Molecular characterization, biological function, tumor microenvironment association and clinical significance of m6A regulators in lung adenocarcinoma

2020 ◽  
Author(s):  
Yin Li ◽  
Jie Gu ◽  
Fengkai Xu ◽  
Qiaoliang Zhu ◽  
Yiwei Chen ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Web Application ◽  
Molecular Mechanisms ◽  
Treatment Strategies ◽  
Interaction Network ◽  
Pathway Interaction ◽  
Clinical Benefits ◽  
Pathway Interaction Network ◽  
Scoring Tool

Abstract N6-methyladenosine (m6A) modification can regulate a variety of biological processes. However, the implications of m6A modification in lung adenocarcinoma (LUAD) remain largely unknown. Here, we systematically evaluated the m6A modification features in more than 2400 LUAD samples by analyzing the multi-omics features of 23 m6A regulators. We depicted the genetic variation features of m6A regulators, and found mutations of FTO and YTHDF3 were linked to worse overall survival. Many m6A regulators were aberrantly expressed in tumors, among which FTO, IGF2BP3, YTHDF1 and RBM15 showed consistent alteration features across 11 independent cohorts. Besides, the regulator-pathway interaction network demonstrated that m6A modification was associated with various biological pathways, including immune-related pathways. The correlation between m6A regulators and tumor microenvironment was also assessed. We found that LRPPRC was negatively correlated with most tumor-infiltrating immune cells. On the other hand, we established a scoring tool named m6Sig, which was positively correlated with PD-L1 expression and could reflect both the tumor microenvironment characterization and prognosis of LUAD patients. Comparison of CNV between high and low m6Sig groups revealed differences on chromosome 7. Application of m6Sig on an anti-PD-L1 immunotherapy cohort confirmed that the high m6Sig group demonstrated therapeutic advantages and clinical benefits. Our study indicated that m6A modification is involved in many aspects of LUAD and contributes to tumor microenvironment formation. A better understanding of m6A modification will provide more insights into the molecular mechanisms of LUAD and facilitate developing more effective personalized treatment strategies. A web application was built along with this study (http://www.bioinfo-zs.com/luadexpress/).

scholarly journals Modulatory Effects of Circadian Rhythms in the Lung Adenocarcinoma Tumor Microenvironment

2021 ◽  
Author(s):  
Qianzhun Huang ◽  
Xiaoyang Su ◽  
Ning Fang ◽  
Jian Huang
Keyword(s):  
Tumor Microenvironment ◽  
Circadian Rhythms ◽  
Lung Adenocarcinoma ◽  
Circadian Clock ◽  
Drug Sensitivity ◽  
Molecular Mechanisms ◽  
Clock Genes ◽  
Functional Enrichment ◽  
Expression Levels ◽  
Circadian Clock Genes

Abstract Background: Dysregulated circadian dynamic balance is strongly associated with cancer development. However, biological functions of circadian rhythms in lung adenocarcinoma (LUAD) have not been elucidated. This study aimed at valuating the modulatory effects of circadian rhythms in the LUAD tumor microenvironment.Methods: Multiple open-source bioinformatics research platforms are used to comprehensively elucidate the expression level, prognosis, potential biological function, drug sensitivity, and immune microenvironment of circadian clock genes in LUAD.Results: Most circadian clock genes in LUAD are dysregulated and are strongly correlated with patient prognosis, and missense mutations at splicing sites of these genes. Besides, these genes are closely associated with some well-known cancer-related marker pathways, which are mainly involved in the inhibition of the Apoptosis, Cell cycle, and DNA Damage Response Pathway. Furthermore, functional enrichment analysis revealedthat circadian clock genes regulate transcription factor activities and circadian rhythms in LUAD tissues. As for drug sensitivity, high expression of CLOCK, CRY1, and NR1D2 as well as suppressedPER2 and CRY2 expression levels are associated with drug resistance. The expression levels of circadian clock genes in LUAD correlate with immune infiltration and are involved in the regulation of immunosuppression.Conclusions: Our multi-omics analysis provides a more comprehensive understanding of the molecular mechanisms of the circadian clock genes in LUAD and provides new insights for a more precise screening of prognostic biomarkers and immunotherapy.

scholarly journals Cooperative driver pathway discovery via fusion of multi-relational data of genes, miRNAs and pathways

2020 ◽  
Author(s):  
Jun Wang ◽  
Ziying Yang ◽  
Carlotta Domeniconi ◽  
Xiangliang Zhang ◽  
Guoxian Yu
Keyword(s):  
Heterogeneous Network ◽  
Characteristic Curve ◽  
Interaction Network ◽  
The Cancer Genome Atlas ◽  
Driver Genes ◽  
Cancer Data ◽  
Pathway Interaction ◽  
Target Disease ◽  
Driver Pathway ◽  
Pathway Interaction Network

