scholarly journals Identification of hub genes in colorectal cancer based on weighted gene co-expression network analysis

2021 ◽  
Author(s):  
Yu Zhang ◽  
Jia Luo ◽  
Zhe Liu ◽  
Xudong Liu ◽  
Ying Ma ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Network Analysis ◽  
Ion Homeostasis ◽  
Therapeutic Targets ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Oxysterol Binding Protein ◽  
Interactive Analysis ◽  
Kaplan Meier ◽  
Novel Biomarkers

Colorectal cancer (CRC) is one of the most common tumors worldwide and is associated with high mortality. Here we performed bioinformatics analysis, which we validated using immunohistochemistry in order to search for hub genes that might serve as biomarkers or therapeutic targets in CRC. Based on data from the Cancer Genome Atlas, we identified 4,832 genes differentially expressed between CRC and normal samples (1,562 up-regulated and 3,270 down-regulated in CRC). Gene ontology analysis showed that up-regulated genes were enriched mainly in organelle fission, cell cycle regulation, and DNA replication; down-regulated genes were enriched primarily in the regulation of ion transmembrane transport and ion homeostasis. Weighted gene co-expression network analysis identified eight gene modules that were associated with clinical characteristics of CRC patients, including brown and blue modules that were associated with cancer onset. Analysis of the latter two hub modules revealed the following six hub genes: adhesion G protein-coupled receptor B3 (BAI3, also known as ADGRB3), cyclin F (CCNF), cytoskeleton-associated protein 2 like (CKAP2L), diaphanous related formin 3 (DIAPH3), oxysterol binding protein-like 3 (OSBPL3), and RERG-like protein (RERGL). Expression levels of these hub genes were associated with prognosis, based on Kaplan-Meier survival analysis of data from the Gene Expression Profiling Interactive Analysis database. Immunohistochemistry of CRC tumor tissues confirmed that OSBPL3 is up-regulated in CRC. Our findings suggest that CCNF, DIAPH3, OSBPL3, and RERGL may be useful as therapeutic targets against CRC. BAI3 and CKAP2L may be novel biomarkers of the disease.

scholarly journals Identification and verification of HCAR3 and INSL5 as new potential therapeutic targets of colorectal cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Xuan Yang ◽  
Wangao Wei ◽  
Shisheng Tan ◽  
Linrui Guo ◽  
Song Qiao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Tumor Tissue ◽  
Therapeutic Targets ◽  
The Cancer Genome Atlas ◽  
Pcr Analysis ◽  
Hub Genes ◽  
Bioinformatics Analyses ◽  
Real Time Quantitative Pcr

Abstract Background Colorectal cancer (CRC) is one of the most common cancers of the gastrointestinal tract and ranks third in cancer-related deaths worldwide. This study was conducted to identify novel biomarkers related to the pathogenesis of CRC based upon a bioinformatics analysis, and further verify the biomarkers in clinical tumor samples and CRC cell lines. Methods A series of bioinformatics analyses were performed using datasets from NCBI-GEO and constructed a protein–protein interaction (PPI) network. This analysis enabled the identification of Hub genes, for which the mRNA expression and overall survival of CRC patients data distribution was explored in The Cancer Genome Atlas (TCGA) colon cancer and rectal cancer (COADREAD) database. Furthermore, the differential expression of HCAR3 and INLS5 was validated in clinical tumor samples by Real-time quantitative PCR analysis, western blotting analysis, and immunohistochemistry analysis. Finally, CRC cells over-expressing INSL5 were constructed and used for CCK8, cell cycle, and cell apoptosis validation assays in vitro. Results A total of 286 differentially expressed genes (DEGs) were screened, including 64 genes with increased expression and 143 genes with decreased expression in 2 CRC database, from which 10 key genes were identified: CXCL1, HCAR3, CXCL6, CXCL8, CXCL2, CXCL5, PPY, SST, INSL5, and NPY1R. Among these genes, HCAR3 and INSL5 had not previously been explored and were further verified in vitro. Conclusions HCAR3 expression was higher in CRC tissues and associated with better overall survival of CRC patients. INSL5 expression in normal tissue was higher than that in tumor tissue and its high expression was associated with a better prognosis for CRC. The overexpression of INSL5 significantly inhibited the proliferation and promoted the shearing of PARP of CRC cells. This integrated bioinformatics study presented 10 key hub genes associated with CRC. HCAR3 and INSL5 were expressed in tumor tissue and these were associated with poor survival and warrant further studies as potential therapeutic targets.

