Bioinformatic analysis reveals hub genes and pathways that promote melanoma metastasis

Abstract Background Melanoma has the highest mortality rate of all skin tumors, and metastases are the major cause of death from it. The molecular mechanism leading to melanoma metastasis is currently unclear. Methods With the goal of revealing the underlying mechanism, three data sets with accession numbers GSE8401, GSE46517 and GSE7956 were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the differentially expressed gene (DEG) of primary melanoma and metastatic melanoma, three kinds of analyses were performed, namely functional annotation, protein-protein interaction (PPI) network and module construction, and co-expression and drug-gene interaction prediction analysis. Results A total of 41 up-regulated genes and 79 down-regulated genes was selected for subsequent analyses. Results of pathway enrichment analysis showed that extracellular matrix organization and proteoglycans in cancer are closely related to melanoma metastasis. In addition, seven pivotal genes were identified from PPI network, including CXCL8, THBS1, COL3A1, TIMP3, KIT, DCN, and IGFBP5, which have all been verified in the TCGA database and clinical specimens, but only CXCL8, THBS1 and KIT had significant differences in expression. Conclusions To conclude, CXCL8, THBS1 and KIT may be the hub genes in the metastasis of melanoma and thus may be regarded as therapeutic targets in the future.

Download Full-text

Bioinformatic analysis reveals hub genes and pathways that promote melanoma metastasis

10.21203/rs.3.rs-25246/v4 ◽

2020 ◽

Author(s):

Wenxing Su ◽

Yi Guan ◽

Biao Huang ◽

Juanjuan Wang ◽

Yuqian Wei ◽

...

Keyword(s):

Differentially Expressed Gene ◽

Primary Melanoma ◽

Enrichment Analysis ◽

Gene Interaction ◽

Underlying Mechanism ◽

Bioinformatic Analysis ◽

Pathway Enrichment Analysis ◽

Melanoma Metastasis ◽

Ppi Network ◽

Hub Genes

Abstract Background: Melanoma has the highest mortality rate of all skin tumors, and metastases are the major cause of death from it. The molecular mechanism leading to melanoma metastasis is currently unclear. Methods: With the goal of revealing the underlying mechanism, three data sets with accession numbers GSE8401, GSE46517 and GSE7956 were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the differentially expressed gene (DEG) of primary melanoma and metastatic melanoma, three kinds of analyses were performed, namely functional annotation, protein‐protein interaction (PPI) network and module construction, and co-expression and drug-gene interaction prediction analysis. Results: A total of 41 up-regulated genes and 79 down-regulated genes was selected for subsequent analyses. Results of pathway enrichment analysis showed that extracellular matrix organization and proteoglycans in cancer are closely related to melanoma metastasis. In addition, seven pivotal genes were identified from PPI network, including CXCL8, THBS1, COL3A1, TIMP3, KIT, DCN, and IGFBP5, which have all been verified in the TCGA database and clinical specimens, but only CXCL8, THBS1 and KIT had significant differences in expression. Conclusions: To conclude, CXCL8, THBS1 and KIT may be the hub genes in the metastasis of melanoma and thus may be regarded as therapeutic targets in the future.

Download Full-text

Bioinformatic analysis reveals hub genes and pathways that promote melanoma metastasis

10.21203/rs.3.rs-25246/v3 ◽

2020 ◽

Author(s):

wenxing su ◽

yi guan ◽

biao huang ◽

juanjuan wang ◽

yuqian wei ◽

...

Keyword(s):

Differentially Expressed Gene ◽

Primary Melanoma ◽

Enrichment Analysis ◽

Gene Interaction ◽

Underlying Mechanism ◽

Bioinformatic Analysis ◽

Pathway Enrichment Analysis ◽

Melanoma Metastasis ◽

Ppi Network ◽

Hub Genes

Download Full-text

Bioinformatics analysis reveals key genes and pathways that promote melanoma metastasis

10.21203/rs.3.rs-25246/v1 ◽

2020 ◽

Author(s):

wenxing su ◽

yi guan ◽

biao huang ◽

juanjuan wang ◽

yuqian wei ◽

...

