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Journal ArticleDOI

Network-based gene deletion analysis identifies candidate genes and molecular mechanism involved in clear cell renal cell carcinoma

01 Jan 2021-Journal of Genetics (Springer India)-Vol. 100, Iss: 1, pp 1-11
TL;DR: In this article, the authors performed functional enrichment analysis using gene ontology and Elsevier disease pathway collection and constructed a regulatory network of 577 differentially expressed genes (DEGs) where 146 overexpressed and 431 underexpressed with a significant threshold of adjusted P values < 0.05.
Abstract: Human clear cell renal cell carcinoma (ccRCC) is the most common and frequently occurring histological subtype of RCC. Unlike other carcinomas, candidate predictive biomarkers for this type are in need to explore the molecular mechanism of ccRCC and identify candidate target genes for improving disease management. For this, we chose case-control-based studies from the Gene Expression Omnibus and subjected the gene expression microarray data to combined effect size meta-analysis for identifying shared genes signature. Further, we constructed a subnetwork of these gene signatures and evaluated topological parameters during the gene deletion analysis to get to the central hub genes, as they form the backbone of the network and its integrity. Parallelly, we carried out functional enrichment analysis using gene ontology and Elsevier disease pathway collection. We also performed microRNAs target gene analysis and constructed a regulatory network. We identified a total of 577 differentially expressed genes (DEGs), where 146 overexpressed and 431 underexpressed with a significant threshold of adjusted P values <0.05. Enrichment analysis of these DEGs' functions showed a relation to metabolic and cellular pathways like metabolic reprogramming in cancer, proteins with altered expression in cancer metabolic reprogramming, and glycolysis activation in cancer (Warburg effect). Our analysis revealed the potential role of PDHB and ATP5C1 in ccRCC by altering metabolic pathways and amyloid beta precursor protein (APP) role in altering cell-cycle growth for the tumour progression in ccRCC conditions. Identification of these candidate predictive genes paves the way for the development of biomarker-based methods for this carcinoma.
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TL;DR: In this article , a weighted gene co-expression network (WGCN) and protein-protein interaction (PPI) network were constructed to identify network hub genes and a diagnostic model was established based on these hub genes using Least Absolute Shrinkage and Selection Operator (LASSO) and ROC analyses.
Abstract: Abstract Alzheimer’s disease (AD) is the most prevalent dementia disorder globally, and there are still no effective interventions for slowing or stopping the underlying pathogenic mechanisms. There is strong evidence implicating neural oxidative stress (OS) and ensuing neuroinflammation in the progressive neurodegeneration observed in the AD brain both during and prior to symptom emergence. Thus, OS-related biomarkers may be valuable for prognosis and provide clues to therapeutic targets during the early presymptomatic phase. In the current study, we gathered brain RNA-seq data of AD patients and matched controls from the Gene Expression Omnibus (GEO) to identify differentially expressed OS-related genes (OSRGs). These OSRGs were analyzed for cellular functions using the Gene Ontology (GO) database and used to construct a weighted gene co-expression network (WGCN) and protein-protein interaction (PPI) network. Receiver operating characteristic (ROC) curves were then constructed to identify network hub genes. A diagnostic model was established based on these hub genes using Least Absolute Shrinkage and Selection Operator (LASSO) and ROC analyses. Immune-related functions were examined by assessing correlations between hub gene expression and immune cell brain infiltration scores. Further, target drugs were predicted using the Drug-Gene Interaction database, while regulatory miRNAs and transcription factors were predicted using miRNet. In total, 156 candidate genes were identified among 11046 differentially expressed genes, 7098 genes in WGCN modules, and 446 OSRGs, and 5 hub genes (MAPK9, FOXO1, BCL2, ETS1, and SP1) were identified by ROC curve analyses. These hub genes were enriched in GO annotations “Alzheimer’s disease pathway,” “Parkinson’s Disease,” “Ribosome,” and “Chronic myeloid leukemia.” In addition, 78 drugs were predicted to target FOXO1, SP1, MAPK9, and BCL2, including fluorouracil, cyclophosphamide, and epirubicin. A hub gene-miRNA regulatory network with 43 miRNAs and hub gene-transcription factor (TF) network with 36 TFs were also generated. These hub genes may serve as biomarkers for AD diagnosis and provide clues to novel potential treatment targets.

