Multiomics analysis identifies key genes and pathways related to N6-methyladenosine RNA modification in ovarian cancer

Epigenomics ◽  
2021 ◽  
Author(s):  
Haoya Xu ◽  
Xianli Li ◽  
Shengtan Wang ◽  
Feifei Li ◽  
Jian Gao ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Target Genes ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Rna Modification ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Patient Prognosis

Aims: To explore the pathways and target genes related to N6-methyladenosine (m6A) methylation in ovarian cancer and their effect on patient prognosis. Methods & materials: The Cancer Genome Atlas was used to screen genes related to m6A regulators in terms of gene expression, mutation and copy number variation. These genes were subjected to pathway enrichment analysis. Prognosis-related genes were screened and involved in risk signature construction. Immunohistochemistry was used for verification. Results: We obtained 1408 genes dysregulated in parallel to m6A regulators, which were mainly involved in the platelet activation pathway. The m6A-related signature was constructed based on the expression of four prognosis-related genes ( RPS6KA2, JUNB, HNF4A and P2RX1). Conclusion: This work provides new insights into the mechanism of m6A methylation in ovarian cancer.

scholarly journals Identification of Key miRNAs in the Treatment of Dabrafenib-Resistant Melanoma

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Guangyu Gao ◽  
Zhen Yao ◽  
Jiaofeng Shen ◽  
Yulong Liu
Keyword(s):  
Drug Resistance ◽  
Molecular Mechanism ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
Obvious Association

Dabrafenib resistance is a significant problem in melanoma, and its underlying molecular mechanism is still unclear. The purpose of this study is to research the molecular mechanism of drug resistance of dabrafenib and to explore the key genes and pathways that mediate drug resistance in melanoma. GSE117666 was downloaded from the Gene Expression Omnibus (GEO) database and 492 melanoma statistics were also downloaded from The Cancer Genome Atlas (TCGA) database. Besides, differentially expressed miRNAs (DEMs) were identified by taking advantage of the R software and GEO2R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) and FunRich was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to identify potential pathways and functional annotations linked with melanoma chemoresistance. 9 DEMs and 872 mRNAs were selected after filtering. Then, target genes were uploaded to Metascape to construct protein-protein interaction (PPI) network. Also, 6 hub mRNAs were screened after performing the PPI network. Furthermore, a total of 4 out of 9 miRNAs had an obvious association with the survival rate ( P < 0.05 ) and showed a good power of risk prediction model of over survival. The present research may provide a deeper understanding of regulatory genes of dabrafenib resistance in melanoma.

scholarly journals Gene Expression Profile of Active HE4 Stimulation in Epithelial Ovarian Cancer Cells: Microarray Study and Comprehensive Bioinformatics Analysis

2020 ◽  
Author(s):  
Liancheng Zhu ◽  
Mingzi Tan ◽  
Haoya Xu ◽  
Bei Lin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Clinical Significance ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Coexpression Analysis ◽  
Pathway Enrichment

Abstract Background.Human Epididymis Protein 4 (HE4) is a novel serum biomarker for diagnosis of epithelial ovarian cancer (EOC) with high specificity and sensitivity compared with CA125, and the increasing researches have been carried out on its roles in promoting carcinogenesis and chemoresistance in EOC in recent years, however, its underlying molecular mechanisms remain poorly understood. The aim of this study was to elucidate the molecular mechanisms of HE4 stimulation and to identify the key genes and pathways mediating carcinogenesis in EOC using microarray and bioinformatics analysis.Methods. We established a stable HE4-silence ES-2 ovarian cancer cell line labeled as “S”, and its active HE4 protein stimulated cells labeled as “S4”. Human whole genome microarray analysis was used to identify deferentially expressed genes (DEGs) from triplicate samples of S4 and S cells. “clusterProfiler” package in R, DAVID, Metascape, and Gene Set Enrichment Analysis (GSEA) were used to perform gene ontology (GO) and pathway enrichment analysis, and cBioPortal for WFDC2 coexpression analysis. GEO dataset (GSE51088) and quantitative real-time polymerase chain reaction (qRT-PCR) was applied for validation. The protein–protein interaction (PPI) network and modular analyses were performed using Metascape and Cytoscape. Results.In total, 713 DEGs were found (164 up regulated and 549 down regulated) and further analyzed by GO, pathway enrichment and PPI analyses. We found that MAPK pathway accounted for a significant portion of the enriched terms. WFDC2 coexpression analysis revealed ten WFDC2 coexpressed genes (TMEM220A, SEC23A, FRMD6, PMP22, APBB2, DNAJB4, ERLIN1, ZEB1, RAB6B, and PLEKHF1) that were also dramatically changed in S4 cells and validated by dataset GSE51088. Kaplan–Meier survival statistics revealed clinical significance for all of the 10 target genes. Finally, PPI was constructed, sixteen hub genes and eight molecular complex detections (MCODEs) were identified, the seeds of five most significant MCODEs were subjected to GO and KEGG enrichment analysis and their clinical significance was evaluated.Conclusions.By applying microarray and bioinformatics analyses, we identified DEGs and determined a comprehensive gene network of active HE4 stimulation in EOC cells. We offered several possible mechanisms and identified therapeutic and prognostic targets of HE4 in EOC.