scholarly journals Identification of Hub Genes and Construction of a Transcriptional Regulatory Network Associated With Tumor Recurrence in Colorectal Cancer by Weighted Gene Co-expression Network Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Shengwei Liu ◽  
Fanping Zeng ◽  
Guangwen Fan ◽  
Qiyong Dong
Keyword(s):  
Colorectal Cancer ◽  
Network Analysis ◽  
Regulatory Network ◽  
Tumor Recurrence ◽  
Transcriptional Regulatory Network ◽  
Interaction Network ◽  
Underlying Mechanism ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Regulatory Relationship

Tumor recurrence is one of the most important risk factors that can negatively affect the survival rate of colorectal cancer (CRC) patients. However, the key regulators dictating this process and their exact mechanisms are understudied. This study aimed to construct a gene co-expression network to predict the hub genes affecting CRC recurrence and to inspect the regulatory network of hub genes and transcription factors (TFs). A total of 177 cases from the GSE17536 dataset were analyzed via weighted gene co-expression network analysis to explore the modules related to CRC recurrence. Functional annotation of the key module genes was assessed through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein and protein interaction network was then built to screen hub genes. Samples from the Cancer Genome Atlas (TCGA) were further used to validate the hub genes. Construction of a TFs-miRNAs–hub genes network was also conducted using StarBase and Cytoscape approaches. After identification and validation, a total of five genes (TIMP1, SPARCL1, MYL9, TPM2, and CNN1) were selected as hub genes. A regulatory network of TFs-miRNAs-targets with 29 TFs, 58 miRNAs, and five hub genes was instituted, including model GATA6-MIR106A-CNN1, SP4-MIR424-TPM2, SP4-MIR326-MYL9, ETS1-MIR22-TIMP1, and ETS1-MIR22-SPARCL1. In conclusion, the identification of these hub genes and the prediction of the Regulatory relationship of TFs-miRNAs-hub genes may provide a novel insight for understanding the underlying mechanism for CRC recurrence.

Co‑expression Network Analysis by WGCNA and Identify Potential Prognostic Markers Associated with Lung Metastasis in Breast Cancer

2021 ◽  
Author(s):  
xixun zhang
Keyword(s):  
Breast Cancer ◽  
Network Analysis ◽  
Lung Metastasis ◽  
Prognostic Markers ◽  
Clinical Information ◽  
Preventive Treatment ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Breast Cancer Patients ◽  
Kaplan Meier

Abstract Backgroud: Breast cancer (BC) is an aggressive cancer with a high percentage recurrence and metastasis. As one of the most common distant metastasis organ in breast cancer, lung metastasis has a worse prognosis than that of liver and bone. Therefore, it’s important to explore some potential prognostic markers associated with the lung metastasis in breast cancer for preventive treatment. Methods: In our study, transcriptomic data and clinical information of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA) database. Co-expression modules was built by Weighted gene co-expression network analysis (WGCNA) to find out the royalbule modules which is significantly associated with lung metastasis in breast cancer. Then, co-expression genes were analyzed for functional enrichment. Furthermore, the prognostic value of these genes was assessed by GEPIA Database and Kaplan-Meier Plotter. Results: Results showed that the hub genes, LMNB and CDC20, were up-regulated in breast cancer and indicated worse survival. Therefore, we speculate that these two genes play crucial roles in the process of lung metastasis in breast cancer, and can be used as potential prognostic markers in lung metastasis of breast cancer. Conclusion: Collectively, our study identified two potential key genes in the lung metastasis of breast cancer, which might be applied as the prognostic markers of the precise treatment in breast cancer with lung metastasis.

scholarly journals Identification and Analysis of Genes Associated with Epithelial Ovarian Cancer by Integrated Bioinformatics Methods

