Reduced sister chromatid cohesion acts as a tumor penetrance modifier.

Sister chromatid cohesion (SCC) is an important process in chromosome segregation. ESCO2 is essential for establishment of SCC and is often deleted/altered in human cancers. We demonstrate that esco2 haploinsufficiency results in reduced SCC and accelerates the timing of tumor onset in both zebrafish and mouse p53 heterozygous null models, but not in p53 homozygous mutant or wild-type animals. These data indicate that esco2 haploinsufficiency accelerates tumor onset in a loss of heterozygosity (LOH) sensitive background. Analysis of The Cancer Genome Atlas (TCGA) confirmed ESCO2 deficient tumors have elevated number of LOH events throughout the genome. Further, we demonstrated heterozygous loss of sgo1, important in maintaining SCC, also results in reduced SCC and accelerated tumor formation in a p53 heterozygous background. Surprisingly, while we did observe elevated levels of chromosome missegregation and micronuclei formation in esco2 heterozygous mutant animals, this chromosomal instability did not contribute to the accelerated tumor onset in a p53 heterozygous background. Interestingly, SCC also plays a role in homologous recombination, and we did observe elevated levels of mitotic recombination derived p53 LOH in tumors from esco2 haploinsufficient animals; as well as elevated levels of mitotic recombination throughout the genome of human ESCO2 deficient tumors. Together these data suggest that reduced SCC contributes to accelerated tumor penetrance through elevated mitotic recombination.

Long-read genome sequencing for the molecular diagnosis of neurodevelopmental disorders.

Exome and genome sequencing have proven to be effective tools for the diagnosis of neurodevelopmental disorders (NDDs), but large fractions of NDDs cannot be attributed to currently detectable genetic variation. This is likely, at least in part, a result of the fact that many genetic variants are difficult or impossible to detect through typical short-read sequencing approaches. Here, we describe a genomic analysis using Pacific Biosciences circular consensus sequencing (CCS) reads, which are both long (>10 kb) and accurate (>99% bp accuracy). We used CCS on six proband-parent trios with NDDs that were unexplained despite extensive testing, including genome sequencing with short reads. We identified variants and created de novo assemblies in each trio, with global metrics indicating these datasets are more accurate and comprehensive than those provided by short-read data. In one proband, we identified a likely pathogenic (LP), de novo L1-mediated insertion in CDKL5 that results in duplication of exon 3, leading to a frameshift. In a second proband, we identified multiple large de novo structural variants, including insertion-translocations affecting DGKB and MLLT3, which we show disrupt MLLT3 transcript levels. We consider this extensive structural variation likely pathogenic. The breadth and quality of variant detection, coupled to finding variants of clinical and research interest in two of six probands with unexplained NDDs, support the hypothesis that long-read genome sequencing can substantially improve rare disease genetic discovery rates.

Pooled CRISPR screening in pancreatic cancer cells implicates co-repressor complexes as a cause of multiple drug resistance via regulation of epithelial-to-mesenchymal transition.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) patients suffer poor outcomes, including a five-year survival of below 10%. Poor outcomes result in part from therapeutic resistance that limits the impact of cytotoxic first-line therapy. Novel therapeutic approaches are needed, but currently no targeted therapies exist to treat PDAC. METHODS: To assess cellular resistance mechanisms common to four cytotoxic chemotherapies (gemcitabine, 5-fluorouracil, irinotecan, and oxaliplatin) used to treat PDAC patients, we performed four genome-wide CRISPR activation (CRISPRact) and CRISPR knock-out (CRISPRko) screens in two common PDAC cell lines (Panc-1 and BxPC3). We used pathway analysis to identify gene sets enriched among our hits and conducted RNA-sequencing and chromatin immunoprecipitation-sequencing (ChIP-seq) to characterize top hits from our screen. We used scratch assays to assess changes in cellular migration with HDAC1 overexpression. RESULTS: Our data revealed activation of ABCG2, a well-described efflux pump, as the most consistent mediator of resistance in each of our screens. CRISPR-mediated activation of genes involved in transcriptional co-repressor complexes also conferred resistance to multiple drugs. Expression of many of these genes, including HDAC1, is associated with reduced survival in PDAC patients. Up-regulation of HDAC1 in vitro increased promoter occupancy and expression of several genes involved in the epithelial-to-mesenchymal transition (EMT). These cells also displayed phenotypic changes in cellular migration consistent with activation of the EMT pathway. The expression changes resulting from HDAC1 activation were also observed with activation of several other co-repressor complex members. Finally, we developed a publicly available analysis tool, PancDS, which integrates gene expression profiles with our screen results to predict drug sensitivity in resected PDAC tumors and cell lines. CONCLUSION: Our results provide a comprehensive resource for identifying cellular mechanisms of drug resistance in PDAC, mechanistically implicate HDAC1, and co-repressor complex members broadly, in multi-drug resistance, and provide an analytical tool for predicting treatment response in PDAC tumors and cell lines.

