scholarly journals Identification Hub Genes of Consensus Molecular Subtype Correlation with Immune Infiltration and Predict Prognosis in Gastric Cancer

2021 ◽  
Author(s):  
Bin Yu ◽  
Xin Yu ◽  
Jianping Xiong ◽  
Mei Ma
Keyword(s):  
Gastric Cancer ◽  
Molecular Subtype ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
M2 Macrophage ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Potential Biomarkers

Abstract Gastric Cancer (GC) has a great fatality rate, meanwhile, there is still a lack of available biomarkers for prognosis. The goal of the research was to discover key and novel potential biomarkers for GC. We screened for the expression of significantly altered genes based on survival rates from two consensus molecular subtypes (CMS) of GC. Subsequently, functional enrichment analysis showed these genes involved in many cancers. And we picked 6 hub genes that could both secreted in the tumor microenvironment and expression enhanced in immune cells. Then, Kaplan Meier survival and expression detected in the tumor pathological stage were utilized to clarify the prognostic of these 6 hub genes. The results indicated that OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1, respectively, were significantly associated with poor OS in GC patients. And their expression increased with cancer advanced. Moreover, immune infiltration analysis displayed that those hub genes expression positively with M2 macrophage, CD8+ T Cell, most immune inhibitors, and majority immunostimulators. In summary, our results suggested that OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1 were all potential biomarkers for GC prognosis and might also be potential therapeutic targets for GC.

scholarly journals Identification Hub Genes of Consensus Molecular Subtype Correlation With Immune Infiltration and Predict Prognosis in Gastric Cancer

2021 ◽  
Author(s):  
Bin Yu ◽  
Xin Yu ◽  
Jianping Xiong ◽  
Mei Ma
Keyword(s):  
Gastric Cancer ◽  
Molecular Subtype ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
M2 Macrophage ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Potential Biomarkers

Abstract Gastric Cancer (GC) has a great fatality rate, meanwhile, there is still a lack of available biomarkers for prognosis. The goal of the research was to discover key and novel potential biomarkers for GC. We screened for the expression of significantly altered genes based on survival rates from two consensus molecular subtypes (CMS) of GC. Subsequently, functional enrichment analysis showed these genes involved in many cancers. And we picked 6 hub genes that could both secreted in the tumor microenvironment and expression enhanced in immune cells. Then, Kaplan Meier survival and expression detected in the tumor pathological stage were utilized to clarify the prognostic of these 6 hub genes. The results indicated that OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1, respectively, were significantly associated with poor OS in GC patients. And their expression increased with cancer advanced. Moreover, immune infiltration analysis displayed that those hub genes expression positively with M2 macrophage, CD8+ T Cell, most immune inhibitors, and majority immunostimulators. In summary, our results suggested that OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1 were all potential biomarkers for GC prognosis and might also be potential therapeutic targets for GC.

scholarly journals Identification hub genes of consensus molecular subtype correlation with immune infiltration and predict prognosis in gastric cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Xin Yu ◽  
Bin Yu ◽  
Weidan Fang ◽  
Jianping Xiong ◽  
Mei Ma
Keyword(s):  
Gastric Cancer ◽  
Molecular Subtype ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
M2 Macrophage ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Potential Biomarkers

AbstractGastric cancer (GC) has a great fatality rate, meanwhile, there is still a lack of available biomarkers for prognosis. The goal of the research was to discover key and novel potential biomarkers for GC. We screened for the expression of significantly altered genes based on survival rates from two consensus molecular subtypes (CMS) of GC. Subsequently, functional enrichment analysis showed these genes involved in many cancers. And we picked 6 hub genes that could both secreted in the tumor microenvironment and expression enhanced in immune cells. Then, Kaplan Meier survival and expression detected in the tumor pathological stage were utilized to clarify the prognostic of these 6 hub genes. The results indicated that OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1, respectively, were significantly associated with poor OS in GC patients. And their expression increased with cancer advanced. Moreover, immune infiltration analysis displayed that those hub genes expression positively with M2 macrophage, CD8+ T Cell, most immune inhibitors, and majority immunostimulators. In summary, our results suggested that OGN, CHRDL2, C2orf40, THBS4, CHRDL1, and ANGPTL1 were all potential biomarkers for GC prognosis and might also be potential therapeutic targets for GC.