2020 ◽  
Author(s):  
Ting Gui ◽  
Chenhe Yao ◽  
Binghan Jia ◽  
Keng Shen
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Epithelial Ovarian Cancer ◽  
Protein Interactions ◽  
Therapeutic Targets ◽  
Progression Free Survival ◽  
The Cancer Genome Atlas ◽  
Ppi Network ◽  
Hub Genes ◽  
Free Survival

Abstract Background: Though considerable efforts have been made to improve the treatment of epithelial ovarian cancer (EOC), the prognosis of patients has remained poor. Identifying differentially expressed genes (DEGs) involved in EOC progression and exploiting them as novel biomarkers or therapeutic targets for EOC is highly valuable. Methods: Overlapping DEGs were screened out from three independent gene expression omnibus (GEO) datasets and subjected to Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses. The protein-protein interactions (PPI) network of DEGs was constructed in the STRING database. The top 20 hub genes were selected using cytoHubba. The expression of hub genes was detected in GEPIA, Oncomine, and human protein atlas (HPA) databases. The relationship of hub genes with the pathological stage and the overall survival and progression-free survival in EOC patients was investigated using the cancer genome atlas data. Results: A total of 306 DEGs were identified, including 265 up-regulated and 41 down-regulated. Through the PPI network analysis, the top 20 genes were screened out, among which 4 hub genes were selected after literature retrieval, including CDC45, CDCA5, KIF4A, ESPL1. The four genes were up-regulated in EOC tissues and the expression of these four genes decreased gradually with the continuous progression of EOC. Survival curves illustrated that patients with a lower level of CDCA5 and ESPL1 had better overall survival and progression-free survival. Conclusions: Two hub genes, CDCA5 and ESPL1, identified as playing tumor-promotive roles, could be utilized as potential novel therapeutic targets for EOC treatment.

scholarly journals Potential Biomarkers of Colon Adenocarcinoma Based on Weighted Gene Co-Expression Network Analysis

2021 ◽  
Author(s):  
Zhongze Cui ◽  
Shuang He ◽  
Feifei Wen ◽  
Xiaoyang Xu ◽  
Yangyang Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Colon Cancer ◽  
Network Analysis ◽  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Colon Adenocarcinoma ◽  
The Cancer Genome Atlas ◽  
Future Research ◽  
Related Gene

Abstract Background: Colon adenocarcinoma (COAD) is one of the most common malignancies worldwide. Although a large number of studies have elucidated the aetiology of colorectal cancer, the exact mechanism of colorectal cancer development remains to be determined.To identify key modules and prognostic genes that may be involved in the occurrence and development of COAD, weighted gene coexpression network analysis (WGCNA) and differential expression analysis were performed on datasets GSE41657 and GSE74602 from the Gene Expression Omnibus (GEO) database to screen for prognostic differentially expressed genes. Gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) database for verification.Results: Through WGCNA and DEGs analysis, 439 genes in key functional modules were obtained, and 26 prognostic related genes were finally obtained through prognostic analysis: (1) We screened 5 genes（RPP40, DUSP18, PPRC1, MFSD11 and PDCD11） that have not been studied in COAD.（2）We obtained the most critical module in the occurrence and development of colon cancer and obtained one prognosis-related gene, NUP85, from the most critical module.The relationship between it and tumor immune microenvironment was verified.（3） A prognostic model comprising four coexpressed differential genes was constructed; TIMP1, PMM2, E2F3 and MORC2 were selected as the key prognosis-related genes.Conclusions: （1）As new biomarkers，prognostic genes RPP40, DUSP18, PPRC1, MFSD11 and PDCD11 may be potential therapeutic targets for COAD, and provide new ideas for future research on the mechanism of COAD. （2）NUP85 may be an immune-related gene which was negatively correlated with CD4+ T cell and M2 macrophagesthat plays an important role in inhibiting the occurrence and development of colorectal adenocarcinoma. （3）A Cox proportional risk model based on gene expression can be used to predict the prognosis and survival time of patients with colon cancer.

scholarly journals Gene Co-expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Vitiligo Disease: A Systems Biology Study

