Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma

Abstract Background The aim of this study was to construct a model based on the prognostic features associated with epithelial–mesenchymal transition (EMT) to explore the various mechanisms and therapeutic strategies available for the treatment of metastasis and invasion by hepatocellular carcinoma...

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Autores principales:	Dafeng Xu, Yu Wang, Jincai Wu, Shixun Lin, Yonghai Chen, Jinfang Zheng
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	EMT HCC Prognosis G6PD Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Cytology QH573-671
Acceso en línea:	https://doaj.org/article/7db4f30d144f4431a78638ec27c454dc
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spelling	oai:doaj.org-article:7db4f30d144f4431a78638ec27c454dc2021-11-28T12:37:04ZIdentification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma10.1186/s12935-021-02326-81475-2867https://doaj.org/article/7db4f30d144f4431a78638ec27c454dc2021-11-01T00:00:00Zhttps://doi.org/10.1186/s12935-021-02326-8https://doaj.org/toc/1475-2867Abstract Background The aim of this study was to construct a model based on the prognostic features associated with epithelial–mesenchymal transition (EMT) to explore the various mechanisms and therapeutic strategies available for the treatment of metastasis and invasion by hepatocellular carcinoma (HCC) cells. Methods EMT-associated genes were identified, and their molecular subtypes were determined by consistent clustering analysis. The differentially expressed genes (DEGs) among the molecular subtypes were ascertained using the limma package and they were subjected to functional enrichment analysis. The immune cell scores of the molecular subtypes were evaluated using ESTIMATE, MCPcounter, and GSCA packages of R. A multi-gene prognostic model was constructed using lasso regression, and the immunotherapeutic effects of the model were analyzed using the Imvigor210 cohort. In addition, immunohistochemical analysis was performed on a cohort of HCC tissue to validate gene expression. Results Based on the 59 EMT-associated genes identified, the 365—liver hepatocellular carcinoma (LIHC) samples were divided into two subtypes, C1 and C2. The C1 subtype mostly showed poor prognosis, had higher immune scores compared to the C2 subtype, and showed greater correlation with pathways of tumor progression. A four-gene signature construct was fabricated based on the 1130 DEGs among the subtypes. The construct was highly robust and showed stable predictive efficacy when validated using datasets from different platforms (HCCDB18 and GSE14520). Additionally, compared to currently existing models, our model demonstrated better performance. The results of the immunotherapy cohort showed that patients in the low-risk group have a better immune response, leading to a better patient’s prognosis. Immunohistochemical analysis revealed that the expression levels of the FTCD, PON1, and TMEM45A were significantly over-expressed in 41 normal samples compared to HCC samples, while that of the G6PD was significantly over-expressed in cancerous tissues. Conclusions The four-gene signature construct fabricated based on the EMT-associated genes provides valuable information to further study the pathogenesis and clinical management of HCC.Dafeng XuYu WangJincai WuShixun LinYonghai ChenJinfang ZhengBMCarticleEMTHCCPrognosisG6PDNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282CytologyQH573-671ENCancer Cell International, Vol 21, Iss 1, Pp 1-21 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	EMT HCC Prognosis G6PD Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Cytology QH573-671
spellingShingle	EMT HCC Prognosis G6PD Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Cytology QH573-671 Dafeng Xu Yu Wang Jincai Wu Shixun Lin Yonghai Chen Jinfang Zheng Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma
description	Abstract Background The aim of this study was to construct a model based on the prognostic features associated with epithelial–mesenchymal transition (EMT) to explore the various mechanisms and therapeutic strategies available for the treatment of metastasis and invasion by hepatocellular carcinoma (HCC) cells. Methods EMT-associated genes were identified, and their molecular subtypes were determined by consistent clustering analysis. The differentially expressed genes (DEGs) among the molecular subtypes were ascertained using the limma package and they were subjected to functional enrichment analysis. The immune cell scores of the molecular subtypes were evaluated using ESTIMATE, MCPcounter, and GSCA packages of R. A multi-gene prognostic model was constructed using lasso regression, and the immunotherapeutic effects of the model were analyzed using the Imvigor210 cohort. In addition, immunohistochemical analysis was performed on a cohort of HCC tissue to validate gene expression. Results Based on the 59 EMT-associated genes identified, the 365—liver hepatocellular carcinoma (LIHC) samples were divided into two subtypes, C1 and C2. The C1 subtype mostly showed poor prognosis, had higher immune scores compared to the C2 subtype, and showed greater correlation with pathways of tumor progression. A four-gene signature construct was fabricated based on the 1130 DEGs among the subtypes. The construct was highly robust and showed stable predictive efficacy when validated using datasets from different platforms (HCCDB18 and GSE14520). Additionally, compared to currently existing models, our model demonstrated better performance. The results of the immunotherapy cohort showed that patients in the low-risk group have a better immune response, leading to a better patient’s prognosis. Immunohistochemical analysis revealed that the expression levels of the FTCD, PON1, and TMEM45A were significantly over-expressed in 41 normal samples compared to HCC samples, while that of the G6PD was significantly over-expressed in cancerous tissues. Conclusions The four-gene signature construct fabricated based on the EMT-associated genes provides valuable information to further study the pathogenesis and clinical management of HCC.
format	article
author	Dafeng Xu Yu Wang Jincai Wu Shixun Lin Yonghai Chen Jinfang Zheng
author_facet	Dafeng Xu Yu Wang Jincai Wu Shixun Lin Yonghai Chen Jinfang Zheng
author_sort	Dafeng Xu
title	Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma
title_short	Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma
title_full	Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma
title_fullStr	Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma
title_full_unstemmed	Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma
title_sort	identification and clinical validation of emt-associated prognostic features based on hepatocellular carcinoma
publisher	BMC
publishDate	2021
url	https://doaj.org/article/7db4f30d144f4431a78638ec27c454dc
work_keys_str_mv	AT dafengxu identificationandclinicalvalidationofemtassociatedprognosticfeaturesbasedonhepatocellularcarcinoma AT yuwang identificationandclinicalvalidationofemtassociatedprognosticfeaturesbasedonhepatocellularcarcinoma AT jincaiwu identificationandclinicalvalidationofemtassociatedprognosticfeaturesbasedonhepatocellularcarcinoma AT shixunlin identificationandclinicalvalidationofemtassociatedprognosticfeaturesbasedonhepatocellularcarcinoma AT yonghaichen identificationandclinicalvalidationofemtassociatedprognosticfeaturesbasedonhepatocellularcarcinoma AT jinfangzheng identificationandclinicalvalidationofemtassociatedprognosticfeaturesbasedonhepatocellularcarcinoma
_version_	1718407899459354624

Identification and clinical validation of EMT-associated prognostic features based on hepatocellular carcinoma

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