scholarly journals Systematic identification of A-to-I editing associated regulators from multiple human cancers

2019 ◽  
Author(s):  
Tongjun Gu ◽  
Audrey Qiuyan Fu ◽  
Michael J. Bolt ◽  
Xiwu Zhao
Keyword(s):  
Rna Editing ◽  
Kidney Cancer ◽  
Enrichment Analysis ◽  
Second Step ◽  
Pathway Enrichment Analysis ◽  
Human Cancers ◽  
Potential Association ◽  
Regulation Mechanisms ◽  
Systematic Identification ◽  
Editing Process

AbstractA-to-I editing is the most common editing type in human that is catalyzed by ADAR family members (ADARs), ADAR1 and ADAR2. Millions of A-to-I editing sites have been discovered recently, however, the regulation mechanisms of the RNA editing process are still not clear. Here we developed a two-step logistic regression model to identify genes that are potentially involved in RNA editing process in four human cancers. The first step by classifying the editing sites into different categories assists the analysis at the second step. In the first step, ADAR1 was identified as the enzyme that associated with the majority of the A-to-I editing sites. Thus, ADAR1 was taken as a control gene in the second step to identify genes that have a stronger effect on editing sites than ADAR1. In addition, the detectable interferons and their receptors were used as covariates in the both steps to account for potential association caused by interferons. Using our advanced method, we successfully found a set of genes that were significantly positively or negatively associated (PA or NA) with specific sets of RNA editing sites. We highlighted two genes, SRSF5 and MIR22HG which were supported by multiple evidences. Most PA and NA genes were unique to each cancer, and only a few shared across two cancers. Pathway enrichment analysis showed that the PA genes from the four cancer types were enriched in Immune System, while the NA genes were enriched in two pathways: Metabolism of RNA, and Metabolism. The functional similarity of the PA and NA genes across all the four cancers indicates that even though most of the editing associated genes were unique to each cancer, they may impact on editing process through common pathways. Interestingly, the PA genes from kidney cancer were enriched for survival-associated genes while the NA genes were depleted of these genes, indicating that the PA genes may play more important roles in kidney cancer development.

Identification and analysis of RNA editing events in ovarian serous cystadenoma using RNA-seq Data

2021 ◽  
Vol 21 ◽  
Author(s):  
Yulan Wang ◽  
Xiaofeng Song ◽  
Tianyi Xu
Keyword(s):  
Ovarian Cancer ◽  
Rna Editing ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Serous Cystadenoma ◽  
Pathway Enrichment Analysis ◽  
Normal Tissues ◽  
Coding Regions ◽  
Target Binding

Background: Recent studies have revealed thousands of A-to-I RNA editing events in primates. These events are closely related to the occurrence and development of multiple cancers, but the origination and general functions of these events in ovarian cancer remain incompletely understood. Objective: To further the determination of molecular mechanisms of ovarian cancer from the perspective of RNA editing. Methods : Here, we used the SNP-free RNA editing Identification Toolkit (SPRINT) to detect RNA editing sites. These editing sites were then annotated and related functional analysis was performed. Results: In this study, about 1.7 million RES were detected in each sample, and 98% of these sites were due to A-to-G editing and were mainly distributed in non-coding regions. More than 1,000 A-to-G RES were detected in CDS regions, and nearly 700 could lead to amino acid changes. Our results also showed that editing in the 3′UTR regions can influence miRNA-target binding. We predicted the network of changed miRNA-mRNA interaction caused by the A-to-I RNA editing sites. We also screened the differential RNA editing sites between ovarian cancer and adjacent normal tissues, and then performed GO and KEGG pathway enrichment analysis on the genes that contain these differential RNA editing sites. Finally, we identified the potential dysregulated RNA editing events in ovarian cancer samples. Conclusion: This study systematically identified and analyzed RNA editing events in ovarian cancer and laid a foundation to explore the regulatory mechanism of RNA editing and its function in ovarian cancer.