1 citations

References
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Journal ArticleDOI
TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

62,157 citations

Journal ArticleDOI
TL;DR: PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is introduced, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses.
Abstract: Moher and colleagues introduce PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses. Us...

23,203 citations

Journal ArticleDOI
TL;DR: This report examines cancer incidence, mortality, and survival by site, sex, race/ethnicity, education, geographic area, and calendar year, as well as the proportionate contribution of selected sites to the overall trends.
Abstract: Each year, the American Cancer Society estimates the number of new cancer cases and deaths expected in the United States in the current year and compiles the most recent data on cancer incidence, mortality, and survival based on incidence data from the National Cancer Institute, Centers for Disease Control and Prevention, and the North American Association of Central Cancer Registries and mortality data from the National Center for Health Statistics. Incidence and death rates are age-standardized to the 2000 US standard million population. A total of 1,437,180 new cancer cases and 565,650 deaths from cancer are projected to occur in the United States in 2008. Notable trends in cancer incidence and mortality include stabilization of incidence rates for all cancer sites combined in men from 1995 through 2004 and in women from 1999 through 2004 and a continued decrease in the cancer death rate since 1990 in men and since 1991 in women. Overall cancer death rates in 2004 compared with 1990 in men and 1991 in women decreased by 18.4% and 10.5%, respectively, resulting in the avoidance of over a half million deaths from cancer during this time interval. This report also examines cancer incidence, mortality, and survival by site, sex, race/ethnicity, education, geographic area, and calendar year, as well as the proportionate contribution of selected sites to the overall trends. Although much progress has been made in reducing mortality rates, stabilizing incidence rates, and improving survival, cancer still accounts for more deaths than heart disease in persons under age 85 years. Further progress can be accelerated by supporting new discoveries and by applying existing cancer control knowledge across all segments of the population.

10,292 citations

Journal ArticleDOI
TL;DR: These mutants—the ‘Keio collection’—provide a new resource not only for systematic analyses of unknown gene functions and gene regulatory networks but also for genome‐wide testing of mutational effects in a common strain background, E. coli K‐12 BW25113.
Abstract: We have systematically made a set of precisely defined, single-gene deletions of all nonessential genes in Escherichia coli K-12. Open-reading frame coding regions were replaced with a kanamycin cassette flanked by FLP recognition target sites by using a one-step method for inactivation of chromosomal genes and primers designed to create in-frame deletions upon excision of the resistance cassette. Of 4288 genes targeted, mutants were obtained for 3985. To alleviate problems encountered in high-throughput studies, two independent mutants were saved for every deleted gene. These mutants-the 'Keio collection'-provide a new resource not only for systematic analyses of unknown gene functions and gene regulatory networks but also for genome-wide testing of mutational effects in a common strain background, E. coli K-12 BW25113. We were unable to disrupt 303 genes, including 37 of unknown function, which are candidates for essential genes. Distribution is being handled via GenoBase (http://ecoli.aist-nara.ac.jp/).

7,428 citations

Journal ArticleDOI
TL;DR: In situ click chemistry is used to develop COX-2 specific inhibitors with high in vivo anti-inflammatory activity, significantly higher than that of widely used selective cyclooxygenase-2 inhibitors.
Abstract: Cyclooxygenase-2 isozyme is a promising anti-inflammatory drug target, and overexpression of this enzyme is also associated with several cancers and neurodegenerative diseases. The amino-acid sequence and structural similarity between inducible cyclooxygenase-2 and housekeeping cyclooxygenase-1 isoforms present a significant challenge to design selective cyclooxygenase-2 inhibitors. Herein, we describe the use of the cyclooxygenase-2 active site as a reaction vessel for the in situ generation of its own highly specific inhibitors. Multi-component competitive-binding studies confirmed that the cyclooxygenase-2 isozyme can judiciously select most appropriate chemical building blocks from a pool of chemicals to build its own highly potent inhibitor. Herein, with the use of kinetic target-guided synthesis, also termed as in situ click chemistry, we describe the discovery of two highly potent and selective cyclooxygenase-2 isozyme inhibitors. The in vivo anti-inflammatory activity of these two novel small molecules is significantly higher than that of widely used selective cyclooxygenase-2 inhibitors. Traditional inflammation and pain relief drugs target both cyclooxygenase 1 and 2 (COX-1 and COX-2), causing severe side effects. Here, the authors use in situ click chemistry to develop COX-2 specific inhibitors with high in vivo anti-inflammatory activity.

6,061 citations