2020 ◽  
Author(s):  
Afshin Derakhshani ◽  
Homa Mollaei ◽  
Negin Parsamanesh ◽  
Mohammad Fereidouni ◽  
Ebrahim Miri-Moghaddam ◽  
...  
Keyword(s):  
Systems Biology ◽  
Network Analysis ◽  
Messenger Rna ◽  
Molecular Mechanisms ◽  
Biological Activities ◽  
Neutrophil Migration ◽  
Enrichment Analysis ◽  
Autoimmune Disorder ◽  
Hub Genes ◽  
Novel Biomarkers

Vitiligo is the most common cause of skin, hair, and oral depigmentation which is known as an autoimmune disorder. Genetic and environmental factors have important roles in the progression of the disease. Dysregulation of gene expression, like microRNAs (miRNA), may serve as major relevant factors. Several biological processes are involved in vitiligo disease and developing a comprehensive approach helps us to better understand the molecular mechanisms of disease. In this research, we describe how a weighted gene co-expression network analysis as a systems biology approach assists to define the primary gene modules, hub genes, and messenger RNA (mRNA)-miRNA regulatory network in vitiligo disease as the novel biomarkers. The results demonstrated a module with a high correlation with vitiligo state. Moreover, gene enrichment analysis showed that this module's genes were mostly involved in some biological activities including G protein-coupled receptors signaling pathway, lymphocyte chemotaxis, chemokine activity, neutrophil migration, granulocyte chemotaxis, etc. The co-expression network was constructed using top hub genes of the correlated module which are named as CXCL10, ARL9, AKR1B10, COX7B, RPL26, SPA17, NDUFAF2, RPF2, DAPL1, RPL34, CWC15, NDUFB3, RPL26L1, ACOT13, HSPB11, and NSA2. MicroRNAs prediction tool (miRWalk) revealed top miRNAs correlated with the interested module. Finally, a drug-target network was constructed which indicated interactions of some food and drug administration (FDA) approved drugs with hub genes. Our findings specified one important module and main hub genes which can be considered as novel biomarkers for vitiligo therapeutic purposes.   

scholarly journals Identification of key gene modules and genes in colorectal cancer by weighted gene co-expression network analysis (WGCNA)

2019 ◽  
Author(s):  
Zheying Zhang ◽  
Na Li ◽  
Qingzu Gao ◽  
Xinlai Qian
Keyword(s):  
Colorectal Cancer ◽  
Developing Countries ◽  
Network Analysis ◽  
Malignant Tumor ◽  
Hub Genes ◽  
Hub Gene ◽  
Chip Data ◽  
Qrt Pcr ◽  
Gene Modules

Background: Colorectal cancer (CRC) is a malignant tumor particularly common in developing countries. In this study, we used Weighted Gene Co-Expression Network Analysis (WGCNA) of chip data and screened hub genes in CRC to find the gene modules specifically correlated with clinical traits. Methods: WGCNA was used to identify the gene modules specifically associated with metastasis in colorectal cancer. Cytoscape software was used to construct a co-expression network. The expression of CYTH1 was determined by qRT-PCR. Results: Based on the predicted co-expression network, we identified that the turquoise module was associated with CRC clinical metastasis traits. Turquoise module genes were analyzed, and we identified the hub gene CYTH1 using Cytoscape software. Additionally, we found CYTH1’s expression was lower in CRC tissue and cells when compared with normal counterparts.

scholarly journals Identification of a Five-Gene Prognostic Model and Its Potential Drug Repurposing in Colorectal Cancer Based on TCGA, GTEx and GEO Databases

2021 ◽  
Vol 11 ◽  
Author(s):  
Feng Yang ◽  
Shaoyi Cai ◽  
Li Ling ◽  
Haiji Zhang ◽  
Liang Tao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regulatory Region ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Pathway Enrichment Analysis ◽  
Potential Drug ◽  
Hub Genes