Gene expression profiles following active HE4 stimulation in epithelial ovarian cancer cells: microarray study and comprehensive bioinformatics analysis

2020 ◽  
Author(s):  
Liancheng Zhu ◽  
Mingzi Tan ◽  
Haoya Xu ◽  
Bei Lin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Coexpression Analysis ◽  
Pathway Enrichment

Abstract Background: Human epididymis protein 4 (HE4) is a novel serum biomarker for diagnosing epithelial ovarian cancer (EOC) with high specificity and sensitivity, compared with CA125. Recent studies have focused on the roles of HE4 in promoting carcinogenesis and chemoresistance in EOC; however, the molecular mechanisms underlying its action remain poorly understood. This study was conducted to determine the molecular mechanisms underlying HE4 stimulation and identifying key genes and pathways mediating carcinogenesis in EOC by microarray and bioinformatics analysis.Methods: We established a stable HE4-silenced ES-2 ovarian cancer cell line labeled as “S”; the S cells were stimulated with the active HE4 protein, yielding cells labeled as “S4”. Human whole-genome microarray analysis was used to identify differentially expressed genes (DEGs) in S4 and S cells. The “clusterProfiler” package in R, DAVID, Metascape, and Gene Set Enrichment Analysis were used to perform gene ontology (GO) and pathway enrichment analysis, and cBioPortal was used for WFDC2 coexpression analysis. The GEO dataset (GSE51088) and quantitative real-time polymerase chain reaction were used to validate the results. Protein–protein interaction (PPI) network and modular analyses were performed using Metascape and Cytoscape, respectively. Results: In total, 713 DEGs were identified (164 upregulated and 549 downregulated) and further analyzed by GO, pathway enrichment, and PPI analyses. We found that the MAPK pathway accounted for a significant large number of the enriched terms. WFDC2 coexpression analysis revealed ten WFDC2-coexpressed genes (TMEM220A, SEC23A, FRMD6, PMP22, APBB2, DNAJB4, ERLIN1, ZEB1, RAB6B, and PLEKHF1) whose expression levels were dramatically altered in S4 cells; this was validated using the GSE51088 dataset. Kaplan–Meier survival statistics revealed that all 10 target genes were clinically significant. Finally, in the PPI network, 16 hub genes and 8 molecular complex detections (MCODEs) were identified; the seeds of the five most significant MCODEs were subjected to GO and KEGG enrichment analyses and their clinical relevance was evaluated.Conclusions: Through microarray and bioinformatics analyses, we identified DEGs and determined a comprehensive gene network following active HE4 stimulation in EOC cells. We proposed several possible mechanisms underlying the action of HE4 and identified the therapeutic and prognostic targets of HE4 in EOC.

scholarly journals Inferring Homologous Recombination Deficiency of Ovarian Cancer From the Landscape of Copy Number Variation at Subchromosomal and Genetic Resolutions