Abstract Discovering driver pathways is an essential step to uncover the molecular mechanism underlying cancer and to explore precise treatments for cancer patients. However, due to the difficulties of mapping genes to pathways and the limited knowledge about pathway interactions, most previous work focus on identifying individual pathways. In practice, two (or even more) pathways interplay and often cooperatively trigger cancer. In this study, we proposed a new approach called CDPathway to discover cooperative driver pathways. First, CDPathway introduces a driver impact quantification function to quantify the driver weight of each gene. CDPathway assumes that genes with larger weights contribute more to the occurrence of the target disease and identifies them as candidate driver genes. Next, it constructs a heterogeneous network composed of genes, miRNAs and pathways nodes based on the known intra(inter)-relations between them and assigns the quantified driver weights to gene–pathway and gene–miRNA relational edges. To transfer driver impacts of genes to pathway interaction pairs, CDPathway collaboratively factorizes the weighted adjacency matrices of the heterogeneous network to explore the latent relations between genes, miRNAs and pathways. After this, it reconstructs the pathway interaction network and identifies the pathway pairs with maximal interactive and driver weights as cooperative driver pathways. Experimental results on the breast, uterine corpus endometrial carcinoma and ovarian cancer data from The Cancer Genome Atlas show that CDPathway can effectively identify candidate driver genes [area under the receiver operating characteristic curve (AUROC) of $\geq $0.9] and reconstruct the pathway interaction network (AUROC of>0.9), and it uncovers much more known (potential) driver genes than other competitive methods. In addition, CDPathway identifies 150% more driver pathways and 60% more potential cooperative driver pathways than the competing methods. The code of CDPathway is available at http://mlda.swu.edu.cn/codes.php?name=CDPathway.

scholarly journals Predicting the Mechanism of the Analgesic Property of Yanhusuo Based on Network Pharmacology

2019 ◽  
Vol 14 (10) ◽  
pp. 1934578X1988307
Author(s):  
Wen-Ping Xiao ◽  
Yan-Fang Yang ◽  
He-Zhen Wu ◽  
Yi-yi Xiong
Keyword(s):  
Molecular Docking ◽  
Metabolic Pathways ◽  
Interaction Network ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Active Components ◽  
Network Diagram ◽  
Pathway Interaction ◽  
Pathway Interaction Network ◽  
Pathway Analyses

Yanhusuo (Corydalis Rhizoma) extracts are widely used for the treatment of pain and inflammation. The effects of Yanhusuo in pain assays were assessed in a few studies. However, there are few studies on its analgesic mechanism. In this paper, network pharmacology was used to explore the analgesic components of Yanhusuo and its analgesic mechanism. The active components of Yanhusuo were screened by TCMSP database, combined with literature data. PharmMapper and GeneCards databases were used for screening the analgesic targets of the components. The protein interaction network diagram was drawn by String database and Cytoscape software, the gene ontology and KEGG pathway analyses of the target were performed by DAVID database, and the component–target–pathway interaction network diagram was further drawn by Cytoscape3.6.1 software. System Dock Web Site verified the molecular docking among components and targets. Finally, an interaction network of the component–target–pathway of Yanhusuo was constructed, and the functions and pathways were analyzed for preliminarily investigating the mechanism of Yanhusuo in analgesia. The results showed that the active components of analgesic in Yanhusuo were Corynoline, 13-methylpalmatrubine, dehydrocorydaline, saulatine, 2,3,9,10-tetramethoxy-13-methyl-5,6-dihydroisoquinolino[2,1-b]isoquinolin-8-on-e, and Capaurine. The mechanisms were involved in metabolic pathways, PI3k-Akt signaling pathway, pathways in cancer, and so on. The top 3 targets were NOS3, glucose-6-phosphate dehydrogenase, and glucose-6-phosphate isomerase in components-target-pathways network, and they were all enriched in metabolic pathways. Meanwhile the molecular docking showed that there was a high binding activity between the 6 components and the important target proteins, as a further certification for the subsequent network analysis. This study reveals the relationship of the components, targets, and pathways of active components in Yanhusuo, and provides new ideas and methods for further research on the analgesic mechanism of Yanhusuo.

scholarly journals Use of bioinformatic analyses in identifying characteristic genes and mechanisms active in the progression of idiopathic thrombocytopenic purpura in individuals with different phenotypes

