Comprehensive Integrative Analysis Research Articles

Identification of Subtypes of Barrett’s Esophagus and Esophageal Adenocarcinoma Based on DNA Methylation Profiles and Integration of Transcriptome and Genome Data

Esophageal adenocarcinomas (EACs) are heterogeneous and often preceded by Barrett's esophagus (BE). Many genomic changes have been associated with development of BE and EAC, but little is known about epigenetic alterations. We performed epigenetic analyses of BE and EAC tissues and combined these data with transcriptome and genomic data to identify mechanisms that control gene expression and genome integrity. In a retrospective cohort study, we collected tissue samples and clinical data from 150 BE and 285 EAC cases from the Oesophageal Cancer Classification and Molecular Stratification consortium in the United Kingdom. We analyzed methylation profiles of all BE and EAC tissues and assigned them to subgroups using non-negative matrix factorization with k-means clustering. Data from whole-genome sequencing and transcriptome studies were then incorporated; we performed integrative methylation and RNA-sequencing analyses to identify genes that were suppressed with increased methylation in promoter regions. Levels of different immune cell types were computed using single-sample gene set enrichment methods. We derived 8 organoids from 8 EAC tissues and tested their sensitivity to different drugs. BE and EAC samples shared genome-wide methylation features, compared with normal tissues (esophageal, gastric, and duodenum; controls) from the same patients and grouped into 4 subtypes. Subtype 1 was characterized by DNA hypermethylation with a high mutation burden and multiple mutations in genes in cell cycle and receptor tyrosine signaling pathways. Subtype 2 was characterized by a gene expression pattern associated with metabolic processes (ATP synthesis and fatty acid oxidation) and lack methylation at specific binding sites for transcription factors; 83% of samples of this subtype were BE and 17% were EAC. The third subtype did not have changes in methylation pattern, compared with control tissue, but had a gene expression pattern that indicated immune cell infiltration; this tumor type was associated with the shortest time of patient survival. The fourth subtype was characterized by DNA hypomethylation associated with structure rearrangements, copy number alterations, with preferential amplification of CCNE1 (cells with this gene amplification have been reported to be sensitive to CDK2 inhibitors). Organoids with reduced levels of MGMT and CHFR expression were sensitive to temozolomide and taxane drugs. In a comprehensive integrated analysis of methylation, transcriptome, and genome profiles of more than 400 BE and EAC tissues, along with clinical data, we identified 4 subtypes that were associated with patient outcomes and potential responses to therapy.

Integrative analysis of mRNA, miRNA and lncRNA profiles reveals the commonness between bladder cancer and breast cancer.

BackgroundUrinary bladder cancer (BLCA) and breast cancer (BRCA) are two cancers which are the most common cause of death. Recent studies have found that BLCA and BRCA shared commonness on many areas, such as biological mechanism, molecular subtypes and clinical stage. Therefore, a mature knowledge of BRCA can help highlight the treatment and prognosis of BLCA.MethodsTo address this issue, we performed a comprehensive integrative analysis to investigate the similarity between both cancers. Firstly, functional enrichment analysis based on differently expressed transcripts was performed. Secondly, PPI network analysis was performed to identify some hub genes in both cancers. Thirdly, the machine learning method was applied to construct cancer predictor. Finally, competing endogenous RNA (ceRNA) networks of both cancers were constructed by applying the integrated method.ResultsThe functional enrichment analysis showed that ECM-receptor interaction, Focal adhesion, PI3K-Akt signaling pathway were significantly pathways shared by BLCA and BRCA. From the PPI networks analysis, we identified some potential biomarkers shared by both cancers, such as CCNB1, CDC20, BUB2 and so on. The mRNA type and lncRNA type cancer predictor with good classifying performance were generated with machine learning approach, and some mRNA and lncRNA that contribute to cancer diagnostic were identified. By construct ceRNA networks, we identified some common cancer-associated ceRNA pairs, which may be helpful to uncover the relationship between two cancers.ConclusionsOur findings enhance the understanding of the various molecular signatures and commonalities shared by BLCA and BRCA, suggesting that BLCA may be particularly responsive to some treatments for BRCA.

