Ovarian Cancer Risk Variants Are Enriched in Histotype-Specific Enhancers and Disrupt Transcription Factor Binding Sites.

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome-wide association studies have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, where they likely function through interaction with gene regulatory elements. In this study we first estimated the heritability explained by known common low penetrance risk alleles for EOC. The narrow sense heritability (hg2) of EOC overall and high-grade serous ovarian cancer (HGSOCs) were estimated to be 5%-6%. Partitioned SNP heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from Roadmap Epigenomics and ENCODE, and from H3K27Ac ChIP-seq data generated in 26 ovarian cancer and precursor-related cell and tissue types. We identified significant enrichment of risk single-nucleotide polymorphisms (SNPs) in active regulatory elements marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active regulatory elements influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that are predicted to significantly break transcription factor (TF) motifs. The most frequently broken motif was REST (p value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. Overall, these systematic functional annotations with epigenomic data improve interpretation of EOC risk variants and shed light on likely cells of origin.

US Severe Acute Respiratory Syndrome Coronavirus 2 Epsilon Variant: Highly Transmissible but With an Adjusted Muted Host T-Cell Response.

BACKGROUND: The multiple mutations comprising the epsilon variant demonstrate the independent convergent evolution of severe acute respiratory syndrome coronavirus (SARS-CoV-2), with its spike protein mutation L452R present in the delta (L452R), kappa (L452R), and lambda (L452Q) variants. METHODS: Coronavirus disease 2019 (COVID-19) variants were detected in 1017 patients using whole-genome sequencing and were assessed for outcome and severity. The mechanistic effects of the epsilon versus non-epsilon variants were investigated using a multiomic approach including cellular response assays and paired cell and host transcriptomic and proteomic profiling. RESULTS: We found that patients carrying the epsilon variant had increased mortality risk but not increased hospitalizations (P < .02). Cells infected with live epsilon compared with non-epsilon virus displayed increased sensitivity to neutralization antibodies in all patients but a slightly protective response in vaccinated individuals (P < .001). That the epsilon SARS-CoV-2 variant is more infectious but less virulent is supported mechanistically in the down-regulation of viral processing pathways seen by multiomic analyses. Importantly, this paired transcriptomics and proteomic profiling of host cellular response to live virus revealed an altered leukocyte response and metabolic messenger RNA processing with the epsilon variant. To ascertain host response to SARS-CoV-2 infection, primary COVID-19-positive nasopharyngeal samples were transcriptomically profiled and revealed a differential innate immune response (P < .001) and an adjusted T-cell response in patients carrying the epsilon variant (P < .002). In fact, patients infected with SARS-CoV-2 and those vaccinated with the BNT162b2 vaccine have comparable CD4+/CD8+ T-cell immune responses to the epsilon variant (P < .05). CONCLUSIONS: While the epsilon variant is more infectious, by altering viral processing, we showed that patients with COVID-19 have adapted their innate immune response to this fitter variant. A protective T-cell response molecular signature is generated by this more transmissible variant in both vaccinated and unvaccinated patients.

Evidence of disrupted rhombic lip development in the pathogenesis of Dandy-Walker malformation.

Dandy-Walker malformation (DWM) and Cerebellar vermis hypoplasia (CVH) are commonly recognized human cerebellar malformations diagnosed following ultrasound and antenatal or postnatal MRI. Specific radiological criteria are used to distinguish them, yet little is known about their differential developmental disease mechanisms. We acquired prenatal cases diagnosed as DWM and CVH and studied cerebellar morphobiometry followed by histological and immunohistochemical analyses. This was supplemented by laser capture microdissection and RNA-sequencing of the cerebellar rhombic lip, a transient progenitor zone, to assess the altered transcriptome of DWM vs control samples. Our radiological findings confirm that the cases studied fall within the accepted biometric range of DWM. Our histopathological analysis points to reduced foliation and inferior vermian hypoplasia as common features in all examined DWM cases. We also find that the rhombic lip, a dorsal stem cell zone that drives the growth and maintenance of the posterior vermis is specifically disrupted in DWM, with reduced proliferation and self-renewal of the progenitor pool, and altered vasculature, all confirmed by transcriptomics analysis. We propose a unified model for the developmental pathogenesis of DWM. We hypothesize that rhombic lip development is disrupted through either aberrant vascularization and/or direct insult which causes reduced proliferation and failed expansion of the rhombic lip progenitor pool leading to disproportionate hypoplasia and dysplasia of the inferior vermis. Timing of insult to the developing rhombic lip (before or after 14 PCW) dictates the extent of hypoplasia and distinguishes DWM from CVH.