Keyword(s):

Differentially Expressed Gene ◽

Primary Melanoma ◽

Enrichment Analysis ◽

Gene Interaction ◽

Underlying Mechanism ◽

Gene Expression Omnibus ◽

Pathway Enrichment Analysis ◽

Melanoma Metastasis ◽

Ppi Network ◽

Key Genes

Abstract Melanoma has the highest mortality rate of all skin tumors, and metastases are the major cause of death from it. The molecular mechanism leading to melanoma metastasis is currently unclear. With the goal of revealing the underlying mechanism, three data sets with accession numbers GSE8401, GSE46517 and GSE7956 were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the differentially expressed gene (DEG) of primary melanoma and metastatic melanoma, three kinds of analyses were performed, namely functional annotation, protein-protein interaction (PPI) network and module construction, and co-expression and drug-gene interaction prediction analysis. 41 up-regulated genes and 79 down-regulated genes were selected for subsequent analyses. Results of pathway enrichment analysis showed that extracellular matrix organization and proteoglycans in cancer are closely related to melanoma metastasis. In addition, seven pivotal genes were identified from PPI network, including CXCL8, THBS1, COL3A1, TIMP3, KIT, DCN, and IGFBP5, which have all been verified in the TCGA database, but only CXCL8, THBS1 and KIT had significant differences in expression. To conclude, CXCL8, THBS1 and KIT may be the key genes in the metastasis of melanoma and thus may be regarded as therapeutic targets in the future.

Download Full-text

Bioinformatics analysis reveals key genes and pathways that promote melanoma metastasis

10.21203/rs.3.rs-25246/v2 ◽

2020 ◽

Author(s):

wenxing su ◽

yi guan ◽

biao huang ◽

juanjuan wang ◽

yuqian wei ◽

...

Keyword(s):

Differentially Expressed Gene ◽

Primary Melanoma ◽

Enrichment Analysis ◽

Gene Interaction ◽

Underlying Mechanism ◽

Gene Expression Omnibus ◽

Pathway Enrichment Analysis ◽

Melanoma Metastasis ◽

Ppi Network ◽

Key Genes

Abstract Melanoma has the highest mortality rate of all skin tumors, and metastases are the major cause of death from it. The molecular mechanism leading to melanoma metastasis is currently unclear. With the goal of revealing the underlying mechanism, three data sets with accession numbers GSE8401, GSE46517 and GSE7956 were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the differentially expressed gene (DEG) of primary melanoma and metastatic melanoma, three kinds of analyses were performed, namely functional annotation, protein‐protein interaction (PPI) network and module construction, and co-expression and drug-gene interaction prediction analysis. 41 up-regulated genes and 79 down-regulated genes were selected for subsequent analyses. Results of pathway enrichment analysis showed that extracellular matrix organization and proteoglycans in cancer are closely related to melanoma metastasis. In addition, seven pivotal genes were identified from PPI network, including CXCL8, THBS1, COL3A1, TIMP3, KIT, DCN, and IGFBP5, which have all been verified in the TCGA database, but only CXCL8, THBS1 and KIT had significant differences in expression. To conclude, CXCL8, THBS1 and KIT may be the key genes in the metastasis of melanoma and thus may be regarded as therapeutic targets in the future.

Download Full-text

Identification of Issue Inhibitor of Metalloproteinase 1 (TIMP1) as a Potential Biomarker for the Diagnosis, Pathogenesis and Prognosis of Colorectal Cancer via Integrated Bioinformatic Analysis

10.21203/rs.3.rs-136189/v1 ◽

2020 ◽

Author(s):

Guona Li ◽

Mengmeng Kang ◽

Siyuan Sheng ◽

Ziyi Chen ◽

Kunshan Li ◽

...

