Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer.

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

Proteogenomic characterization of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer.

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

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.

Transcriptional Circuitry of NKX2-1 and SOX1 Defines an Unrecognized Lineage Subtype of Small-Cell Lung Cancer.

Rationale: The current molecular classification of small-cell lung cancer (SCLC) on the basis of the expression of four lineage transcription factors still leaves its major subtype SCLC-A as a heterogeneous group, necessitating more precise characterization of lineage subclasses. Objectives: To refine the current SCLC classification with epigenomic profiles and to identify features of the redefined SCLC subtypes. Methods: We performed unsupervised clustering of epigenomic profiles on 25 SCLC cell lines. Functional significance of NKX2-1 (NK2 homeobox 1) was evaluated by cell growth, apoptosis, and xenograft using clustered regularly interspaced short palindromic repeats-Cas9 (CRISPR-associated protein 9)-mediated deletion. NKX2-1-specific cistromic profiles were determined using chromatin immunoprecipitation followed by sequencing, and its functional transcriptional partners were determined using coimmunoprecipitation followed by mass spectrometry. Rb1flox/flox; Trp53flox/flox and Rb1flox/flox; Trp53flox/flox; Nkx2-1flox/flox mouse models were engineered to explore the function of Nkx2-1 in SCLC tumorigenesis. Epigenomic landscapes of six human SCLC specimens and 20 tumors from two mouse models were characterized. Measurements and Main Results: We identified two epigenomic subclusters of the major SCLC-A subtype: SCLC-Aα and SCLC-Aσ. SCLC-Aα was characterized by the presence of a super-enhancer at the NKX2-1 locus, which was observed in human SCLC specimens and a murine SCLC model. We found that NKX2-1, a dual lung and neural lineage factor, is uniquely relevant in SCLC-Aα. In addition, we found that maintenance of this neural identity in SCLC-Aα is mediated by collaborative transcriptional activity with another neuronal transcriptional factor, SOX1 (SRY-box transcription factor 1). Conclusions: We comprehensively describe additional epigenomic heterogeneity of the major SCLC-A subtype and define the SCLC-Aα subtype by the core regulatory circuitry of NKX2-1 and SOX1 super-enhancers and their functional collaborations to maintain neuronal linage state.

Global DNA methylation of WTC prostate cancer tissues show signature differences compared to non-exposed cases.

There is increased incidence of prostate cancer (PC) among World Trade Center (WTC)-exposed responders and community members, with preliminary evidence suggestive of more aggressive disease. While previous research is supportive of differences in DNA methylation and gene expression as a consequence of WTC exposure, as measured in blood of healthy individuals, the epigenetics of WTC PC tissues has yet to be explored. Patients were recruited from the World Trade Center Health Program. Non-WTC PC samples were frequency matched on age, race/ethnicity and Gleason score. Bisulfite-treated DNA was extracted from tumor tissue blocks and used to assess global DNA methylation with the MethylationEPIC BeadChip. Differential and pathway enrichment analyses were conducted. RNA from the same tumor blocks was used for gene expression analysis to further support DNA methylation findings. Methylation data were generated for 28 samples (13 WTC and 15 non-WTC). Statistically significant differences in methylation were observed for 3,586 genes; on average WTC samples were statistically significantly more hypermethylated (P = 0.04131). Pathway enrichment analysis revealed hypermethylation in epithelial mesenchymal transition (EMT), hypoxia, mitotic spindle, TNFA signaling via NFKB, WNT signaling, and TGF beta signaling pathways in WTC compared to non-WTC samples. The androgen response, G2M and MYC target pathways were hypomethylated. These results correlated well with RNA gene expression. In conclusion, long-term epigenic changes associated with WTC dust exposure were observed in PC tissues. These occurred in genes of critical pathways, likely increasing prostate tumorigenesis potential. This warrants analysis of larger WTC groups and other cancer types.

Oncogenic role of SFRP2 in p53-mutant osteosarcoma development via autocrine and paracrine mechanism.

Osteosarcoma (OS), the most common primary bone tumor, is highly metastatic with high chemotherapeutic resistance and poor survival rates. Using induced pluripotent stem cells (iPSCs) generated from Li-Fraumeni syndrome (LFS) patients, we investigate an oncogenic role of secreted frizzled-related protein 2 (SFRP2) in p53 mutation-associated OS development. Interestingly, we find that high SFRP2 expression in OS patient samples correlates with poor survival. Systems-level analyses identified that expression of SFRP2 increases during LFS OS development and can induce angiogenesis. Ectopic SFRP2 overexpression in normal osteoblast precursors is sufficient to suppress normal osteoblast differentiation and to promote OS phenotypes through induction of oncogenic molecules such as FOXM1 and CYR61 in a ß-catenin-independent manner. Conversely, inhibition of SFRP2, FOXM1, or CYR61 represses the tumorigenic potential. In summary, these findings demonstrate the oncogenic role of SFRP2 in the development of p53 mutation-associated OS and that inhibition of SFRP2 is a potential therapeutic strategy.

