome from the National Toxicology Program (NTP). RESULTS: The WSB strain had an overall lower incidence of both benign and malignant tumors compared to the other mouse strains. At 2 years, the incidence of total malignant tumors (Poly-3 incidence rate) ranged from 2% (WSB) to 92% (C3H) in males, and 14% (WSB) to 93% (NZO) in females, and the total incidence of benign and malignant tumor incidence ranged from 13% (WSB) to 99% (C3H) in males and 25% (WSB) to 96% (NOD) in females. Single nucleotide polymorphism (SNP) patterns were examined in the following strains: B6C3F1/N, C57BL/6J, C3H/HeJ, 129S1/SvImJ, A/J, NZO/HILtJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ. We identified 7519 SNPs (involving 5751 Ensembl transcripts of 3453 Ensembl Genes) that resulted in a unique amino acid change in the coding region of the WSB strain. CONCLUSIONS: The inherited genetic patterns in the WSB cancer-resistant mouse strain occurred in genes involved in multiple cell functions including mitochondria, metabolic, immune, and membrane-related cell functions. The unique SNP patterns in a cancer resistant mouse strain provides insights for understanding and developing strategies for cancer prevention.

Transcriptional pathways linked to fetal and maternal hepatic dysfunction caused by gestational exposure to perfluorooctanoic acid (PFOA) or hexafluoropropylene oxide-dimer acid (HFPO-DA or GenX) in CD-1 mice.

Per- and polyfluoroalkyl substances (PFAS) comprise a diverse class of chemicals used in industrial processes, consumer products, and fire-fighting foams which have become environmental pollutants of concern due to their persistence, ubiquity, and associations with adverse human health outcomes, including in pregnant persons and their offspring. Multiple PFAS are associated with adverse liver outcomes in adult humans and toxicological models, but effects on the developing liver are not fully described. Here we performed transcriptomic analyses in the mouse to investigate the molecular mechanisms of hepatic toxicity in the dam and its fetus after exposure to two different PFAS, perfluorooctanoic acid (PFOA) and its replacement, hexafluoropropylene oxide-dimer acid (HFPO-DA, known as GenX). Pregnant CD-1 mice were exposed via oral gavage from embryonic day (E) 1.5-17.5 to PFOA (0, 1, or 5 mg/kg-d) or GenX (0, 2, or 10 mg/kg-d). Maternal and fetal liver RNA was isolated (N = 5 per dose/group) and the transcriptome analyzed by Affymetrix Array. Differentially expressed genes (DEG) and differentially enriched pathways (DEP) were obtained. DEG patterns were similar in maternal liver for 5 mg/kg PFOA, 2 mg/kg GenX, and 10 mg/kg GenX (R2: 0.46-0.66). DEG patterns were similar across all 4 dose groups in fetal liver (R2: 0.59-0.81). There were more DEGs in fetal liver compared to maternal liver at the low doses for both PFOA (fetal = 69, maternal = 8) and GenX (fetal = 154, maternal = 93). Upregulated DEPs identified across all groups included Fatty Acid Metabolism, Peroxisome, Oxidative Phosphorylation, Adipogenesis, and Bile Acid Metabolism. Transcriptome-phenotype correlation analyses demonstrated > 1000 maternal liver DEGs were significantly correlated with maternal relative liver weight (R2 >0.92). These findings show shared biological pathways of liver toxicity for PFOA and GenX in maternal and fetal livers in CD-1 mice. The limited overlap in specific DEGs between the dam and fetus suggests the developing liver responds differently than the adult liver to these chemical stressors. This work helps define mechanisms of hepatic toxicity of two structurally unique PFAS and may help predict latent consequences of developmental exposure.

Saagar-A New, Extensible Set of Molecular Substructures for QSAR/QSPR and Read-Across Predictions.