2020 ◽  
Vol 48 (11) ◽  
pp. 030006052097143
Author(s):  
Mengyi Zhang ◽  
Binhan Guo
Keyword(s):  
Gene Expression ◽  
Idiopathic Thrombocytopenic Purpura ◽  
Molecular Mechanisms ◽  
Treatment Strategies ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Newly Diagnosed ◽  
Thrombocytopenic Purpura ◽  
Protein Protein Interaction

Objective To explore the mechanism underlying the progression of newly diagnosed idiopathic thrombocytopenic purpura (ITP) to its chronic or remission state using bioinformatic methods. Methods GSE56232 and GSE46922 gene expression profile datasets were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes were identified and characteristic genes were screened by weighted gene co-expression network analysis. These genes were used for function enrichment analysis and construction of a protein–protein interaction network. Finally, characteristic genes were verified to determine potential molecular mechanisms underlying ITP progression. Results We found that characteristic genes in the chronic ITP group were mainly involved in intracellular processes and ion binding, while characteristic genes in the remission ITP group were involved in intracellular processes and nuclear physiological activities. We identified a sub-network of characteristic genes, LMNA, JUN, PRKACG, SMC3, which may indicate the mechanism by which newly diagnosed ITP progresses to chronic. Although no meaningful signaling pathways were found, the expression of NR3C1, TPR, SMC4, PANBP2, CHD1, and U2SURP may affect ITP progression from newly diagnosed to remission. Conclusion Our findings improve the understanding of the pathogenesis and progression of ITP, and may provide new directions for the development of treatment strategies.

scholarly journals Pathway Interaction Network Analysis Identifies Dysregulated Pathways in Human Monocytes Infected by Listeria monocytogenes

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Wufeng Fan ◽  
Yuhan Zhou ◽  
Hao Li
Keyword(s):  
Listeria Monocytogenes ◽  
Rna Polymerase ◽  
Rna Polymerase Ii ◽  
Interaction Network ◽  
Principal Component ◽  
Centrality Measures ◽  
Network Centrality ◽  
Human Monocytes ◽  
Pathway Interaction ◽  
Pathway Interaction Network

In our study, we aimed to extract dysregulated pathways in human monocytes infected by Listeria monocytogenes (LM) based on pathway interaction network (PIN) which presented the functional dependency between pathways. After genes were aligned to the pathways, principal component analysis (PCA) was used to calculate the pathway activity for each pathway, followed by detecting seed pathway. A PIN was constructed based on gene expression profile, protein-protein interactions (PPIs), and cellular pathways. Identifying dysregulated pathways from the PIN was performed relying on seed pathway and classification accuracy. To evaluate whether the PIN method was feasible or not, we compared the introduced method with standard network centrality measures. The pathway of RNA polymerase II pretranscription events was selected as the seed pathway. Taking this seed pathway as start, one pathway set (9 dysregulated pathways) with AUC score of 1.00 was identified. Among the 5 hub pathways obtained using standard network centrality measures, 4 pathways were the common ones between the two methods. RNA polymerase II transcription and DNA replication owned a higher number of pathway genes and DEGs. These dysregulated pathways work together to influence the progression of LM infection, and they will be available as biomarkers to diagnose LM infection.

scholarly journals Integrated Network and Gene Ontology Analysis Identifies Key Genes and Pathways for Coronary Artery Diseases

2020 ◽  
Author(s):  
Tejaswini Prakash ◽  
Nallur B Ramachandra
Keyword(s):  
Gene Ontology ◽  
Coronary Artery ◽  
Molecular Mechanisms ◽  
Foam Cell ◽  
Treatment Strategies ◽  
Specific Treatment ◽  
Interaction Network ◽  
Fibrin Clot ◽  
Potential Candidate ◽  
Integrated Network

Background: The prevalence of Coronary Artery Disease (CAD) in developing countries is on the rise, owing to rapidly changing lifestyle. Therefore, it is imperative that the underlying genetic and molecular mechanisms be understood to develop specific treatment strategies. Comprehensive disease network and Gene Ontology (GO) studies aid in prioritizing potential candidate genes for CAD and also give insights into gene function by establishing gene and disease pathway relationships. Methods: In the present study, CAD-associated genes were collated from different data sources and protein-protein interaction network was constructed using STRING. Highly interconnected network clusters were inferred and GO analysis was performed. Results: Interrelation between genes and pathways were analyzed on ClueGO and 38 candidates were identified from 1475 CAD-associated genes, which were significantly enriched in CAD-related pathways such as metabolism and regulation of lipid molecules, platelet activation, macrophage derived foam cell differentiation, and blood coagulation and fibrin clot formation. Discussion: Integrated network and ontology analysis enables biomarker prioritization for common complex diseases such as CAD. Experimental validation and future studies on the prioritized genes may reveal valuable insights into CAD development mechanism and targeted treatment strategies.