GENAVi: a shiny web application for gene expression normalization, analysis and visualization.

BACKGROUND: The development of next generation sequencing (NGS) methods led to a rapid rise in the generation of large genomic datasets, but the development of user-friendly tools to analyze and visualize these datasets has not developed at the same pace. This presents a two-fold challenge to biologists; the expertise to select an appropriate data analysis pipeline, and the need for bioinformatics or programming skills to apply this pipeline. The development of graphical user interface (GUI) applications hosted on web-based servers such as Shiny can make complex workflows accessible across operating systems and internet browsers to those without programming knowledge. RESULTS: We have developed GENAVi (Gene Expression Normalization Analysis and Visualization) to provide a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. GENAVi is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. We provide a panel of 20 cell lines commonly used for the study of breast and ovarian cancer within GENAVi as a foundation for users to bring their own data to the application. Users can visualize expression across samples, cluster samples based on gene expression or correlation, calculate and plot the results of principal components analysis, perform DEA and gene set enrichment and produce plots for each of these analyses. To allow scalability for large datasets we have provided local install via three methods. We improve on available tools by offering a range of normalization methods and a simple to use interface that provides clear and complete session reporting and for reproducible analysis. CONCLUSION: The development of tools using a GUI makes them practical and accessible to scientists without bioinformatics expertise, or access to a data analyst with relevant skills. While several GUI based tools are currently available for RNA-Seq analysis we improve on these existing tools. This user-friendly application provides a convenient platform for the normalization, analysis and visualization of gene expression data for scientists without bioinformatics expertise.

Challenges and Opportunities in Building a Global Representative Single-Cell and Spatial Atlas in Cancer.

SUMMARY: Cancer health disparities are complex and a mixture of factors that need to be accounted for in both our planning, implementation, and execution across all researchers, especially in single-cell and spatial technologies, which have a higher burden for adoption in low- and middle-income countries. This commentary tackles the hurdles these technologies face in creating a diverse, representative atlas of cancer and is a call to arms for a strategic plan toward inclusivity across all global populations.

Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer's disease.

Human middle temporal gyrus (MTG) is a vulnerable brain region in early Alzheimer's disease (AD), but little is known about the molecular mechanisms underlying this regional vulnerability. Here we utilize the 10 × Visium platform to define the spatial transcriptomic profile in both AD and control (CT) MTG. We identify unique marker genes for cortical layers and the white matter, and layer-specific differentially expressed genes (DEGs) in human AD compared to CT. Deconvolution of the Visium spots showcases the significant difference in particular cell types among cortical layers and the white matter. Gene co-expression analyses reveal eight gene modules, four of which have significantly altered co-expression patterns in the presence of AD pathology. The co-expression patterns of hub genes and enriched pathways in the presence of AD pathology indicate an important role of cell-cell-communications among microglia, oligodendrocytes, astrocytes, and neurons, which may contribute to the cellular and regional vulnerability in early AD. Using single-molecule fluorescent in situ hybridization, we validated the cell-type-specific expression of three novel DEGs (e.g., KIF5A, PAQR6, and SLC1A3) and eleven previously reported DEGs associated with AD pathology (i.e., amyloid beta plaques and intraneuronal neurofibrillary tangles or neuropil threads) at the single cell level. Our results may contribute to the understanding of the complex architecture and neuronal and glial response to AD pathology of this vulnerable brain region.

DNA methylation and transcriptomic features are preserved throughout disease recurrence and chemoresistance in high grade serous ovarian cancers.

BACKGROUND: Little is known about the role of global DNA methylation in recurrence and chemoresistance of high grade serous ovarian cancer (HGSOC). METHODS: We performed whole genome bisulfite sequencing and transcriptome sequencing in 62 primary and recurrent tumors from 28 patients with stage III/IV HGSOC, of which 11 patients carried germline, pathogenic BRCA1 and/or BRCA2 mutations. RESULTS: Landscapes of genome-wide methylation (on average 24.2 million CpGs per tumor) and transcriptomes in primary and recurrent tumors showed extensive heterogeneity between patients but were highly preserved in tumors from the same patient. We identified significant differences in the burden of differentially methylated regions (DMRs) in tumors from BRCA1/2 compared to non-BRCA1/2 carriers (mean 659 DMRs and 388 DMRs in paired comparisons respectively). We identified overexpression of immune pathways in BRCA1/2 carriers compared to non-carriers, implicating an increased immune response in improved survival (P = 0.006) in these BRCA1/2 carriers. CONCLUSION: These findings indicate methylome and gene expression programs established in the primary tumor are conserved throughout disease progression, even after extensive chemotherapy treatment, and that changes in methylation and gene expression are unlikely to serve as drivers for chemoresistance in HGSOC.

Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci.

BACKGROUND: Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort. METHODS: Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types. RESULTS: We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types. CONCLUSIONS: CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

An N-Cadherin 2 expressing epithelial cell subpopulation predicts response to surgery, chemotherapy and immunotherapy in bladder cancer.

Neoadjuvant chemotherapy (NAC) prior to surgery and immune checkpoint therapy (ICT) have revolutionized bladder cancer management. However, stratification of patients that would benefit most from these modalities remains a major clinical challenge. Here, we combine single nuclei RNA sequencing with spatial transcriptomics and single-cell resolution spatial proteomic analysis of human bladder cancer to identify an epithelial subpopulation with therapeutic response prediction ability. These cells express Cadherin 12 (CDH12, N-Cadherin 2), catenins, and other epithelial markers. CDH12-enriched tumors define patients with poor outcome following surgery with or without NAC. In contrast, CDH12-enriched tumors exhibit superior response to ICT. In all settings, patient stratification by tumor CDH12 enrichment offers better prediction of outcome than currently established bladder cancer subtypes. Molecularly, the CDH12 population resembles an undifferentiated state with inherently aggressive biology including chemoresistance, likely mediated through progenitor-like gene expression and fibroblast activation. CDH12-enriched cells express PD-L1 and PD-L2 and co-localize with exhausted T-cells, possibly mediated through CD49a (ITGA1), providing one explanation for ICT efficacy in these tumors. Altogether, this study describes a cancer cell population with an intriguing diametric response to major bladder cancer therapeutics. Importantly, it also provides a compelling framework for designing biomarker-guided clinical trials.

Human iPSC-derived fallopian tube organoids with BRCA1 mutation recapitulate early-stage carcinogenesis.

Germline pathogenic mutations in BReast CAncer (BRCA1) genes are thought to drive normal fallopian tube epithelial (FTE) cell transformation to high-grade serous ovarian cancer. No human models capture the sequence of events for disease initiation and progression. Here, we generate induced pluripotent stem cells (iPSCs) from healthy individuals and young ovarian cancer patients with germline pathogenic BRCA1 mutations (BRCA1mut). Following differentiation into FTE organoids, BRCA1mut lines exhibit cellular abnormalities consistent with neoplastic transformation compared to controls. BRCA1mut organoids show an increased production of cancer-specific proteins and survival following transplantation into mice. Organoids from women with the most aggressive ovarian cancer show the greatest pathology, indicating the potential value to predict clinical severity prior to disease onset. These human FTE organoids from BRCA1mut carriers provide a faithful physiological in vitro model of FTE lesion generation and early carcinogenesis. This platform can be used for personalized mechanistic and drug screening studies.

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer.

Familial, sequencing, and genome-wide association studies (GWASs) and genetic correlation analyses have progressively unraveled the shared or pleiotropic germline genetics of breast and ovarian cancer. In this study, we aimed to leverage this shared germline genetics to improve the power of transcriptome-wide association studies (TWASs) to identify candidate breast cancer and ovarian cancer susceptibility genes. We built gene expression prediction models using the PrediXcan method in 681 breast and 295 ovarian tumors from The Cancer Genome Atlas and 211 breast and 99 ovarian normal tissue samples from the Genotype-Tissue Expression project and integrated these with GWAS meta-analysis data from the Breast Cancer Association Consortium (122,977 cases/105,974 controls) and the Ovarian Cancer Association Consortium (22,406 cases/40,941 controls). The integration was achieved through application of a pleiotropy-guided conditional/conjunction false discovery rate (FDR) approach in the setting of a TWASs. This identified 14 candidate breast cancer susceptibility genes spanning 11 genomic regions and 8 candidate ovarian cancer susceptibility genes spanning 5 genomic regions at conjunction FDR < 0.05 that were >1 Mb away from known breast and/or ovarian cancer susceptibility loci. We also identified 38 candidate breast cancer susceptibility genes and 17 candidate ovarian cancer susceptibility genes at conjunction FDR < 0.05 at known breast and/or ovarian susceptibility loci. The 22 genes identified by our cross-cancer analysis represent promising candidates that further elucidate the role of the transcriptome in mediating germline breast and ovarian cancer risk.