Molecular structure-based predictive models provide a proven alternative to costly and inefficient animal testing. However, due to a lack of interpretability of predictive models built with abstract molecular descriptors they have earned the notoriety of being black boxes. Interpretable models require interpretable descriptors to provide chemistry-backed predictive reasoning and facilitate intelligent molecular design. We developed a novel set of extensible chemistry-aware substructures, Saagar, to support interpretable predictive models and read-across protocols. Performance of Saagar in chemical characterization and search for structurally similar actives for read-across applications was compared with four publicly available fingerprint sets (MACCS (166), PubChem (881), ECFP4 (1024), ToxPrint (729)) in three benchmark sets (MUV, ULS, and Tox21) spanning ∼145 000 compounds and 78 molecular targets at 1%, 2%, 5%, and 10% false discovery rates. In 18 of the 20 comparisons, interpretable Saagar features performed better than the publicly available, but less interpretable and fixed-bit length, fingerprints. Examples are provided to show the enhanced capability of Saagar in extracting compounds with higher scaffold similarity. Saagar features are interpretable and efficiently characterize diverse chemical collections, thus making them a better choice for building interpretable predictive in silico models and read-across protocols.

BMDExpress 2: enhanced transcriptomic dose-response analysis workflow.

SUMMARY: A new version (version 2) of the genomic dose-response analysis software, BMDExpress, has been created. The software addresses the increasing use of transcriptomic dose-response data in toxicology, drug design, risk assessment and translational research. In this new version, we have implemented additional statistical filtering options (e.g. Williams' trend test), curve fitting models, Linux and Macintosh compatibility and support for additional transcriptomic platforms with up-to-date gene annotations. Furthermore, we have implemented extensive data visualizations, on-the-fly data filtering, and a batch-wise analysis workflow. We have also significantly re-engineered the code base to reflect contemporary software engineering practices and streamline future development. The first version of BMDExpress was developed in 2007 to meet an unmet demand for easy-to-use transcriptomic dose-response analysis software. Since its original release, however, transcriptomic platforms, technologies, pathway annotations and quantitative methods for data analysis have undergone a large change necessitating a significant re-development of BMDExpress. To that end, as of 2016, the National Toxicology Program assumed stewardship of BMDExpress. The result is a modernized and updated BMDExpress 2 that addresses the needs of the growing toxicogenomics user community. AVAILABILITY AND IMPLEMENTATION: BMDExpress 2 is available at https://github.com/auerbachs/BMDExpress-2/releases. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

KRAS-retroviral fusion transcripts and gene amplification in arsenic-transformed, human prostate CAsE-PE cancer cells.

CAsE-PE cells are an arsenic-transformed, human prostate epithelial line containing oncogenic mutations in KRAS compared to immortalized, normal KRAS parent cells, RWPE-1. We previously reported increased copy number of mutated KRAS in CAsE-PE cells, suggesting gene amplification. Here, KRAS flanking genomic and transcriptomic regions were sequenced in CAsE-PE cells for insight into KRAS amplification. Comparison of DNA-Seq and RNA-Seq showed increased reads from background aligning to all KRAS exons in CAsE-PE cells, while a uniform DNA-Seq read distribution occurred in RWPE-1 cells with normal transcript expression. We searched for KRAS fusions in DNA and RNA sequencing data finding a portion of reads aligning to KRAS and viral sequence. After generation of cDNA from total RNA, short and long KRAS probes were generated to hybridize cDNA and KRAS enriched fragments were PacBio sequenced. More KRAS reads were captured from CAsE-PE cDNA versus RWPE-1 by each probe set. Only CAsE-PE cDNA showed KRAS viral fusion transcripts, primarily mapping to LTR and endogenous retrovirus sequences on either 5'- or 3'-ends of KRAS. Most KRAS viral fusion transcripts contained 4 to 6 exons but some PacBio sequences were in unusual orientations, suggesting viral insertions within the gene body. Additionally, conditioned media was extracted for potential retroviral particles. RNA-Seq of culture media isolates identified KRAS retroviral fusion transcripts in CAsE-PE media only. Truncated KRAS transcripts suggested multiple retroviral integration sites occurred within the KRAS gene producing KRAS retroviral fusions of various lengths. Findings suggest activation of endogenous retroviruses in arsenic carcinogenesis should be explored.