Integrative genomic analysis identified common regulatory networks underlying the correlation between coronary artery disease and plasma lipid levels

BackgroundCoronary artery disease (CAD) and plasma lipid levels are highly correlated, indicating the presence of common pathways between them. Nevertheless, the molecular pathways underlying the pathogenic comorbidities for both traits remain poorly studied. We sought to identify common pathways and key driver genes by performing a comprehensive integrative analysis based on multi-omic datasets.MethodsBy performing a pathway-based analysis of GWAS summary data, we identified that lipoprotein metabolism process-related pathways were significantly associated with CAD risk. Based on LD score regression analysis of CAD-related SNPs, significant heritability enrichments were observed in the cardiovascular and digestive system, as well as in liver and gastrointestinal tissues, which are the main regulators for lipid level.ResultsWe found there existed significant genetic correlation between CAD and other lipid metabolism related traits (the smallest P value < 1 × 10− 16). A total of 13 genes (e.g., LPA, APOC1, APOE and SLC22A3) was found to be overlapped between CAD and plasma lipid levels. By using the data-driven approach that integrated transcriptome information, we discovered co-expression modules associated prominently with both CAD and plasma lipids. With the detailed topology information on gene-gene regulatory relationship, we illustrated that the identified hub genes played important roles in the pathogenesis of CAD and plasma lipid turbulence.ConclusionTogether, we identified the shared molecular mechanisms underlying the correlation between CAD and plasma lipid levels.

RBTT-06. TESSA JOWELL BRAIN MATRIX STUDY: A BRITISH FEASIBILITY STUDY OF MOLECULAR STRATIFICATION AND TARGETED THERAPY TO OPTIMIZE THE CLINICAL MANAGEMENT OF PATIENTS WITH GLIOMA

Abstract In 2016 there were 5250 brain cancer deaths in the UK. Standard treatment is surgical resection followed by chemo-radiotherapy. In most cases of diffuse glioma, complete tumour resection is not feasible. Many chemotherapy drugs have untested penetration through the blood brain barrier, potentially leading to sub-therapeutic concentrations in the tumour. There is need to refine current treatment strategies in relation to the understanding of tumour biology, and rapidly introduce and evaluate novel therapeutic approaches and agents through delivering rigorous clinical trials. The TESSA JOWELL BRAIN MATRIX Study will evaluate the feasibility of delivering precision medicine for brain cancer patients within the NHS. A multicentre, platform feasibility study of 1200 patients with diffuse glioma will build on the 100,000 genome project to develop and evaluate an infrastructure to collect and integrate: 1) real time comprehensive integrated molecular analysis, including whole genome sequencing and epigenetic classification; 2) serial sampling and annotation of tumours; 3) collection of matched clinical data; 4) assessment of patient quality of life; 5) centralised radiological review and response assessment as per RANO criteria. Once developed this will allow rapid introduction of therapeutic trials to specific patient groups. Secondary objectives include: understanding the association between extent of resection and molecular stratification to refine the role of surgery; optimisation and harmonisation of protocols to best collect, manage and store tissue, clinical data, and radiological images in order to provide a resource for researchers, both within and outside of the study. Improve patient recruitment by identifying and removing recruitment barriers and improve the information and consent processes for patients. Promote the development of a national network with expertise in brain cancer. Enrolment of the first patient is expected in late 2019. For further information, please contact the Brain Matrix Trial Office BrainMatrix@trials.bham.ac.uk.

Inter-individual differences in human brain structure and morphology link to variation in demographics and behavior.

