scholarly journals Relationship Between Insulin Resistance and Endometrial Cancer: Determination of Key Genes and Pathways

2021 ◽  
Author(s):  
Dou-Dou Ding ◽  
Quan Zhou ◽  
Ze He ◽  
Hong-Xia He ◽  
Man-Zhen Zuo
Keyword(s):  
Insulin Resistance ◽  
Endometrial Cancer ◽  
Endometrial Carcinoma ◽  
Metabolic Diseases ◽  
Single Gene ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Analysis Tool ◽  
Key Genes

Abstract Introduction:Epidemiological studies have found that the occurrence of endometrial cancer(EC) is closely related to metabolic diseases, and insulin resistance (IR) plays an important role in the pathogenesis of endometrium, but the specific pathogenesis is still unclear. The purpose of this study is to reveal the relationship between insulin resistance and endothelial cells by gene screening technology. Material and methods:We analyzed one endometrial carcinoma database (GSE106191) and one insulin-resistant database (GSE63992), with Gene Expression Omnibus (GEO) database and Venny online analysis tool, then, we found an add-up to 148 different genes. Functional enrichment analysis of these genes using DAVID showed that they were participated in transcription factor activity,signaling pathways and response to factors, etc. Then used cytoHubba in Cytoscape,we got 25 hub genes.Results: The results showed that the survival time of OGT, IGSF3, TRO, NEURL2 and PIK3C2B was significantly and closely related to EC, and the percentage of gene changes of five central genes ranged from 3% to 10% of a single gene, was also related to the infiltration of seven kinds of immune cells in endometrial carcinoma.Conclusion:The five key genes (OGT,IGSF3, PIK3C2B,TRO and NEURL2) are involved in immune infiltration in the progression of endometrial carcinoma, and there is also a certain mutation probability in gene mutation. This may be the pathogenesis of insulin resistance and endometrial cancer.

scholarly journals Identification of key genes and biological processes contributing to colitis associated dysplasia in ulcerative colitis

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11321
Author(s):  
Di Zhang ◽  
Pengguang Yan ◽  
Taotao Han ◽  
Xiaoyun Cheng ◽  
Jingnan Li
Keyword(s):  
Ulcerative Colitis ◽  
Mitochondrial Dysfunction ◽  
Single Gene ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Junction ◽  
Biological Processes ◽  
Hub Genes ◽  
Key Genes

Background Ulcerative colitis-associated colorectal cancer (UC-CRC) is a life-threatening complication of ulcerative colitis (UC). The mechanisms underlying UC-CRC remain to be elucidated. The purpose of this study was to explore the key genes and biological processes contributing to colitis-associated dysplasia (CAD) or carcinogenesis in UC via database mining, thus offering opportunities for early prediction and intervention of UC-CRC. Methods Microarray datasets (GSE47908 and GSE87466) were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between groups of GSE47908 were identified using the “limma” R package. Weighted gene co-expression network analysis (WGCNA) based on DEGs between the CAD and control groups was conducted subsequently. Functional enrichment analysis was performed, and hub genes of selected modules were identified using the “clusterProfiler” R package. Single-gene gene set enrichment analysis (GSEA) was conducted to predict significant biological processes and pathways associated with the specified gene. Results Six functional modules were identified based on 4929 DEGs. Green and blue modules were selected because of their consistent correlation with UC and CAD, and the highest correlation coefficient with the progress of UC-associated carcinogenesis. Functional enrichment analysis revealed that genes of these two modules were significantly enriched in biological processes, including mitochondrial dysfunction, cell-cell junction, and immune responses. However, GSEA based on differential expression analysis between sporadic colorectal cancer (CRC) and normal controls from The Cancer Genome Atlas (TCGA) indicated that mitochondrial dysfunction may not be the major carcinogenic mechanism underlying sporadic CRC. Thirteen hub genes (SLC25A3, ACO2, AIFM1, ATP5A1, DLD, TFE3, UQCRC1, ADIPOR2, SLC35D1, TOR1AIP1, PRR5L, ATOX1, and DTX3) were identified. Their expression trends were validated in UC patients of GSE87466, and their potential carcinogenic effects in UC were supported by their known functions and other relevant studies reported in the literature. Single-gene GSEA indicated that biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to angiogenesis and immune response were positively correlated with the upregulation of TFE3, whereas those related to mitochondrial function and energy metabolism were negatively correlated with the upregulation of TFE3. Conclusions Using WGCNA, this study found two gene modules that were significantly correlated with CAD, of which 13 hub genes were identified as the potential key genes. The critical biological processes in which the genes of these two modules were significantly enriched include mitochondrial dysfunction, cell-cell junction, and immune responses. TFE3, a transcription factor related to mitochondrial function and cancers, may play a central role in UC-associated carcinogenesis.

