Prostate cancer patient stratification by molecular signatures in the Veterans Precision Oncology Data Commons.

Veterans are at an increased risk for prostate cancer, a disease with extraordinary clinical and molecular heterogeneity, compared with the general population. However, little is known about the underlying molecular heterogeneity within the veteran population and its impact on patient management and treatment. Using clinical and targeted tumor sequencing data from the National Veterans Affairs health system, we conducted a retrospective cohort study on 45 patients with advanced prostate cancer in the Veterans Precision Oncology Data Commons (VPODC), most of whom were metastatic castration-resistant. We characterized the mutational burden in this cohort and conducted unsupervised clustering analysis to stratify patients by molecular alterations. Veterans with prostate cancer exhibited a mutational landscape broadly similar to prior studies, including KMT2A and NOTCH1 mutations associated with neuroendocrine prostate cancer phenotype, previously reported to be enriched in veterans. We also identified several potential novel mutations in PTEN, MSH6, VHL, SMO, and ABL1 Hierarchical clustering analysis revealed two subgroups containing therapeutically targetable molecular features with novel mutational signatures distinct from those reported in the Catalogue of Somatic Mutations in Cancer database. The clustering approach presented in this study can potentially be used to clinically stratify patients based on their distinct mutational profiles and identify actionable somatic mutations for precision oncology.

Immune gene variation associated with chromosome-scale differences among individual zebrafish genomes.

Immune genes have evolved to maintain exceptional diversity, offering robust defense against pathogens. We performed genomic assembly to examine immune gene variation in zebrafish. Gene pathway analysis identified immune genes as significantly enriched among genes with evidence of positive selection. A large subset of genes was absent from analysis of coding sequences due to apparent lack of reads, prompting us to examine genes overlapping zero coverage regions (ZCRs), defined as 2 kb stretches without mapped reads. Immune genes were identified as highly enriched within ZCRs, including over 60% of major histocompatibility complex (MHC) genes and NOD-like receptor (NLR) genes, mediators of direct and indirect pathogen recognition. This variation was most highly concentrated throughout one arm of chromosome 4 carrying a large cluster of NLR genes, associated with large-scale structural variation covering more than half of the chromosome. Our genomic assemblies uncovered alternative haplotypes and distinct complements of immune genes among individual zebrafish, including the MHC Class II locus on chromosome 8 and the NLR gene cluster on chromosome 4. While previous studies have shown marked variation in NLR genes between vertebrate species, our study highlights extensive variation in NLR gene regions between individuals of the same species. Taken together, these findings provide evidence of immune gene variation on a scale previously unknown in other vertebrate species and raise questions about potential impact on immune function.

Contrived Materials and a Data Set for the Evaluation of Liquid Biopsy Tests: A Blood Profiling Atlas in Cancer (BLOODPAC) Community Study.

The Blood Profiling Atlas in Cancer (BLOODPAC) Consortium is a collaborative effort involving stakeholders from the public, industry, academia, and regulatory agencies focused on developing shared best practices on liquid biopsy. This report describes the results from the JFDI (Just Freaking Do It) study, a BLOODPAC initiative to develop standards on the use of contrived materials mimicking cell-free circulating tumor DNA, to comparatively evaluate clinical laboratory testing procedures. Nine independent laboratories tested the concordance, sensitivity, and specificity of commercially available contrived materials with known variant-allele frequencies (VAFs) ranging from 0.1% to 5.0%. Each participating laboratory utilized its own proprietary evaluation procedures. The results demonstrated high levels of concordance and sensitivity at VAFs of >0.1%, but reduced concordance and sensitivity at a VAF of 0.1%; these findings were similar to those from previous studies, suggesting that commercially available contrived materials can support the evaluation of testing procedures across multiple technologies. Such materials may enable more objective comparisons of results on materials formulated in-house at each center in multicenter trials. A unique goal of the collaborative effort was to develop a data resource, the BLOODPAC Data Commons, now available to the liquid-biopsy community for further study. This resource can be used to support independent evaluations of results, data extension through data integration and new studies, and retrospective evaluation of data collection.

