Cargando…

Prognostic 7-SLC-Gene Signature Identified via Weighted Gene Co-Expression Network Analysis for Patients with Hepatocellular Carcinoma

BACKGROUND: Solute carrier (SLC) proteins play an important role in tumor metabolism. But SLC-associated genes' prognostic significance in hepatocellular carcinoma (HCC) remained elusive. We identified SLC-related factors and developed an SLC-related classifier to predict and improve HCC progno...

Descripción completa

Detalles Bibliográficos
Autores principales: Xiong, Lingfeng, Luo, Yongping, Yuan, Tianbai, Lin, Weipeng, Lin, Bohui, Wu, Chen, Duan, Yuyou, Ou, Yimeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9957622/
https://www.ncbi.nlm.nih.gov/pubmed/36844876
http://dx.doi.org/10.1155/2023/4364654
_version_ 1784894867092013056
author Xiong, Lingfeng
Luo, Yongping
Yuan, Tianbai
Lin, Weipeng
Lin, Bohui
Wu, Chen
Duan, Yuyou
Ou, Yimeng
author_facet Xiong, Lingfeng
Luo, Yongping
Yuan, Tianbai
Lin, Weipeng
Lin, Bohui
Wu, Chen
Duan, Yuyou
Ou, Yimeng
author_sort Xiong, Lingfeng
collection PubMed
description BACKGROUND: Solute carrier (SLC) proteins play an important role in tumor metabolism. But SLC-associated genes' prognostic significance in hepatocellular carcinoma (HCC) remained elusive. We identified SLC-related factors and developed an SLC-related classifier to predict and improve HCC prognosis and treatment. METHODS: From the TCGA database, corresponding clinical data and mRNA expression profiles of 371 HCC patients were acquired, and those of 231 tumor samples were derived from the ICGC database. Genes associated with clinical features were filtered using weighted gene correlation network analysis (WGCNA). Next, univariate LASSO Cox regression studies developed SLC risk profiles, with the ICGC cohort data being used in validation. RESULT: Univariate Cox regression analysis revealed that 31 SLC genes (P < 0.05) were related to HCC prognosis. 7 (SLC22A25, SLC2A2, SLC41A3, SLC44A1, SLC48A1, SLC4A2, and SLC9A3R1) of these genes were applied in developing a SLC gene prognosis model. Samples were classified into the low-andhigh-risk groups by the prognostic signature, with those in the high-risk group showing a significantly worse prognosis (P < 0.001 in the TCGA cohort and P=0.0068 in the ICGC cohort). ROC analysis validated the signature's prediction power. In addition, functional analyses showed enrichment of immune-related pathways and different immune status between the two risk groups. CONCLUSION: The 7-SLC-gene prognostic signature established in this study helped predict the prognosis, and was also correlated with the tumor immune status and infiltration of different immune cells in the tumor microenvironment. The current findings may provide important clinical indications for proposing a novel combination therapy consists of targeted anti-SLC therapy and immunotherapy for HCC patients.
format Online
Article
Text
id pubmed-9957622
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-99576222023-02-25 Prognostic 7-SLC-Gene Signature Identified via Weighted Gene Co-Expression Network Analysis for Patients with Hepatocellular Carcinoma Xiong, Lingfeng Luo, Yongping Yuan, Tianbai Lin, Weipeng Lin, Bohui Wu, Chen Duan, Yuyou Ou, Yimeng J Oncol Research Article BACKGROUND: Solute carrier (SLC) proteins play an important role in tumor metabolism. But SLC-associated genes' prognostic significance in hepatocellular carcinoma (HCC) remained elusive. We identified SLC-related factors and developed an SLC-related classifier to predict and improve HCC prognosis and treatment. METHODS: From the TCGA database, corresponding clinical data and mRNA expression profiles of 371 HCC patients were acquired, and those of 231 tumor samples were derived from the ICGC database. Genes associated with clinical features were filtered using weighted gene correlation network analysis (WGCNA). Next, univariate LASSO Cox regression studies developed SLC risk profiles, with the ICGC cohort data being used in validation. RESULT: Univariate Cox regression analysis revealed that 31 SLC genes (P < 0.05) were related to HCC prognosis. 