scholarly journals Application of Bioinformatics Methods to Identify Key Genes and Functions in Chronic Pelvic Pain

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wenchao Sun ◽  
Qiji Ju
Keyword(s):  
Pelvic Pain ◽  
Chronic Pelvic Pain ◽  
Single Gene ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Receptor Interaction ◽  
Protein Protein Interaction ◽  
Key Genes

Neuropathologic pain (NPP) occurs in most patients with chronic pelvic pain (CPP), and the unique physiological characteristics of visceral sensory neurons make the current analgesic effect of CPP patients not optimistic. Therefore, this study explored the possible biological characteristics of key genes in CPP through the bioinformatics method. CPP-related dataset GSE131619 was downloaded from Gene Expression Omnibus to investigate the differentially expressed genes (DEGs) between lumbar dorsal root ganglia (DRG) and sacral DRG, and the functional enrichment analysis was performed. A protein-protein interaction (PPI) network was constructed to search subnet modules of specific biological processes, and then, the genes in the subnet were enriched by single gene set analysis. A CPP mouse model was established, and the expression of key genes were identified by qPCR. The results showed that 127 upregulated DEGs and 103 downregulated DEGs are identified. Functional enrichment analysis showed that most of the genes involved in signal transduction were involved in the pathway of receptor interaction. A subnet module related to neural signal regulation was identified in PPI, including CHRNB4, CHRNA3, and CHRNB2. All three genes were associated with neurological or inflammatory activity and are downregulated in the sacral spinal cord of CPP mice. This study provided three key candidate genes for CPP: CHRNB4, CHRNA3, and CHRNB2, which may be involved in the occurrence and development of CPP, and provided a powerful molecular target for the clinical diagnosis and treatment of CPP.

scholarly journals GOMA: functional enrichment analysis tool based on GO modules

2013 ◽  
Vol 32 (4) ◽  
pp. 195-204 ◽  
Author(s):  
Qiang Huang ◽  
Ling-Yun Wu ◽  
Yong Wang ◽  
Xiang-Sun Zhang
Keyword(s):  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Analysis Tool

scholarly journals Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

2020 ◽  
Vol 9 (2) ◽  
pp. LMT30
Author(s):  
Chuanli Ren ◽  
Weixiu Sun ◽  
Xu Lian ◽  
Chongxu Han
Keyword(s):  
Lung Adenocarcinoma ◽  
Differentially Expressed Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Kaplan Meier ◽  
Key Genes ◽  
Core Genes

Aim: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD). Materials & methods: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID. Results: Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD. Conclusion: 23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

scholarly journals The Expression and Prognostic Role of Peroxiredoxins in Lung Cancer

2019 ◽  
Author(s):  
Ben Li ◽  
Bo Zhang ◽  
Qiong Wu ◽  
Xinming Chen ◽  
Xiang Cao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Expression Level ◽  
Normal Lung ◽  
Lung Cells ◽  
Analysis Tool