2021 ◽  
Vol 11 ◽  
Author(s):  
Meng Zhang ◽  
Si-Cong Ma ◽  
Jia-Le Tan ◽  
Jian Wang ◽  
Xue Bai ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Homologous Recombination ◽  
Copy Number Variation ◽  
Copy Number ◽  
The Cancer Genome Atlas ◽  
Homologous Recombination Deficiency ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Tumor Types ◽  
Pan Cancer

BackgroundHomologous recombination deficiency (HRD) is characterized by overall genomic instability and has emerged as an indispensable therapeutic target across various tumor types, particularly in ovarian cancer (OV). Unfortunately, current detection assays are far from perfect for identifying every HRD patient. The purpose of this study was to infer HRD from the landscape of copy number variation (CNV).MethodsGenome-wide CNV landscape was measured in OV patients from the Australian Ovarian Cancer Study (AOCS) clinical cohort and &gt;10,000 patients across 33 tumor types from The Cancer Genome Atlas (TCGA). HRD-predictive CNVs at subchromosomal resolution were identified through exploratory analysis depicting the CNV landscape of HRD versus non-HRD OV patients and independently validated using TCGA and AOCS cohorts. Gene-level CNVs were further analyzed to explore their potential predictive significance for HRD across tumor types at genetic resolution.ResultsAt subchromosomal resolution, 8q24.2 amplification and 5q13.2 deletion were predominantly witnessed in HRD patients (both p &lt; 0.0001), whereas 19q12 amplification occurred mainly in non-HRD patients (p &lt; 0.0001), compared with their corresponding counterparts within TCGA-OV. The predictive significance of 8q24.2 amplification (p &lt; 0.0001), 5q13.2 deletion (p = 0.0056), and 19q12 amplification (p = 0.0034) was externally validated within AOCS. Remarkably, pan-cancer analysis confirmed a cross-tumor predictive role of 8q24.2 amplification for HRD (p &lt; 0.0001). Further analysis of CNV in 8q24.2 at genetic resolution revealed that amplifications of the oncogenes, MYC (p = 0.0001) and NDRG1 (p = 0.0004), located on this fragment were also associated with HRD in a pan-cancer manner.ConclusionsThe CNV landscape serves as a generalized predictor of HRD in cancer patients not limited to OV. The detection of CNV at subchromosomal or genetic resolution could aid in the personalized treatment of HRD patients.

scholarly journals Mechanism of YuPingFeng in the Treatment of COPD Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yunhong Yin ◽  
Jianyu Liu ◽  
Mengyu Zhang ◽  
Rui Li ◽  
Xiao Liu ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Signalling Pathways ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Herbal Formula ◽  
Pathway Enrichment ◽  
Topological Parameters

YuPingFeng (YPF) granules are a classic herbal formula extensively used in clinical practice in China for the treatment of COPD. However, the pathological mechanisms of YPF in COPD remain undefined. In the present research, a network pharmacology-based strategy was implemented to elucidate the underlying multicomponent, multitarget, and multipathway modes of action of YPF against COPD. First, we identified putative YPF targets based on TCMSP databases and constructed a network containing interactions between putative YPF targets and known therapeutic targets of COPD. Next, two topological parameters, “degree” and “closeness,” were calculated to identify target genes in the network. The major hubs were imported to the MetaCore database for pathway enrichment analysis. In total, 23 YPF active ingredients and 83 target genes associated with COPD were identified. Through protein interaction network analysis, 26 genes were identified as major hubs due to their topological importance. GO and KEGG enrichment analysis results revealed YPF to be mainly associated with the response to glucocorticoids and steroid hormones, with apoptotic and HIF-1 signalling pathways being dominant and correlative pathways. The promising utility of YPF in the treatment of COPD has been demonstrated by a network pharmacology approach.