A highly diverse set of novel immunoglobulin-like transcript (NILT) genes in zebrafish indicates a wide range of functions with complex relationships to mammalian receptors.

Multiple novel immunoglobulin-like transcripts (NILTs) have been identified from salmon, trout, and carp. NILTs typically encode activating or inhibitory transmembrane receptors with extracellular immunoglobulin (Ig) domains. Although predicted to provide immune recognition in ray-finned fish, we currently lack a definitive framework of NILT diversity, thereby limiting our predictions for their evolutionary origin and function. In order to better understand the diversity of NILTs and their possible roles in immune function, we identified five NILT loci in the Atlantic salmon (Salmo salar) genome, defined 86 NILT Ig domains within a 3-Mbp region of zebrafish (Danio rerio) chromosome 1, and described 41 NILT Ig domains as part of an alternative haplotype for this same genomic region. We then identified transcripts encoded by 43 different NILT genes which reflect an unprecedented diversity of Ig domain sequences and combinations for a family of non-recombining receptors within a single species. Zebrafish NILTs include a sole putative activating receptor but extensive inhibitory and secreted forms as well as membrane-bound forms with no known signaling motifs. These results reveal a higher level of genetic complexity, interindividual variation, and sequence diversity for NILTs than previously described, suggesting that this gene family likely plays multiple roles in host immunity.

Tcf-1 promotes genomic instability and T cell transformation in response to aberrant ß-catenin activation.

Understanding the mechanisms promoting chromosomal translocations of the rearranging receptor loci in leukemia and lymphoma remains incomplete. Here we show that leukemias induced by aberrant activation of ß-catenin in thymocytes, which bear recurrent Tcra/Myc-Pvt1 translocations, depend on Tcf-1. The DNA double strand breaks (DSBs) in the Tcra site of the translocation are Rag-generated, whereas the Myc-Pvt1 DSBs are not. Aberrantly activated ß-catenin redirects Tcf-1 binding to novel DNA sites to alter chromatin accessibility and down-regulate genome-stability pathways. Impaired homologous recombination (HR) DNA repair and replication checkpoints lead to retention of DSBs that promote translocations and transformation of double-positive (DP) thymocytes. The resulting lymphomas, which resemble human T cell acute lymphoblastic leukemia (T-ALL), are sensitive to PARP inhibitors (PARPis). Our findings indicate that aberrant ß-catenin signaling contributes to translocations in thymocytes by guiding Tcf-1 to promote the generation and retention of replication-induced DSBs allowing their coexistence with Rag-generated DSBs. Thus, PARPis could offer therapeutic options in hematologic malignancies with active Wnt/ß-catenin signaling.

Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.

Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resistant (AMR) predictions. Existing statistical rule-based Mycobacterium tuberculosis (MTB) drug resistance prediction methods using bacterial genomic sequencing data often achieve varying results: high accuracy on some antibiotics but relatively low accuracy on others. Traditional machine learning (ML) approaches have been applied to classify drug resistance for MTB and have shown more stable performance. However, there is no study that uses deep learning architecture like Convolutional Neural Network (CNN) on a large and diverse cohort of MTB samples for AMR prediction. We developed 24 binary classifiers of MTB drug resistance status across eight anti-MTB drugs and three different ML algorithms: logistic regression, random forest and 1D CNN using a training dataset of 10,575 MTB isolates collected from 16 countries across six continents, where an extended pan-genome reference was used for detecting genetic features. Our 1D CNN architecture was designed to integrate both sequential and non-sequential features. In terms of F1-scores, 1D CNN models are our best classifiers that are also more accurate and stable than the state-of-the-art rule-based tool Mykrobe predictor (81.1 to 93.8%, 93.7 to 96.2%, 93.1 to 94.8%, 95.9 to 97.2% and 97.1 to 98.2% for ethambutol, rifampicin, pyrazinamide, isoniazid and ofloxacin respectively). We applied filter-based feature selection to find AMR relevant features. All selected variant features are AMR-related ones in CARD database. 78.8% of them are also in the catalogue of MTB mutations that were recently identified as drug resistance-associated ones by WHO. To facilitate ML model development for AMR prediction, we packaged every step into an automated pipeline and shared the source code at https://github.com/KuangXY3/MTB-AMR-classification-CNN .

