Systematic Enrichment Analysis Research Articles

Structure-based design of small molecule and peptide inhibitors for selective targeting of ROCK1: an integrative computational approach

Rho-associated, coiled-coil-containing protein kinase (ROCK1) regulates cell contraction, morphology, and motility by phosphorylating its downstream targets. ROCK1 is a proven target for many pathological conditions like cancer, atherosclerosis, glaucoma, neuro-degeneration, etc. Though many kinase inhibitors are available, there is a dearth of studies on repurposing approved drugs and novel peptide inhibitors that could potentially target ROCK1. Hence, in this study, an extensive integration of open-source pipelines was employed to probe the potential inhibitors (ligand/peptide) for targeting ROCK1. To start with, a systematic enrichment analysis was performed to delineate the most optimal ROCK1 crystal structure that can be harnessed for drug design. A comparative analysis of conformational flexibility between monomeric and dimeric forms was also performed to prioritize the optimal assembly for structural studies. Subsequently, Virtual screening of FDA-approved drugs in Drugbank was performed using POAP pipeline. Further, the top hits were probed for binding affinity, crucial interaction fingerprints, and complex stability during MD simulation. In parallel, a combinatorial tetrapeptide library was also virtually screened against ROCK1 using the PepVis pipeline. Following which, all these shortlisted inhibitors (compounds/peptides) were subjected to Kinomerun analysis to infer other potential kinase targets. Finally, Polydatin and conivaptan were prioritized as the most potential repurposable inhibitors, and WWWF, WWVW as potential inhibitory peptides for targeting ROCK1. The prioritized inhibitors are highly promising for use in therapeutics, as these are resultants of the multilevel stringent filtration process. The computational strategies implemented in this study could potentially serve as a scaffold towards selective inhibitor design for other kinases. Communicated by Ramaswamy H. Sarma

Dynamical network analysis reveals key microRNAs in progressive stages of lung cancer.

Non-coding RNAs are fundamental to the competing endogenous RNA (CeRNA) hypothesis in oncology. Previous work focused on static CeRNA networks. We construct and analyze CeRNA networks for four sequential stages of lung adenocarcinoma (LUAD) based on multi-omics data of long non-coding RNAs (lncRNAs), microRNAs and mRNAs. We find that the networks possess a two-level bipartite structure: common competing endogenous network (CCEN) composed of an invariant set of microRNAs over all the stages and stage-dependent, unique competing endogenous networks (UCENs). A systematic enrichment analysis of the pathways of the mRNAs in CCEN reveals that they are strongly associated with cancer development. We also find that the microRNA-linked mRNAs from UCENs have a higher enrichment efficiency. A key finding is six microRNAs from CCEN that impact patient survival at all stages, and four microRNAs that affect the survival from a specific stage. The ten microRNAs can then serve as potential biomarkers and prognostic tools for LUAD.

Abstract 2839: Systematic enrichment analysis of gene expression profiling studies identifies SPARC dependent consensus pathways implicated in bladder cancer

Abstract Bladder cancer (urothelial cancer of the bladder) is the most common malignancy affecting the urinary system with increasing incidence and mortality. Treatment of bladder cancer has not advanced in the past 30 years. Therefore, there is a crucial unmet need for novel therapies, especially for advanced disease. We have recently reported Secreted Protein Acidic and Rich in Cysteine (SPARC) as a tumor suppressor in urinary bladder cancer that inhibits the multistep cascades on tumor initiation, progression and metastasis. SPARC gene and protein expression was among candidates associated with the tumorigenicity of the isogenic T24/T24t cell lines. We reported that SPARC depletion in human bladder cancer cell lines including T24 cells increased their tumorigenicity and metastatic potential. In addition, SPARC protein and transcript expression are significantly downregulated in advanced urothelial cancer. To gain insight on the molecular mechanisms of the tumor suppressor effects of SPARC in urothelial cancer, we did whole transcriptome profiling of T24 cells depleted of SPARC to identify SPARC-signature associated with bladder cancer invasiveness, progression, and metastasis. Subsequently, we used gene signature enrichment analysis (GSEA) pathway enrichment tools to define functionally related genes that are consistently up- or down- regulated as a function of loss of SPARC. We found that loss of SPARC expression is associated with enrichment of multiple oncogenic signaling pathways that are enriched in muscle invasive urothelial cancer and have been associated with poor prognosis. These pathways include K-ras, Myc-oncogene, p53 pathways as well as DNA damage/repair. Consistent with our earlier reports, loss of SPARC is associated with genes and proteins involved in angiogenesis, inflammation and hypoxia. In addition, we have identified novel signatures involved in unfolded protein response, mTOR signaling, glycolysis and cholesterol metabolism. These comprehensive signatures not only reveal SPARC-dependent networks that cooperate to elicit its biological responses but enables coherent understanding of the etiology of complex bladder cancer disease. Importantly, these signatures identify novel therapeutic opportunities for bladder cancer. Citation Format: Bincy Anu John, Neveen Said. Systematic enrichment analysis of gene expression profiling studies identifies SPARC dependent consensus pathways implicated in bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2839. doi:10.1158/1538-7445.AM2017-2839