SHMT2 is Associated with Tumor Purity, CD8+ T Immune Cells Infiltration, and a Novel Therapeutic Target in Four Different Human Cancers

2022 ◽  
Vol 22 ◽  
Author(s):  
Muhammad Usman ◽  
Yasir Hameed ◽  
Mukhtiar Ahmad ◽  
Muhammad Junaid Iqbal ◽  
Aghna Maryam ◽  
...  
Keyword(s):  
Immune Cells ◽  
Promoter Methylation ◽  
In Silico ◽  
Human Cancer ◽  
Enrichment Analysis ◽  
Genetic Alterations ◽  
Pathway Enrichment Analysis ◽  
Human Cancers ◽  
Tumor Purity

Aims: This study was launched to identify the SHMT2 associated Human Cancer subtypes. Background: Cancer is the 2nd leading cause of death worldwide. Previous reports revealed the limited involvement of SHMT2 in human cancer. In the current study, we comprehensively analyzed the role of SHMT2 in 24 major subtypes of human cancers using in silico approach and identified a few subtypes that are mainly associated with SHMT2. Objective:: We aim to comprehensively analyze the role of SHMT2 in 24 major subtypes of human cancers using in silico approach and identified a few subtypes that are mainly associated with SHMT2. Earlier, limited knowledge exists in the medical literature regarding the involvement of Serine Hydroxymethyltransferase 2 (SHMT2) in human cancer. Methods: In the current study, we comprehensively analyzed the role of SHMT2 in 24 major subtypes of human cancers using in silico approach and identified a few subtypes that are mainly associated with SHMT2. Pan-cancer transcriptional expression profiling of SHMT2 was done using UALCAN while further validation was performed using GENT2. For translational profiling of SHMT2, we utilized Human Protein Atlas (HPA) platform. Promoter methylation, genetic alteration, and copy number variations (CNVs) profiles were analyzed through MEXPRESS and cBioPortal. Survival analysis was carried out through Kaplan–Meier (KM) plotter platform. Pathway enrichment analysis of SHMT2 was performed using DAVID, while the gene-drug network was drawn through CTD and Cytoscape. Furthermore, in the tumor microenvironment, a correlation between tumor purity, CD8+ T immune cells infiltration, and SHMT2 expression was accessed using TIMER. Results: SHMT2 was found overexpressed in 24 different subtypes of human cancers and its overexpression was significantly associated with the reduced Overall survival (OS) and Relapse-free survival durations of Breast cancer (BRCA), Kidney renal papillary cell carcinoma (KIRP), Liver hepatocellular carcinoma (LIHC), and Lung adenocarcinoma (LUAD) patients. This implies that SHMT2 plays a significant role in the development and progression of these cancers. We further noticed that SHMT2 was also up-regulated in BRCA, KIRP, LIHC, and LUAD patients of different clinicopathological features. Pathways enrichment analysis revealed the involvement of SHMT2 enriched genes in five diverse pathways. Furthermore, we also explored some interesting correlations between SHMT2 expression and promoter methylation, genetic alterations, CNVs, tumor purity, and CD8+ T immune cell infiltrates. Conclusion: Our results suggested that overexpressed SHMT2 is correlated with the reduced OS and RFS of the BRCA, KIRP, LIHC, and LUAD patients and can be a potential diagnostic and prognostic biomarker for these cancers.

A Method of Pathway Enrichment Analysis Based Gene Expression Variability

2013 ◽  
Vol 40 (12) ◽  
pp. 1256
Author(s):  
XiaoDong JIA ◽  
XiuJie CHEN ◽  
Xin WU ◽  
JianKai XU ◽  
FuJian TAN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Expression Variability ◽  
Pathway Enrichment

Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

2019 ◽  
Vol 22 (6) ◽  
pp. 411-420 ◽  
Author(s):  
Xian-Jun Wu ◽  
Xin-Bin Zhou ◽  
Chen Chen ◽  
Wei Mao
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Pathway Enrichment ◽  
Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

Determination of Usnic Acid Responsive miRNAs in Breast Cancer Cell Lines

2019 ◽  
Vol 19 (12) ◽  
pp. 1463-1472 ◽  
Author(s):  
Nil Kiliç ◽  
Yasemin Ö. Islakoğlu ◽  
İlker Büyük ◽  
Bala Gür-Dedeoğlu ◽  
Demet Cansaran-Duman
Keyword(s):  
Breast Cancer ◽  
Hedgehog Signaling ◽  
Treatment Options ◽  
Usnic Acid ◽  
Enrichment Analysis ◽  
Breast Cancer Cell Lines ◽  
Pathway Enrichment Analysis ◽  
Molecular Heterogeneity ◽  
Proliferative Effect ◽  
Mcf 7