Genome-wide promoter DNA methylation profiling of hepatocellular carcinomas arising either spontaneously or due to chronic exposure to Ginkgo biloba extract (GBE) in B6C3F1/N mice.

Epigenetic modifications, such as DNA methylation, play an important role in carcinogenesis. In a recent NTP study, chronic exposure of B6C3F1/N mice to Ginkgo biloba extract (GBE) resulted in a high incidence of hepatocellular carcinomas (HCC). Genome-wide promoter methylation profiling on GBE-exposed HCC (2000 mg/kg group), spontaneous HCC (vehicle-control group), and age-matched vehicle control liver was performed to identify differentially methylated genes in GBE-exposed HCC and spontaneous HCC. DNA methylation alterations were correlated to the corresponding global gene expression changes. Compared to control liver, 1296 gene promoters (719 hypermethylated, 577 hypomethylated) in GBE-exposed HCC and 738 (427 hypermethylated, 311 hypomethylated) gene promoters in spontaneous HCC were significantly differentially methylated, suggesting an impact of methylation on GBE-exposed HCC. Differential methylation of promoter regions in relevant cancer genes (cMyc, Spry2, Dusp5) and their corresponding differential gene expression was validated by quantitative pyrosequencing and qRT-PCR, respectively. In conclusion, we have identified differentially methylated promoter regions of relevant cancer genes altered in GBE-exposed HCC compared to spontaneous HCC. Further study of unique sets of differentially methylated genes in chemical-exposed mouse HCC could potentially be used to differentiate treatment-related tumors from spontaneous-tumors in cancer bioassays and provide additional understanding of the underlying epigenetic mechanisms of chemical carcinogenesis.

Whole exome sequencing in the rat.

BACKGROUND: The rat genome was sequenced in 2004 with the aim to improve human health altered by disease and environmental influences through gene discovery and animal model validation. Here, we report development and testing of a probe set for whole exome sequencing (WES) to detect sequence variants in exons and UTRs of the rat genome. Using an in-silico approach, we designed probes targeting the rat exome and compared captured mutations in cancer-related genes from four chemically induced rat tumor cell lines (C6, FAT7, DSL-6A/C1, NBTII) to validated cancer genes in the human database, Catalogue of Somatic Mutations in Cancer (COSMIC) as well as normal rat DNA. Paired, fresh frozen (FF) and formalin-fixed, paraffin-embedded (FFPE) liver tissue from naive rats were sequenced to confirm known dbSNP variants and identify any additional variants. RESULTS: Informatics analysis of available gene annotation from rat RGSC6.0/rn6 RefSeq and Ensembl transcripts provided 223,636 unique exons representing a total of 26,365 unique genes and untranslated regions. Using this annotation and the Rn6 reference genome, an in-silico probe design generated 826,878 probe sequences of which 94.2% were uniquely aligned to the rat genome without mismatches. Further informatics analysis revealed 25,249 genes (95.8%) covered by at least one probe and 23,603 genes (93.5%) had every exon covered by one or more probes. We report high performance metrics from exome sequencing of our probe set and Sanger validation of annotated, highly relevant, cancer gene mutations as cataloged in the human COSMIC database, in addition to several exonic variants in cancer-related genes. CONCLUSIONS: An in-silico probe set was designed to enrich the rat exome from isolated DNA. The platform was tested on rat tumor cell lines and normal FF and FFPE liver tissue. The method effectively captured target exome regions in the test DNA samples with exceptional sensitivity and specificity to obtain reliable sequencing data representing variants that are likely chemically induced somatic mutations. Genomic discovery conducted by means of high throughput WES queries should benefit investigators in discovering rat genomic variants in disease etiology and in furthering human translational research.

MBD3 localizes at promoters, gene bodies and enhancers of active genes.