Systematic enrichment analysis of potentially functional regions for 103 prostate cancer risk-associated loci.

More than 100 prostate cancer (PCa) risk-associated single nucleotide polymorphisms (SNPs) have been identified by genome wide association studies (GWAS). However, the molecular mechanisms are unclear for most of these SNPs. All reported PCa risk-associated SNPs reaching the genome-wide significance level of P < 1 × 10(-7) (index SNPs), as well as SNPs in linkage disequilibrium (LD, r(2) ≥ 0.5) with them were cataloged. Genomic regions with potentially functional impact were also identified, including UCSC annotated coding regions (exon and snoRNA/miRNA) and regulatory regions, as well as binding regions for transcription factors (TFs), histone modifications (HMs), DNase I hypersensitivity (DHSs), and RNA Polymerase IIA (POLR2A) defined by ChIP-Seq in prostate cell lines and tissues. Enrichment analysis was performed to test whether PCa risk-associated SNPs are located in these functional regions more than expected. A total of 103 PCa risk-associated index SNPs and 7,244 SNPs in LD with these index SNPs were cataloged. Genomic regions with potentially functional impact, grouped in 30 different categories of functionalities, were identified. Enrichment analysis indicated that genomic regions in the following 15 categories were enriched for the PCa risk-associated SNPs: exons, CpG regions, 6 TFs (AR, ERG, FOXA1, HOXB13, CTCF, and NR3C1), 5 HMs (H3K4me1, H3K4me2, H3K4me3, H3K27AC, and H3T11P), DHSs and POLR2A. In contrast, significantly fewer PCa risk SNPs were mapped to binding regions for H3K27me3, a repressive chromatin marker. The PCa risk-associated SNPs discovered to date may affect PCa risk through multiple different mechanisms, especially by affecting binding regions of TFs/HMs.

Systematic enrichment analysis of microRNA expression profiling studies in endometriosis.

The purpose of this study was to conduct a meta-analysis on human microRNAs (miRNAs) expression data of endometriosis tissue profiles versus those of normal controls and to identify novel putative diagnostic markers. PubMed, Embase, Web of Science, Ovid Medline were used to search for endometriosis miRNA expression profiling studies of endometriosis. The miRNAs expression data were extracted, and study quality of each article was assessed. The frequently reported miRNAs with consistent regulation were screened out by a meta-profiling algorithm. The putative targets of consistently expressed miRNAs were predicted by using four target prediction tools (TargetScan, PicTar, miRanda, miRDB), and gene ontology pathway enrichment analysis (KEGG and Panther pathways) of the miRNA targets were carried out with GeneCodis web tool. A total of 194 related literatures were retrieved in four databases. One hundred and thirty four differentially expressed miRNAs were found in the 12 microRNA expression profiling studies that compared endometriosis tissues with normal tissues, with 28 miRNAs reported in at least two studies, and 9882 candidate genes retrieved for 13 consistently expressed miRNAs. Kyoto encyclopedia of genes and genomes (KEGG) and Panther pathways enrichment analysis showed that endometriosis related differently expressed miRNA targets were mainly enriched in cancer, endocytosis, Wnt signalling pathway, and angiogenesis. It showed that these differently expressed miRNAs and gene are potential biomarkers of endometriosis. miRNAs appear to be potent regulators of gene expression in endometriosis and its associated reproductive disorders, raising the prospect of using miRNAs as biomarkers and therapeutic agent in endometriosis.