Occupancy maps of 208 chromatin-associated proteins in one human cell type.

Transcription factors are DNA-binding proteins that have key roles in gene regulation1,2. Genome-wide occupancy maps of transcriptional regulators are important for understanding gene regulation and its effects on diverse biological processes3-6. However, only a minority of the more than 1,600 transcription factors encoded in the human genome has been assayed. Here we present, as part of the ENCODE (Encyclopedia of DNA Elements) project, data and analyses from chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experiments using the human HepG2 cell line for 208 chromatin-associated proteins (CAPs). These comprise 171 transcription factors and 37 transcriptional cofactors and chromatin regulator proteins, and represent nearly one-quarter of CAPs expressed in HepG2 cells. The binding profiles of these CAPs form major groups associated predominantly with promoters or enhancers, or with both. We confirm and expand the current catalogue of DNA sequence motifs for transcription factors, and describe motifs that correspond to other transcription factors that are co-enriched with the primary ChIP target. For example, FOX family motifs are enriched in ChIP-seq peaks of 37 other CAPs. We show that motif content and occupancy patterns can distinguish between promoters and enhancers. This catalogue reveals high-occupancy target regions at which many CAPs associate, although each contains motifs for only a minority of the numerous associated transcription factors. These analyses provide a more complete overview of the gene regulatory networks that define this cell type, and demonstrate the usefulness of the large-scale production efforts of the ENCODE Consortium.

Dissecting the regulatory activity and sequence content of loci with exceptional numbers of transcription factor associations.

DNA-associated proteins (DAPs) classically regulate gene expression by binding to regulatory loci such as enhancers or promoters. As expanding catalogs of genome-wide DAP binding maps reveal thousands of loci that, unlike the majority of conventional enhancers and promoters, associate with dozens of different DAPs with apparently little regard for motif preference, an understanding of DAP association and coordination at such regulatory loci is essential to deciphering how these regions contribute to normal development and disease. In this study, we aggregated publicly available ChIP-seq data from 469 human DAPs assayed in three cell lines and integrated these data with an orthogonal data set of 352 nonredundant, in vitro-derived motifs mapped to the genome within DNase I hypersensitivity footprints to characterize regions with high numbers of DAP associations. We establish a generalizable definition for high occupancy target (HOT) loci and identify putative driver DAP motifs in HepG2 cells, including HNF4A, SP1, SP5, and ETV4, that are highly prevalent and show sequence conservation at HOT loci. The number of different DAPs associated with an element is positively associated with evidence of regulatory activity, and by systematically mutating 245 HOT loci with a massively parallel mutagenesis assay, we localized regulatory activity to a central core region that depends on the motif sequences of our previously nominated driver DAPs. In sum, this work leverages the increasingly large number of DAP motif and ChIP-seq data publicly available to explore how DAP associations contribute to genome-wide transcriptional regulation.