Human iPSC-Derived Cardiomyocytes Are Susceptible to SARS-CoV-2 Infection.

Coronavirus disease 2019 (COVID-19) is a pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is defined by respiratory symptoms, but cardiac complications including viral myocarditis are also prevalent. Although ischemic and inflammatory responses caused by COVID-19 can detrimentally affect cardiac function, the direct impact of SARS-CoV-2 infection on human cardiomyocytes is not well understood. Here, we utilize human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) as a model to examine the mechanisms of cardiomyocyte-specific infection by SARS-CoV-2. Microscopy and RNA sequencing demonstrate that SARS-CoV-2 can enter hiPSC-CMs via ACE2. Viral replication and cytopathic effect induce hiPSC-CM apoptosis and cessation of beating after 72 h of infection. SARS-CoV-2 infection activates innate immune response and antiviral clearance gene pathways, while inhibiting metabolic pathways and suppressing ACE2 expression. These studies show that SARS-CoV-2 can infect hiPSC-CMs in vitro, establishing a model for elucidating infection mechanisms and potentially a cardiac-specific antiviral drug screening platform.

Analysis of Genomic Characteristics and Transmission Routes of Patients With Confirmed SARS-CoV-2 in Southern California During the Early Stage of the US COVID-19 Pandemic.

Importance: In late December 2019, an outbreak of a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China. Data on the routes of transmission to Los Angeles, California, the US West Coast epicenter for coronavirus disease 2019 (COVID-19), and subsequent community spread are limited. Objective: To determine the transmission routes of SARS-CoV-2 to Southern California and elucidate local community spread within the Los Angeles metropolitan area. Design, Setting, and Participants: This case series included 192 consecutive patients with reverse transcription-polymerase chain reaction (RT-PCR) test results positive for SARS-CoV-2 who were evaluated at Cedars-Sinai Medical Center in Los Angeles, California, from March 22 to April 15, 2020. Data analysis was performed from April to May 2020. Main Outcomes and Measures: SARS-CoV-2 viral genomes were sequenced. Los Angeles isolates were compared with genomes from global subsampling and from New York, New York; Washington state; and China to determine potential sources of viral dissemination. Demographic data and outcomes were collected. Results: The cohort included 192 patients (median [interquartile range] age, 59.5 [43-75] years; 110 [57.3%] men). The genetic characterization of SARS-CoV-2 isolates in the Los Angeles population pinpointed community transmission of 13 patients within a 3.81 km2 radius. Variation landscapes of this case series also revealed a cluster of 10 patients that contained 5 residents at a skilled nursing facility, 1 resident of a nearby skilled nursing facility, 3 health care workers, and a family member of a resident of one of the skilled nursing facilities. Person-to-person transmission was detected in a cluster of 5 patients who shared the same single-nucleotide variation in their SARS-CoV-2 genomes. High viral genomic diversity was identified: 20 Los Angeles isolates (15.0%) resembled SARS-CoV-2 genomes from Asia, while 109 Los Angeles isolates (82.0%) were similar to isolates originating from Europe. Analysis of other common respiratory viral pathogens did not reveal coinfection in the cohort. Conclusions and Relevance: These findings highlight the precision of detecting person-to-person transmission and accurate contact tracing directly through SARS-CoV-2 genome isolation and sequencing. Development and application of phylogenetic analyses from the Los Angeles population established connections between COVID-19 clusters locally and throughout the US.

Lineage-Specific Epigenomic and Genomic Activation of Oncogene HNF4A Promotes Gastrointestinal Adenocarcinomas.

Gastrointestinal adenocarcinomas (GIAC) of the tubular gastrointestinal (GI) tract including esophagus, stomach, colon, and rectum comprise most GI cancers and share a spectrum of genomic features. However, the unified epigenomic changes specific to GIAC are poorly characterized. Using 907 GIAC samples from The Cancer Genome Atlas, we applied mathematical algorithms to large-scale DNA methylome and transcriptome profiles to reconstruct transcription factor (TF) networks and identify a list of functionally hyperactive master regulator (MR) TF shared across different GIAC. The top candidate HNF4A exhibited prominent genomic and epigenomic activation in a GIAC-specific manner. A complex interplay between the HNF4A promoter and three distal enhancer elements was coordinated by GIAC-specific MRTF including ELF3, GATA4, GATA6, and KLF5. HNF4A also self-regulated its own promoter and enhancers. Functionally, HNF4A promoted cancer proliferation and survival by transcriptional activation of many downstream targets, including HNF1A and factors of interleukin signaling, in a lineage-specific manner. Overall, our study provides new insights into the GIAC-specific gene regulatory networks and identifies potential therapeutic strategies against these common cancers. SIGNIFICANCE: These findings show that GIAC-specific master regulatory transcription factors control HNF4A via three distal enhancers to promote GIAC cell proliferation and survival. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/13/2722/F1.large.jpg.