IPAD: the integrated pathway analysis database for systematic enrichment analysis

Next-Generation Sequencing (NGS) technologies and Genome-Wide Association Studies (GWAS) generate millions of reads and hundreds of datasets, and there is an urgent need for a better way to accurately interpret and distill such large amounts of data. Extensive pathway and network analysis allow for the discovery of highly significant pathways from a set of disease vs. healthy samples in the NGS and GWAS. Knowledge of activation of these processes will lead to elucidation of the complex biological pathways affected by drug treatment, to patient stratification studies of new and existing drug treatments, and to understanding the underlying anti-cancer drug effects. There are approximately 141 biological human pathway resources as of Jan 2012 according to the Pathguide database. However, most currently available resources do not contain disease, drug or organ specificity information such as disease-pathway, drug-pathway, and organ-pathway associations. Systematically integrating pathway, disease, drug and organ specificity together becomes increasingly crucial for understanding the interrelationships between signaling, metabolic and regulatory pathway, drug action, disease susceptibility, and organ specificity from high-throughput omics data (genomics, transcriptomics, proteomics and metabolomics). We designed the I ntegrated P athway A nalysis D atabase for Systematic Enrichment Analysis (IPAD, http://bioinfo.hsc.unt.edu/ipad ), defining inter-association between pathway, disease, drug and organ specificity, based on six criteria: 1) comprehensive pathway coverage; 2) gene/protein to pathway/disease/drug/organ association; 3) inter-association between pathway, disease, drug, and organ; 4) multiple and quantitative measurement of enrichment and inter-association; 5) assessment of enrichment and inter-association analysis with the context of the existing biological knowledge and a gold standard constructed from reputable and reliable sources; and 6) cross-linking of multiple available data sources. IPAD is a comprehensive database covering about 22,498 genes, 25,469 proteins, 1956 pathways, 6704 diseases, 5615 drugs, and 52 organs integrated from databases including the BioCarta, KEGG, NCI-Nature curated, Reactome, CTD, PharmGKB, DrugBank, PharmGKB, and HOMER. The database has a web-based user interface that allows users to perform enrichment analysis from genes/proteins/molecules and inter-association analysis from a pathway, disease, drug, and organ. Moreover, the quality of the database was validated with the context of the existing biological knowledge and a gold standard constructed from reputable and reliable sources. Two case studies were also presented to demonstrate: 1) self-validation of enrichment analysis and inter-association analysis on brain-specific markers, and 2) identification of previously undiscovered components by the enrichment analysis from a prostate cancer study. IPAD is a new resource for analyzing, identifying, and validating pathway, disease, drug, organ specificity and their inter-associations. The statistical method we developed for enrichment and similarity measurement and the two criteria we described for setting the threshold parameters can be extended to other enrichment applications. Enriched pathways, diseases, drugs, organs and their inter-associations can be searched, displayed, and downloaded from our online user interface. The current IPAD database can help users address a wide range of biological pathway related, disease susceptibility related, drug target related and organ specificity related questions in human disease studies.

IPAD: the Integrated Pathway Analysis Database for Systematic Enrichment Analysis

BackgroundNext-Generation Sequencing (NGS) technologies and Genome-Wide Association Studies (GWAS) generate millions of reads and hundreds of datasets, and there is an urgent need for a better way to accurately interpret and distill such large amounts of data. Extensive pathway and network analysis allow for the discovery of highly significant pathways from a set of disease vs. healthy samples in the NGS and GWAS. Knowledge of activation of these processes will lead to elucidation of the complex biological pathways affected by drug treatment, to patient stratification studies of new and existing drug treatments, and to understanding the underlying anti-cancer drug effects. There are approximately 141 biological human pathway resources as of Jan 2012 according to the Pathguide database. However, most currently available resources do not contain disease, drug or organ specificity information such as disease-pathway, drug-pathway, and organ-pathway associations. Systematically integrating pathway, disease, drug and organ specificity together becomes increasingly crucial for understanding the interrelationships between signaling, metabolic and regulatory pathway, drug action, disease susceptibility, and organ specificity from high-throughput omics data (genomics, transcriptomics, proteomics and metabolomics).ResultsWe designed the Integrated Pathway Analysis Database for Systematic Enrichment Analysis (IPAD, http://bioinfo.hsc.unt.edu/ipad), defining inter-association between pathway, disease, drug and organ specificity, based on six criteria: 1) comprehensive pathway coverage; 2) gene/protein to pathway/disease/drug/organ association; 3) inter-association between pathway, disease, drug, and organ; 4) multiple and quantitative measurement of enrichment and inter-association; 5) assessment of enrichment and inter-association analysis with the context of the existing biological knowledge and a "gold standard" constructed from reputable and reliable sources; and 6) cross-linking of multiple available data sources.IPAD is a comprehensive database covering about 22,498 genes, 25,469 proteins, 1956 pathways, 6704 diseases, 5615 drugs, and 52 organs integrated from databases including the BioCarta, KEGG, NCI-Nature curated, Reactome, CTD, PharmGKB, DrugBank, PharmGKB, and HOMER. The database has a web-based user interface that allows users to perform enrichment analysis from genes/proteins/molecules and inter-association analysis from a pathway, disease, drug, and organ.Moreover, the quality of the database was validated with the context of the existing biological knowledge and a "gold standard" constructed from reputable and reliable sources. Two case studies were also presented to demonstrate: 1) self-validation of enrichment analysis and inter-association analysis on brain-specific markers, and 2) identification of previously undiscovered components by the enrichment analysis from a prostate cancer study.ConclusionsIPAD is a new resource for analyzing, identifying, and validating pathway, disease, drug, organ specificity and their inter-associations. The statistical method we developed for enrichment and similarity measurement and the two criteria we described for setting the threshold parameters can be extended to other enrichment applications. Enriched pathways, diseases, drugs, organs and their inter-associations can be searched, displayed, and downloaded from our online user interface. The current IPAD database can help users address a wide range of biological pathway related, disease susceptibility related, drug target related and organ specificity related questions in human disease studies.