The Mi-2/nucleosome remodeling and histone deacetylase (NuRD) complex is a multiprotein machine proposed to regulate chromatin structure by nucleosome remodeling and histone deacetylation activities. Recent reports describing localization of NuRD provide new insights that question previous models on NuRD action, but are not in complete agreement. Here, we provide location analysis of endogenous MBD3, a component of NuRD complex, in two human breast cancer cell lines (MCF-7 and MDA-MB-231) using two independent genomic techniques: DNA adenine methyltransferase identification (DamID) and ChIP-seq. We observed concordance of the resulting genomic localization, suggesting that these studies are converging on a robust map for NuRD in the cancer cell genome. MBD3 preferentially associated with CpG rich promoters marked by H3K4me3 and showed cell-type specific localization across gene bodies, peaking around the transcription start site. A subset of sites bound by MBD3 was enriched in H3K27ac and was in physical proximity to promoters in three-dimensional space, suggesting function as enhancers. MBD3 enrichment was also noted at promoters modified by H3K27me3. Functional analysis of chromatin indicated that MBD3 regulates nucleosome occupancy near promoters and in gene bodies. These data suggest that MBD3, and by extension the NuRD complex, may have multiple roles in fine tuning expression for both active and silent genes, representing an important step in defining regulatory mechanisms by which NuRD complex controls chromatin structure and modification status.

RNA-Seq-based toxicogenomic assessment of fresh frozen and formalin-fixed tissues yields similar mechanistic insights.

Formalin-fixed, paraffin-embedded (FFPE) pathology specimens represent a potentially vast resource for transcriptomic-based biomarker discovery. We present here a comparison of results from a whole transcriptome RNA-Seq analysis of RNA extracted from fresh frozen and FFPE livers. The samples were derived from rats exposed to aflatoxin B1 (AFB1 ) and a corresponding set of control animals. Principal components analysis indicated that samples were separated in the two groups representing presence or absence of chemical exposure, both in fresh frozen and FFPE sample types. Sixty-five percent of the differentially expressed transcripts (AFB1 vs. controls) in fresh frozen samples were also differentially expressed in FFPE samples (overlap significance: P < 0.0001). Genomic signature and gene set analysis of AFB1 differentially expressed transcript lists indicated highly similar results between fresh frozen and FFPE at the level of chemogenomic signatures (i.e., single chemical/dose/duration elicited transcriptomic signatures), mechanistic and pathology signatures, biological processes, canonical pathways and transcription factor networks. Overall, our results suggest that similar hypotheses about the biological mechanism of toxicity would be formulated from fresh frozen and FFPE samples. These results indicate that phenotypically anchored archival specimens represent a potentially informative resource for signature-based biomarker discovery and mechanistic characterization of toxicity.

Human variation and risk assessment: microarray and other studies utilizing human hepatocytes and human liver subcellular preparations.

The new paradigms proposed for human health risk assessment stress the need for the use of human and human-derived cell lines, and this review summarizes the use of primary human hepatocytes and hepatocyte subcellular preparations for the investigation of the metabolism and metabolic interactions of environmental chemicals. This includes interactions based on inhibition, induction, and activation. The role of cytotoxicity is also considered. The use of hepatocytes and hepatocyte preparations provides especially important information for the investigation of human variation and is summarized. This area is, at present, relatively neglected but will in the future be essential for accurate assessment of human health risk. A detailed summary of an initial attempt to utilize microarray technology for the study of genome-wide effects is included.

Hazard and risk characterization of 56 structurally diverse PFAS using a targeted battery of broad coverage assays using six human cell types.