Colorectal cancer (CRC) is a major cause of cancer deaths worldwide. Unfortunately, many CRC patients are still being diagnosed at an advanced stage of the cancer, and the 5-year survival rate is only ~30%. Effective prognostic markers of CRC are therefore urgently needed. To address this issue, we performed a detailed bioinformatics analysis based on the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases to identify prognostic biomarkers for CRC, which in turn help in exploring potential drug-repurposing. We identified five hub genes (PGM2, PODXL, RHNO1, SCD, and SEPHS1), which had good performance in survival prediction and might be involved in CRC through three key pathways (“Cell cycle,” “Purine metabolism,” and “Spliceosome” KEGG pathways) identified by a KEGG pathway enrichment analysis. What is more, we performed a co-expression analysis between five hub genes and transcription factors to explore the upstream regulatory region. Furthermore, we screened the potential drug-repurposing for the five hub genes in CRC according to the Binding DB and ZINC15 databases. Taking together, we constructed a five-gene signature to predict overall survival of CRC and found the potential drug-repurposing, which may improve the outcome of CRC in the future.

scholarly journals Identification of Genes Associated with the Metastasis of Pheochromocytoma/Paraganglioma Based on Weighted Gene Coexpression Network Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Qisheng Su ◽  
Qinpei Ding ◽  
Zunni Zhang ◽  
Zheng Yang ◽  
Yuling Qiu ◽  
...  
Keyword(s):  
Network Analysis ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
The Cancer Genome Atlas ◽  
Coexpression Network ◽  
Neuroendocrine Neoplasm ◽  
Gene Coexpression Network ◽  
Hub Genes ◽  
Gene Coexpression ◽  
Coexpression Network Analysis

Background. Pheochromocytoma/paraganglioma (PCPG) is a benign neuroendocrine neoplasm in most cases, but metastasis and other malignant behaviors can be observed in this tumor. The aim of this study was to identify genes associated with the metastasis of PCPG. Methods. The Cancer Genome Atlas (TCGA) expression profile data and clinical information were downloaded from the cbioportal, and the weighted gene coexpression network analysis (WGCNA) was conducted. The gene coexpression modules were extracted from the network through the WGCNA package of R software. We further extracted metastasis-related modules of PCPG. Enrichment analysis of Biological Process of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes was carried out for important modules, and survival analysis of hub genes in the modules was performed. Results. A total of 168 PCPG samples were included in this study. The weighted gene coexpression network was constructed with 5125 genes of the top 25% variance among the 20501 genes obtained from the database. We identified 11 coexpression modules, among which the salmon module was associated with the age of PCPG patients at diagnosis, metastasis, and malignancy of the tumors. Conclusion. WGCNA was performed to identify the gene coexpression modules and hub genes in the metastasis-related gene module of PCPG. The findings in this study provide a new clue for further study of the mechanisms underlying the PCPG metastasis.

scholarly journals Common Nevus and Skin Cutaneous Melanoma: Prognostic Genes Identified by Gene Co-Expression Network Analysis

Genes ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 747 ◽  
Author(s):  
Lingge Yang ◽  
Yu Xu ◽  
Yan Yan ◽  
Peng Luo ◽  
Shiqi Chen ◽  
...  
Keyword(s):  
Network Analysis ◽  
Cutaneous Melanoma ◽  
Normal Skin ◽  
Hub Genes ◽  
Interactive Analysis ◽  
Diagnosis And Prognosis ◽  
Human Protein Atlas ◽  
The Difference ◽  
Imagej Software ◽  
The Relationship

Skin cutaneous melanoma (SCM) is a common malignant tumor of the skin and its pathogenesis still needs to be studied. In this work, we constructed a co-expression network and screened for hub genes by weighted gene co-expression network analysis (WGCNA) using the GSE98394 dataset. The relationship between the mRNA expression of hub genes and the prognosis of patients with melanoma was validated by Gene Expression Profiling Interactive Analysis (GEPIA) database. Furthermore, immunohistochemistry in the Human Protein Atlas was used to validate hub genes and grayscale analysis was performed using ImageJ software. It was found that the yellow module was most significantly associated with the difference between common nevus and SCM, and 13 genes whose expression correlation >0.9 were candidate hub genes. The expression of three genes (STK26, KCNT2, CASP12) was correlated with the prognosis of SCM. STK26 (P = 0.0024) and KCNT2 (P < 0.0001) were significantly different between normal skin and SCM. These three hub genes have potential value as predictors for accurate diagnosis and prognosis of SCM in the future.

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