We perform a comprehensive integrative analysis of multiple structural MR-based brain features and find for the first-time strong evidence relating inter-individual brain structural variations to a wide range of demographic and behavioral variates across a large cohort of young healthy human volunteers. Our analyses reveal that a robust 'positive-negative' spectrum of behavioral and demographic variates, recently associated to covariation in brain function, can already be identified using only structural features, highlighting the importance of careful integration of structural features in any analysis of inter-individual differences in functional connectivity and downstream associations with behavioral/demographic variates.

Revisiting the Role of Transcription Factors in Coordinating the Defense Response Against Citrus Bark Cracking Viroid Infection in Commercial Hop (Humulus Lupulus L.).

Transcription factors (TFs) play a major role in controlling gene expression by intricately regulating diverse biological processes such as growth and development, the response to external stimuli and the activation of defense responses. The systematic identification and classification of TF genes are essential to gain insight into their evolutionary history, biological roles, and regulatory networks. In this study, we performed a global mining and characterization of hop TFs and their involvement in Citrus bark cracking viroid CBCVd infection by employing a digital gene expression analysis. Our systematic analysis resulted in the identification of a total of 3,818 putative hop TFs that were classified into 99 families based on their conserved domains. A phylogenetic analysis classified the hop TFs into several subgroups based on a phylogenetic comparison with reference TF proteins from Arabidopsis thaliana providing glimpses of their evolutionary history. Members of the same subfamily and subgroup shared conserved motif compositions. The putative functions of the CBCVd-responsive hop TFs were predicted using their orthologous counterparts in A. thaliana. The analysis of the expression profiling of the CBCVd-responsive hop TFs revealed a massive differential modulation, and the expression of the selected TFs was validated using qRT-PCR. Together, the comprehensive integrated analysis in this study provides better insights into the TF regulatory networks associated with CBCVd infections in the hop, and also offers candidate TF genes for improving the resistance in hop against viroids.

BAP1 haploinsufficiency predicts a distinct immunogenic class of malignant peritoneal mesothelioma

BackgroundMalignant peritoneal mesothelioma (PeM) is a rare and fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no effective targeted therapies for PeM exist. Some immune checkpoint inhibitor studies of mesothelioma have found positivity to be associated with a worse prognosis.MethodsTo search for novel therapeutic targets for PeM, we performed a comprehensive integrative multi-omics analysis of the genome, transcriptome, and proteome of 19 treatment-naïve PeM, and in particular, we examined BAP1 mutation and copy number status and its relationship to immune checkpoint inhibitor activation.ResultsWe found that PeM could be divided into tumors with an inflammatory tumor microenvironment and those without and that this distinction correlated with haploinsufficiency of BAP1. To further investigate the role of BAP1, we used our recently developed cancer driver gene prioritization algorithm, HIT’nDRIVE, and observed that PeM with BAP1 haploinsufficiency form a distinct molecular subtype characterized by distinct gene expression patterns of chromatin remodeling, DNA repair pathways, and immune checkpoint receptor activation. We demonstrate that this subtype is correlated with an inflammatory tumor microenvironment and thus is a candidate for immune checkpoint blockade therapies.ConclusionsOur findings reveal BAP1 to be a potential, easily trackable prognostic and predictive biomarker for PeM immunotherapy that refines PeM disease classification. BAP1 stratification may improve drug response rates in ongoing phases I and II clinical trials exploring the use of immune checkpoint blockade therapies in PeM in which BAP1 status is not considered. This integrated molecular characterization provides a comprehensive foundation for improved management of a subset of PeM patients.

Prediction of causal genes and gene expression analysis of attention-deficit hyperactivity disorder in the different brain region, a comprehensive integrative analysis of ADHD.