Per- and poly-fluoroalkyl substances (PFAS) are extensively used in commerce leading to their prevalence in the environment. Due to their chemical stability, PFAS are considered to be persistent and bioaccumulative; they are frequently detected in both the environment and humans. Because of this, PFAS as a class (composed of hundreds to thousands of chemicals) are contaminants of very high concern. Little information is available for the vast majority of PFAS, and regulatory agencies lack safety data to determine whether exposure limits or restrictions are needed. Cell-based assays are a pragmatic approach to inform decision-makers on potential health hazards; therefore, we hypothesized that a targeted battery of human in vitro assays can be used to determine whether there are structure-bioactivity relationships for PFAS, and to characterize potential risks by comparing bioactivity (points of departure) to exposure estimates. We tested 56 PFAS from 8 structure-based subclasses in concentration response (0.1-100 µM) using six human cell types selected from target organs with suggested adverse effects of PFAS - human induced pluripotent stem cell (iPSC)-derived hepatocytes, neurons, and cardiomyocytes, primary human hepatocytes, endothelial and HepG2 cells. While many compounds were without effect; certain PFAS demonstrated cell-specific activity highlighting the necessity of using a compendium of in vitro models to identify potential hazards. No class-specific groupings were evident except for some chain length- and structure-related trends. In addition, margins of exposure (MOE) were derived using empirical and predicted exposure data. Conservative MOE calculations showed that most tested PFAS had a MOE in the 1-100 range; ∼20% of PFAS had MOE<1, providing tiered priorities for further studies. Overall, we show that a compendium of human cell-based models can be used to derive bioactivity estimates for a range of PFAS, enabling comparisons with human biomonitoring data. Furthermore, we emphasize that establishing structure-bioactivity relationships may be challenging for the tested PFAS.

Exposure to PFAS chemicals induces sex-dependent alterations in key rate-limiting steps of lipid metabolism in liver steatosis.

Toxicants with the potential to bioaccumulate in humans and animals have long been a cause for concern, particularly due to their association with multiple diseases and organ injuries. Per- and polyfluoro alkyl substances (PFAS) and polycyclic aromatic hydrocarbons (PAH) are two such classes of chemicals that bioaccumulate and have been associated with steatosis in the liver. Although PFAS and PAH are classified as chemicals of concern, their molecular mechanisms of toxicity remain to be explored in detail. In this study, we aimed to identify potential mechanisms by which an acute exposure to PFAS and PAH chemicals can induce lipid accumulation and whether the responses depend on chemical class, dose, and sex. To this end, we analyzed mechanisms beginning with the binding of the chemical to a molecular initiating event (MIE) and the consequent transcriptomic alterations. We collated potential MIEs using predictions from our previously developed ToxProfiler tool and from published steatosis adverse outcome pathways. Most of the MIEs are transcription factors, and we collected their target genes by mining the TRRUST database. To analyze the effects of PFAS and PAH on the steatosis mechanisms, we performed a computational MIE-target gene analysis on high-throughput transcriptomic measurements of liver tissue from male and female rats exposed to either a PFAS or PAH. The results showed peroxisome proliferator-activated receptor (PPAR)-α targets to be the most dysregulated, with most of the genes being upregulated. Furthermore, PFAS exposure disrupted several lipid metabolism genes, including upregulation of fatty acid oxidation genes (Acadm, Acox1, Cpt2, Cyp4a1-3) and downregulation of lipid transport genes (Apoa1, Apoa5, Pltp). We also identified multiple genes with sex-specific behavior. Notably, the rate-limiting genes of gluconeogenesis (Pck1) and bile acid synthesis (Cyp7a1) were specifically downregulated in male rats compared to female rats, while the rate-limiting gene of lipid synthesis (Scd) showed a PFAS-specific upregulation. The results suggest that the PPAR signaling pathway plays a major role in PFAS-induced lipid accumulation in rats. Together, these results show that PFAS exposure induces a sex-specific multi-factorial mechanism involving rate-limiting genes of gluconeogenesis and bile acid synthesis that could lead to activation of an adverse outcome pathway for steatosis.

Differential responses to retinoic acid and endocrine disruptor compounds of subpopulations within human embryonic stem cell lines.