Keyword(s):

Colorectal Cancer ◽

Network Analysis ◽

Enrichment Analysis ◽

Bioinformatic Analysis ◽

Molecular Therapy ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Pathway Enrichment ◽

Potential Biomarker

Abstract Background: Colorectal cancer (CRC) is a common malignant tumor of the digestive system. It is crucial to screen potential biomarkers for the diagnosis, pathogenesis, and prognosis of CRC because there are limited clinical symptoms associated with this cancer. Therefore, we attempted to identify biomarkers associated with the occurrence and progression of CRC by utilizing bioinformatic analysis and to elucidate a molecular mechanism for the diagnosis and treatment of CRC. Methods: Two independent gene expression profile datasets of colonic neoplasms (GSE44076 and GSE37182) were collected from public GEO datasets, which included 182 tumor tissues and 236 normal tissues. Next, differentially expressed genes (DEGs) between CRC colonic samples and non-CRC colonic samples were obtained via GEO2R online tools. Subsequently, hub genes were selected by several analyses of DEGs, including GO pathway enrichment analysis, KEGG pathway enrichment analysis, and PPI network analysis. Finally, the correlation between the hub genes and the occurrence of CRC was tested by harnessing survival analysis and ROC curve analysis. Results: Sixty-one shared DEGs were screened, including 44 high-expression genes and 17 low-expression genes, in CRC samples. Four genes (MYC, TIMP1, MMP7, and COL1A1) were considered to be hub genes because they exhibited higher connectivity degree scores through PPI network analysis. More importantly, there was a significant correlation between increased expression of TIMP1 and reduced survival time in patients with colorectal cancer. Conclusion: By using bioinformatic analysis, this study suggested that Timp-1 may represent a potential biomarker for the diagnosis and prognosis of targeted molecular therapy for CRC.

Download Full-text

Identification of Differentially Expressed Genes and associated pathways common to Eyelid and Non-Ocular Basal Cell Carcinoma to understand the Molecular Biology of BCC

10.1101/2021.05.01.442022 ◽

2021 ◽

Author(s):

Perumal Jayaraj ◽

Seema Sen ◽

Pranjal Vats ◽

Shefali Dahiya ◽

Vanshika Mohindroo

Keyword(s):

Basal Cell Carcinoma ◽

Cell Carcinoma ◽

Basal Cell ◽

Expression Profiles ◽

Enrichment Analysis ◽

Bioinformatic Analysis ◽

Malignant Neoplasms ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Pathway Enrichment

Background: Eyelid BCC accounts for more than 90% of Eyelid malignant neoplasms. Various aberrant signalling pathways and genes in Non-Ocular BCC have been found whereas Eyelid bcc remains elusive. Objective: This study aims to find the common DEGs of Eyelid and Non-Ocular BCC using bioinformatic analysis and text mining to gain more insights into the molecular aspects common to both BCC non-ocular and Eyelid BCC and to identify common potential prognostic markers. Material and method: The Gene Expression profiles of Eyelid BCC (GSE103439) and Non-Ocular BCC (GSE53462) were obtained from the NCBI GEO database followed by identification of common DEGs. Protein-Protein interaction and Pathway Enrichment analysis of these screened genes was done using bioinformatic tools like STRING, Cytoscape and BiNGO, DAVID, KEGG respectively. Results: A total of 181 genes were found common in both datasets. A PPI network was formed for the screened genes and 20 HUB genes were sorted which included CTNNB1, MAPK14, BTRC, EGFR, ADAM17. Pathway enrichment of HUB genes showed that they were dysregulated in carcinogenic and apoptotic pathways that seem to play a role in the progression of both the BCC. Conclusion: The result and findings of bioinformatic analysis highlighted the molecular pathways and genes enriched in both Eyelid BCC as well as Non- Ocular BCC. The identified pathways should be studied further to recognise common molecular events that would lead to the progression of BCC. This may provide a window to explore the prognostic and therapeutic strategies common to both BCC. Keywords: Basal cell carcinoma (BCC), Cancer, Microarray, Ophthalmology, Tumour marker

Download Full-text

Prediction and Validation of Hub Genes Associated with Colorectal Cancer by Integrating PPI Network and Gene Expression Data

BioMed Research International ◽

10.1155/2017/2421459 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 4

Author(s):