Population-Specific Patterns of Epigenetic Defects in the B Cell Lineage in Patients With Systemic Lupus Erythematosus.

OBJECTIVE: To determine the stage of B cell development at which a systemic lupus erythematosus (SLE)-associated DNA methylation signature originates in African American (AA) and European American (EA) subjects, and to assess whether epigenetic defects in B cell development patterns could be predictive of SLE status in individual and mixed immune cell populations. METHODS: B cells from AA patients (n = 31) and EA patients (n = 49) with or without SLE were sorted using fluorescence-activated cell sorting into 5 B cell subsets. DNA methylation, measured at ~460,000 CpG sites, was interrogated in each subset. Enrichment analysis of transcription factor interaction at SLE-associated methylation sites was performed. A random forests algorithm was used to identify an epigenetic signature of SLE in the B cell subsets, which was then validated in an independent cohort of AA and EA patients and healthy controls. RESULTS: Regression analysis across all B cell stages resulted in identification of 60 CpGs that reached genome-wide significance for SLE-associated methylation differences (P ≤ 1.07 × 10-7 ). Interrogation of ethnicity-specific CpGs associated with SLE revealed a hypomethylated pattern that was enriched for interferon (IFN)-regulated genes and binding of EBF1 in AA patients (each P < 0.001). AA patients with SLE could be distinguished from healthy controls when the predictive model developed with the transitional B cell subset was applied to other B cell subsets (mean receiver operating characteristic [ROC] area under the curve [AUC] 0.98), and when applied to CD19+ pan-B cells (mean ROC AUC 0.95) and CD4+ pan-T cells (mean ROC AUC 0.97) from the independent validation cohort. CONCLUSION: These results indicate that SLE-specific methylation patterns are ethnicity dependent. A pattern of epigenetic changes near IFN-regulated genes early in B cell development is a hallmark of SLE in AA female subjects. EBF1 binding sites are highly enriched for significant methylation changes, implying that this may be a potential regulator of SLE-associated epigenetic changes.

CRISPR/Cas9-targeted removal of unwanted sequences from small-RNA sequencing libraries.

In small RNA (smRNA) sequencing studies, highly abundant molecules such as adapter dimer products and tissue-specific microRNAs (miRNAs) inhibit accurate quantification of lowly expressed species. We previously developed a method to selectively deplete highly abundant miRNAs. However, this method does not deplete adapter dimer ligation products that, unless removed by gel-separation, comprise most of the library. Here, we have adapted and modified recently described methods for CRISPR/Cas9-based Depletion of Abundant Species by Hybridization ('DASH') to smRNA-seq, which we have termed miRNA and Adapter Dimer-DASH (MAD-DASH). In MAD-DASH, Cas9 is complexed with single guide RNAs (sgRNAs) targeting adapter dimer ligation products, alongside highly expressed tissue-specific smRNAs, for cleavage in vitro. This process dramatically reduces adapter dimer and targeted smRNA sequences, can be multiplexed, shows minimal off-target effects, improves the quantification of lowly expressed miRNAs from human plasma and tissue derived RNA, and obviates the need for gel-separation, greatly increasing sample throughput. Additionally, the method is fully customizable to other smRNA-seq preparation methods. Like depletion of ribosomal RNA for mRNA-seq and mitochondrial DNA for ATAC-seq, our method allows for greater proportional read-depth of non-targeted sequences.

De novo mutations in the GTP/GDP-binding region of RALA, a RAS-like small GTPase, cause intellectual disability and developmental delay.

