Repurposing Type I-A CRISPR-Cas3 for a robust diagnosis of human papillomavirus (HPV).

R-loop-triggered collateral single-stranded DNA (ssDNA) nuclease activity within Class 1 Type I CRISPR-Cas systems holds immense potential for nucleic acid detection. However, the hyperactive ssDNase activity of Cas3 introduces unwanted noise and false-positive results. In this study, we identified a novel Type I-A Cas3 variant derived from Thermococcus siculi, which remains in an auto-inhibited state until it is triggered by Cascade complex and R-loop formation. This Type I-A CRISPR-Cas3 system not only exhibits an expanded protospacer adjacent motif (PAM) recognition capability but also demonstrates remarkable intolerance towards mismatched sequences. Furthermore, it exhibits dual activation modes-responding to both DNA and RNA targets. The culmination of our research efforts has led to the development of the Hyper-Active-Verification Establishment (HAVE, ). This innovation enables swift and precise human papillomavirus (HPV) diagnosis in clinical samples, providing a robust molecular diagnostic tool based on the Type I-A CRISPR-Cas3 system. Our findings contribute to understanding type I-A CRISPR-Cas3 system regulation and facilitate the creation of advanced diagnostic solutions with broad clinical applicability.

A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies.

Large-scale whole-genome sequencing (WGS) studies have improved our understanding of the contributions of coding and noncoding rare variants to complex human traits. Leveraging association effect sizes across multiple traits in WGS rare variant association analysis can improve statistical power over single-trait analysis, and also detect pleiotropic genes and regions. Existing multi-trait methods have limited ability to perform rare variant analysis of large-scale WGS data. We propose MultiSTAAR, a statistical framework and computationally-scalable analytical pipeline for functionally-informed multi-trait rare variant analysis in large-scale WGS studies. MultiSTAAR accounts for relatedness, population structure and correlation among phenotypes by jointly analyzing multiple traits, and further empowers rare variant association analysis by incorporating multiple functional annotations. We applied MultiSTAAR to jointly analyze three lipid traits (low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides) in 61,861 multi-ethnic samples from the Trans-Omics for Precision Medicine (TOPMed) Program. We discovered new associations with lipid traits missed by single-trait analysis, including rare variants within an enhancer of NIPSNAP3A and an intergenic region on chromosome 1.

FAVOR: functional annotation of variants online resource and annotator for variation across the human genome.

Large biobank-scale whole genome sequencing (WGS) studies are rapidly identifying a multitude of coding and non-coding variants. They provide an unprecedented resource for illuminating the genetic basis of human diseases. Variant functional annotations play a critical role in WGS analysis, result interpretation, and prioritization of disease- or trait-associated causal variants. Existing functional annotation databases have limited scope to perform online queries and functionally annotate the genotype data of large biobank-scale WGS studies. We develop the Functional Annotation of Variants Online Resources (FAVOR) to meet these pressing needs. FAVOR provides a comprehensive multi-faceted variant functional annotation online portal that summarizes and visualizes findings of all possible nine billion single nucleotide variants (SNVs) across the genome. It allows for rapid variant-, gene- and region-level queries of variant functional annotations. FAVOR integrates variant functional information from multiple sources to describe the functional characteristics of variants and facilitates prioritizing plausible causal variants influencing human phenotypes. Furthermore, we provide a scalable annotation tool, FAVORannotator, to functionally annotate large-scale WGS studies and efficiently store the genotype and their variant functional annotation data in a single file using the annotated Genomic Data Structure (aGDS) format, making downstream analysis more convenient. FAVOR and FAVORannotator are available at https://favor.genohub.org.

Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.

Meta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.

A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies.

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer.

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

AFA: Ancestry-specific allele frequency estimation in admixed populations: The Hispanic Community Health Study/Study of Latinos.