Yongfu Xiong ◽

Wenxian You ◽

Rong Wang ◽

Linglong Peng ◽

Zhongxue Fu

Keyword(s):

Colorectal Cancer ◽

Mrna Expression ◽

Interaction Network ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Advanced Tumor Stage ◽

Ppi Network ◽

Hub Genes ◽

Clinical Value ◽

Advanced Tumor

Although hundreds of colorectal cancer- (CRC-) related genes have been screened, the significant hub genes still need to be further identified. The aim of this study was to identify the hub genes based on protein-protein interaction network and uncover their clinical value. Firstly, 645 CRC patients’ data from the Tumor Cancer Genome Atlas were downloaded and analyzed to screen the differential expression genes (DEGs). And then, the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed, and PPI network of the DEGs was constructed by Cytoscape software. Finally, four hub genes (CXCL3, ELF5, TIMP1, and PHLPP2) were obtained from four subnets and further validated in our clinical setting and TCGA dataset. The results showed that mRNA expression of CXCL3, ELF5, and TIMP1 was increased in CRC tissues, whereas PHLPP2 mRNA expression was decreased. More importantly, high expression of CXCL3, ELF5, and TIMP1 was significantly associated with lymphatic invasion, distance metastasis, and advanced tumor stage. In addition, a shorter overall survival was observed in patients with increased CXCL3, TIMP1, and ELF5 expression and decreased PHLPP2 expression. In conclusion, the four hub genes screened by our strategy could serve as novel biomarkers for prognosis prediction of CRC patients.

Download Full-text

Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses

10.1101/2020.12.21.20248688 ◽

2020 ◽

Author(s):

Basavaraj Vastrad ◽

Chanabasayya Vastrad ◽

Iranna Kotturshetti

Keyword(s):

Regulatory Network ◽

Molecular Mechanisms ◽

Target Genes ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Bioinformatics Analyses ◽

Go Enrichment ◽

Jakob Disease

AbstractSporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. Pathway and GO enrichment analyses of DEGs were performed. Furthermore, the protein-protein interaction (PPI) network was predicted using the IntAct Molecular Interaction Database and visualized with Cytoscape software. In addition, hub genes and important modules were selected based on the network. Finally, we constructed target genes - miRNA regulatory network and target genes - TF regulatory network. Hub genes were validated. A total of 891 DEGs 448 of these DEGs presented significant up regulated, and the remaining 443 down regulated were obtained. Pathway enrichment analysis indicated that up regulated genes were mainly linked with glutamine degradation/glutamate biosynthesis, while the down regulated genes were involved in melatonin degradation. GO enrichment analyses indicated that up regulated genes were mainly linked with chemical synaptic transmission, while the down regulated genes were involved in regulation of immune system process. hub and target genes were selected from the PPI network, modules, and target genes - miRNA regulatory network and target genes - TF regulatory network namely YWHAZ, GABARAPL1, EZR, CEBPA, HSPB8, TUBB2A and CDK14. The current study sheds light on the molecular mechanisms of sCJD and may provide molecular targets and diagnostic biomarkers for sCJD.

Download Full-text

Exploration and Validation of Metastasis-associated Genes for Skin Cutaneous Melanoma

10.21203/rs.3.rs-940144/v2 ◽

2021 ◽

Author(s):

Hong Luan ◽

Linge Jian ◽

Ye He ◽

Tuo Zhang ◽

Yanna Su ◽

...

Keyword(s):