African Americans and European Americans exhibit distinct gene expression patterns across tissues and tumors associated with immunologic functions and environmental exposures.

The COVID-19 pandemic has affected African American populations disproportionately with respect to prevalence, and mortality. Expression profiles represent snapshots of combined genetic, socio-environmental (including socioeconomic and environmental factors), and physiological effects on the molecular phenotype. As such, they have potential to improve biological understanding of differences among populations, and provide therapeutic biomarkers and environmental mitigation strategies. Here, we undertook a large-scale assessment of patterns of gene expression between African Americans and European Americans, mining RNA-Seq data from 25 non-diseased and diseased (tumor) tissue-types. We observed the widespread enrichment of pathways implicated in COVID-19 and integral to inflammation and reactive oxygen stress. Chemokine CCL3L3 expression is up-regulated in African Americans. GSTM1, encoding a glutathione S-transferase that metabolizes reactive oxygen species and xenobiotics, is upregulated. The little-studied F8A2 gene is up to 40-fold more highly expressed in African Americans; F8A2 encodes HAP40 protein, which mediates endosome movement, potentially altering the cellular response to SARS-CoV-2. African American expression signatures, superimposed on single cell-RNA reference data, reveal increased number or activity of esophageal glandular cells and lung ACE2-positive basal keratinocytes. Our findings establish basal prognostic signatures that can be used to refine approaches to minimize risk of severe infection and improve precision treatment of COVID-19 for African Americans. To enable dissection of causes of divergent molecular phenotypes, we advocate routine inclusion of metadata on genomic and socio-environmental factors for human RNA-sequencing studies.

SARS-CoV-2 genomic diversity and the implications for qRT-PCR diagnostics and transmission.

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq data sets and 6928 consensus genomes to contrast the intra-host and inter-host diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights intra-host single nucleotide variant (iSNV) and SNP similarity, albeit with differences in C > U changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of insertions and deletions contribute to the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission.

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons' Data.

We present a systematic analysis of the effects of synchronizing a large-scale, deeply characterized, multi-omic dataset to the current human reference genome, using updated software, pipelines, and annotations. For each of 5 molecular data platforms in The Cancer Genome Atlas (TCGA)-mRNA and miRNA expression, single nucleotide variants, DNA methylation and copy number alterations-comprehensive sample, gene, and probe-level studies were performed, towards quantifying the degree of similarity between the 'legacy' GRCh37 (hg19) TCGA data and its GRCh38 (hg38) version as 'harmonized' by the Genomic Data Commons. We offer gene lists to elucidate differences that remained after controlling for confounders, and strategies to mitigate their impact on biological interpretation. Our results demonstrate that the hg19 and hg38 TCGA datasets are very highly concordant, promote informed use of either legacy or harmonized omics data, and provide a rubric that encourages similar comparisons as new data emerge and reference data evolve.

Glucocorticoid receptor modulation decreases ER-positive breast cancer cell proliferation and suppresses wild-type and mutant ER chromatin association.