The heterogeneous nature of stem cells is an important issue in both research and therapeutic use in terms of directing cell lineage differentiation pathways, as well as self-renewal properties. Using flow cytometry we have identified two distinct subpopulations by size, large and small, within cultures of human embryonic stem (hES) cell lines. These two cell populations respond differentially to retinoic acid (RA) differentiation and several endocrine disruptor compounds (EDC). The large cell population responds to retinoic acid differentiation with greater than a 50% reduction in cell number and loss of Oct-4 expression, whereas the number of the small cell population does not change and Oct-4 protein expression is maintained. In addition, four estrogenic compounds altered SSEA-3 expression differentially between the two cell subpopulations changing their ratios relative to each other. Both populations express stem cell markers Oct-4, Nanog, Tra-1-60, Tra-1-80 and SSEA-4, but express low levels of differentiation markers common to the three germ layers. Cloning studies indicate that both populations can revive the parental population. Furthermore, whole genome microarray identified approximately 400 genes with significantly different expression between the two populations (p<0.01). We propose the differential response to RA in these populations is due to differential gene expression of Notch signaling members, CoupTF1 and CoupTF2, chromatin remodeling and histone modifying genes that render the small population resistant to RA differentiation. The findings that hES cells exist as heterogeneous populations with distinct responses to differentiation signals and environmental stimuli will be relevant for their use for drug discovery and disease therapy.

Low-calorie sweeteners and health outcomes: an evaluation of rapid versus traditional evidence mapping.

OBJECTIVE: Scientific evidence related to environmental exposures continues to mount. Tools such as evidence mapping support decision making, but can be resource- and time-intensive. We explored "rapid evidence mapping" to efficiently map scientific evidence using rigorous and transparent methodologies. We undertook a proof-of-concept case study on the topic of low-calorie sweeteners. Our intent was to conduct a traditional evidence map based on the same evidence base from a prior rapid evidence map case study to compare approaches, findings, and conclusions. We searched the literature, screened full text of studies, manually tagged and categorized articles, and created visualizations to map the evidence. RESULTS: We conducted full-text screening of studies from the prior rapid evidence map and identified 255 relevant studies. Our findings corroborated those of the rapid evidence map, identifying most studies as short-term conducted in healthy individuals studying outcomes of appetite, energy sensing and body weight. We identified gaps in research areas related to outcomes of appetite and dietary intake, particularly in study populations with diabetes. Our findings illustrate the promise of rapid evidence mapping as a rigorous approach that can summarize scientific evidence, identify knowledge gaps, and identify areas for a future systematic review in a time-efficient manner.

Impact of Aligner, Normalization Method, and Sequencing Depth on TempO-seq Accuracy.

High-throughput transcriptomics has advanced through the introduction of TempO-seq, a targeted alternative to traditional RNA-seq. TempO-seq platforms use 50 nucleotide probes, each specifically designed to target a known transcript, thus allowing for reduced sequencing depth per sample compared with RNA-seq without compromising the accuracy of results. Thus far, studies using the TempO-seq method have relied on existing tools for processing the resulting short read data. However, these tools were originally designed for other data types. While they have been used for processing of early TempO-seq data, they have not been systematically assessed for accuracy or compared to determine an optimal framework for processing and analyzing TempO-seq data. In this work, we re-analyze several publicly available TempO-seq data sets covering a range of experimental designs and use corresponding RNA-seq data sets as a gold standard to rigorously assess accuracy at multiple levels. We compare 6 aligners and 5 normalization methods across various accuracy and performance metrics. Our results demonstrate the overall robust accuracy of the TempO-seq platform, independent of data processing methods. Complex aligners and advanced normalization methods do not appear to have any general advantage over simpler methods when it comes to analyzing TempO-seq data. The reduced complexity of the sequencing space, and the fact that TempO-seq probes are all equal length, appears to reduce the need for elaborate bioinformatic or statistical methods used to address these factors in RNA-seq data.

Glucocorticoids modulate microRNA expression and processing during lymphocyte apoptosis.

