A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes
Several epithelial-mesenchymal transition (EMT)-associated genes (EAGs) have been confirmed to correlate with the prognosis of hepatocellular carcinoma (HCC) patients. Herein, we explored the value of EAGs in the prognosis of HCC relying on data from The Cancer Genome Atlas (TCGA) database. A total...
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doaj-a48b6181f69c4d7b821633092cf5d9372021-06-02T08:43:41ZengTaylor & Francis GroupBioengineered2165-59792165-59872020-01-011111034104610.1080/21655979.2020.18227151822715A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genesChen Xiong0Guifu Wang1Dousheng Bai2Dalian Medical UniversityDalian Medical UniversityClinical Medical College, Yangzhou UniversitySeveral epithelial-mesenchymal transition (EMT)-associated genes (EAGs) have been confirmed to correlate with the prognosis of hepatocellular carcinoma (HCC) patients. Herein, we explored the value of EAGs in the prognosis of HCC relying on data from The Cancer Genome Atlas (TCGA) database. A total of 200 EMT-associated genes were downloaded from the Gene set enrichment analysis (GSEA) website. Moreover, 96 differentially expressed EAGs were identified. Using Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we forecasted the potential molecular mechanisms of EAGs. To identify prognostic EAGs, Cox regression was used in developing a prognostic risk model. Then, the Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the prognostic significance of the model. A total of 5 prognostic correlated EAGs (P3H1, SPP1, MMP1, LGALS1, and ITGB5) were screened via Cox regression, which provided the basis for developing a novel prognostic risk model. Based on the risk model, patients were subdivided into high-risk and low-risk groups. The overall survival of the low-risk group was better compared to the high-risk group (P < 0.00001). The ROC curve of the risk model showed a higher AUC (Area under Curve) (AUC = 0.723) compared to other clinical features (AUC ≤ 0.511). A nomogram based on this model was constructed to predict the 1-year, 2-year, and 3-year overall survival rates (OS) of patients. Conclusively, we developed a novel HCC prognostic risk model based on the expression of EAGs, which help advance the prognostic management of HCC patients. Abbreviations: HCC: hepatocellular carcinoma; TCGA: The Cancer Genome Atlas; EMT: epithelial-mesenchymal transition; EAGs: EMT-associated genes; GSEA: gene set enrichment analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; PPI: protein-protein interaction; TF: transcription factor; ROC: receiver operating characteristic; K-M: Kaplan-Meier; AUC: the area under the ROC curve; FDR: false discovery rate; TNM: Tumor size/lymph nodes/distance metastasishttp://dx.doi.org/10.1080/21655979.2020.1822715hepatocellular carcinomaepithelial-mesenchymal transitionprognosisnomogram |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chen Xiong Guifu Wang Dousheng Bai |
spellingShingle |
Chen Xiong Guifu Wang Dousheng Bai A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes Bioengineered hepatocellular carcinoma epithelial-mesenchymal transition prognosis nomogram |
author_facet |
Chen Xiong Guifu Wang Dousheng Bai |
author_sort |
Chen Xiong |
title |
A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes |
title_short |
A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes |
title_full |
A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes |
title_fullStr |
A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes |
title_full_unstemmed |
A novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes |
title_sort |
novel prognostic models for identifying the risk of hepatocellular carcinoma based on epithelial-mesenchymal transition-associated genes |
publisher |
Taylor & Francis Group |
series |
Bioengineered |
issn |
2165-5979 2165-5987 |
publishDate |
2020-01-01 |
description |
Several epithelial-mesenchymal transition (EMT)-associated genes (EAGs) have been confirmed to correlate with the prognosis of hepatocellular carcinoma (HCC) patients. Herein, we explored the value of EAGs in the prognosis of HCC relying on data from The Cancer Genome Atlas (TCGA) database. A total of 200 EMT-associated genes were downloaded from the Gene set enrichment analysis (GSEA) website. Moreover, 96 differentially expressed EAGs were identified. Using Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, we forecasted the potential molecular mechanisms of EAGs. To identify prognostic EAGs, Cox regression was used in developing a prognostic risk model. Then, the Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the prognostic significance of the model. A total of 5 prognostic correlated EAGs (P3H1, SPP1, MMP1, LGALS1, and ITGB5) were screened via Cox regression, which provided the basis for developing a novel prognostic risk model. Based on the risk model, patients were subdivided into high-risk and low-risk groups. The overall survival of the low-risk group was better compared to the high-risk group (P < 0.00001). The ROC curve of the risk model showed a higher AUC (Area under Curve) (AUC = 0.723) compared to other clinical features (AUC ≤ 0.511). A nomogram based on this model was constructed to predict the 1-year, 2-year, and 3-year overall survival rates (OS) of patients. Conclusively, we developed a novel HCC prognostic risk model based on the expression of EAGs, which help advance the prognostic management of HCC patients. Abbreviations: HCC: hepatocellular carcinoma; TCGA: The Cancer Genome Atlas; EMT: epithelial-mesenchymal transition; EAGs: EMT-associated genes; GSEA: gene set enrichment analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; PPI: protein-protein interaction; TF: transcription factor; ROC: receiver operating characteristic; K-M: Kaplan-Meier; AUC: the area under the ROC curve; FDR: false discovery rate; TNM: Tumor size/lymph nodes/distance metastasis |
topic |
hepatocellular carcinoma epithelial-mesenchymal transition prognosis nomogram |
url |
http://dx.doi.org/10.1080/21655979.2020.1822715 |
work_keys_str_mv |
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