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pmid:32903837

Integrated PPI- and WGCNA-Retrieval of Hub Gene Signatures Shared Between Barrett's Esophagus and Esophageal Adenocarcinoma.

Asma Sindhoo Nangraj · Gurudeeban Selvaraj · Satyavani Kaliamurthi · Aman Chandra Kaushik · William C Cho · Dong Qing Wei

Frontiers in pharmacology · 2020 doi:10.3389/fphar.2020.00881

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Experiment

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Data

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:32903837
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title
Integrated PPI- and WGCNA-Retrieval of Hub Gene Signatures Shared Between Barrett's Esophagus and Esophageal Adenocarcinoma.
doi
10.3389/fphar.2020.00881
pmid
32903837
authors array · 6 items
[0]
Asma Sindhoo Nangraj
[1]
Gurudeeban Selvaraj
[2]
Satyavani Kaliamurthi
[3]
Aman Chandra Kaushik
[4]
William C Cho
[5]
Dong Qing Wei
journal
Frontiers in pharmacology
year
2020
abstract
Esophageal adenocarcinoma (EAC) is a deadly cancer with high mortality rate, especially in economically advanced countries, while Barrett's esophagus (BE) is reported to be a precursor that strongly increases the risk of EAC. Due to the complexity of these diseases, their molecular mechanisms have not been revealed clearly. This study aims to explore the gene signatures shared between BE and EAC based on integrated network analysis. We obtained EAC- and BE-associated microarray datasets GSE26886, GSE1420, GSE37200, and GSE37203 from the Gene Expression Omnibus and ArrayExpress using systematic meta-analysis. These data were accompanied by clinical data and RNAseq data from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to explore the relationship between gene sets and clinical traits as well as to discover the key relationships behind the co-expression modules. A differentially expressed gene-based protein-protein interaction (PPI) complex was used to extract hub genes through Cytoscape plugins. As a result, 403 DEGs were excavated, comprising 236 upregulated and 167 downregulated genes, which are involved in the cell cycle and replication pathways. Forty key genes were identified using modules of MCODE, CytoHubba, and CytoNCA with different algorithms. A dark-gray module with 207 genes was identified which having a high correlation with phenotype (gender) in the WGCNA. Furthermore, five shared hub gene signatures (SHGS), namely, pre-mRNA processing factor 4 (PRPF4), serine and arginine-rich splicing factor 1 (SRSF1), heterogeneous nuclear ribonucleoprotein M (HNRNPM), DExH-Box Helicase 9 (DHX9), and origin recognition complex subunit 2 (ORC2), were identified between BE and EAC. SHGS enrichment denotes that RNA metabolism and splicosomes play a key role in esophageal cancer development and progress. We conclude that the PPI complex and WGCNA co-expression network highlight the importance of phenotypic identifying hub gene signatures for BE and EAC.
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The R package survival was employed to calculate Kaplan–Meier (KM) survival plots with hazard ratio (HR) and log-rank tests of hubs, which was implemented in the OSeac 6 (consensus survival analysis for EAC) web interface. OSeac retrieved the gene expression profiles and clinical data including TNM (Stage I, II, III, and IV), gender (male and female), race (White, Black, and African American), and grade (G1, G2, G3, and GX) of 198 patients from TCGA and GEO.
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sections[9] "Survival Analysis and Validation of SHGS" paragraph 2
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The R package survival was employed to calculate Kaplan–Meier (KM) survival plots with hazard ratio (HR) and log-rank tests of hubs, which was implemented in the OSeac 6 (consensus survival analysis for EAC) web interface. OSeac retrieved the gene expression profiles and clinical data including TNM (Stage I, II, III, and IV), gender (male and female), race (White, Black, and African American), and grade (G1, G2, G3, and GX) of 198 patients from TCGA and GEO.
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The dataset GSE37200 was used to construct a co-expression network with the relevant clinical trait information. After preprocessing and normalization, the GSE37200 dataset with 22,284 genes was further processed, and variant genes (12,701) were selected for WGCNA studies.
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Gene expression profiling of Barrett’s esophageal tissues and esophageal adenocarcinoma specimens
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The R package survival was employed to calculate Kaplan–Meier (KM) survival plots with hazard ratio (HR) and log-rank tests of hubs, which was implemented in the OSeac 6 (consensus survival analysis for EAC) web interface. OSeac retrieved the gene expression profiles and clinical data including TNM (Stage I, II, III, and IV), gender (male and female), race (White, Black, and African American), and grade (G1, G2, G3, and GX) of 198 patients from TCGA and GEO.
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analysis. We obtained EAC- and BE-associated microarray datasets GSE26886, GSE1420, GSE37200, and GS
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The R package survival was employed to calculate Kaplan–Meier (KM) survival plots with hazard ratio (HR) and log-rank tests of hubs, which was implemented in the OSeac 6 (consensus survival analysis for EAC) web interface. OSeac retrieved the gene expression profiles and clinical data including TNM (Stage I, II, III, and IV), gender (male and female), race (White, Black, and African American), and grade (G1, G2, G3, and GX) of 198 patients from TCGA and GEO.
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Complete file
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Due to the complexity of these diseases, their molecular mechanisms have not been revealed clearly. This study aims to explore the gene signatures shared between BE and EAC based on integrated network analysis. We obtained EAC- and BE-associated microarray datasets GSE26886, GSE1420, GSE37200, and GSE37203 from the Gene Expression Omnibus and ArrayExpress using systematic meta-analysis. These data were accompanied by clinical data and RNAseq data from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were conducted to explore the relationship between gene sets and clinical traits as well as to discover the key relationships behind the co-expression modules. A differentially expressed gene-based protein-protein interaction (PPI) complex was used to extract hub genes through Cytoscape plugins. As a result, 403 DEGs were excavated, comprising 236 upregulated and 167 downregulated genes, which are involved in the cell cycle and replication pathways. Forty key genes were identified using modules of MCODE, CytoHubba, and CytoNCA with different algorithms. A dark-gray module with 207 genes was identified which having a high correlation with phenotype (gender) in the WGCNA. Furthermore, five shared hub gene signatures (SHGS), namely, pre-mRNA processing factor 4 (PRPF4), serine and arginine-rich splicing factor 1 (SRSF1), heterogeneous nuclear ribonucleoprotein M (HNRNPM), DExH-Box Helicase 9 (DHX9), and origin recognition complex subunit 2 (ORC2), were identified between BE and EAC. SHGS enrichment denotes that RNA metabolism and splicosomes play a key role in esophageal cancer development and progress. 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