scholarly journals Detecting Hub Genes Associated With Lauren Subtype of Gastric Cancer by Weighted Gene Co-Expression Network Analysis

2020 ◽  
Author(s):  
XU LIU ◽  
Li Yao ◽  
Jingkun Qu ◽  
Lin Liu ◽  
XU LIU ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Network Analysis ◽  
Cancer Survival ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Diffuse Gastric Cancer ◽  
Hub Genes ◽  
Gene Modules

Abstract Background Gastric cancer is a rather heterogeneous type of malignant tumor. Among the several classification system, Lauren classification can reflect biological and pathological differences of different gastric cancer.Method to provide systematic biological perspectives, we employ weighted gene co-expression network analysis to reveal transcriptomic characteristics of gastric cancer. GSE15459 and TCGA STAD dataset were downloaded. Co-expressional network was constructed and gene modules were identified. Result Two key modules blue and red were suggested to be associated with diffuse gastric cancer. Functional enrichment analysis of genes from the two modules was performed. Validating in TCGA STAD dataset, we propose 10 genes TNS1, PGM5, CPXM2, LIMS2, AOC3, CRYAB, ANGPTL1, BOC and TOP2A to be hub-genes for diffuse gastric cancer. Finally these ten genes were associated with gastric cancer survival. Conclusion More attention need to be paid and further experimental study is required to elucidate the role of these genes.

scholarly journals Based on bioinformatics analysis, NF1, BTRC and MAPK14 are the potential biomarkers in the progression of osteoarthritis synovitis

2021 ◽  
Author(s):  
Mingyi Yang ◽  
Yani Su ◽  
Yao Ma ◽  
Yirixiati Aihaiti ◽  
Peng Xu
Keyword(s):  
Differentially Expressed Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Hub Gene ◽  
Potential Biomarkers

Abstract Objective: To study the potential biomarkers and related pathways in osteoarthritis (OA) synovial lesions, and to provide theoretical basis and research directions for the pathogenesis and treatment of OA. Methods: Download the microarray data sets GSE12021 and GSE82107 from Gene Expression Omnibus. GEO2R recognizes differentially expressed genes. Perform functional enrichment analysis of differentially expressed genes and construct protein-protein interaction network. Cytoscape performs module analysis and enrichment analysis of top-level modules. Further identify the Hub gene and perform functional enrichment analysis. TargetScan, miRDB and miRWalk three databases predict the target miRNAs of Hub gene and identify key miRNAs. Results: Finally, 10 Hub genes and 17 key miRNAs related to the progression of OA synovitis were identified. NF1, BTRC and MAPK14 may play a vital role in OA synovial disease. Conclusion: The Hub genes and key miRNAs discovered in this study may be potential biomarkers in the development of OA synovitis, and provide research methods and target basis for the pathogenesis and treatment of OA.

scholarly journals Identification of Tumorigenic and Prognostic Biomarkers in Colorectal Cancer Based on microRNA Expression Profiles

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Yuntao Shi ◽  
Yingying Zhuang ◽  
Jialing Zhang ◽  
Mengxue Chen ◽  
Shangnong Wu
Keyword(s):  
Target Genes ◽  
Cox Regression ◽  
Expression Profiles ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Risk Groups ◽  
Normal Mucosa ◽  
Microrna Expression ◽  
Functional Enrichment

Objective. Although noncoding RNAs, especially the microRNAs, have been found to play key roles in CRC development in intestinal tissue, the specific mechanism of these microRNAs has not been fully understood. Methods. GEO and TCGA database were used to explore the microRNA expression profiles of normal mucosa, adenoma, and carcinoma. And the differential expression genes were selected. Computationally, we built the SVM model and multivariable Cox regression model to evaluate the performance of tumorigenic microRNAs in discriminating the adenomas from normal tissues and risk prediction. Results. In this study, we identified 20 miRNA biomarkers dysregulated in the colon adenomas. The functional enrichment analysis showed that MAPK activity and MAPK cascade were highly enriched by these tumorigenic microRNAs. We also investigated the target genes of the tumorigenic microRNAs. Eleven genes, including PIGF, TPI1, KLF4, RARS, PCBP2, EIF5A, HK2, RAVER2, HMGN1, MAPK6, and NDUFA2, were identified to be frequently targeted by the tumorigenic microRNAs. The high AUC value and distinct overall survival rates between the two risk groups suggested that these tumorigenic microRNAs had the potential of diagnostic and prognostic value in CRC. Conclusions. The present study revealed possible mechanisms and pathways that may contribute to tumorigenesis of CRC, which could not only be used as CRC early detection biomarkers, but also be useful for tumorigenesis mechanism studies.