Glucocorticoids modulate immune development and function through the induction of lymphocyte apoptosis via mechanisms requiring alterations in gene expression. Recently, short, noncoding, microRNAs have been identified as key regulators of lymphocyte function; however, it is unknown whether glucocorticoids regulate noncoding microRNAs and whether this regulation contributes to lymphocyte apoptosis. We now show by both microarray and deep sequencing analysis that microRNAs are substantially repressed during glucocorticoid-induced apoptosis of primary rat thymocytes. Mechanistic studies revealed that primary microRNA transcripts were not repressed, whereas the expression of the key microRNA processing enzymes: Dicer, Drosha, and DGCR8/Pasha, were significantly reduced at both the mRNA and protein levels during glucocorticoid-induced apoptosis. To delineate the role of Dicer depletion and microRNA repression in apoptosis, we silenced Dicer expression in two human leukemic cell lines and demonstrated that Dicer depletion significantly enhanced glucocorticoid-induced apoptosis in both model systems. Finally, in vitro and in vivo overexpression of the conserved miR-17-92 polycistron, which was repressed significantly by dexamethasone treatment in both our microarray and deep sequencing studies, blunted glucocorticoid-induced apoptosis. These studies provide evidence of altered post-transcriptional microRNA expression and the repression of the microRNA bioprocessing pathway during glucocorticoid-induced apoptosis of lymphocytes, suggesting a role for microRNA processors and specific microRNAs in cell life/death decisions.

Autoimmunity is triggered by cPR-3(105-201), a protein complementary to human autoantigen proteinase-3.

It remains unclear how and why autoimmunity occurs. Here we show evidence for a previously unrecognized and possibly general mechanism of autoimmunity. This new finding was discovered serendipitously using material from patients with inflammatory vascular disease caused by antineutrophil cytoplasmic autoantibodies (ANCA) with specificity for proteinase-3 (PR-3). Such patients harbor not only antibodies to the autoantigen (PR-3), but also antibodies to a peptide translated from the antisense DNA strand of PR-3 (complementary PR-3, cPR-3) or to a mimic of this peptide. Immunization of mice with the middle region of cPR-3 resulted in production of antibodies not only to cPR-3, but also to the immunogen's sense peptide counterpart, PR-3. Both human and mouse antibodies to PR-3 and cPR-3 bound to each other, indicating idiotypic relationships. These findings indicate that autoimmunity can be initiated through an immune response against a peptide that is antisense or complementary to the autoantigen, which then induces anti-idiotypic antibodies (autoantibodies) that cross-react with the autoantigen.

Whole genome sequencing of low input circulating cell-free DNA obtained from normal human subjects.

Cell-free DNA circulates in plasma at low levels as a normal by-product of cellular apoptosis. Multiple clinical pathologies, as well as environmental stressors can lead to increased circulating cell-free DNA (ccfDNA) levels. Plasma DNA studies frequently employ targeted amplicon deep sequencing platforms due to limited concentrations (ng/ml) of ccfDNA in the blood. Here, we report whole genome sequencing (WGS) and read distribution across chromosomes of ccfDNA extracted from two human plasma samples from normal, healthy subjects, representative of limited clinical samples at <1 ml. Amplification was sufficiently robust with ~90% of the reference genome (GRCh38.p2) exhibiting 10X coverage. Chromosome read coverage was uniform and directly proportional to the number of reads for each chromosome across both samples. Almost 99% of the identified genomic sequence variants were known annotated dbSNP variants in the hg38 reference genome. A high prevalence of C>T and T>C mutations was present along with a strong concordance of variants shared between the germline genome databases; gnomAD (81.1%) and the 1000 Genome Project (93.6%). This study demonstrates isolation and amplification procedures from low input ccfDNA samples that can detect sequence variants across the whole genome from amplified human plasma ccfDNA that can translate to multiple clinical research disciplines.

Runx2 transcriptome of prostate cancer cells: insights into invasiveness and bone metastasis.