Allele frequency estimates in admixed populations, such as Hispanics and Latinos, rely on the sample's specific admixture composition and thus may differ between two seemingly similar populations. However, ancestry-specific allele frequencies, i.e., pertaining to the ancestral populations of an admixed group, may be particularly useful for prioritizing genetic variants for genetic discovery and personalized genomic health. We developed a method, ancestry-specific allele frequency estimation in admixed populations (AFA), to estimate the frequencies of biallelic variants in admixed populations with an unlimited number of ancestries. AFA uses maximum-likelihood estimation by modeling the conditional probability of having an allele given proportions of genetic ancestries. It can be applied using either local ancestry interval proportions encompassing the variant (local-ancestry-specific allele frequency estimations in admixed populations [LAFAs]) or global proportions of genetic ancestries (global-ancestry-specific allele frequency estimations in admixed populations [GAFAs]), which are easier to compute and are more widely available. Simulations and comparisons to existing software demonstrated the high accuracy of the method. We implemented AFA on high-quality imputed data of ∼9,000 Hispanics and Latinos from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), an understudied, admixed population with three predominant continental ancestries: Amerindian, European, and African. Comparison of the European and African estimated frequencies to the respective gnomAD frequencies demonstrated high correlations (Pearson R2 = 0.97-0.99). We provide a genome-wide dataset of the estimated ancestry-specific allele frequencies for available variants with allele frequency between 5% and 95% in at least one of the three ancestral populations. Association analysis of Amerindian-enriched variants with cardiometabolic traits identified five loci associated with lipid traits in Hispanics and Latinos, demonstrating the utility of ancestry-specific allele frequencies in admixed populations.

A multi-dimensional integrative scoring framework for predicting functional variants in the human genome.

Attempts to identify and prioritize functional DNA elements in coding and non-coding regions, particularly through use of in silico functional annotation data, continue to increase in popularity. However, specific functional roles can vary widely from one variant to another, making it challenging to summarize different aspects of variant function with a one-dimensional rating. Here we propose multi-dimensional annotation-class integrative estimation (MACIE), an unsupervised multivariate mixed-model framework capable of integrating annotations of diverse origin to assess multi-dimensional functional roles for both coding and non-coding variants. Unlike existing one-dimensional scoring methods, MACIE views variant functionality as a composite attribute encompassing multiple characteristics and estimates the joint posterior functional probabilities of each genomic position. This estimate offers more comprehensive and interpretable information in the presence of multiple aspects of functionality. Applied to a variety of independent coding and non-coding datasets, MACIE demonstrates powerful and robust performance in discriminating between functional and non-functional variants. We also show an application of MACIE to fine-mapping and heritability enrichment analysis by using the lipids GWAS summary statistics data from the European Network for Genetic and Genomic Epidemiology Consortium.

Genome-wide association study of neck circumference identifies sex-specific loci independent of generalized adiposity.

BACKGROUND/OBJECTIVES: Neck circumference, an index of upper airway fat, has been suggested to be an important measure of body-fat distribution with unique associations with health outcomes such as obstructive sleep apnea and metabolic disease. This study aims to study the genetic bases of neck circumference. METHODS: We conducted a multi-ethnic genome-wide association study of neck circumference, adjusted and unadjusted for BMI, in up to 15,090 European Ancestry (EA) and African American (AA) individuals. Because sexually dimorphic associations have been observed for anthropometric traits, we conducted both sex-combined and sex-specific analysis. RESULTS: We identified rs227724 near the Noggin (NOG) gene as a possible quantitative locus for neck circumference in men (N = 8831, P = 1.74 × 10-9) but not in women (P = 0.08). The association was replicated in men (N = 1554, P = 0.045) in an independent dataset. This locus was previously reported to be associated with human height and with self-reported snoring. We also identified rs13087058 on chromosome 3 as a suggestive locus in sex-combined analysis (N = 15090, P = 2.94 × 10-7; replication P =0.049). This locus was also associated with electrocardiogram-assessed PR interval and is a cis-expression quantitative locus for the PDZ Domain-containing ring finger 2 (PDZRN3) gene. Both NOG and PDZRN3 interact with members of transforming growth factor-beta superfamily signaling proteins. CONCLUSIONS: Our study suggests that neck circumference may have unique genetic basis independent of BMI.

Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer.

Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1ß pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.

Epstein-Barr Virus Episome Physically Interacts with Active Regions of the Host Genome in Lymphoblastoid Cells.