scholarly journals Identification of Key Genes and Pathways Associated with Differences of Subchondral Bone in Osteoarthritis

2020 ◽  
Author(s):  
Yiyuan Zhang ◽  
Rongguo Yu ◽  
Jiayu Zhang ◽  
Eryou Feng ◽  
Haiyang Wang ◽  
...  
Keyword(s):  
Subchondral Bone ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Hub Genes ◽  
Common Chronic Disease ◽  
Drug Candidates ◽  
Therapeutic Modalities ◽  
Pathogenic Genes

Abstract BackgroundOsteoarthritis (OA) is a common chronic disease worldwide. Subchondral bone is an important pathological change in OA and responds more rapidly to adverse loading and events compared to cartilage. However, the pathogenic genes and pathways of subchondral bone are largely unclear.ObjectiveThis study aimed to identify signature differences in genes involved in knee lateral tibial (LT) and medial tibial (MT) plateaus of subchondral bone tissue while exploring their potential molecular mechanisms via bioinformatics analysis.MethodsFirst, the gene expression data of GSE51588 was downloaded from the GEO database. Differentially expressed genes (DEGs) between knee LT and MT were identified, and functional enrichment analyses were performed. Then, a protein-protein interactive network was constructed in order to acquire the hub genes, and modules analysis was conducted using STRING and Cytoscape for further analysis. The enriched hub genes were queried in DGIdb database to find suitable drug candidates in OA.ResultsA total of 202 DEGs (112 upregulated genes and 84 downregulated genes) were determined. In the PPI network, ten hub genes were identified. Five significant modules were identified using the MCODE plugin unit. Functional enrichment analysis revealed the most important signaling pathways. Six of the ten hub genes were targetable by a total of 35 drugs, suggesting their possible therapeutic use for OA .ConclusionsThe identified hub genes and functional enrichment pathways were implicated in the development and progression of subchondral bone in OA, thus improving our understanding of OA and offering molecular targets for future therapeutic modalities.

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 Identification of PKP 2/3 as potential biomarkers of ovarian cancer based on bioinformatics and experiments

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Lingling Gao ◽  
Xiao Li ◽  
Qian Guo ◽  
Xin Nie ◽  
Yingying Hao ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Signaling Pathway ◽  
Poor Prognosis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Biological Behavior ◽  
Cell Junction ◽  
Immune Infiltration ◽  
Potential Biomarker

Abstract Background Plakophilins (PKPs) are widely involved in gene transcription, translation, and signal transduction, playing a crucial role in tumorigenesis and progression. However, the function and potential mechanism of PKP1/2/3 in ovarian cancer (OC) remains unclear. It’s of great value to explore the expression and prognostic values of PKP1/2/3 and their potential mechanisms, immune infiltration in OC. Methods The expression levels, prognostic values and genetic variations of PKP1/2/3 in OC were explored by various bioinformatics tools and databases, and PKP2/3 were selected for further analyzing their regulation network and immune infiltration. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathways (KEGG) enrichment were also conducted. Finally, the expression and prognosis of PKP2 were validated by immunohistochemistry. Results The expression level and prognosis of PKP1 showed little significance in ovarian cancer, and the expression of PKP2/3 mRNA and protein were upregulated in OC, showing significant correlations with poor prognosis of OC. Functional enrichment analysis showed that PKP2/3 and their correlated genes were significantly enriched in adaptive immune response, cytokine receptor activity, organization of cell–cell junction and extracellular matrix; KEGG analysis showed that PKP2/3 and their significantly correlated genes were involved in signaling pathways including cytokine-mediated signaling pathway, receptor signaling pathway and pathways in cancer. Moreover, PKP2/3 were correlated with lymphocytes and immunomodulators. We confirmed that high expression of PKP2 was significantly associated with advanced stage, poor differentiation and poor prognosis of OC patients. Conclusion Members of plakophilins family showed various degrees of abnormal expressions and prognostic values in ovarian cancer. PKP2/3 played crucial roles in tumorigenesis, aggressiveness, malignant biological behavior and immune infiltration of OC, and can be regarded as potential biomarker for early diagnosis and prognosis evaluation in OC.