BACKGROUND: Non-ER nuclear receptor activity can alter estrogen receptor (ER) chromatin association and resultant ER-mediated transcription. Consistent with GR modulation of ER activity, high tumor glucocorticoid receptor (GR) expression correlates with improved relapse-free survival in ER+ breast cancer (BC) patients. METHODS: In vitro cell proliferation assays were used to assess ER-mediated BC cell proliferation following GR modulation. ER chromatin association following ER/GR co-liganding was measured using global ChIP sequencing and directed ChIP analysis of proliferative gene enhancers. RESULTS: We found that GR liganding with either a pure agonist or a selective GR modulator (SGRM) slowed estradiol (E2)-mediated proliferation in ER+ BC models. SGRMs that antagonized transcription of GR-unique genes both promoted GR chromatin association and inhibited ER chromatin localization at common DNA enhancer sites. Gene expression analysis revealed that ER and GR co-activation decreased proliferative gene activation (compared to ER activation alone), specifically reducing CCND1, CDK2, and CDK6 gene expression. We also found that ligand-dependent GR occupancy of common ER-bound enhancer regions suppressed both wild-type and mutant ER chromatin association and decreased corresponding gene expression. In vivo, treatment with structurally diverse SGRMs also reduced MCF-7 Y537S ER-expressing BC xenograft growth. CONCLUSION: These studies demonstrate that liganded GR can suppress ER chromatin occupancy at shared ER-regulated enhancers, including CCND1 (Cyclin D1), regardless of whether the ligand is a classic GR agonist or antagonist. Resulting GR-mediated suppression of ER+ BC proliferative gene expression and cell division suggests that SGRMs could decrease ER-driven gene expression.

Proteomics reveals NNMT as a master metabolic regulator of cancer-associated fibroblasts.

High-grade serous carcinoma has a poor prognosis, owing primarily to its early dissemination throughout the abdominal cavity. Genomic and proteomic approaches have provided snapshots of the proteogenomics of ovarian cancer1,2, but a systematic examination of both the tumour and stromal compartments is critical in understanding ovarian cancer metastasis. Here we develop a label-free proteomic workflow to analyse as few as 5,000 formalin-fixed, paraffin-embedded cells microdissected from each compartment. The tumour proteome was stable during progression from in situ lesions to metastatic disease; however, the metastasis-associated stroma was characterized by a highly conserved proteomic signature, prominently including the methyltransferase nicotinamide N-methyltransferase (NNMT) and several of the proteins that it regulates. Stromal NNMT expression was necessary and sufficient for functional aspects of the cancer-associated fibroblast (CAF) phenotype, including the expression of CAF markers and the secretion of cytokines and oncogenic extracellular matrix. Stromal NNMT expression supported ovarian cancer migration, proliferation and in vivo growth and metastasis. Expression of NNMT in CAFs led to depletion of S-adenosyl methionine and reduction in histone methylation associated with widespread gene expression changes in the tumour stroma. This work supports the use of ultra-low-input proteomics to identify candidate drivers of disease phenotypes. NNMT is a central, metabolic regulator of CAF differentiation and cancer progression in the stroma that may be therapeutically targeted.

Genetic analysis of impulsive personality traits: Examination of a priori candidates and genome-wide variation.

Impulsive personality traits are heritable risk factors and putative endophenotypes for addiction and other psychiatric disorders involving disinhibition. This study examined the genetic basis of impulsive personality traits, defined as scores on the Barratt Impulsiveness Scale (BIS-11) and the UPPS-P Impulsive Behavior Scale (UPPS-P). In 983 healthy young adults of European ancestry, the study examined genetic variation in relation to a combined phenotype of seven subscales based on high phenotypic intercorrelations. The study first tested 14 a priori loci that have previously been associated impulsive personality traits or closely related constructs. Second, the study included an exploratory genome-wide scan (i.e., GWAS), acknowledging that only relatively large effects would be detectable in a sample size of ~ 1000. A priori SNP analyses revealed a significant association between the combined impulsivity phenotype and two SNPs within the 5-HT2a receptor gene (HTR2A; rs6313 and rs6311). Follow-up analyses suggested that the effects were specific to the Motor and Non-planning subscales on the BIS-11, and also that the two loci were in linkage disequilibrium. The GWAS yielded no statistically significant findings. This study further implicates loci within HTR2A with certain forms of self-reported impulsivity and identifies candidates for future investigation from the genome-wide analyses.

