Tao, Ran

Abstract Medulloblastoma (MB) is a highly malignant childhood brain tumor comprising a collection of molecularly and clinically distinct entities. Mutations in chromatin-modifying genes distribute across subgroups and account for nearly half of all MBs. However, the molecular consequences of chromatin modifier alterations remain poorly understood. Herein, we characterize the chromatin landscape of fifty-two primary MBs representing each MB subgroup using chromatin immunoprecipitation followed by sequencing (ChIP-seq) for six histone marks and perform multi-layered integration with somatic genetics, genome-wide DNA methylation, and transcriptomic datasets extracted from the same tumors. Analysis of differential chromatin states across MB subgroups identified significant enrichment of a bivalent enhancer state (EnhBiv) in Group 4 MB. Group 4-specific EnhBivs mapped to promoters of key neurodevelopmental genes and transcription factors and was associated with increased DNA methylation and reduced expression. In accordance with higher EnhBivs coverage in Group 4 MB, we found that KDM2B, a H3K4me3 and H3K36me2 demethylase, is highly expressed in Group 4 MBs and patient-derived xenografts (PDXs). KDM2B knockout mediated by CRISPR targeting suppressed growth of both Group 3 MB cell lines in vitro and Group 4 MB PDXs in vivo but had no effect on control SHH-MB cells, suggesting that KDM2B is a novel selective dependency in MB. Knockout of KDM2B in MB cells induced profound upregulation of PRC2 targets, genes regulated by bivalent histone marks, as well as genes involved in neuronal differentiation. Further biochemical and molecular studies demonstrated that KDM2B interacts with PRC2 complex subunits and occupies gene promoters associated with Group 4-specific EnhBiv chromatin. In summary, our comprehensive characterization of the MB chromatin landscape in a large cohort of primary tumors provides novel insights into the epigenetic basis of MB and implicates KDM2B as a novel Group 4 MB dependency that should be prioritized as a therapeutic target in this subgroup.

AbstractBackground:The role of methylation in pancreatic cancer risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpG) with the genetically predicted methylation to be associated with pancreatic cancer risk. We also studied gene expression to understand the identified associations.Methods:Using genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 pancreatic cancer cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with pancreatic cancer risk. For associated CpGs, we compared their measured levels in pancreatic tumor versus benign tissue.Results:We identified 45 CpGs at nine loci showing an association with pancreatic cancer risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with pancreatic cancer risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.Conclusions:We identified methylation biomarker candidates associated with pancreatic cancer using genetic instruments and added additional insights into the role of methylation in regulating gene expression in pancreatic cancer development.Impact:A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for pancreatic cancer risk.

Several loci have been discovered and replicated for urine albumin-creatinine ratio (ACR), a measure of kidney function, in European populations; however, other ethnic populations such as African-Americans have been less studied for this trait. We examined the association of genetic variants on the Metabochip with natural log transformed ACR (ln(ACR)) in 4,629 African-Americans from the Population Architecture using Genomics and Epidemiology (PAGE) Study which includes participants from the Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Coronary Artery Risk Development in Young Adults (CARDIA), and Epidemiologic Architecture for Genes Linked to the Environment (EAGLE-BioVU) studies. We then replicated our findings in 1,533 African-American participants from the Multi-Ethnic Study of Atherosclerosis (MESA). Linear regression models were used to examine associations, assuming additive effects of the SNPs. Within each study, models were adjusted for age, field center (where applicable), and principal components of ancestry, and stratified by sex. Fixed effects inverse variance weighted meta-analysis was used to combine results from contributing studies. Array-wide statistical significance was concluded for SNP associations of p-value less than 2.8 x 10-7. Mean ln(ACR) ranged from 1.4 to 2.9 mg/g, average age ranged from 44 to 77 years, and percent female participants ranged from 59-65% in the contributing studies. Four SNPs were significantly associated array-wide with ACR in the discovery sample: rs17399841 in GRHL2 (β=-0.67, MAF=0.01, p=2.7x10-9), rs153914 near SPATA9/RHOBTB3 (β=-0.59, MAF=0.01, p=1.0x10-7), rs17439845 in LEF1 (β=-0.49, MAF=0.02, p=1.3x10-7), and rs11836243 near ZNF641/ANP32D (β=0.23, MAF=0.12, p=1.8x10-7). Of these four loci, only the association of rs17439845 with ACR replicated in MESA (β=-0.36, p=0.038), with a combined discovery-replication beta of -0.46 and p value of 1.8x10-8. Combined discovery-replication for rs17399841, rs153914, and rs11836243 no longer achieved array-wide significance (p-values 9.84x10-7, 1.98x10-5, and 1.32x10-4, respectively). LEF1 is a mediator in the Wnt signaling pathway, and has been previously implicated in systemic lupus erythematosus and osteoporosis, as well as previously associated with waist circumference, echocardiographic traits, bone mineral density, and blood count traits. Continuing studies in diverse populations are warranted to identify a set of loci important in contributing to the variation in ACR.