Recent genome-wide association study (GWAS) identified 12 independent loci for Attention-deficit hyperactivity disorder (ADHD). However, the causal genes expression and pathways of ADHD is still vague. We integrated GWAS, eQTL and genes expression data to find the causal genes, genes expression, and genes prioritization in the different brain tissues and whole blood cells. Overall 47 genes were prioritized, the most promising genes were LSG1, HYAL3, PIDD, PNPLA2, BLOC1S2, PLK1S1, CALN1, KAT2B, CTNNB1 and WDR11. Whereas, the CALN1, KAT2B, and WDR11 were previously associated with schizophrenia (SZ), bipolar (BP) and drug abuse. Gene ontology analysis shows that the glutamate receptor signaling pathway (P = 8.009E-07, with false discovery rate (FDR) < 5%), GRIK5 sub network (P = 2.887E-06, FDR < 5%), abnormal gait (P = 3.657E-06, FDR < 5%), REACTOME_SIGNALING_BY_ERBB2 (P = 5.161E-06, FDR < 5%), and abnormal nervous system physiology (P = 5.239E-06, FDR < 5%) were associated with ADHD. These causal genes were highly expressed in Fetal Astrocytes, Neurons, and Microglia/Macrophage. This study illustrates the comprehensive GWAS integrative approach of ADHD. However, further genetic and functional studies are required to validate the role of these genes in the etiology of ADHD, which should provide novel insights into the understanding of this disease.

Integrative genomic analysis predicts novel functional enhancer-SNPs for bone mineral density.

Osteoporosis is a skeletal disorder characterized by low bone mineral density (BMD) and deterioration of bone microarchitecture. To identify novel genetic loci underlying osteoporosis, an effective strategy is to focus on scanning of variants with high potential functional impacts. Enhancers play a crucial role in regulating cell-type-specific transcription. Therefore, single-nucleotide polymorphisms (SNPs) located in enhancers (enhancer-SNPs) may represent strong candidate functional variants. Here, we performed a targeted analysis for potential functional enhancer-SNPs that may affect gene expression and biological processes in bone-related cells, specifically, osteoblasts, and peripheral blood monocytes (PBMs), using five independent cohorts (n = 5905) and the genetics factors for osteoporosis summary statistics, followed by comprehensive integrative genomic analyses of chromatin states, transcription, and metabolites. We identified 15 novel enhancer-SNPs associated with femoral neck and lumbar spine BMD, including 5 SNPs mapped to novel genes (e.g., rs10840343 and rs10770081 in IGF2 gene) and 10 novel SNPs mapped to known BMD-associated genes (e.g., rs2941742 in ESR1 gene, and rs10249092 and rs4342522 in SHFM1 gene). Interestingly, enhancer-SNPs rs10249092 and rs4342522 in SHFM1 were tightly linked, but annotated to different enhancers in PBMs and osteoblasts, respectively, suggesting that even tightly linked SNPs may regulate the same target gene and contribute to the phenotype variation in cell-type-specific manners. Importantly, ten enhancer-SNPs may also regulate BMD variation by affecting the serum metabolite levels. Our findings revealed novel susceptibility loci that may regulate BMD variation and provided intriguing insights into the genetic mechanisms of osteoporosis.

Plant Regulomics Portal (PRP): a comprehensive integrated regulatory information and analysis portal for plant genomes.

Gene regulation is a highly complex and networked phenomenon where multiple tiers of control determine the cell state in a spatio-temporal manner. Among these, the transcription factors, DNA and histone modifications, and post-transcriptional control by small RNAs like miRNAs serve as major regulators. An understanding of the integrative and spatio-temporal impact of these regulatory factors can provide better insights into the state of a ‘cell system’. Yet, there are limited resources available to this effect. Therefore, we hereby report an integrative information portal (Plant Regulomics Portal; PRP) for plants for the first time. The portal has been developed by integrating a huge amount of curated data from published sources, RNA-, methylome- and sRNA/miRNA sequencing, histone modifications and repeats, gene ontology, digital gene expression and characterized pathways. The key features of the portal include a regulatory search engine for fetching numerous analytical outputs and tracks of the abovementioned regulators and also a genome browser for integrated visualization of the search results. It also has numerous analytical features for analyses of transcription factors (TFs) and sRNA/miRNA, spot-specific methylation, gene expression and interactions and details of pathways for any given genomic element. It can also provide information on potential RdDM regulation, while facilitating enrichment analysis, generation of visually rich plots and downloading of data in a selective manner. Visualization of intricate biological networks is an important feature which utilizes the Neo4j Graph database making analysis of relationships and long-range system viewing possible. Till date, PRP hosts 571-GB processed data for four plant species namely Arabidopsis thaliana, Oryza sativa subsp. japonica, Zea mays and Glycine max.Database URL: https://scbb.ihbt.res.in/PRP