Dysregulated microRNAs in laryngeal cancer: a comprehensive meta-analysis using a robust rank aggregation approach

2020 ◽  
Vol 16 (33) ◽  
pp. 2723-2734
Author(s):  
Zaizai Cao ◽  
Yu Guo ◽  
Yinjie Ao ◽  
Shuihong Zhou
Keyword(s):  
Target Genes ◽  
Laryngeal Squamous Cell Carcinoma ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Rank Aggregation ◽  
The Cancer Genome Atlas ◽  
Aggregation Method ◽  
Multiple Cancer ◽  
Cancer Genome Atlas ◽  
Genome Atlas

We need a reasonable method of compiling data from different studies regarding the expression of microRNA (miRNA) in laryngeal squamous cell carcinoma (LSCC). The robust rank aggregation method was used to integrate the rank lists of miRNAs from 11 studies. The enrichment analysis was performed on target genes of meta-signature miRNAs. The Cancer Genome Atlas database was used to confirm the results of meta-analysis. Three meta-signature miRNAs (miR-21-5p, miR-196a-5p and miR-145-5p) were obtained. All three miRNAs could be prognostic for LSCC. The enrichment analysis showed that these miRNAs were associated significantly with multiple cancer-related signaling pathways. The robust rank aggregation approach is an effective way to identify important miRNAs from different studies. All identified miRNAs could be candidates for LSCC diagnostic and prognostic biomarkers.

Genetic and epigenetic modifications of HPDL and SOX17 associated with breast cancer prognosis: a study based on The Cancer Genome Atlas

2020 ◽  
Author(s):  
Chundi Gao ◽  
Huayao Li ◽  
Cun Liu ◽  
Jibiao Wu ◽  
Chao Zhou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Molecular Mechanisms ◽  
Cpg Islands ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Expression Of Genes ◽  
Number Variation ◽  
Patient Prognosis

Abstract Background：The high heterogeneity of breast cancer (BRCA) makes it more challenging to interpret the genetic variation mechanisms involved in BRCA pathogenesis and prognosis. Areas with high DNA methylation (such as CpG islands) were accompanied by copy number variation (CNV), and these genomic variations affected the level of DNA methylation. Methods: In this study, we characterized inter-tumor heterogeneity and analyzed the effects of CNV on DNA methylation and gene expression. In addition, we performed a Genetic Set Enrichment Analysis (GSEA) to identify key pathways for changes between patients with low and high expression of genes. Results: Our analysis found that the CNV of HPDL and SOX17 is not only related to the patient's prognosis, but also related to gene methylation and expression levels affecting the patient's survival time. Conclusion: This study provided an effective bioinformatics basis for further exploration of molecular mechanisms related to BRCA and assessment of patient prognosis, but the development of biomarkers for diagnosis and treatment still requires further clinical data validation.

scholarly journals Novel Biomarker MicroRNAs for Subtyping of Acute Coronary Syndrome: A Bioinformatics Approach

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Yujie Zhu ◽  
Yuxin Lin ◽  
Wenying Yan ◽  
Zhandong Sun ◽  
Zhi Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Coronary Syndrome ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Pathway Enrichment Analysis ◽  
Biological Processes ◽  
Pathway Enrichment ◽  
Coronary Syndrome ◽  
Life Threatening

Acute coronary syndrome (ACS) is a life-threatening disease that affects more than half a million people in United States. We currently lack molecular biomarkers to distinguish the unstable angina (UA) and acute myocardial infarction (AMI), which are the two subtypes of ACS. MicroRNAs play significant roles in biological processes and serve as good candidates for biomarkers. In this work, we collected microRNA datasets from the Gene Expression Omnibus database and identified specific microRNAs in different subtypes and universal microRNAs in all subtypes based on our novel network-based bioinformatics approach. These microRNAs were studied for ACS association by pathway enrichment analysis of their target genes. AMI and UA were associated with 27 and 26 microRNAs, respectively, nine of them were detected for both AMI and UA, and five from each subtype had been reported previously. The remaining 22 and 21 microRNAs are novel microRNA biomarkers for AMI and UA, respectively. The findings are then supported by pathway enrichment analysis of the targets of these microRNAs. These novel microRNAs deserve further validation and will be helpful for personalized ACS diagnosis.

scholarly journals LncRNA HOTAIR promotes proliferation and inhibits apoptosis by sponging miR-214-3p in HPV16 positive cervical cancer cells

2021 ◽  
Author(s):  
Yu Zhou ◽  
Yuqing Wang ◽  
Mingying Lin ◽  
Daiqian Wu ◽  
Min Zhao
Keyword(s):  
Cervical Cancer ◽  
Cancer Cells ◽  
Signaling Pathway ◽  
Binding Sites ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Cervical Cancer Cells ◽  
Lncrna Hotair