Integrative analysis of DNA methylation and gene expression data identifies EPAS1 as a key regulator of COPD.

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.

A pilot systematic genomic comparison of recurrence risks of hepatitis B virus-associated hepatocellular carcinoma with low- and high-degree liver fibrosis.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Impact of non-neoplastic vs intratumoural hepatitis B viral DNA and replication on hepatocellular carcinoma recurrence.

BACKGROUND: This study aims to determine the impact of intracellular hepatitis B virus (HBV) DNA, covalently closed circular DNA (cccDNA) and viral replicative activity in both tumour and non-neoplastic liver on prognosis and to determine the relationship of viral replicative activity and Ishak fibrosis in predicting outcome following resection. METHODS: A total of 99 prospectively enrolled patients treated with primary liver resection for HBV-HCC are included. Intracellular HBV DNA and cccDNA were quantitated by real-time PCR. The RNA-sequencing (RNA-seq) was performed in a subset of 21 patients who had either minimal liver fibrosis (Ishak stages 0-2) or end-stage fibrosis (Ishak stage 6). RESULTS: Tumour tissue contained a lower cccDNA copy number compared with paired non-neoplastic liver, and larger tumours (>3 cm) had less cccDNA compared with small tumours (⩽3 cm). High viral replicative activity in non-neoplastic liver was associated with higher HCC recurrence rate independent of Ishak fibrosis stage. Genes correlated with viral replicative activity in non-neoplastic liver (620 genes) were distinct from those associated with end-stage fibrosis (1226 genes). Genes associated with viral replicative activity were preferentially distributed in regions on chr3, chr16 and chr19. CONCLUSIONS: Viral replicative activity in non-neoplastic liver is associated with HCC recurrence through mechanisms that are distinct from and independent of Ishak fibrosis stage.

Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.

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).

MODMatcher: multi-omics data matcher for integrative genomic analysis.

Errors in sample annotation or labeling often occur in large-scale genetic or genomic studies and are difficult to avoid completely during data generation and management. For integrative genomic studies, it is critical to identify and correct these errors. Different types of genetic and genomic data are inter-connected by cis-regulations. On that basis, we developed a computational approach, Multi-Omics Data Matcher (MODMatcher), to identify and correct sample labeling errors in multiple types of molecular data, which can be used in further integrative analysis. Our results indicate that inspection of sample annotation and labeling error is an indispensable data quality assurance step. Applied to a large lung genomic study, MODMatcher increased statistically significant genetic associations and genomic correlations by more than two-fold. In a simulation study, MODMatcher provided more robust results by using three types of omics data than two types of omics data. We further demonstrate that MODMatcher can be broadly applied to large genomic data sets containing multiple types of omics data, such as The Cancer Genome Atlas (TCGA) data sets.

SiteComp: a server for ligand binding site analysis in protein structures.

MOTIVATION: Computational characterization of ligand-binding sites in proteins provides preliminary information for functional annotation, protein design and ligand optimization. SiteComp implements binding site analysis for comparison of binding sites, evaluation of residue contribution to binding sites and identification of sub-sites with distinct molecular interaction properties. AVAILABILITY AND IMPLEMENTATION: The SiteComp server and tutorials are freely available at http://sitecomp.sanchezlab.org.

Autophagy enables microglia to engage amyloid plaques and prevents microglial senescence.

Dysfunctional autophagy has been implicated in the pathogenesis of Alzheimer's disease (AD). Previous evidence suggested disruptions of multiple stages of the autophagy-lysosomal pathway in affected neurons. However, whether and how deregulated autophagy in microglia, a cell type with an important link to AD, contributes to AD progression remains elusive. Here we report that autophagy is activated in microglia, particularly of disease-associated microglia surrounding amyloid plaques in AD mouse models. Inhibition of microglial autophagy causes disengagement of microglia from amyloid plaques, suppression of disease-associated microglia, and aggravation of neuropathology in AD mice. Mechanistically, autophagy deficiency promotes senescence-associated microglia as evidenced by reduced proliferation, increased Cdkn1a/p21Cip1, dystrophic morphologies and senescence-associated secretory phenotype. Pharmacological treatment removes autophagy-deficient senescent microglia and alleviates neuropathology in AD mice. Our study demonstrates the protective role of microglial autophagy in regulating the homeostasis of amyloid plaques and preventing senescence; removal of senescent microglia is a promising therapeutic strategy.

HBV genome-enriched single cell sequencing revealed heterogeneity in HBV-driven hepatocellular carcinoma (HCC).