Integrated transcriptome, small RNA and degradome sequencing approaches provide insights into Ascochyta blight resistance in chickpea.

SummaryAscochyta blight (AB) is one of the major biotic stresses known to limit the chickpea production worldwide. To dissect the complex mechanisms of AB resistance in chickpea, three approaches, namely, transcriptome, small RNA and degradome sequencing were used. The transcriptome sequencing of 20 samples including two resistant genotypes, two susceptible genotypes and one introgression line under control and stress conditions at two time points (3rd and 7th day post inoculation) identified a total of 6767 differentially expressed genes (DEGs). These DEGs were mainly related to pathogenesis‐related proteins, disease resistance genes like NBS‐LRR, cell wall biosynthesis and various secondary metabolite synthesis genes. The small RNA sequencing of the samples resulted in the identification of 651 miRNAs which included 478 known and 173 novel miRNAs. A total of 297 miRNAs were differentially expressed between different genotypes, conditions and time points. Using degradome sequencing and in silico approaches, 2131 targets were predicted for 629 miRNAs. The combined analysis of both small RNA and transcriptome datasets identified 12 miRNA‐mRNA interaction pairs that exhibited contrasting expression in resistant and susceptible genotypes and also, a subset of genes that might be post‐transcriptionally silenced during AB infection. The comprehensive integrated analysis in the study provides better insights into the transcriptome dynamics and regulatory network components associated with AB stress in chickpea and, also offers candidate genes for chickpea improvement.

Molecular Characterization of Malignant Mesothelioma: Time for New Targets?

Malignant pleural mesothelioma (MPM) is an aggressive lethal malignancy for which very few therapeutic options exist. In this issue of Cancer Discovery, Hmeljak and colleagues report on a comprehensive integrative analysis of histology-independent genomic characteristics of MPM. They confirm previous observations that inactivation of tumor suppressor genes is the predominant oncogenic mechanism. This study provides a scientific rationale for potentially novel therapeutic options, including immune-checkpoint targeting VISTA and small-molecule inhibitors targeting the epigenome, DNA-repair pathways, and aurora kinase.See related article by Hmeljak et al., p. 1548.

Integrative proteomic analysis reveals potential high-frequency alternative open reading frame-encoded peptides in human colorectal cancer

Identification of alternative open reading frame-encoded peptides (AEPs) for the diagnosis of colorectal cancer at the proteome level is largely unexplored because of a lack of comprehensive proteomics data. Here, we performed a comprehensive integrative analysis of mass spectral data published by Clinical Proteomic Tumor Analysis Consortium and characterized 93 high-confident AEPs encoded within 75 genes. There are four cancer-related genes appeared to have AEPs identified frequently in >20 out of 95 colorectal cancer samples, including ABCF2, AR, RBM10 and NRG1. Further network analysis of the identified AEPs found the enrichment of novel AEPs within hormone androgen receptor and a highly-modularised network with 42 genes associated with patient survival. Our results not only suggested a mechanistic view of how AEPs work in cancer progression, but also shed light on somatic amino acid mutations in AEPs, which might be overlooked previously because of their low frequencies. In particular, potential high-frequency mutations in 77 samples associated with EDARADD may contribute to the discovery of new biomarkers and the development of innovative therapeutic approaches.