The Genetic Intersection of Neurodevelopmental Disorders and Shared Medical Comorbidities - Relations that Translate from Bench to Bedside.

Most psychiatric disorders are considered neurodevelopmental, and the associated genes often are expressed in tissues outside of the brain. This suggests a biological relatedness with medical co-occurrences that could have broad clinical implications for diagnosis and patient management over a lifetime. A qualitative integration of public data from genetic consortia of psychiatric disorders and medical comorbidities explores the question of whether genetically associated psychiatric illnesses present with co-occurring disturbances can be used to define specific mental-physical health relations. Novel patterns of gene-disorder relations appear with approximately one-third of conservatively defined, consortia-generated candidate risk genes with multiple psychiatric diagnoses. Moreover, nearly as many genes overlap with non-psychiatric phenotypes, including cardiovascular, renal, respiratory, and metabolic disturbances. While the landscape of genetic risk will change as study populations are expanded and biological confirmations accrue, the current relationships suggest that a mostly siloed perspective of gene relatedness to one categorical psychiatric diagnosis is not clinically useful. The future holds the promise that once candidates are fully validated, genome screening and mutation identification will bring more precision for predicting the risk for complex health conditions. Our view is that as genetic data are refined, continuing to decipher a shared pattern of genetic risk for brain and peripheral organ pathophysiology is not simply an academic exercise. Rather, determining relatedness will impact predictions of multifaceted health risks, patient treatment, and management.

Comparative DNA methylation among females with neurodevelopmental disorders and seizures identifies TAC1 as a MeCP2 target gene.

BACKGROUND: Several proteins involved in epigenetic regulation cause syndromic neurodevelopmental disorders when human genes are mutated. More general involvement of epigenetic mechanisms in neurodevelopmental phenotypes is unclear. METHODS: In an attempt to determine whether DNA methylation differentiates clinical subgroups, profiling was performed on bisulfite converted DNA from lymphoblastoid cell lines (LCLs) in discovery (n = 20) and replication (n = 40) cohorts of females with Rett syndrome (RTT; n = 18), autism (AUT; n = 17), seizure disorder (SEZ; n = 6), and controls (CTL; n = 19) using Illumina HumanMethylation27 arrays. TAC1 CpGs were validated using a Sequenom EpiTYPER assay and expression was measured in LCLs and postmortem brain. Chromatin immunoprecipitation was performed in HEK cells. Cells were treated with valproic acid and MeCP2 binding was assessed. RESULTS: Two female-only cohorts were analyzed. DNA methylation profiling in a discovery cohort identified 40 CpGs that exhibited statistically significant differential methylation (≥15%) between clinical groups (P <0.01). Hierarchical clustering and principal components analysis suggested neurodevelopmental groups were distinct from CTL, but not from each other. In a larger and more heterogeneous replication cohort, these 40 CpG sites suggested no clear difference between clinical groups. Pooled analysis of DNA methylation across all 60 samples suggested only four differentially methylated CpG sites (P <0.0005), including TAC1. TAC1 promoter CpG hypermethylation was validated in AUT and SEZ (P <0.005). Analyzed for the first time in postmortem brain, TAC1 expression was reduced in cingulate cortex in RTT and AUT+SEZ (P = 0.003). However, no significant difference in TAC1 promoter CpG methylation was detected in RTT and AUT+SEZ brains. Additional molecular analyses revealed that MeCP2 binds directly to the TAC1 promoter and is sensitive to antiepileptic drug treatment. CONCLUSION: These data suggest that DNA methylation is not widely altered in RTT, consistent with subtle changes in gene expression previously observed. However, TAC1 may be an important target for further functional analyses in RTT. Studies of larger sample cohorts using primary cells that also consider shared clinical features and drug treatments may be required to address apparent subtle disruptions of DNA methylation in neurodevelopmental disorders.