Identification of a Pathway-Based 5-Gene Expression Signature for Predicting Outcomes in Gastric Cancer

Alabi, Nikolay; Sheka, Dropen; Gupta, Mehul; Kannappan, Sunand

doi:10.4172/jpb.1000482

Cited by 2 publications

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“…For those genes in the samples that showed significant changes, we used analysis of variance (ANOVA) in R ( R Core Team, 2013 ) to determine the variance in genes between the two groups. ANOVA is a collection of statistical models useful for DEG analysis ( Alabi et al, 2018 ; Monterisi et al, 2015 ). We obtained 2,953 significant DEGs ( Table S2 ) in ACC with a p < 0.001 and |log2 (fold-change)| > 1 cutoff.…”

Section: Methodsmentioning

confidence: 99%

Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA

Xia

et al. 2019

PeerJ

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Background Adrenocortical carcinoma (ACC) is a rare and aggressive malignant cancer in the adrenal cortex with poor prognosis. Though previous research has attempted to elucidate the progression of ACC, its molecular mechanism remains poorly understood. Methods Gene transcripts per million (TPM) data were downloaded from the UCSC Xena database, which included ACC (The Cancer Genome Atlas, n = 77) and normal samples (Genotype Tissue Expression, n = 128). We used weighted gene co-expression network analysis to identify gene connections. Overall survival (OS) was determined using the univariate Cox model. A protein–protein interaction (PPI) network was constructed by the search tool for the retrieval of interacting genes. Results To determine the critical genes involved in ACC progression, we obtained 2,953 significantly differentially expressed genes and nine modules. Among them, the blue module demonstrated significant correlation with the “Stage” of ACC. Enrichment analysis revealed that genes in the blue module were mainly enriched in cell division, cell cycle, and DNA replication. Combined with the PPI and co-expression networks, we identified four hub genes (i.e., TOP2A, TTK, CHEK1, and CENPA) that were highly expressed in ACC and negatively correlated with OS. Thus, these identified genes may play important roles in the progression of ACC and serve as potential biomarkers for future diagnosis.

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Section: Methodsmentioning

confidence: 99%

Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA

Xia

et al. 2019

PeerJ

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“…For those genes in the samples that showed significant changes, we used analysis of variance (ANOVA) in R (v3.0.2) to determine the variance in genes between the two groups. ANOVA is a collection of statistical models useful for DEG analysis (Alabi et al, 2018;Simona et al, 2015). We obtained 2,953 significant DEGs (Table S2) in ACC with a p < 0.001 and |log2 (fold-change)| > 1 cutoff.…”

Section: Deg Screeningmentioning

confidence: 99%

Peer Review #3 of "Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA (v0.2)"

2019

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Background. Adrenocortical carcinoma (ACC) is a rare and aggressive malignant cancer in the adrenal cortex with poor prognosis. Though previous research has attempted to elucidate the progression of ACC, its molecular mechanism remains poorly understood. Methods. Gene TPM (transcripts per million) data were downloaded from the UCSC Xena database, which included ACC (The Cancer Genome Atlas (TCGA), n = 77) and normal samples (Genotype Tissue Expression (GTEx), n = 128). We used weighted gene co-expression network analysis (WGCNA) to identify gene connections. Overall survival (OS) was determined using the univariate Cox model. A protein-protein interaction (PPI) network was constructed by the Search Tool for the Retrieval of Interacting Genes (STRING). Results. To determine the critical genes involved in ACC progression, we obtained 2,953 significantly differentially expressed genes (DEGs) and nine modules. Among them, the blue module demonstrated significant correlation with the "Stage" of ACC. Enrichment analysis revealed that genes in the blue module were mainly enriched in cell division, cell cycle, and DNA replication. Combined with the PPI and co-expression networks, we identified four hub genes (i.e., TOP2A, TTK, CHEK1, and CENPA) that were highly expressed in ACC and negatively correlated with OS. Thus, these identified genes may play important roles in the progression of ACC and serve as potential biomarkers for future diagnosis.

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Identification of a Pathway-Based 5-Gene Expression Signature for Predicting Outcomes in Gastric Cancer

Cited by 2 publications

References 0 publications

Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA

Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA

Peer Review #3 of "Identification of four hub genes associated with adrenocortical carcinoma progression by WGCNA (v0.2)"

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