Objective: Breast Cancer (BC) is the most common type of cancer diagnosed in women. A common treatment strategy for BC is still not available because of its molecular heterogeneity and resistance is developed in most of the patients through the course of treatment. Therefore, alternative medicine resources as being novel treatment options are needed to be used for the treatment of BC. Usnic Acid (UA) that is one of the secondary metabolites of lichens used for different purposes in the field of medicine and its anti-proliferative effect has been shown in certain cancer types, suggesting its potential use for the treatment. Methods: Anti-proliferative effect of UA in BC cells (MDA-MB-231, MCF-7, BT-474) was identified through MTT analysis. Microarray analysis was performed in cells treated with the effective concentration of UA and UA-responsive miRNAs were detected. Their targets and the pathways that they involve were determined using a miRNA target prediction tool. Results: Microarray experiments showed that 67 miRNAs were specifically responsive to UA in MDA-MB-231 cells while 15 and 8 were specific to BT-474 and MCF-7 cells, respectively. The miRNA targets were mostly found to play role in Hedgehog signaling pathway. TGF-Beta, MAPK and apoptosis pathways were also the prominent ones according to the miRNA enrichment analysis. Conclusion: The current study is important as being the first study in the literature which aimed to explore the UA related miRNAs, their targets and molecular pathways that may have roles in the BC. The results of pathway enrichment analysis and anti-proliferative effects of UA support the idea that UA might be used as a potential alternative therapeutic agent for BC treatment.

scholarly journals Signature RNAS and related regulatory roles in type 1 diabetes mellitus based on competing endogenous RNA regulatory network analysis

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Qinghong Shi ◽  
Hanxin Yao
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Network Analysis ◽  
Type 1 Diabetes Mellitus ◽  
Regulatory Network ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Competing Endogenous Rna ◽  
Pathway Enrichment

Abstract Background Our study aimed to investigate signature RNAs and their potential roles in type 1 diabetes mellitus (T1DM) using a competing endogenous RNA regulatory network analysis. Methods Expression profiles of GSE55100, deposited from peripheral blood mononuclear cells of 12 T1DM patients and 10 normal controls, were downloaded from the Gene Expression Omnibus to uncover differentially expressed long non-coding RNAs (lncRNAs), mRNAs, and microRNAs (miRNAs). The ceRNA regulatory network was constructed, then functional and pathway enrichment analysis was conducted. AT1DM-related ceRNA regulatory network was established based on the Human microRNA Disease Database to carry out pathway enrichment analysis. Meanwhile, the T1DM-related pathways were retrieved from the Comparative Toxicogenomics Database (CTD). Results In total, 847 mRNAs, 41 lncRNAs, and 38 miRNAs were significantly differentially expressed. The ceRNA regulatory network consisted of 12 lncRNAs, 10 miRNAs, and 24 mRNAs. Two miRNAs (hsa-miR-181a and hsa-miR-1275) were screened as T1DM-related miRNAs to build the T1DM-related ceRNA regulatory network, in which genes were considerably enriched in seven pathways. Moreover, three overlapping pathways, including the phosphatidylinositol signaling system (involving PIP4K2A, INPP4A, PIP4K2C, and CALM1); dopaminergic synapse (involving CALM1 and PPP2R5C); and the insulin signaling pathway (involving CBLB and CALM1) were revealed by comparing with T1DM-related pathways in the CTD, which involved four lncRNAs (LINC01278, TRG-AS1, MIAT, and GAS5-AS1). Conclusion The identified signature RNAs may serve as important regulators in the pathogenesis of T1DM.

scholarly journals Plasma Metabolome Profiling Identifies Metabolic Subtypes of Pancreatic Ductal Adenocarcinoma

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1821
Author(s):  
Ujjwal Mukund Mahajan ◽  
Ahmed Alnatsha ◽  
Qi Li ◽  
Bettina Oehrle ◽  
Frank-Ulrich Weiss ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Enrichment Analysis ◽  
Response Prediction ◽  
Ductal Adenocarcinoma ◽  
Pathway Enrichment Analysis ◽  
Metabolome Analysis ◽  
Dismal Prognosis ◽  
Chemotherapeutic Response ◽  
Plasma Metabolome ◽  
Metabolome Profiling