INTRODUCTION The human cerebral cortex has undergone an extraordinary increase in size and complexity during mammalian evolution. Cortical cell lineages are specified in the embryo, and genetic and epidemiological evidence implicates early cortical development in the etiology of neuropsychiatric disorders such as autism spectrum disorder (ASD), intellectual disabilities, and schizophrenia. Most of the disease-implicated genomic variants are located outside of genes, and the interpretation of noncoding mutations is lagging behind owing to limited annotation of functional elements in the noncoding genome. RATIONALE We set out to discover gene-regulatory elements and chart their dynamic activity during prenatal human cortical development, focusing on enhancers, which carry most of the weight upon regulation of gene expression. We longitudinally modeled human brain development using human induced pluripotent stem cell (hiPSC)–derived cortical organoids and compared organoids to isogenic fetal brain tissue. RESULTS Fetal fibroblast–derived hiPSC lines were used to generate cortically patterned organoids and to compare oganoids’ epigenome and transcriptome to that of isogenic fetal brains and external datasets. Organoids model cortical development between 5 and 16 postconception weeks, thus enabling us to study transitions from cortical stem cells to progenitors to early neurons. The greatest changes occur at the transition from stem cells to progenitors. The regulatory landscape encompasses a total set of 96,375 enhancers linked to target genes, with 49,640 enhancers being active in organoids but not in mid-fetal brain, suggesting major roles in cortical neuron specification. Enhancers that gained activity in the human lineage are active in the earliest stages of organoid development, when they target genes that regulate the growth of radial glial cells. Parallel weighted gene coexpression network analysis (WGCNA) of transcriptome and enhancer activities defined a number of modules of coexpressed genes and coactive enhancers, following just six and four global temporal patterns that we refer to as supermodules, likely reflecting fundamental programs in embryonic and fetal brain. Correlations between gene expression and enhancer activity allowed stratifying enhancers into two categories: activating regulators (A-regs) and repressive regulators (R-regs). Several enhancer modules converged with gene modules, suggesting that coexpressed genes are regulated by enhancers with correlated patterns of activity. Furthermore, enhancers active in organoids and fetal brains were enriched for ASD de novo variants that disrupt binding sites of homeodomain, Hes1, NR4A2, Sox3, and NFIX transcription factors. CONCLUSION We validated hiPSC-derived cortical organoids as a suitable model system for studying gene regulation in human embryonic brain development, evolution, and disease. Our results suggest that organoids may reveal how noncoding mutations contribute to ASD etiology. Summary of the study, analyses, and main results. Data were generated for iPSC-derived human telencephalic organoids and isogenic fetal cortex. Organoids modeled embryonic and early fetal cortex and show a larger repertoire of enhancers. Enhancers could be divided into activators and repressors of gene expression. We derived networks of modules and supermodules with correlated gene and enhancer activities, some of which were implicated in autism spectrum disorders (ASD).