Mutations that alter signaling of RAS/MAPK-family proteins give rise to a group of Mendelian diseases known as RASopathies. However, among RASopathies, the matrix of genotype-phenotype relationships is still incomplete, in part because there are many RAS-related proteins and in part because the phenotypic consequences may be variable and/or pleiotropic. Here, we describe a cohort of ten cases, drawn from six clinical sites and over 16,000 sequenced probands, with de novo protein-altering variation in RALA, a RAS-like small GTPase. All probands present with speech and motor delays, and most have intellectual disability, low weight, short stature, and facial dysmorphism. The observed rate of de novo RALA variants in affected probands is significantly higher (p = 4.93 x 10(-11)) than expected from the estimated random mutation rate. Further, all de novo variants described here affect residues within the GTP/GDP-binding region of RALA; in fact, six alleles arose at only two codons, Val25 and Lys128. The affected residues are highly conserved across both RAL- and RAS-family genes, are devoid of variation in large human population datasets, and several are homologous to positions at which disease-associated variants have been observed in other GTPase genes. We directly assayed GTP hydrolysis and RALA effector-protein binding of the observed variants, and found that all but one tested variant significantly reduced both activities compared to wild-type. The one exception, S157A, reduced GTP hydrolysis but significantly increased RALA-effector binding, an observation similar to that seen for oncogenic RAS variants. These results show the power of data sharing for the interpretation and analysis of rare variation, expand the spectrum of molecular causes of developmental disability to include RALA, and provide additional insight into the pathogenesis of human disease caused by mutations in small GTPases.

Discovery and Validation of Circulating Biomarkers of Colorectal Adenoma by High-Depth Small RNA Sequencing.

Purpose: Colorectal cancer is the third most common cancer worldwide, causing approximately 700,000 deaths each year. The majority of colorectal cancers begin as adenomas. Definitive screening for colorectal adenomas is currently accomplished through colonoscopy but, owing largely to costs and invasiveness, is typically limited to patient groups at higher risk by virtue of age or family history. We sought to determine if blood-based small RNA markers could detect colorectal adenoma.Experimental Design: We applied high-depth small RNA sequencing to plasma from a large (n = 189) cohort of patients, balanced for age, sex, and ancestry. Our analytical methodology allowed for the detection of both microRNAs and other small RNA species. We replicated sequencing results by qPCR on plasma samples from an independent cohort (n = 140).Results: We found several small RNA species with significant associations to colorectal adenoma, including both microRNAs and non-microRNA small RNAs. These associations were robust to correction for patient covariates, including age. Among the adenoma-associated small RNAs, two, a miR-335-5p isoform and an un-annotated small RNA, were validated by qPCR in an independent cohort. A classifier trained on measures of these two RNAs in the discovery cohort yields an AUC of 0.755 (0.775 with age) for adenoma detection in the independent cohort. This classifier accurately detects adenomas in patients under 50 and is robust to sex or ancestry.Conclusions: Circulating small RNAs (including but not limited to miRNAs) discovered by sequencing and validated by qPCR identify patients with colorectal adenomas effectively. Clin Cancer Res; 24(9); 2092-9. ©2018 AACR.

R2DGC: threshold-free peak alignment and identification for 2D gas chromatography-mass spectrometry in R.

Summary: Comprehensive 2D gas chromatography-mass spectrometry is a powerful method for analyzing complex mixtures of volatile compounds, but produces a large amount of raw data that requires downstream processing to align signals of interest (peaks) across multiple samples and match peak characteristics to reference standard libraries prior to downstream statistical analysis. Very few existing tools address this aspect of analysis and those that do have shortfalls in usability or performance. We have developed an R package that implements retention time and mass spectra similarity threshold-free alignments, seamlessly integrates retention time standards for universally reproducible alignments, performs common ion filtering and provides compatibility with multiple peak quantification methods. We demonstrate that our package's performance compares favorably to existing tools on a controlled mix of metabolite standards separated under variable chromatography conditions and data generated from cell lines. Availability and implementation: R2DGC can be downloaded at https://github.com/rramaker/R2DGC or installed via the Comprehensive R Archive Network (CRAN). Contact: sjcooper@hudsonalpha.org. Supplementary information: Supplementary data are available at Bioinformatics online.

A genome-wide interactome of DNA-associated proteins in the human liver.