scholarly journals DNA Methylation Regulator-Meditated Modification Patterns Define the Distinct Tumor Microenvironment in Lung Adenocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Didi Yuan ◽  
Zehong Wei ◽  
Yicheng Wang ◽  
Fang Cheng ◽  
Yujie Zeng ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Cancer Progression ◽  
Molecular Mechanisms ◽  
Immune Cell ◽  
Global Analysis ◽  
Mutation Burden ◽  
Methylation Score ◽  
Methylation Patterns

BackgroundEpigenetic changes of lung adenocarcinoma (LUAD) have been reported to be a relevant factor in tumorigenesis and cancer progression. However, the molecular mechanisms responsible for DNA methylation patterns in the tumor immune-infiltrating microenvironment and in cancer immunotherapy remain unclear.MethodsWe conducted a global analysis of the DNA methylation modification pattern (DMP) and immune cell-infiltrating characteristics of LUAD patients based on 21 DNA methylation regulators. A DNA methylation score (DMS) system was constructed to quantify the DMP model in each patient and estimate their potential benefit from immunotherapy.ResultsTwo DNA methylation modification patterns able to distinctly characterize the immune microenvironment characterization were identified among 513 LUAD samples. A lower DMS, characterized by increased CTLA-4/PD-1/L1 gene expression, greater methylation modifications, and tumor mutation burden, characterized a noninflamed phenotype with worse survival. A higher DMS, characterized by decreased methylation modification, a greater stromal-relevant response, and immune hyperactivation, characterized an inflamed phenotype with better prognosis. Moreover, a lower DMS indicated an increased mutation load and exhibited a poor immunotherapeutic response in the anti-CTLA-4/PD-1/PD-L1 cohort.ConclusionEvaluating the DNA methylation modification pattern of LUAD patients could enhance our understanding of the features of tumor microenvironment characterization and may promote more favorable immunotherapy strategies.

scholarly journals High Expression of UBB, RAC1, and ITGB1 Predicts Worse Prognosis among Nonsmoking Patients with Lung Adenocarcinoma through Bioinformatics Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Huan Deng ◽  
Yichao Huang ◽  
Li Wang ◽  
Ming Chen
Keyword(s):  
Extracellular Matrix ◽  
Lung Adenocarcinoma ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Indicators ◽  
Hub Genes ◽  
Go Enrichment

Purpose. The molecular mechanism underlying the tumorigenesis and progression of lung adenocarcinoma (LUAD) in nonsmoking patients remains unclear. This study was conducted to select crucial therapeutic and prognostic biomarkers for nonsmoking patients with LUAD. Methods. Microarray datasets from the Gene Expression Omnibus (GSE32863 and GSE75037) were analyzed for differentially expressed genes (DEGs). Gene Ontology (GO) enrichment analysis of DEGs was performed, and protein-protein interaction network was then constructed using the Search Tool for the Retrieval of Interacting Genes and Cytoscape. Hub genes were then identified by the rank of degree. Overall survival (OS) analyses of hub genes were performed among nonsmoking patients with LUAD in Kaplan-Meier plotter. The Cancer Genome Atlas (TCGA) and The Human Protein Atlas (THPA) databases were applied to verify hub genes. In addition, we performed Gene Set Enrichment Analysis (GSEA) of hub genes. Results. We identified 1283 DEGs, including 743 downregulated and 540 upregulated genes. GO enrichment analyses showed that DEGs were significantly enriched in collagen-containing extracellular matrix and extracellular matrix organization. Moreover, 19 hub genes were identified, and 12 hub genes were closely associated with OS. Although no obvious difference was detected in ITGB1, the downregulation of UBB and upregulation of RAC1 were observed in LUAD tissues of nonsmoking patients. Immunohistochemistry in THPA database confirmed that UBB and ITGB1 were downregulated, while RAC1 was upregulated in LUAD. GSEA suggested that ribosome, B cell receptor signaling pathway, and cell cycle were associated with UBB, RAC1, and ITGB1 expression, respectively. Conclusions. Our study provides insights into the underlying molecular mechanisms of the carcinogenesis and progression of LUAD in nonsmoking patients and demonstrated UBB, RAC1, and ITGB1 as therapeutic and prognostic indicators for nonsmoking LUAD. This is the first study to report the crucial role of UBB in nonsmoking LUAD.

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