To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non‐demented controls, we investigated global disruptions in the co‐regulation of genes in two neurodegenerative diseases, late‐onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co‐expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242‐gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter‐connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A , of which we predicted the former but not latter as a key regulator. To validate the inter‐connection of these two processes and our key regulator prediction, we generated two brain‐specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork ( P = 3.1 × 10 ⁻¹² ), while Dnmt3a KO signature does not ( P = 0.017).

Chronic Obstructive Pulmonary Disease (COPD) is a complex disease. Genetic, epigenetic, and environmental factors are known to contribute to COPD risk and disease progression. Therefore we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity. EPAS1 is distinct in comparison with other key regulators in terms of methylation profile and downstream target genes. Genes predicted to be regulated by EPAS1 were enriched for biological processes including signaling, cell communications, and system development. We confirmed that EPAS1 protein levels are lower in human COPD lung tissue compared to non-disease controls and that Epas1 gene expression is reduced in mice chronically exposed to cigarette smoke. As EPAS1 downstream genes were significantly enriched for hypoxia responsive genes in endothelial cells, we tested EPAS1 function in human endothelial cells. EPAS1 knockdown by siRNA in endothelial cells impacted genes that significantly overlapped with EPAS1 downstream genes in lung tissue including hypoxia responsive genes, and genes associated with emphysema severity. Our first integrative analysis of genome-wide DNA methylation and gene expression profiles illustrates that not only does DNA methylation play a ‘causal’ role in the molecular pathophysiology of COPD, but it can be leveraged to directly identify novel key mediators of this pathophysiology. Chronic Obstructive Pulmonary Disease (COPD) is a common lung disease. It is the fourth leading cause of death in the world and is expected to be the third by 2020. COPD is a heterogeneous and complex disease consisting of obstruction in the small airways, emphysema, and chronic bronchitis. COPD is generally caused by exposure to noxious particles or gases, most commonly from cigarette smoking. However, only 20–25% of smokers develop clinically significant airflow obstruction. Smoking is known to cause epigenetic changes in lung tissues. Thus, genetics, epigenetic, and their interaction with environmental factors play an important role in COPD pathogenesis and progression. Currently, there are no therapeutics that can reverse COPD progression. In order to identify new targets that may lead to the development of therapeutics for curing COPD, we developed a systematic approach to identify key regulators of COPD that integrates genome-wide DNA methylation, gene expression, and phenotype data in lung tissue from COPD and control samples. Our integrative analysis identified 126 key regulators of COPD. We identified EPAS1 as the only key regulator whose downstream genes significantly overlapped with multiple genes sets associated with COPD disease severity.

Oligodendrocytes derive from progenitors (OPCs) through the interplay of epigenomic and transcriptional events. By integrating high-resolution methylomics, RNA-sequencing, and multiple transgenic lines, this study defines the role of DNMT1 in developmental myelination. We detected hypermethylation of genes related to cell cycle and neurogenesis during differentiation of OPCs, yet genetic ablation of Dnmt1 resulted in inefficient OPC expansion and severe hypomyelination associated with ataxia and tremors in mice. This phenotype was not caused by lineage switch or massive apoptosis but was characterized by a profound defect of differentiation associated with changes in exon-skipping and intron-retention splicing events and by the activation of an endoplasmic reticulum stress response. Therefore, loss of Dnmt1 in OPCs is not sufficient to induce a lineage switch but acts as an important determinant of the coordination between RNA splicing and protein synthesis necessary for myelin formation.

Chronic hepatitis B virus (HBV) infection leads to liver fibrosis, which is a major risk factor in hepatocellular carcinoma (HCC) and an independent risk factor of recurrence after HCC tumor resection. The HBV genome can be inserted into the human genome, and chronic inflammation may trigger somatic mutations. However, how HBV integration and other genomic changes contribute to the risk of tumor recurrence with regards to the different degree of liver fibrosis is not clearly understood. We sequenced mRNAs of 21 pairs of tumor and distant non-neoplastic liver tissues of HBV-HCC patients and performed comprehensive genomic analyses of our RNAseq data and public available HBV-HCC sequencing data. We developed a robust pipeline for sensitively identifying HBV integration sites based on sequencing data. Simulations showed that our method outperformed existing methods. Applying it to our data, 374 and 106 HBV host genes were identified in non-neoplastic liver and tumor tissues, respectively. When applying it to other RNA sequencing datasets, consistently more HBV integrations were identified in non-neoplastic liver than in tumor tissues. HBV host genes identified in non-neoplastic liver samples significantly overlapped with known tumor suppressor genes. More significant enrichment of tumor suppressor genes was observed among HBV host genes identified from patients with tumor recurrence, indicating the potential risk of tumor recurrence driven by HBV integration in non-neoplastic liver tissues. We also compared SNPs of each sample with SNPs in a cancer census database and inferred samples’ pathogenic SNP loads. Pathogenic SNP loads in non-neoplastic liver tissues were consistently higher than those in normal liver tissues. Additionally, HBV host genes identified in non-neoplastic liver tissues significantly overlapped with pathogenic somatic mutations, suggesting that HBV integration and somatic mutations targeting the same set of genes are important to tumorigenesis. HBV integrations and pathogenic mutations showed distinct patterns between low and high liver fibrosis patients with regards to tumor recurrence. The results suggest that HBV integrations and pathogenic SNPs in non-neoplastic tissues are important for tumorigenesis and different recurrence risk models are needed for patients with low and high degrees of liver fibrosis.