Large-scale efforts like the ENCODE Project have made tremendous progress in cataloging the genomic binding patterns of DNA-associated proteins (DAPs), such as transcription factors (TFs). However, most chromatin immunoprecipitation-sequencing (ChIP-seq) analyses have focused on a few immortalized cell lines whose activities and physiology differ in important ways from endogenous cells and tissues. Consequently, binding data from primary human tissue are essential to improving our understanding of in vivo gene regulation. Here, we identify and analyze more than 440,000 binding sites using ChIP-seq data for 20 DAPs in two human liver tissue samples. We integrated binding data with transcriptome and phased WGS data to investigate allelic DAP interactions and the impact of heterozygous sequence variation on the expression of neighboring genes. Our tissue-based data set exhibits binding patterns more consistent with liver biology than cell lines, and we describe uses of these data to better prioritize impactful noncoding variation. Collectively, our rich data set offers novel insights into genome function in human liver tissue and provides a valuable resource for assessing disease-related disruptions.

Post-mortem molecular profiling of three psychiatric disorders.

BACKGROUND: Psychiatric disorders are multigenic diseases with complex etiology that contribute significantly to human morbidity and mortality. Although clinically distinct, several disorders share many symptoms, suggesting common underlying molecular changes exist that may implicate important regulators of pathogenesis and provide new therapeutic targets. METHODS: We performed RNA sequencing on tissue from the anterior cingulate cortex, dorsolateral prefrontal cortex, and nucleus accumbens from three groups of 24 patients each diagnosed with schizophrenia, bipolar disorder, or major depressive disorder, and from 24 control subjects. We identified differentially expressed genes and validated the results in an independent cohort. Anterior cingulate cortex samples were also subjected to metabolomic analysis. ChIP-seq data were used to characterize binding of the transcription factor EGR1. RESULTS: We compared molecular signatures across the three brain regions and disorders in the transcriptomes of post-mortem human brain samples. The most significant disease-related differences were in the anterior cingulate cortex of schizophrenia samples compared to controls. Transcriptional changes were assessed in an independent cohort, revealing the transcription factor EGR1 as significantly down-regulated in both cohorts and as a potential regulator of broader transcription changes observed in schizophrenia patients. Additionally, broad down-regulation of genes specific to neurons and concordant up-regulation of genes specific to astrocytes was observed in schizophrenia and bipolar disorder patients relative to controls. Metabolomic profiling identified disruption of GABA levels in schizophrenia patients. CONCLUSIONS: We provide a comprehensive post-mortem transcriptome profile of three psychiatric disorders across three brain regions. We highlight a high-confidence set of independently validated genes differentially expressed between schizophrenia and control patients in the anterior cingulate cortex and integrate transcriptional changes with untargeted metabolite profiling.

RNA sequencing-based cell proliferation analysis across 19 cancers identifies a subset of proliferation-informative cancers with a common survival signature.

Despite advances in cancer diagnosis and treatment strategies, robust prognostic signatures remain elusive in most cancers. Cell proliferation has long been recognized as a prognostic marker in cancer, but the generation of comprehensive, publicly available datasets allows examination of the links between cell proliferation and cancer characteristics such as mutation rate, stage, and patient outcomes. Here we explore the role of cell proliferation across 19 cancers (n = 6,581 patients) by using tissue-based RNA sequencing data from The Cancer Genome Atlas Project and calculating a 'proliferative index' derived from gene expression associated with Proliferating Cell Nuclear Antigen (PCNA) levels. This proliferative index is significantly associated with patient survival (Cox, p-value < 0.05) in 7 of 19 cancers, which we have defined as "proliferation-informative cancers" (PICs). In PICs, the proliferative index is strongly correlated with tumor stage and nodal invasion. PICs demonstrate reduced baseline expression of proliferation machinery relative to non-PICs. Additionally, we find the proliferative index is significantly associated with gross somatic mutation burden (Spearman, p = 1.76 x 10-23) as well as with mutations in individual driver genes. This analysis provides a comprehensive characterization of tumor proliferation indices and their association with disease progression and prognosis in multiple cancer types and highlights specific cancers that may be particularly susceptible to improved targeting of this classic cancer hallmark.