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Developing biomarkers for early detection and chemotherapeutic response prediction is crucial to improve the dismal prognosis of PDAC patients. However, molecular cancer signatures based on transcriptome analysis do not reflect intratumoral heterogeneity. To explore a more accurate stratification of PDAC phenotypes in an easily accessible matrix, plasma metabolome analysis using MxP® Global Profiling and MxP® Lipidomics was performed in 361 PDAC patients. We identified three metabolic PDAC subtypes associated with distinct complex lipid patterns. Subtype 1 was associated with reduced ceramide levels and a strong enrichment of triacylglycerols. Subtype 2 demonstrated increased abundance of ceramides, sphingomyelin and other complex sphingolipids, whereas subtype 3 showed decreased levels of sphingolipid metabolites in plasma. Pathway enrichment analysis revealed that sphingolipid-related pathways differ most among subtypes. Weighted correlation network analysis (WGCNA) implied PDAC subtypes differed in their metabolic programs. Interestingly, a reduced expression among related pathway genes in tumor tissue was associated with the lowest survival rate. However, our metabolic PDAC subtypes did not show any correlation to the described molecular PDAC subtypes. Our findings pave the way for further studies investigating sphingolipids metabolisms in PDAC.

scholarly journals Lipidomics profiling of goose granulosa cell model of stearoyl-CoA desaturase function identifies a pattern of lipid droplets associated with follicle development

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Yuan ◽  
Shenqiang Hu ◽  
Liang Li ◽  
Chunchun Han ◽  
Hehe Liu ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Lipid Droplets ◽  
Cell Model ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Follicle Development ◽  
Microscopy Analysis ◽  
Stearoyl Coa Desaturase ◽  
Underlying Mechanisms

Abstract Background Despite their important functions and nearly ubiquitous presence in cells, an understanding of the biology of intracellular lipid droplets (LDs) in goose follicle development remains limited. An integrated study of lipidomic and transcriptomic analyses was performed in a cellular model of stearoyl-CoA desaturase (SCD) function, to determine the effects of intracellular LDs on follicle development in geese. Results Numerous internalized LDs, which were generally spherical in shape, were dispersed throughout the cytoplasm of granulosa cells (GCs), as determined using confocal microscopy analysis, with altered SCD expression affecting LD content. GC lipidomic profiling showed that the majority of the differentially abundant lipid classes were glycerophospholipids, including PA, PC, PE, PG, PI, and PS, and glycerolipids, including DG and TG, which enriched glycerophospholipid, sphingolipid, and glycerolipid metabolisms. Furthermore, transcriptomics identified differentially expressed genes (DEGs), some of which were assigned to lipid-related Gene Ontology slim terms. More DEGs were assigned in the SCD-knockdown group than in the SCD-overexpression group. Integration of the significant differentially expressed genes and lipids based on pathway enrichment analysis identified potentially targetable pathways related to glycerolipid/glycerophospholipid metabolism. Conclusions This study demonstrated the importance of lipids in understanding follicle development, thus providing a potential foundation to decipher the underlying mechanisms of lipid-mediated follicle development.

scholarly journals Systematic assessment of gene co-regulation within chromatin domains determines differentially active domains across human cancers

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Marie Zufferey ◽  
Yuanlong Liu ◽  
Daniele Tavernari ◽  
Marco Mina ◽  
Giovanni Ciriello
Keyword(s):  
Complementary Information ◽  
Chromatin Domains ◽  
Algorithmic Approach ◽  
Systematic Assessment ◽  
Regulatory Interactions ◽  
Human Cancers ◽  
Domain Boundaries ◽  
Gene Regulatory ◽  
Systematic Identification ◽  
The Relationship

Abstract Background Spatial interactions and insulation of chromatin regions are associated with transcriptional regulation. Domains of frequent chromatin contacts are proposed as functional units, favoring and delimiting gene regulatory interactions. However, contrasting evidence supports the association between chromatin domains and transcription. Result Here, we assess gene co-regulation in chromatin domains across multiple human cancers, which exhibit great transcriptional heterogeneity. Across all datasets, gene co-regulation is observed only within a small yet significant number of chromatin domains. We design an algorithmic approach to identify differentially active domains (DADo) between two conditions and show that these provide complementary information to differentially expressed genes. Domains comprising co-regulated genes are enriched in the less active B sub-compartments and for genes with similar function. Notably, differential activation of chromatin domains is not associated with major changes of domain boundaries, but rather with changes of sub-compartments and intra-domain contacts. Conclusion Overall, gene co-regulation is observed only in a minority of chromatin domains, whose systematic identification will help unravel the relationship between chromatin structure and transcription.

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