Metastatic Melanoma ◽

Cutaneous Melanoma ◽

Molecular Mechanisms ◽

Interaction Analysis ◽

Primary Melanoma ◽

Gene Interaction ◽

Skin Tumor ◽

Melanoma Metastasis ◽

Hub Genes ◽

Hub Gene

Abstract Background: Skin cutaneous melanoma is a malignant and highly metastatic skin tumor, and its morbidity and mortality are still rising worldwide. However, the molecular mechanisms that promote melanoma metastasis are unclear. Methods: Two datasets (GSE15605 and GSE46517) were retrieved to identify the differentially expressed genes (DEGs), including 23 normal skin tissues (N), 77 primary melanoma tissues (T) and 85 metastatic melanoma tissues (M). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were performed to explore the functions of the DEGs. The protein–protein interaction (PPI) network was constructed using the STRING tool and Cytoscape software. We used the cytoHubba plugin of Cytoscape to identify the most significant hub genes by five topological analyses (Degree, Bottleneck, MCC, MNC, and EPC). Hub gene expression was validated using the UALCAN website. Clinical relevance was investigated using The Cancer Genome Atlas (TCGA) resources. Finally, we explored the association between metastasis-associated genes and immune infiltrates through the Tumor Immune Estimation Resource (TIMER) database and performed drug-gene interaction analysis using the Drug-Gene Interaction database.Results: A total of 294 specific genes were related to melanoma metastasis and were mainly involved in the positive regulation of locomotion, mitotic cell cycle process, and epithelial cell differentiation. Four hub genes (CDK1, FOXM1, KIF11, and RFC4) were identified from the cytoHubba plugin of Cytoscape. CDK1 was significantly upregulated in metastatic melanoma compared with primary melanoma, and high expression of CDK1 was positively correlated with poor prognosis. We found that CDK1 expression correlated positively with the infiltration levels of macrophage cells (Rho = -0.164, P = 2.02e-03) and neutrophil cells (Rho = 0.269, P = 2.72e-07) in SKCM metastasis. In addition, we identified that CDK1 had a close interaction with 10 antitumor drugs. Conclusions: CDK1 was identified as a hub gene involved in the progression of melanoma metastasis and may be regarded as a therapeutic target for melanoma patients to improve prognosis and prevent metastasis in the future.

Download Full-text

Potential Molecular Mechanism of the NPPB Gene in Postischemic Heart Failure with and without T2DM

BioMed Research International ◽

10.1155/2020/2159460 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Yao-Zong Guan ◽

Rui-Xing Yin ◽

Guo-Xiong Deng ◽

Peng-Fei Zheng ◽

Chun-Xiao Liu ◽

...

Keyword(s):

Heart Failure ◽

Tricarboxylic Acid Cycle ◽

Enrichment Analysis ◽

Microarray Dataset ◽

Tricarboxylic Acid ◽

Metabolic Process ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Go Annotation

Background. This study is aimed at investigating natriuretic peptide B (NPPB) coexpression genes and their pathways involved in heart failure (HF) among patients both with and without type 2 diabetes mellitus (T2DM). Methods. The microarray dataset GSE26887, containing 19 postischemic HF patients’ peripheral blood samples (7 with T2DM and 12 without T2DM), was examined to detect the genes coexpressed with NPPB using the corr.test function in the R packet. Furthermore, using online analytical tools, we determined the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, Gene Ontology (GO) annotation, and protein-protein interaction (PPI) network of the coexpression genes. The modules and hub genes of the PPI network were then identified using the Cytoscape software. Results. In patients with T2DM, a total of 41 biological processes (BP), 20 cellular components (CC), 13 molecular functions (MF), and 41 pathways were identified. Furthermore, a total of 61 BPs, 16 CCs, 13 MFs, and 22 pathways in patients without T2DM were identified. In both groups of patients, 17 BPs, 10 CCs, 6 MFs, and 13 pathways were enriched. We also identified 173 intersectional coexpression genes (63 positively, 106 negatively, and 4 differently coexpressed in patients with and without T2DM, respectively) in both types of patients, which were enriched in 16 BPs, 8 CCs, 3 MFs, and 8 KEGG pathways. Moreover, the PPI network (containing 237 edges and 170 nodes) with the top module significantly enriched in 4 BPs (tricarboxylic acid metabolic process, citrate metabolic process, tricarboxylic acid cycle, and aerobic respiration) and 3 pathways (citrate cycle, malaria parasite metabolic pathway, and AGE-RAGE signaling pathway in diabetic complications) was constructed. DECR1, BGN, TIMP1, VCAN, and CTCF are the top hub genes. Conclusions. Our findings may elucidate the functions and roles of the NPPB gene in patients with postischemic HF and facilitate HF management.

Download Full-text