The Epstein-Barr virus (EBV) episome is known to interact with the three-dimensional structure of the human genome in infected cells. However, the exact locations of these interactions and their potential functional consequences remain unclear. Recently, high-resolution chromatin conformation capture (Hi-C) assays in lymphoblastoid cells have become available, enabling us to precisely map the contacts between the EBV episome(s) and the human host genome. Using available Hi-C data at a 10-kb resolution, we have identified 15,000 reproducible contacts between EBV episome(s) and the human genome. These contacts are highly enriched in chromatin regions denoted by typical or super enhancers and active markers, including histone H3K27ac and H3K4me1. Additionally, these contacts are highly enriched at loci bound by host transcription factors that regulate B cell growth (e.g., IKZF1 and RUNX3), factors that enhance cell proliferation (e.g., HDGF), or factors that promote viral replication (e.g., NBS1 and NFIC). EBV contacts show nearly 2-fold enrichment in host regions bound by EBV nuclear antigen 2 (EBNA2) and EBNA3 transcription factors. Circular chromosome conformation capture followed by sequencing (4C-seq) using the EBV origin of plasmid replication (oriP) as a "bait" in lymphoblastoid cells further confirmed contacts with active chromatin regions. Collectively, our analysis supports interactions between EBV episome(s) and active regions of the human genome in lymphoblastoid cells.IMPORTANCE EBV is associated with ∼200,000 cancers each year. In vitro, EBV can transform primary human B lymphocytes into immortalized cell lines. EBV-encoded proteins, along with noncoding RNAs and microRNAs, hijack cellular proteins and pathways to control cell growth. EBV nuclear proteins usurp normal transcriptional programs to activate the expression of key oncogenes, including MYC, to provide a proliferation signal. EBV nuclear antigens also repress CDKN2A to suppress senescence. EBV membrane protein activates NF-κB to provide survival signals. EBV genomes are maintained by EBNA1, which tethers EBV episomes to the host chromosomes during mitosis. However, little is known about where EBV episomes are located in interphase cells. In interphase cells, EBV promoters drive the expression of latency genes, while oriP functions as an enhancer for these promoters. In this study, integrative analyses of published lymphoblastoid cell line (LCL) Hi-C data and our 4C-seq experiments position EBV episomes to host genomes with active epigenetic marks. These contact points were significantly enriched for super enhancers. The close proximity of EBV episomes and the super enhancers that are enriched for transcription cofactors or mediators in lymphoblasts may benefit EBV gene expression, suggesting a novel mechanism of transcriptional activation.

Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale.

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.

Dynamic Scan Procedure for Detecting Rare-Variant Association Regions in Whole-Genome Sequencing Studies.

Whole-genome sequencing (WGS) studies are being widely conducted in order to identify rare variants associated with human diseases and disease-related traits. Classical single-marker association analyses for rare variants have limited power, and variant-set-based analyses are commonly used by researchers for analyzing rare variants. However, existing variant-set-based approaches need to pre-specify genetic regions for analysis; hence, they are not directly applicable to WGS data because of the large number of intergenic and intron regions that consist of a massive number of non-coding variants. The commonly used sliding-window method requires the pre-specification of fixed window sizes, which are often unknown as a priori, are difficult to specify in practice, and are subject to limitations given that the sizes of genetic-association regions are likely to vary across the genome and phenotypes. We propose a computationally efficient and dynamic scan-statistic method (Scan the Genome [SCANG]) for analyzing WGS data; this method flexibly detects the sizes and the locations of rare-variant association regions without the need to specify a prior, fixed window size. The proposed method controls for the genome-wise type I error rate and accounts for the linkage disequilibrium among genetic variants. It allows the detected sizes of rare-variant association regions to vary across the genome. Through extensive simulated studies that consider a wide variety of scenarios, we show that SCANG substantially outperforms several alternative methods for detecting rare-variant-associations while controlling for the genome-wise type I error rates. We illustrate SCANG by analyzing the WGS lipids data from the Atherosclerosis Risk in Communities (ARIC) study.

Haemophilus parasuis Infection Disrupts Adherens Junctions and Initializes EMT Dependent on Canonical Wnt/ß-Catenin Signaling Pathway.

In this study, animal experimentation verified that the canonical Wnt/ß-catenin signaling pathway was activated under a reduced activity of p-ß-catenin (Ser33/37/Thr41) and an increased accumulation of ß-catenin in the lungs and kidneys of pigs infected with a highly virulent strain of H. parasuis. In PK-15 and NPTr cells, it was also confirmed that infection with a high-virulence strain of H. parasuis induced cytoplasmic accumulation and nuclear translocation of ß-catenin. H. parasuis infection caused a sharp degradation of E-cadherin and an increase of the epithelial cell monolayer permeability, as well as a broken interaction between ß-catenin and E-cadherin dependent on Wnt/ß-catenin signaling pathway. Moreover, Wnt/ß-catenin signaling pathway also contributed to the initiation of epithelial-mesenchymal transition (EMT) during high-virulence strain of H. parasuis infection with expression changes of epithelial/mesenchymal markers, increased migratory capabilities as well as the morphologically spindle-like switch in PK-15 and NPTr cells. Therefore, we originally speculated that H. parasuis infection activates the canonical Wnt/ß-catenin signaling pathway leading to a disruption of the epithelial barrier, altering cell structure and increasing cell migration, which results in severe acute systemic infection characterized by fibrinous polyserositis during H. parasuis infection.

Epstein-Barr Virus Nuclear Antigen Leader Protein Coactivates EP300.