Abstract Background Cervical cancer (CC) is one of the most common gynecological malignancies all around the world. The mechanisms of cervical carcinoma formation remain under close scrutiny. The long non-coding RNAs (lncRNA) and microRNAs (miRNAs) play important roles in controlling gene expression and promoting the development and progression of cervical cancer by acting as competitive endogenous RNA (ceRNA). However, the roles of lncRNA associated with ceRNAs in cervical carcinogenesis remains unknown. In this study, the expression of LncRNA HOTAIR was investigated in HPV16 positive cervical cancer cells, the candidate miRNAs and target genes were identified to clarify putative ceRNAs of HOTAIR/miRNA in cervical cancer cells. Methods The proliferate ability of cells was measured by CCK8 and EdU incorporation assays and cell apoptosis was analyzed by flow cytometry. The expression of HOTAIR, miR-214-3p, HPV16 E7 mRNA were detected by qRT-PCR. As for searching for the interaction between miR-214-3p and HOTAIR, the binding sites for miR-214-3p on HOTAIR was predicted by starbase v2.0 database, then dual-luciferase assay was used to verify the binding sites. In addition, Gene Ontology (GO) and protein-protein interaction (PPI) network analysis of target genes of miR-214-3p were performed with bioinformatics analysis. For potential signaling pathway regulated by miR-214-3p, we conducted pathway enrichment analysis by KEGG analysis and obtained key pathways in cervical cancer cells. Results Our results showed that the expression of HOTAIR was up-regulated, while that of miR-214-3p was down-regulated in HPV16-positive cervical cancer cells. The expression status of HPV16 E7 played an important role in regulating the expression of HOTAIR or miR-214-3p in cervical cancer cells. LncRNA HOTAIR knockdown could significantly inhibited cell proliferate ability and promote cellular apoptosis, whereas the inhibition of miR-214-3p expression partially reversed such results. Bioinformatics analysis identified 1451 genes as target genes of miR-214-3p. The Gene ontology (GO) and KEGG Pathway enrichment analysis showed that these target genes were mainly related to regulation of cell communication, protein binding, enzyme binding and transferase activity, and Wnt ligand biogenesis. Pathway enrichment analysis results showed that the predicted target genes were significantly enriched in Wnt/β-catenin signaling pathway. Finally, our results confirmed that miR-214-3p could significantly inhibit β-catenin expression in HPV16 positive cancer cells by qPCR and WB analysis. Conclusion HOTAIR could act as a ceRNA through binding to miR-214-3p, promote cell proliferation and inhibit the apoptosis of HPV16 positive cervical cancer. HOTAIR/miR-214-3p/Wnt/β-catenin signaling pathway might play important roles related with HPV16 positive cervical cancer. Our results provided a new perspective for identifying novel biomarkers for cervical cancer.

scholarly journals Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
G. Prashanth ◽  
Basavaraj Vastrad ◽  
Anandkumar Tengli ◽  
Chanabasayya Vastrad ◽  
Iranna Kotturshetti
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Pathway Enrichment ◽  
Drug Molecules

Abstract Background Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results A total of 820 DEGs were identified between healthy obese and metabolically unhealthy obese, among 409 up regulated and 411 down regulated genes. The GO enrichment analysis results showed that these DEGs were significantly enriched in ion transmembrane transport, intrinsic component of plasma membrane, transferase activity, transferring phosphorus-containing groups, cell adhesion, integral component of plasma membrane and signaling receptor binding, whereas, the REACTOME pathway enrichment analysis results showed that these DEGs were significantly enriched in integration of energy metabolism and extracellular matrix organization. The hub genes CEBPD, TP73, ESR2, TAB1, MAP 3K5, FN1, UBD, RUNX1, PIK3R2 and TNF, which might play an essential role in obesity associated type 2 diabetes mellitus was further screened. Conclusions The present study could deepen the understanding of the molecular mechanism of obesity associated type 2 diabetes mellitus, which could be useful in developing therapeutic targets for obesity associated type 2 diabetes mellitus.

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