BACKGROUND: Prostate cancer (PCa) cells preferentially metastasize to bone at least in part by acquiring osteomimetic properties. Runx2, an osteoblast master transcription factor, is aberrantly expressed in PCa cells, and promotes their metastatic phenotype. The transcriptional programs regulated by Runx2 have been extensively studied during osteoblastogenesis, where it activates or represses target genes in a context-dependent manner. However, little is known about the gene regulatory networks influenced by Runx2 in PCa cells. We therefore investigated genome wide mRNA expression changes in PCa cells in response to Runx2. RESULTS: We engineered a C4-2B PCa sub-line called C4-2B/Rx2 dox, in which Doxycycline (Dox) treatment stimulates Runx2 expression from very low to levels observed in other PCa cells. Transcriptome profiling using whole genome expression array followed by in silico analysis indicated that Runx2 upregulated a multitude of genes with prominent cancer associated functions. They included secreted factors (CSF2, SDF-1), proteolytic enzymes (MMP9, CST7), cytoskeleton modulators (SDC2, Twinfilin, SH3PXD2A), intracellular signaling molecules (DUSP1, SPHK1, RASD1) and transcription factors (Sox9, SNAI2, SMAD3) functioning in epithelium to mesenchyme transition (EMT), tissue invasion, as well as homing and attachment to bone. Consistent with the gene expression data, induction of Runx2 in C4-2B cells enhanced their invasiveness. It also promoted cellular quiescence by blocking the G1/S phase transition during cell cycle progression. Furthermore, the cell cycle block was reversed as Runx2 levels declined after Dox withdrawal. CONCLUSIONS: The effects of Runx2 in C4-2B/Rx2 dox cells, as well as similar observations made by employing LNCaP, 22RV1 and PC3 cells, highlight multiple mechanisms by which Runx2 promotes the metastatic phenotype of PCa cells, including tissue invasion, homing to bone and induction of high bone turnover. Runx2 is therefore an attractive target for the development of novel diagnostic, prognostic and therapeutic approaches to PCa management. Targeting Runx2 may prove more effective than focusing on its individual downstream genes and pathways.

Predicting the hepatocarcinogenic potential of alkenylbenzene flavoring agents using toxicogenomics and machine learning.

Identification of carcinogenic activity is the primary goal of the 2-year bioassay. The expense of these studies limits the number of chemicals that can be studied and therefore chemicals need to be prioritized based on a variety of parameters. We have developed an ensemble of support vector machine classification models based on male F344 rat liver gene expression following 2, 14 or 90 days of exposure to a collection of hepatocarcinogens (aflatoxin B1, 1-amino-2,4-dibromoanthraquinone, N-nitrosodimethylamine, methyleugenol) and non-hepatocarcinogens (acetaminophen, ascorbic acid, tryptophan). Seven models were generated based on individual exposure durations (2, 14 or 90 days) or a combination of exposures (2+14, 2+90, 14+90 and 2+14+90 days). All sets of data, with the exception of one yielded models with 0% cross-validation error. Independent validation of the models was performed using expression data from the liver of rats exposed at 2 dose levels to a collection of alkenylbenzene flavoring agents. Depending on the model used and the exposure duration of the test data, independent validation error rates ranged from 47% to 10%. The variable with the most notable effect on independent validation accuracy was exposure duration of the alkenylbenzene test data. All models generally exhibited improved performance as the exposure duration of the alkenylbenzene data increased. The models differentiated between hepatocarcinogenic (estragole and safrole) and non-hepatocarcinogenic (anethole, eugenol and isoeugenol) alkenylbenzenes previously studied in a carcinogenicity bioassay. In the case of safrole the models correctly differentiated between carcinogenic and non-carcinogenic dose levels. The models predict that two alkenylbenzenes not previously assessed in a carcinogenicity bioassay, myristicin and isosafrole, would be weakly hepatocarcinogenic if studied at a dose level of 2 mmol/kg bw/day for 2 years in male F344 rats; therefore suggesting that these chemicals should be a higher priority relative to other untested alkenylbenzenes for evaluation in the carcinogenicity bioassay. The results of the study indicate that gene expression-based predictive models are an effective tool for identifying hepatocarcinogens. Furthermore, we find that exposure duration is a critical variable in the success or failure of such an approach, particularly when evaluating chemicals with unknown carcinogenic potency.