Epstein-Barr virus nuclear antigen (EBNA) leader protein (EBNALP) is one of the first viral genes expressed upon B-cell infection. EBNALP is essential for EBV-mediated B-cell immortalization. EBNALP is thought to function primarily by coactivating EBNA2-mediated transcription. Chromatin immune precipitation followed by deep sequencing (ChIP-seq) studies highlight that EBNALP frequently cooccupies DNA sites with host cell transcription factors (TFs), in particular, EP300, implicating a broader role in transcription regulation. In this study, we investigated the mechanisms of EBNALP transcription coactivation through EP300. EBNALP greatly enhanced EP300 transcription activation when EP300 was tethered to a promoter. EBNALP coimmunoprecipitated endogenous EP300 from lymphoblastoid cell lines (LCLs). EBNALP W repeat serine residues 34, 36, and 63 were required for EP300 association and coactivation. Deletion of the EP300 histone acetyltransferase (HAT) domain greatly reduced EBNALP coactivation and abolished the EBNALP association. An EP300 bromodomain inhibitor also abolished EBNALP coactivation and blocked the EP300 association with EBNALP. EBNALP sites cooccupied by EP300 had significantly higher ChIP-seq signals for sequence-specific TFs, including SPI1, RelA, EBF1, IRF4, BATF, and PAX5. EBNALP- and EP300-cooccurring sites also had much higher H3K4me1 and H3K27ac signals, indicative of activated enhancers. EBNALP-only sites had much higher signals for DNA looping factors, including CTCF and RAD21. EBNALP coactivated reporters under the control of NF-κB or SPI1. EP300 inhibition abolished EBNALP coactivation of these reporters. Clustered regularly interspaced short palindromic repeat interference targeting of EBNALP enhancer sites significantly reduced target gene expression, including that of EP300 itself. These data suggest a previously unrecognized mechanism by which EBNALP coactivates transcription through subverting of EP300 and thus affects the expression of LCL genes regulated by a broad range of host TFs.IMPORTANCE Epstein-Barr virus was the first human DNA tumor virus discovered over 50 years ago. EBV is causally linked to ∼200,000 human malignancies annually. These cancers include endemic Burkitt lymphoma, Hodgkin lymphoma, lymphoma/lymphoproliferative disease in transplant recipients or HIV-infected people, nasopharyngeal carcinoma, and ∼10% of gastric carcinoma cases. EBV-immortalized human B cells faithfully model key aspects of EBV lymphoproliferative diseases and are useful models of EBV oncogenesis. EBNALP is essential for EBV to transform B cells and transcriptionally coactivates EBNA2 by removing repressors from EBNA2-bound DNA sites. Here, we found that EBNALP can also modulate the activity of the key transcription activator EP300, an acetyltransferase that activates a broad range of transcription factors. Our data suggest that EBNALP regulates a much broader range of host genes than was previously appreciated. A small-molecule inhibitor of EP300 abolished EBNALP coactivation of multiple target genes. These findings suggest novel therapeutic approaches to control EBV-associated lymphoproliferative diseases.

Haemophilus parasuis infection activates NOD1/2-RIP2 signaling pathway in PK-15 cells.

Haemophilus parasuis, an important swine pathogen, was recently proven able to invade into endothelial or epithelial cell in vitro. NOD1/2 are specialized NLRs that participate in the recognition of pathogens able to invade intracellularly and therefore, we assessed that the contribution of NOD1/2 to inflammation responses during H. parasuis infection. We observed that H. parasuis infection enhanced NOD2 expression and RIP2 phosphorylation in porcine kidney 15 cells. Our results also showed that knock down of NOD1/2 or RIP2 expression respectively significantly decreased H. parasuis-induced NF-κB activity, while the phosphorylation level of p38, JNK or ERK was not changed. Moreover, real-time PCR result showed that NOD1, NOD2 or RIP2 was involved in the expression of CCL4, CCL5 and IL-8. Inhibition of NOD1 and NOD2 significantly reduced CCL5 promoter activity, even in a more effective way compared with inhibition of TLR.

The Epstein-Barr Virus Regulome in Lymphoblastoid Cells.