Consensus Pathways Implicated in Prognosis of Colorectal Cancer Identified Through Systematic Enrichment Analysis of Gene Expression Profiling Studies

BackgroundA large number of gene expression profiling (GEP) studies on prognosis of colorectal cancer (CRC) has been performed, but no reliable gene signature for prediction of CRC prognosis has been found. Bioinformatic enrichment tools are a powerful approach to identify biological processes in high-throughput data analysis.Principal FindingsWe have for the first time collected the results from the 23 so far published independent GEP studies on CRC prognosis. In these 23 studies, 1475 unique, mapped genes were identified, from which 124 (8.4%) were reported in at least two studies, with 54 of them showing consisting direction in expression change between the single studies. Using these data, we attempted to overcome the lack of reproducibility observed in the genes reported in individual GEP studies by carrying out a pathway-based enrichment analysis. We used up to ten tools for overrepresentation analysis of Gene Ontology (GO) categories or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in each of the three gene lists (1475, 124 and 54 genes). This strategy, based on testing multiple tools, allowed us to identify the oxidative phosphorylation chain and the extracellular matrix receptor interaction categories, as well as a general category related to cell proliferation and apoptosis, as the only significantly and consistently overrepresented pathways in the three gene lists, which were reported by several enrichment tools.ConclusionsOur pathway-based enrichment analysis of 23 independent gene expression profiling studies on prognosis of CRC identified significantly and consistently overrepresented prognostic categories for CRC. These overrepresented categories have been functionally clearly related with cancer progression, and deserve further investigation.

Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

Background:A large number of gene expression profiling (GEP) studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis. Materials and Methods:We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9%) had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO) categories or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration. Results:Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities. Conclusions:We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation.

CD40: an upstream master switch for endothelial cell activation uncovered by RNAi-coupled transcriptional profiling

The CD40-CD154 dyad seems to play a prominent role fostering the immune-inflammatory response triggered by endothelial cell (EC)-T-cell communication. To delineate comprehensively the involvement of CD40 (TNFRSF5) in EC activation, we combined RNAi-mediated CD40 knockdown with comparative genome-wide transcriptional profiling of ECs interacting with (CD154+) T cells. We report the initiation of a profound stress response in ECs upon CD40-CD154 engagement through early up-regulation of, among others, the major proinflammatory NF-kappaB and MAPK/SAPK pathways and their associated transcription factors. Moreover, we have identified novel genes regulated through the CD40-CD154 interaction, and pathways previously unrecognized to be induced by CD40 signaling in ECs. Thus, we document a significant down-regulation of endothelial APLN by CD40-CD154 interaction, TNFalpha/IFNgamma exposure, and in immune-inflammatory pathologies, which could lead to hemodynamic dysfunction. Conversely, CD40-mediated up-regulation of the viral immune surveillance system, notably TLR3, IFIH1, RIG-I, and RNASEL, establishes a reverse link from adaptive to innate immunity in ECs. Moreover, systematic enrichment analysis substantiates endothelial CD40 involvement in the transcriptional regulation of gene networks associated with adhesion and motility, immunity, cell fate control, hemostasis, and metabolism. Our study also highlights the anti-inflammatory potential of RNAi-mediated CD40 inhibition, and the relevance of CD40 signaling for therapeutic intervention.