Genome-wide DNA methylation measurements in prostate tissues uncovers novel prostate cancer diagnostic biomarkers and transcription factor binding patterns.

BACKGROUND: Current diagnostic tools for prostate cancer lack specificity and sensitivity for detecting very early lesions. DNA methylation is a stable genomic modification that is detectable in peripheral patient fluids such as urine and blood plasma that could serve as a non-invasive diagnostic biomarker for prostate cancer. METHODS: We measured genome-wide DNA methylation patterns in 73 clinically annotated fresh-frozen prostate cancers and 63 benign-adjacent prostate tissues using the Illumina Infinium HumanMethylation450 BeadChip array. We overlaid the most significantly differentially methylated sites in the genome with transcription factor binding sites measured by the Encyclopedia of DNA Elements consortium. We used logistic regression and receiver operating characteristic curves to assess the performance of candidate diagnostic models. RESULTS: We identified methylation patterns that have a high predictive power for distinguishing malignant prostate tissue from benign-adjacent prostate tissue, and these methylation signatures were validated using data from The Cancer Genome Atlas Project. Furthermore, by overlaying ENCODE transcription factor binding data, we observed an enrichment of enhancer of zeste homolog 2 binding in gene regulatory regions with higher DNA methylation in malignant prostate tissues. CONCLUSIONS: DNA methylation patterns are greatly altered in prostate cancer tissue in comparison to benign-adjacent tissue. We have discovered patterns of DNA methylation marks that can distinguish prostate cancers with high specificity and sensitivity in multiple patient tissue cohorts, and we have identified transcription factors binding in these differentially methylated regions that may play important roles in prostate cancer development.

aRNApipe: a balanced, efficient and distributed pipeline for processing RNA-seq data in high-performance computing environments.

SUMMARY: The wide range of RNA-seq applications and their high-computational needs require the development of pipelines orchestrating the entire workflow and optimizing usage of available computational resources. We present aRNApipe, a project-oriented pipeline for processing of RNA-seq data in high-performance cluster environments. aRNApipe is highly modular and can be easily migrated to any high-performance computing (HPC) environment. The current applications included in aRNApipe combine the essential RNA-seq primary analyses, including quality control metrics, transcript alignment, count generation, transcript fusion identification, alternative splicing and sequence variant calling. aRNApipe is project-oriented and dynamic so users can easily update analyses to include or exclude samples or enable additional processing modules. Workflow parameters are easily set using a single configuration file that provides centralized tracking of all analytical processes. Finally, aRNApipe incorporates interactive web reports for sample tracking and a tool for managing the genome assemblies available to perform an analysis. AVAILABILITY AND DOCUMENTATION: https://github.com/HudsonAlpha/aRNAPipe ; DOI: 10.5281/zenodo.202950. CONTACT: rmyers@hudsonalpha.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genomic regulation of invasion by STAT3 in triple negative breast cancer.

Breast cancer is a heterogeneous disease comprised of four molecular subtypes defined by whether the tumor-originating cells are luminal or basal epithelial cells. Breast cancers arising from the luminal mammary duct often express estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth receptor 2 (HER2). Tumors expressing ER and/or PR are treated with anti-hormonal therapies, while tumors overexpressing HER2 are targeted with monoclonal antibodies. Immunohistochemical detection of ER, PR, and HER2 receptors/proteins is a critical step in breast cancer diagnosis and guided treatment. Breast tumors that do not express these proteins are known as "triple negative breast cancer" (TNBC) and are typically basal-like. TNBCs are the most aggressive subtype, with the highest mortality rates and no targeted therapy, so there is a pressing need to identify important TNBC tumor regulators. The signal transducer and activator of transcription 3 (STAT3) transcription factor has been previously implicated as a constitutively active oncogene in TNBC. However, its direct regulatory gene targets and tumorigenic properties have not been well characterized. By integrating RNA-seq and ChIP-seq data from 2 TNBC tumors and 5 cell lines, we discovered novel gene signatures directly regulated by STAT3 that were enriched for processes involving inflammation, immunity, and invasion in TNBC. Functional analysis revealed that STAT3 has a key role regulating invasion and metastasis, a characteristic often associated with TNBC. Our findings suggest therapies targeting STAT3 may be important for preventing TNBC metastasis.