7 (SLC22A25, SLC2A2, SLC41A3, SLC44A1, SLC48A1, SLC4A2, and SLC9A3R1) of these genes were applied in developing a SLC gene prognosis model. Samples were classified into the low-andhigh-risk groups by the prognostic signature, with those in the high-risk group showing a significantly worse prognosis (P < 0.001 in the TCGA cohort and P=0.0068 in the ICGC cohort). ROC analysis validated the signature's prediction power. In addition, functional analyses showed enrichment of immune-related pathways and different immune status between the two risk groups. CONCLUSION: The 7-SLC-gene prognostic signature established in this study helped predict the prognosis, and was also correlated with the tumor immune status and infiltration of different immune cells in the tumor microenvironment. The current findings may provide important clinical indications for proposing a novel combination therapy consists of targeted anti-SLC therapy and immunotherapy for HCC patients. Hindawi 2023-02-17 /pmc/articles/PMC9957622/ /pubmed/36844876 http://dx.doi.org/10.1155/2023/4364654 Text en Copyright © 2023 Lingfeng Xiong et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Xiong, Lingfeng
Luo, Yongping
Yuan, Tianbai
Lin, Weipeng
Lin, Bohui
Wu, Chen
Duan, Yuyou
Ou, Yimeng
Prognostic 7-SLC-Gene Signature Identified via Weighted Gene Co-Expression Network Analysis for Patients with Hepatocellular Carcinoma
title Prognostic 7-SLC-Gene Signature Identified via Weighted Gene Co-Expression Network Analysis for Patients with Hepatocellular Carcinoma
title_full Prognostic 7-SLC-Gene Signature Identified via Weighted Gene Co-Expression Network Analysis for Patients with Hepatocellular Carcinoma
title_fullStr Prognostic 7-SLC-Gene Signature Identified via Weighted Gene Co-Expression Network Analysis for Patients with Hepatocellular Carcinoma
title_full_unstemmed Prognostic 7-SLC-Gene Signature Identified via Weighted Gene Co-Expression Network Analysis for Patients with Hepatocellular Carcinoma
title_short Prognostic 7-SLC-Gene Signature Identified via Weighted Gene Co-Expression Network Analysis for Patients with Hepatocellular Carcinoma
title_sort prognostic 7-slc-gene signature identified via weighted gene co-expression network analysis for patients with hepatocellular carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9957622/
https://www.ncbi.nlm.nih.gov/pubmed/36844876
http://dx.doi.org/10.1155/2023/4364654
work_keys_str_mv AT xionglingfeng prognostic7slcgenesignatureidentifiedviaweightedgenecoexpressionnetworkanalysisforpatientswithhepatocellularcarcinoma
AT luoyongping prognostic7slcgenesignatureidentifiedviaweightedgenecoexpressionnetworkanalysisforpatientswithhepatocellularcarcinoma
AT yuantianbai prognostic7slcgenesignatureidentifiedviaweightedgenecoexpressionnetworkanalysisforpatientswithhepatocellularcarcinoma
AT linweipeng prognostic7slcgenesignatureidentifiedviaweightedgenecoexpressionnetworkanalysisforpatientswithhepatocellularcarcinoma
AT linbohui prognostic7slcgenesignatureidentifiedviaweightedgenecoexpressionnetworkanalysisforpatientswithhepatocellularcarcinoma
AT wuchen prognostic7slcgenesignatureidentifiedviaweightedgenecoexpressionnetworkanalysisforpatientswithhepatocellularcarcinoma
AT duanyuyou prognostic7slcgenesignatureidentifiedviaweightedgenecoexpressionnetworkanalysisforpatientswithhepatocellularcarcinoma
AT ouyimeng prognostic7slcgenesignatureidentifiedviaweightedgenecoexpressionnetworkanalysisforpatientswithhepatocellularcarcinoma