BACKGROUND: Hepatitis B virus (HBV) related hepatocellular carcinoma (HCC) is heterogeneous and frequently contains multifocal tumors, but how the multifocal tumors relate to each other in terms of HBV integration and other genomic patterns is not clear. METHODS: To interrogate heterogeneity of HBV-HCC, we developed a HBV genome enriched single cell sequencing (HGE-scSeq) procedure and a computational method to identify HBV integration sites and infer DNA copy number variations (CNVs). RESULTS: We performed HGE-scSeq on 269 cells from four tumor sites and two tumor thrombi of a HBV-HCC patient. HBV integrations were identified in 142 out of 269 (53%) cells sequenced, and were enriched in two HBV integration hotspots chr1:34,397,059 (CSMD2) and chr8:118,557,327 (MED30/EXT1). There were also 162 rare integration sites. HBV integration sites were enriched in DNA fragile sites and sequences around HBV integration sites were enriched for microhomologous sequences between human and HBV genomes. CNVs were inferred for each individual cell and cells were grouped into four clonal groups based on their CNVs. Cells in different clonal groups had different degrees of HBV integration heterogeneity. All of 269 cells carried chromosome 1q amplification, a recurrent feature of HCC tumors, suggesting that 1q amplification occurred before HBV integration events in this case study. Further, we performed simulation studies to demonstrate that the sequential events (HBV infecting transformed cells) could result in the observed phenotype with biologically reasonable parameters. CONCLUSION: Our HGE-scSeq data reveals high heterogeneity of HCC tumor cells in terms of both HBV integrations and CNVs. There were two HBV integration hotspots across cells, and cells from multiple tumor sites shared some HBV integration and CNV patterns.

Early-Stage Lung Adenocarcinoma MDM2 Genomic Amplification Predicts Clinical Outcome and Response to Targeted Therapy.

Lung cancer is the most common cause of cancer-related deaths in both men and women, accounting for one-quarter of total cancer-related mortality globally. Lung adenocarcinoma is the major subtype of non-small cell lung cancer (NSCLC) and accounts for around 40% of lung cancer cases. Lung adenocarcinoma is a highly heterogeneous disease and patients often display variable histopathological morphology, genetic alterations, and genomic aberrations. Recent advances in transcriptomic and genetic profiling of lung adenocarcinoma by investigators, including our group, has provided better stratification of this heterogeneous disease, which can facilitate devising better treatment strategies suitable for targeted patient cohorts. In a recent study we have shown gene expression profiling identified novel clustering of early stage LUAD patients and correlated with tumor invasiveness and patient survival. In this study, we focused on copy number alterations in LUAD patients. SNP array data identified amplification at chromosome 12q15 on MDM2 locus and protein overexpression in a subclass of LUAD patients with an invasive subtype of the disease. High copy number amplification and protein expression in this subclass correlated with poor overall survival. We hypothesized that MDM2 copy number and overexpression predict response to MDM2-targeted therapy. In vitro functional data on a panel of LUAD cells showed that MDM2-targeted therapy effectively suppresses cell proliferation, migration, and invasion in cells with MDM2 amplification/overexpression but not in cells without MDM2 amplification, independent of p53 status. To determine the key signaling mechanisms, we used RNA sequencing (RNA seq) to examine the response to therapy in MDM2-amplified/overexpressing p53 mutant and wild-type LUAD cells. RNA seq data shows that in MDM2-amplified/overexpression with p53 wild-type condition, the E2F → PEG10 → MMPs pathway is operative, while in p53 mutant genetic background, MDM2-targeted therapy abrogates tumor progression in LUAD cells by suppressing epithelial to mesenchymal transition (EMT) signaling. Our study provides a potentially clinically relevant strategy of selecting LUAD patients for MDM2-targeted therapy that may provide for increased response rates and, thus, better survival.

Integrative network analysis of early-stage lung adenocarcinoma identifies aurora kinase inhibition as interceptor of invasion and progression.

Here we focus on the molecular characterization of clinically significant histological subtypes of early-stage lung adenocarcinoma (esLUAD), which is the most common histological subtype of lung cancer. Within lung adenocarcinoma, histology is heterogeneous and associated with tumor invasion and diverse clinical outcomes. We present a gene signature distinguishing invasive and non-invasive tumors among esLUAD. Using the gene signatures, we estimate an Invasiveness Score that is strongly associated with survival of esLUAD patients in multiple independent cohorts and with the invasiveness phenotype in lung cancer cell lines. Regulatory network analysis identifies aurora kinase as one of master regulators of the gene signature and the perturbation of aurora kinases in vitro and in a murine model of invasive lung adenocarcinoma reduces tumor invasion. Our study reveals aurora kinases as a therapeutic target for treatment of early-stage invasive lung adenocarcinoma.