Density of immunogenic antigens does not explain the presence or absence of the T-cell-inflamed tumor microenvironment in melanoma.

Melanoma metastases can be categorized by gene expression for the presence of a T-cell-inflamed tumor microenvironment, which correlates with clinical efficacy of immunotherapies. T cells frequently recognize mutational antigens corresponding to nonsynonymous somatic mutations (NSSMs), and in some cases shared differentiation or cancer-testis antigens. Therapies are being pursued to trigger immune infiltration into non-T-cell-inflamed tumors in the hope of rendering them immunotherapy responsive. However, whether those tumors express antigens capable of T-cell recognition has not been explored. To address this question, 266 melanomas from The Cancer Genome Atlas (TCGA) were categorized by the presence or absence of a T-cell-inflamed gene signature. These two subsets were interrogated for cancer-testis, differentiation, and somatic mutational antigens. No statistically significant differences were observed, including density of NSSMs. Focusing on hypothetical HLA-A2+ binding scores, 707 peptides were synthesized, corresponding to all identified candidate neoepitopes. No differences were observed in measured HLA-A2 binding between inflamed and noninflamed cohorts. Twenty peptides were randomly selected from each cohort to evaluate priming and recognition by human CD8+ T cells in vitro with 25% of peptides confirmed to be immunogenic in both. A similar gene expression profile applied to all solid tumors of TCGA revealed no association between T-cell signature and NSSMs. Our results indicate that lack of spontaneous immune infiltration in solid tumors is unlikely due to lack of antigens. Strategies that improve T-cell infiltration into tumors may therefore be able to facilitate clinical response to immunotherapy once antigens become recognized.

Genomics of Ovarian Cancer Progression Reveals Diverse Metastatic Trajectories Including Intraepithelial Metastasis to the Fallopian Tube.

Accumulating evidence has supported the fallopian tube rather than the ovary as the origin for high-grade serous ovarian cancer (HGSOC). To understand the relationship between putative precursor lesions and metastatic tumors, we performed whole-exome sequencing on specimens from eight HGSOC patient progression series consisting of serous tubal intraepithelial carcinomas (STIC), invasive fallopian tube lesions, invasive ovarian lesions, and omental metastases. Integration of copy number and somatic mutations revealed patient-specific patterns with similar mutational signatures and copy-number variation profiles across all anatomic sites, suggesting that genomic instability is an early event in HGSOC. Phylogenetic analyses supported STIC as precursor lesions in half of our patient cohort, but also identified STIC as metastases in 2 patients. Ex vivo assays revealed that HGSOC spheroids can implant in the fallopian tube epithelium and mimic STIC lesions. That STIC may represent metastases calls into question the assumption that STIC are always indicative of primary fallopian tube cancers. SIGNIFICANCE: We find that the putative precursor lesions for HGSOC, STIC, possess most of the genomic aberrations present in advanced cancers. In addition, a proportion of STIC represent intraepithelial metastases to the fallopian tube rather than the origin of HGSOC. Cancer Discov; 6(12); 1342-51. ©2016 AACR.See related commentary by Swisher et al., p. 1309This article is highlighted in the In This Issue feature, p. 1293.

Integrative genomics reveals hypoxia inducible genes that are associated with a poor prognosis in neuroblastoma patients.