Differential stress induced c-Fos expression and identification of region-specific miRNA-mRNA networks in the dorsal raphe and amygdala of high-responder/low-responder rats.

Chronic stress triggers a variety of physical and mental health problems, and how individuals cope with stress influences risk for emotional disorders. To investigate molecular mechanisms underlying distinct stress coping styles, we utilized rats that were selectively-bred for differences in emotionality and stress reactivity. We show that high novelty responding (HR) rats readily bury a shock probe in the defensive burying test, a measure of proactive stress coping behavior, while low novelty responding (LR) rats exhibit enhanced immobility, a measure of reactive coping. Shock exposure in the defensive burying test elicited greater activation of HR rats' caudal dorsal raphe serotonergic cells compared to LRs, but lead to more pronounced activation throughout LRs' amygdala (lateral, basolateral, central, and basomedial nuclei) compared to HRs. RNA-sequencing revealed 271 mRNA transcripts and 33 microRNA species that were differentially expressed in HR/LR raphe and amygdala. We mapped potential microRNA-mRNA networks by correlating and clustering mRNA and microRNA expression and identified networks that differed in either the HR/LR dorsal raphe or amygdala. A dorsal raphe network linked three microRNAs which were down-regulated in LRs (miR-206-3p, miR-3559-5p, and miR-378a-3p) to repression of genes related to microglia and immune response (Cd74, Cyth4, Nckap1l, and Rac2), the genes themselves were up-regulated in LR dorsal raphe. In the amygdala, another network linked miR-124-5p, miR-146a-5p, miR-3068-3p, miR-380-5p, miR-539-3p, and miR-7a-1-3p with repression of chromatin remodeling-related genes (Cenpk, Cenpq, Itgb3bp, and Mis18a). Overall this work highlights potential drivers of gene-networks and downstream molecular pathways within the raphe and amygdala that contribute to individual differences in stress coping styles and stress vulnerabilities.

Kinase Gene Expression Profiling of Metastatic Clear Cell Renal Cell Carcinoma Tissue Identifies Potential New Therapeutic Targets.

Kinases are therapeutically actionable targets. Kinase inhibitors targeting vascular endothelial growth factor receptors (VEGFR) and mammalian target of rapamycin (mTOR) improve outcomes in metastatic clear cell renal cell carcinoma (ccRCC), but are not curative. Metastatic tumor tissue has not been comprehensively studied for kinase gene expression. Paired intra-patient kinase gene expression analysis in primary tumor (T), matched normal kidney (N) and metastatic tumor tissue (M) may assist in identifying drivers of metastasis and prioritizing therapeutic targets. We compared the expression of 519 kinase genes using NanoString in T, N and M in 35 patients to discover genes over-expressed in M compared to T and N tissue. RNA-seq data derived from ccRCC tumors in The Cancer Genome Atlas (TCGA) were used to demonstrate differential expression of genes in primary tumor tissue from patients that had metastasis at baseline (n = 79) compared to those that did not develop metastasis for at least 2 years (n = 187). Functional analysis was conducted to identify key signaling pathways by using Ingenuity Pathway Analysis. Of 10 kinase genes overexpressed in metastases compared to primary tumor in the discovery cohort, 9 genes were also differentially expressed in TCGA primary tumors with metastasis at baseline compared to primary tumors without metastasis for at least 2 years: EPHB2, AURKA, GSG2, IKBKE, MELK, CSK, CHEK2, CDC7 and MAP3K8; p<0.001). The top pathways overexpressed in M tissue were pyridoxal 5'-phosphate salvage, salvage pathways of pyrimidine ribonucleotides, NF-kB signaling, NGF signaling and cell cycle control of chromosomal replication. The 9 kinase genes validated to be over-expressed in metastatic ccRCC may represent currently unrecognized but potentially actionable therapeutic targets that warrant functional validation.