Epstein-Barr virus (EBV) transforms B cells to continuously proliferating lymphoblastoid cell lines (LCLs), which represent an experimental model for EBV-associated cancers. EBV nuclear antigens (EBNAs) and LMP1 are EBV transcriptional regulators that are essential for LCL establishment, proliferation, and survival. Starting with the 3D genome organization map of LCL, we constructed a comprehensive EBV regulome encompassing 1,992 viral/cellular genes and enhancers. Approximately 30% of genes essential for LCL growth were linked to EBV enhancers. Deleting EBNA2 sites significantly reduced their target gene expression. Additional EBV super-enhancer (ESE) targets included MCL1, IRF4, and EBF. MYC ESE looping to the transcriptional stat site of MYC was dependent on EBNAs. Deleting MYC ESEs greatly reduced MYC expression and LCL growth. EBNA3A/3C altered CDKN2A/B spatial organization to suppress senescence. EZH2 inhibition decreased the looping at the CDKN2A/B loci and reduced LCL growth. This study provides a comprehensive view of the spatial organization of chromatin during EBV-driven cellular transformation.

Nasopharyngeal carcinoma super-enhancer-driven ETV6 correlates with prognosis.

Nasopharyngeal carcinoma (NPC) most frequently occurs in southern China and southeast Asia. Epidemiology studies link NPC to genetic predisposition, Epstein-Barr virus (EBV) infection, and environmental factors. Genetic studies indicate that mutations in chromatin-modifying enzymes are the most frequent genetic alterations in NPC. Here, we used H3K27ac chromatin immune precipitation followed by deep sequencing (ChIP-seq) to define the NPC epigenome in primary NPC biopsies, NPC xenografts, and an NPC cell line, and compared them to immortalized normal nasopharyngeal or oral epithelial cells. We identified NPC-specific enhancers and found these enhancers were enriched with nuclear factor κB (NF-κB), IFN-responsive factor 1 (IRF1) and IRF2, and ETS family members ETS1 motifs. Normal cell-specific enhancers were enriched with basic leucine zipper family members and TP53 motifs. NPC super-enhancers with extraordinarily broad and high H3K27ac signals were also identified, and they were linked to genes important for oncogenesis including ETV6. ETV6 was also highly expressed in NPC biopsies by immunohistochemistry. High ETV6 expression correlated with a poor prognosis. Furthermore, we defined the EBV episome epigenetic landscapes in primary NPC tissue.

Identification of a nucleoside analog active against adenosine kinase-expressing plasma cell malignancies.

Primary effusion lymphoma (PEL) is a largely incurable malignancy of B cell origin with plasmacytic differentiation. Here, we report the identification of a highly effective inhibitor of PEL. This compound, 6-ethylthioinosine (6-ETI), is a nucleoside analog with toxicity to PEL in vitro and in vivo, but not to other lymphoma cell lines tested. We developed and performed resistome analysis, an unbiased approach based on RNA sequencing of resistant subclones, to discover the molecular mechanisms of sensitivity. We found different adenosine kinase-inactivating (ADK-inactivating) alterations in all resistant clones and determined that ADK is required to phosphorylate and activate 6-ETI. Further, we observed that 6-ETI induces ATP depletion and cell death accompanied by S phase arrest and DNA damage only in ADK-expressing cells. Immunohistochemistry for ADK served as a biomarker approach to identify 6-ETI-sensitive tumors, which we documented for other lymphoid malignancies with plasmacytic features. Notably, multiple myeloma (MM) expresses high levels of ADK, and 6-ETI was toxic to MM cell lines and primary specimens and had a robust antitumor effect in a disseminated MM mouse model. Several nucleoside analogs are effective in treating leukemias and T cell lymphomas, and 6-ETI may fill this niche for the treatment of PEL, plasmablastic lymphoma, MM, and other ADK-expressing cancers.

Mouse model of Epstein-Barr virus LMP1- and LMP2A-driven germinal center B-cell lymphoproliferative disease.

Epstein-Barr virus (EBV) is a major cause of immunosuppression-related B-cell lymphomas and Hodgkin lymphoma (HL). In these malignancies, EBV latent membrane protein 1 (LMP1) and LMP2A provide infected B cells with surrogate CD40 and B-cell receptor growth and survival signals. To gain insights into their synergistic in vivo roles in germinal center (GC) B cells, from which most EBV-driven lymphomas arise, we generated a mouse model with conditional GC B-cell LMP1 and LMP2A coexpression. LMP1 and LMP2A had limited effects in immunocompetent mice. However, upon T- and NK-cell depletion, LMP1/2A caused massive plasmablast outgrowth, organ damage, and death. RNA-sequencing analyses identified EBV oncoprotein effects on GC B-cell target genes, including up-regulation of multiple proinflammatory chemokines and master regulators of plasma cell differentiation. LMP1/2A coexpression also up-regulated key HL markers, including CD30 and mixed hematopoietic lineage markers. Collectively, our results highlight synergistic EBV membrane oncoprotein effects on GC B cells and provide a model for studies of their roles in immunosuppression-related lymphoproliferative diseases.