Proteogenomic characterization and comprehensive integrative genomic analysis of human colorectal cancer liver metastasis

BackgroundProteogenomic characterization and integrative and comparative genomic analysis provide a functional context to annotate genomic abnormalities with prognostic value.MethodsHere, we analyzed the proteomes and performed whole exome and transcriptome sequencing and single nucleotide polymorphism array profiling for 2 sets of triplet samples comprised of normal colorectal tissue, primary CRC tissue, and synchronous matched liver metastatic tissue.ResultsWe identified 112 CNV-mRNA-protein correlated molecules, including up-regulated COL1A2 and BGN associated with prognosis, and four strongest hot spots (chromosomes X, 7, 16 and 1) driving global mRNA abundance variation in CRC liver metastasis. Two sites (DMRTB1R202H and PARP4V458I) were revealed to frequent mutate only in the liver metastatic cohort and displayed dysregulated protein abundance. Moreover, we confirmed that the mutated peptide number has potential prognosis value and somatic variants displayed increased protein abundance, including high MYH9 and CCT6A expression, with clinical significance.ConclusionsOur proteogenomic characterization and integrative and comparative genomic analysis provides a new paradigm for understanding human colon and rectal cancer liver metastasis.Trial registrationClinicalTrials, NCT02917707. Registered 28 September 2016, https://clinicaltrials.gov/ct2/show/NCT02917707.

Pancreatic cancer survival analysis defines a signature that predicts outcome.

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer death in the US. Despite multiple large-scale genetic sequencing studies, identification of predictors of patient survival remains challenging. We performed a comprehensive assessment and integrative analysis of large-scale gene expression datasets, across multiple platforms, to enable discovery of a prognostic gene signature for patient survival in pancreatic cancer. PDAC RNA-Sequencing data from The Cancer Genome Atlas was stratified into Survival+ (>2-year survival) and Survival–(<1-year survival) cohorts (n = 47). Comparisons of RNA expression profiles between survival groups and normal pancreatic tissue expression data from the Gene Expression Omnibus generated an initial PDAC specific prognostic differential expression gene list. The candidate prognostic gene list was then trained on the Australian pancreatic cancer dataset from the ICGC database (n = 103), using iterative sampling based algorithms, to derive a gene signature predictive of patient survival. The gene signature was validated in 2 independent patient cohorts and against existing PDAC subtype classifications. We identified 707 candidate prognostic genes exhibiting differential expression in tumor versus normal tissue. A substantial fraction of these genes was also found to be differentially methylated between survival groups. From the candidate gene list, a 5-gene signature (ADM, ASPM, DCBLD2, E2F7, and KRT6A) was identified. Our signature demonstrated significant power to predict patient survival in two distinct patient cohorts and was independent of AJCC TNM staging. Cross-validation of our gene signature reported a better ROC AUC (≥ 0.8) when compared to existing PDAC survival signatures. Furthermore, validation of our signature through immunohistochemical analysis of patient tumor tissue and existing gene expression subtyping data in PDAC, demonstrated a correlation to the presence of vascular invasion and the aggressive squamous tumor subtype. Assessment of these genes in patient biopsies could help further inform risk-stratification and treatment decisions in pancreatic cancer.

Abstract 225: Tumor-infiltrating CD8-positive T-lymphocytes in tubo-ovarian high-grade serous cancer are associated with multiple germline variants in 22q12.1 in a genome-wide association analysis