Distinct gene regulatory programs define the inhibitory effects of liver X receptors and PPARG on cancer cell proliferation.

BACKGROUND: The liver X receptors (LXRs, NR1H2 and NR1H3) and peroxisome proliferator-activated receptor gamma (PPARG, NR1C3) nuclear receptor transcription factors (TFs) are master regulators of energy homeostasis. Intriguingly, recent studies suggest that these metabolic regulators also impact tumor cell proliferation. However, a comprehensive temporal molecular characterization of the LXR and PPARG gene regulatory responses in tumor cells is still lacking. METHODS: To better define the underlying molecular processes governing the genetic control of cellular growth in response to extracellular metabolic signals, we performed a comprehensive, genome-wide characterization of the temporal regulatory cascades mediated by LXR and PPARG signaling in HT29 colorectal cancer cells. For this analysis, we applied a multi-tiered approach that incorporated cellular phenotypic assays, gene expression profiles, chromatin state dynamics, and nuclear receptor binding patterns. RESULTS: Our results illustrate that the activation of both nuclear receptors inhibited cell proliferation and further decreased glutathione levels, consistent with increased cellular oxidative stress. Despite a common metabolic reprogramming, the gene regulatory network programs initiated by these nuclear receptors were widely distinct. PPARG generated a rapid and short-term response while maintaining a gene activator role. By contrast, LXR signaling was prolonged, with initial, predominantly activating functions that transitioned to repressive gene regulatory activities at late time points. CONCLUSIONS: Through the use of a multi-tiered strategy that integrated various genomic datasets, our data illustrate that distinct gene regulatory programs elicit common phenotypic effects, highlighting the complexity of the genome. These results further provide a detailed molecular map of metabolic reprogramming in cancer cells through LXR and PPARG activation. As ligand-inducible TFs, these nuclear receptors can potentially serve as attractive therapeutic targets for the treatment of various cancers.

RNA sequencing of pancreatic adenocarcinoma tumors yields novel expression patterns associated with long-term survival and reveals a role for ANGPTL4.

BACKGROUND: Pancreatic adenocarcinoma patients have low survival rates due to late-stage diagnosis and high rates of cancer recurrence even after surgical resection. It is important to understand the molecular characteristics associated with survival differences in pancreatic adenocarcinoma tumors that may inform patient care. RESULTS: RNA sequencing was performed for 51 patient tumor tissues extracted from patients undergoing surgical resection, and expression was associated with overall survival time from diagnosis. Our analysis uncovered 323 transcripts whose expression correlates with survival time in our pancreatic patient cohort. This genomic signature was validated in an independent RNA-seq dataset of 68 additional patients from the International Cancer Genome Consortium. We demonstrate that this transcriptional profile is largely independent of markers of cellular division and present a 19-transcript predictive model built from a subset of the 323 transcripts that can distinguish patients with differing survival times across both the training and validation patient cohorts. We present evidence that a subset of the survival-associated transcripts is associated with resistance to gemcitabine treatment in vitro, and reveal that reduced expression of one of the survival-associated transcripts, Angiopoietin-like 4, impairs growth of a gemcitabine-resistant pancreatic cancer cell line. CONCLUSIONS: Gene expression patterns in pancreatic adenocarcinoma tumors can distinguish patients with differing survival outcomes after undergoing surgical resection, and the survival difference could be associated with the intrinsic gemcitabine sensitivity of primary patient tumors. Thus, these transcriptional differences may impact patient care by distinguishing patients who would benefit from a non-gemcitabine based therapy.