Neuroblastoma is notable for its broad spectrum of clinical behavior ranging from spontaneous regression to rapidly progressive disease. Hypoxia is well known to confer a more aggressive phenotype in neuroblastoma. We analyzed transcriptome data from diagnostic neuroblastoma tumors and hypoxic neuroblastoma cell lines to identify genes whose expression levels correlate with poor patient outcome and are involved in the hypoxia response. By integrating a diverse set of transcriptome datasets, including those from neuroblastoma patients and neuroblastoma derived cell lines, we identified nine genes (SLCO4A1, ENO1, HK2, PGK1, MTFP1, HILPDA, VKORC1, TPI1, and HIST1H1C) that are up-regulated in hypoxia and whose expression levels are correlated with poor patient outcome in three independent neuroblastoma cohorts. Analysis of 5-hydroxymethylcytosine and ENCODE data indicate that at least five of these nine genes have an increase in 5-hydroxymethylcytosine and a more open chromatin structure in hypoxia versus normoxia and are putative targets of hypoxia inducible factor (HIF) as they contain HIF binding sites in their regulatory regions. Four of these genes are key components of the glycolytic pathway and another three are directly involved in cellular metabolism. We experimentally validated our computational findings demonstrating that seven of the nine genes are significantly up-regulated in response to hypoxia in the four neuroblastoma cell lines tested. This compact and robustly validated group of genes, is associated with the hypoxia response in aggressive neuroblastoma and may represent a novel target for biomarker and therapeutic development.

Quantitative trait loci associated with natural diversity in water-use efficiency and response to soil drying in Brachypodium distachyon.

All plants must optimize their growth with finite resources. Water use efficiency (WUE) measures the relationship between biomass acquisition and transpired water. In the present study, we performed two experiments to understand the genetic basis of WUE and other parameters of plant-water interaction under control and water-limited conditions. Our study used two inbred natural accessions of Brachypodium distachyon, a model grass species with close phylogenetic affinity to temperate forage and cereal crops. First, we identify the soil water content which causes a reduction in leaf relative water content and an increase in WUE. Second, we present results from a large phenotyping experiment utilizing a recombinant inbred line mapping population derived from these same two natural accessions. We identify QTLs associated with environmentally-insensitive genetic variation in WUE, including a pair of epistatically interacting loci. We also identify QTLs associated with constitutive differences in biomass and a QTL describing an environmentally-sensitive difference in leaf carbon content. Finally, we present a new linkage map for this mapping population based on new SNP markers as well as updated genomic positions for previously described markers. Our studies provide an initial characterization of plant-water relations in B. distachyon and identify candidate genomic regions involved in WUE.

Alternative haplotypes of antigen processing genes in zebrafish diverged early in vertebrate evolution.

Antigen processing and presentation genes found within the MHC are among the most highly polymorphic genes of vertebrate genomes, providing populations with diverse immune responses to a wide array of pathogens. Here, we describe transcriptome, exome, and whole-genome sequencing of clonal zebrafish, uncovering the most extensive diversity within the antigen processing and presentation genes of any species yet examined. Our CG2 clonal zebrafish assembly provides genomic context within a remarkably divergent haplotype of the core MHC region on chromosome 19 for six expressed genes not found in the zebrafish reference genome: mhc1uga, proteasome-ß 9b (psmb9b), psmb8f, and previously unknown genes psmb13b, tap2d, and tap2e We identify ancient lineages for Psmb13 within a proteasome branch previously thought to be monomorphic and provide evidence of substantial lineage diversity within each of three major trifurcations of catalytic-type proteasome subunits in vertebrates: Psmb5/Psmb8/Psmb11, Psmb6/Psmb9/Psmb12, and Psmb7/Psmb10/Psmb13. Strikingly, nearby tap2 and MHC class I genes also retain ancient sequence lineages, indicating that alternative lineages may have been preserved throughout the entire MHC pathway since early diversification of the adaptive immune system ∼500 Mya. Furthermore, polymorphisms within the three MHC pathway steps (antigen cleavage, transport, and presentation) are each predicted to alter peptide specificity. Lastly, comparative analysis shows that antigen processing gene diversity is far more extensive than previously realized (with ancient coelacanth psmb8 lineages, shark psmb13, and tap2t and psmb10 outside the teleost MHC), implying distinct immune functions and conserved roles in shaping MHC pathway evolution throughout vertebrates.