Abstract Tubo-ovarian high-grade serous cancer (HGSC) is the most common histotype of epithelial ovarian cancer (70%-80%) and the leading cause of death from gynecological malignancy. Novel monoclonal antibody and adoptive cell transfer immunotherapies have found success in cancer in the past five years; however success in HGSC treatment has been elusive thus far. We have recently shown that CD8+ T-lymphocytes infiltrating the tumor proper (TILs) associate in a dose response manner with longer patient survival time regardless of age, stage or residual disease. As understanding host factors associated with this clinically relevant tumor phenotype will contribute to the development of targeted therapies, we sought to identify germline genetic factors associated with CD8+ TIL levels in HGSC. We performed a germline genome-wide association study (GWAS) of CD8+ TILs using 1204 HGSC patients of European ancestry from twelve studies with centralized genotyping, immunohistochemistry, and harmonization of clinical data. Germline genotypes were assayed using the Illumina Infinium OncoArray Beadchip and were imputed to over 11.4 million variants based on the 1000 Genomes Project reference panel. CD8 immunohistochemistry was performed on tissue microarrays using the Leica Bond Rx stainer and scored into four levels of CD8+ TILs per x400 magnification of a 0.55-mm diameter field for each tumor hotspot: none (no CD8+ TILs), low (1-2 CD8+ TILs), moderate (3-19 CD8+ TILs), high (20 or more CD8+ TILs). GWAS used multinomial regression modelling of these four CD8+ TIL levels adjusted for study site, age, and European ancestry principal components. On the average, CD8+ TIL levels were 18%, 19%, 44% and 18% for none, low, moderate and high levels, respectively. As expected, CD8+ TIL levels associated with overall survival time (p &amp;lt; 2.6x10-8), and CD8+ TIL levels and age at diagnosis were similarly distributed across study sites. We identified a region on chromosome 22 with multiple, correlated variants (MAF &amp;gt; 20%) associated with CD8+ TIL levels at p-value &amp;lt; 2.0x10-5. The most statistically significant variant was an indel (rs557925408) located in the an intron of the MYO18B gene (Myosin XVIIIB, p-value &amp;lt; 8.7x10-6). Each copy of this variant associated with a reduced extent of CD8+ TIL infiltration (OR low v none = 0.92; OR moderate v none = 0.61). An independent set of 1200 OncoArray genotyped HGSC cases are undergoing CD8+ TIL scoring in December 2017 and will be included in final genome-wide analysis. This will provide improved statistical power and enable consideration of additional genetic models (e.g., linear trend tests). Comprehensive integrative analysis of germline, tumor, and clinical features provides a model for clinical molecular epidemiology studies and will be key to increasing our understanding of this important HGSC immunophenotype. Citation Format: Yanina Natanzon, Martin Köbel, Stacey J. Winham, Sebastian M. Armasu, Bryan M. McCauley, Robert A. Vierkant, Julie M. Cunningham, David Bowtell, Ian G. Campbell, Jenny Chang-Claude, Anna deFazio, Peter A. Fasching, Mark T. Goodman, Beth Y. Karlan, Francesmary Modugno, Kirsten B. Moysich, Roberta B. Ness, Weiva Sieh, Paul D. Pharoah, Susan J. Ramus, Ellen L. Goode. Tumor-infiltrating CD8-positive T-lymphocytes in tubo-ovarian high-grade serous cancer are associated with multiple germline variants in 22q12.1 in a genome-wide association analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 225.

Comprehensive integrated analysis of gene expression datasets identifies key anti-cancer targets in different stages of breast cancer.