scholarly journals Identification and Validation of a Potential Prognostic 7-lncRNA Signature for Predicting Survival in Patients with Multiple Myeloma

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Yun Zhong ◽  
Zhe Liu ◽  
Dangchi Li ◽  
Qinyuan Liao ◽  
Jingao Li
Keyword(s):  
Gene Expression ◽  
Risk Score ◽  
Cox Regression ◽  
External Validation ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Test Set ◽  
Cox Regression Analysis

Background. An increasing number of studies have indicated that the abnormal expression of certain long noncoding RNAs (lncRNAs) is linked to the overall survival (OS) of patients with myeloma. Methods. Gene expression data of myeloma patients were downloaded from the Gene Expression Omnibus (GEO) database (GSE4581 and GSE57317). Cox regression analysis, Kaplan-Meier, and receiver operating characteristic (ROC) analysis were performed to construct and validate the prediction model. Single sample gene set enrichment (ssGSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to predict the function of a specified lncRNA. Results. In this study, a seven-lncRNA signature was identified and used to construct a risk score system for myeloma prognosis. This system was used to stratify patients with different survival rates in the training set into high-risk and low-risk groups. Test set, the entire test set, the external validation set, and the myeloma subtype achieved the authentication of the results. In addition, functional enrichment analysis indicated that 7 prognostic lncRNAs may be involved in the tumorigenesis of myeloma through cancer-related pathways and biological processes. The results of the immune score showed that IF_I was negatively correlated with the risk score. Compared with the published gene signature, the 7-lncRNA model has a higher C-index (above 0.8). Conclusion. In summary, our data provide evidence that seven lncRNAs could be used as independent biomarkers to predict the prognosis of myeloma, which also indicated that these 7 lncRNAs may be involved in the progression of myeloma.

scholarly journals Identification of Potential Biomarkers and Related Transcription Factors in Peripheral Blood of Tuberculosis Patients

2020 ◽  
Vol 17 (19) ◽  
pp. 6993
Author(s):  
Longxiang Xie ◽  
Xiaoyu Chao ◽  
Tieshan Teng ◽  
Qiming Li ◽  
Jianping Xie
Keyword(s):  
Transcription Factors ◽  
T Cell Activation ◽  
Peripheral Blood ◽  
Cell Activation ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Peripheral Blood Mononuclear ◽  
Potential Biomarkers

Tuberculosis (TB), one major threat to humans, can infect one third of the worldwide population, and cause more than one million deaths each year. This study aimed to identify the effective diagnosis and therapy biomarkers of TB. Hence, we analyzed two microarray datasets (GSE54992 and GSE62525) derived from the Gene Expression Omnibus (GEO) database to find the differentially expressed genes (DEGs) of peripheral blood mononuclear cell (PBMC) between TB patients and healthy specimens. Functional and pathway enrichment of the DEGs were analyzed by Metascape database. Protein-protein interaction (PPI) network among the DEGs were constructed by STRING databases and visualized in Cytoscape software. The related transcription factors regulatory network of the DEGs was also constructed. A total of 190 DEGs including 36 up-regulated genes and 154 down-regulated genes were obtained in TB samples. Gene functional enrichment analysis showed that these DEGs were enriched in T cell activation, chemotaxis, leukocyte activation involved in immune response, cytokine secretion, head development, etc. The top six hub genes (namely, LRRK2, FYN, GART, CCR7, CXCR5, and FASLG) and two significant modules were got from PPI network of DEGs. Vital transcriptional factors, such as FoxC1 and GATA2, were discovered with close interaction with these six hub DEGs. By systemic bioinformatic analysis, many DEGs associated with TB were screened, and these identified hub DEGs may be potential biomarkers for diagnosis and treatment of TB in the future.

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