Background: Peroxiredoxins (Prxs) comprise antioxidant factors that are widely found in prokaryotes and eukaryotes. Abnormal expression of Prxs is closely related to tumorigenesis. Methods: This study examined the prognostic value and expression of Prxs in lung cancer by Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, Kaplan-Meier Plotter, cBioPortal and Functional Enrichment Analysis Tool (FunRich) databases. Results: We found that Prx1/2/3/4/5 were overexpressed in both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) relative to normal lung cells. However, the expression level of Prx6 was lower in LUAD and higher in LUSC than normal lung cells. The level of Prx3 and Prx6 were associated with pathological stage. Prognostic analysis showed that elevated Prx1 and Prx2 expression were correlated with low Overall Survival (OS), whereas high Prx5 and Prx6 expression level predicted high OS. Conclusions: Our results effectively revealed the level of Prxs in lung cancer and its influence on the prognosis of lung carcinoma, contributing to the study of the role of Prxs in tumorigenesis.

scholarly journals Interaction Between Functionally Activate Endometrial Microbiota and Host Gene Regulation in Endometrial Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Peigen Chen ◽  
Yingchun Guo ◽  
Lei Jia ◽  
Jing Wan ◽  
TianTian He ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Normal Subjects ◽  
Functional Enrichment ◽  
Sialyl Lewis X ◽  
Human Host ◽  
Host Interaction ◽  
The Difference ◽  
And Migration

Objective: In this study, we mainly explored two questions: Which microorganisms were functionally active in the endometrium of patients with endometrial cancer (EC)? What kind of response did the human host respond to functionally active microorganisms?Methods: Nine endometrial cancer patients and eight normal subjects were included in this study. HMP Unified Metabolic Analysis Network 3 (HUMAnN3) was used to obtain functional information of microorganisms. In addition, metaCyc-based GSEA functional enrichment analysis was used to obtain information on the metabolic pathways of the human host. At the same time, the O2PLS model and Spearman correlation analysis were used to analyze the microorganisms–host interaction.Results: With the novel metatranscriptome analysis pipeline, we described the composition of more than 5,000 functionally active microorganisms and analyzed the difference in microorganisms between the EC and the normal group. Our research found that these microorganisms were involved in part of the metabolic process of endometrial cancer, such as 6-sulfo-sialyl Lewis x epitope, N-acetyl-beta-glucosaminyl. In addition, the host–microbiota crosstalk of EC endometrium also included many biological processes, mainly functions related to tumor migration and the Apelin signaling pathway.Conclusion: The functionally active microorganisms in the EC endometrium played an essential role in the occurrence and migration of tumors. This meant that functionally active microorganisms could not be ignored in the treatment of endometrial cancer. This study helped to better understand the possible role of endometrial functional, active microorganisms in the occurrence and development of EC in patients with endometrial cancer and provided new information for new attempts to treat EC.

scholarly journals Identification of Key Genes Associated With the Process of Hepatitis B Inflammation and Cancer Transformation by Integrated Bioinformatics Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Jingyuan Zhang ◽  
Xinkui Liu ◽  
Wei Zhou ◽  
Shan Lu ◽  
Chao Wu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Hepatitis B ◽  
Differential Expression ◽  
Chronic Inflammation ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Gene Markers ◽  
Key Genes

BackgroundHepatocellular carcinoma (HCC) has become the main cause of cancer death worldwide. More than half of hepatocellular carcinoma developed from hepatitis B virus infection (HBV). The purpose of this study is to find the key genes in the transformation process of liver inflammation and cancer and to inhibit the development of chronic inflammation and the transformation from disease to cancer.MethodsTwo groups of GEO data (including normal/HBV and HBV/HBV-HCC) were selected for differential expression analysis. The differential expression genes of HBV-HCC in TCGA were verified to coincide with the above genes to obtain overlapping genes. Then, functional enrichment analysis, modular analysis, and survival analysis were carried out on the key genes.ResultsWe identified nine central genes (CDK1, MAD2L1, CCNA2, PTTG1, NEK2) that may be closely related to the transformation of hepatitis B. The survival and prognosis gene markers composed of PTTG1, MAD2L1, RRM2, TPX2, CDK1, NEK2, DEPDC1, and ZWINT were constructed, which performed well in predicting the overall survival rate.ConclusionThe findings of this study have certain guiding significance for further research on the transformation of hepatitis B inflammatory cancer, inhibition of chronic inflammation, and molecular targeted therapy of cancer.