Breast cancer is one of the primary threats to women's health worldwide. However, the molecular mechanisms underlying the development of breast cancer remain to be fully elucidated. The present study aimed to investigate specific target gene expression profiles in breast cancer tissues in general and in different breast cancer stages, as well as to explore their functions in tumor development. For integrated analysis, a total of 5 gene expression profiling datasets for 3 different stages of breast cancer (stages I–III) were downloaded from the Gene Expression Omnibus of the National Center for Biotechnology Information. Pre-processing of these datasets was performed using the Robust Multi-array Average algorithm and global renormalization was performed for all studies. Differentially expressed genes between breast cancer patients and controls were estimated using the empirical Bayes algorithm. The Database for Annotation, Visualization and Integrated Discovery web server was used for analyzing the enrichment of the differentially expressed genes in Gene Ontology terms of the category biological process and in Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, breast cancer target genes were downloaded from the Thomson Reuters Integrity Database. We merged these target genes with the genes in breast cancer datasets. Analysis of anti-breast cancer gene networks was performed using the Genome-scale Integrated Analysis of Gene Networks in Tissues web server. The results demonstrated that the normal functions of the cell cycle, cell migration and cell adhesion were altered in all stages of breast cancer. Furthermore, 12 anti-breast cancer genes were identified to be dysregulated in at least one of the three stages. Among all of these genes, ribonucleotide reductase regulatory subunit M2 (RRM2) exhibited the highest degree of interaction with other interacting genes. Analysis of the network interactions revealed that the transcription factor of RRM2 is crucial for cancer development. Other genes, including mucin 1, progesterone receptor and cyclin-dependent kinase 5 regulatory subunit associated protein 3, also exhibited a high degree of interaction with the associated genes. In conclusion, several key anti-breast cancer genes identified in the present study are mainly associated with the regulation of the cell cycle, cell migration, cell adhesion and other cancer-associated cell functions, particularly RRM2.

Sarcoidosis Related Novel Candidate Genes Identified by Multi-Omics Integrative Analyses

Sarcoidosis is a multifactorial systemic disease characterized by granulomatous inflammation and greatly impacting on global public health. The etiology and mechanisms of sarcoidosis are not fully understood. Recent high-throughput biological research has generated vast amounts of multi-omics big data on sarcoidosis, but their significance remains to be determined. We sought to identify novel candidate regions, and genes consistently altered in heterogeneous omics studies so as to reveal the underlying molecular mechanisms. We conducted a comprehensive integrative literature analysis on global data on sarcoidosis, including genomic, transcriptomic, proteomic, and phenomic studies. We performed positional integration analysis of 38 eligible datasets originating from 17 different biological layers. Using the integration interval length of 50 kb, we identified 54 regions reaching significance value p ≤ 0.0001 and 15 regions with significance value p ≤ 0.00001, when applying more stringent criteria. Secondary literature analysis of the top 20 regions, with the most significant accumulation of signals, revealed several novel candidate genes for which associations with sarcoidosis have not yet been established, but have considerable support for their involvement based on omic data. These new plausible candidate genes include NELFE, CFB, EGFL7, AGPAT2, FKBPL, NRC3, and NEU1. Furthermore, annotated data were prepared to enable custom visualization and browsing of these sarcoidosis related omics evidence in the University of California Santa Cruz (UCSC) Genome Browser. Further multi-omics approaches are called for sarcoidosis biomarkers and diagnostic and therapeutic innovation. Our approach for harnessing multi-omics data and the findings presented herein reflect important steps toward understanding the etiology and underlying pathological mechanisms of sarcoidosis.

Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer

SUMMARYWe conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development.

Comprehensive integrative analyses identify GLT8D1 and CSNK2B as schizophrenia risk genes

Recent genome-wide association studies (GWAS) have identified multiple risk loci that show strong associations with schizophrenia. However, pinpointing the potential causal genes at the reported loci remains a major challenge. Here we identify candidate causal genes for schizophrenia using an integrative genomic approach. Sherlock integrative analysis shows that ALMS1, GLT8D1, and CSNK2B are schizophrenia risk genes, which are validated using independent brain expression quantitative trait loci (eQTL) data and integrative analysis method (SMR). Consistently, gene expression analysis in schizophrenia cases and controls further supports the potential role of these three genes in the pathogenesis of schizophrenia. Finally, we show that GLT8D1 and CSNK2B knockdown promote the proliferation and inhibit the differentiation abilities of neural stem cells, and alter morphology and synaptic transmission of neurons. These convergent lines of evidence suggest that the ALMS1, CSNK2B, and GLT8D1 genes may be involved in pathophysiology of schizophrenia.