scholarly journals Identification of long noncoding RNA RP11-89K21.1 and RP11-357H14.17 as prognostic signature of endometrial carcinoma via integrated bioinformatics analysis

2020 ◽  
Author(s):  
Lingling Gao ◽  
Xin Nie ◽  
Wenchao Zhang ◽  
Rui Gou ◽  
Yuexin Hu ◽  
...  
Keyword(s):  
Endometrial Carcinoma ◽  
Noncoding Rna ◽  
Growth Regulation ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Biological Behavior ◽  
Vessel Development

Abstract Background: Endometrial carcinoma (EC) is one of the most common malignant tumors in gynecology. The potential functions and mechanisms of long noncoding RNAs (lncRNAs) in the occurrence and progression of EC remains unclear. It’s meaningful to explore lncRNAs signature for providing prognostic value of EC. Methods：The differentially expressed lncRNAs and their prognostic values in EC were investigated based on The Cancer Genome Atlas (TCGA) database; the transcriptional factors (TFs), the competing endogenous RNA (ceRNA) mechanism, functional regulatory network and immune infiltration of RP11-89K21.1 and RP11-357H14.17 were further explored by various bioinformatics tools and databases. Results: We first identified high expression of RP11-89K21.1 and RP11-357H14.17 were closely associated with shorten overall survival (OS) and poor prognosis in patients with EC. We also elucidated the networks of transcription factor and co-expression genes associated with RP11-89K21.1 and RP11-357H14.17. Furthermore, the ceRNA network mechanism was successfully constructed through 2 lncRNAs (RP11-89K21.1 and RP11-357H14.17), 11 miRNAs and 183 mRNAs. Functional enrichment analysis revealed that the targeting genes of RP11-89K21.1 and RP11-357H14.17 were strongly associated with microRNAs in cancer, vessel development, growth regulation, growth factor and cell differentiation, and involved in pathways including pathways in cancer, microRNAs in cancer and apoptotic signaling pathway. Conclusions: We demonstrated for the first time that RP11-89K21.1 and RP11-357H14.17 may play crucial roles in the occurrence, development and malignant biological behavior of EC, and can be regarded as potential prognostic biomarkers for EC.

scholarly journals Identification of Key Genes Affecting the Tumor Microenvironment and Prognosis of Triple-Negative Breast Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Jiarong Yi ◽  
Wenjing Zhong ◽  
Haoming Wu ◽  
Jikun Feng ◽  
Xiazi Zouxu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Microenvironment ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Key Genes

Although the tumor microenvironment (TME) plays an important role in the development of many cancers, its roles in breast cancer, especially triple-negative breast cancer (TNBC), are not well studied. This study aimed to identify genes related to the TME and prognosis of TNBC. Firstly, we identified differentially expressed genes (DEG) in the TME of TNBC, using Expression data (ESTIMATE) datasets obtained from the Cancer Genome Atlas (TCGA) and Estimation of Stromal and Immune cells in Malignant Tumor tissues. Next, survival analysis was performed to analyze the relationship between TME and prognosis of TNBC, as well as determine DEGs. Genes showing significant differences were scored as alternative genes. A protein-protein interaction (PPI) network was constructed and functional enrichment analysis conducted using the DEG. Proteins with a degree greater than 5 and 10 in the PPI network correspond with hub genes and key genes, respectively. Finally, CCR2 and CCR5 were identified as key genes in TME and prognosis of TNBC. Finally, these results were verified using Gene Expression Omnibus (GEO) datasets and immunohistochemistry of TNBC patients. In conclusion, CCR2 and CCR5 are key genes in the TME and prognosis of TNBC with the potential of prognostic biomarkers in TNBC.

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