Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis

Abstract Background Hepatocellular carcinoma (HCC) is often caused by chronic liver infection or inflammation. Searching for potential immunotherapy targets will aid the early diagnosis and treatment of HCC. Methods Firstly, detailed HCC data were downloaded from The Cancer Genome Atlas database. GD...

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Main Authors: Yinghui Hou, Guizhi Zhang
Format: Article
Language:English
Published: BMC 2021-07-01
Series:Diagnostic Pathology
Subjects:
LCK
Online Access:https://doi.org/10.1186/s13000-021-01118-y
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spelling doaj-4ccd034dc4d44dada568c6c4a2635a9c2021-07-04T11:48:52ZengBMCDiagnostic Pathology1746-15962021-07-0116111410.1186/s13000-021-01118-yIdentification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysisYinghui Hou0Guizhi Zhang1Department of Gastroenterology, The Second People’s Hospital of Liaocheng CityDepartment of Gastroenterology, The Second People’s Hospital of Liaocheng CityAbstract Background Hepatocellular carcinoma (HCC) is often caused by chronic liver infection or inflammation. Searching for potential immunotherapy targets will aid the early diagnosis and treatment of HCC. Methods Firstly, detailed HCC data were downloaded from The Cancer Genome Atlas database. GDCRNATools was used for the comprehensive analysis of RNA sequencing data. Subsequently, the CIBERSORT package was used to estimate infiltration scores of 22 types of immune cells in complex samples. Furthermore, hub genes were identified via weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis. In addition, multiple databases were used to validate the expression of hub gene in the tumor tissue. Finally, prognostic, diagnostic and immunohistochemical analysis of key hub genes was performed. Results In the present study, 9 hub genes were identified using WGCNA and PPI network analysis. Furthermore, the expression levels of 9 genes were positively correlated with the infiltration levels of CD8-positive T (CD8+ T) cells. In multiple dataset validations, the expression levels of CCL5, CXCR6, CD3E, and LCK were decreased in cancer tissues. In addition, survival analysis revealed that patients with LCK low expression had a poor survival prognosis (P < 0.05). Immunohistochemistry results demonstrated that CCL5, CD3E and LCK were expressed at low levels in HCC cancer tissues. Conclusion The identification of CCL5, CXCR6, CD3E and LCK may be helpful in the development of early diagnosis and therapy of HCC. LCK may be a potential prognostic biomarker for immunotherapy for HCC.https://doi.org/10.1186/s13000-021-01118-yHepatocellular carcinomaCD8+ T cellsLCKWeighted gene co-expression network analysisDiagnosis and prognosis
collection DOAJ
language English
format Article
sources DOAJ
author Yinghui Hou
Guizhi Zhang
spellingShingle Yinghui Hou
Guizhi Zhang
Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis
Diagnostic Pathology
Hepatocellular carcinoma
CD8+ T cells
LCK
Weighted gene co-expression network analysis
Diagnosis and prognosis
author_facet Yinghui Hou
Guizhi Zhang
author_sort Yinghui Hou
title Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis
title_short Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis
title_full Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis
title_fullStr Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis
title_full_unstemmed Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis
title_sort identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis
publisher BMC
series Diagnostic Pathology
issn 1746-1596
publishDate 2021-07-01
description Abstract Background Hepatocellular carcinoma (HCC) is often caused by chronic liver infection or inflammation. Searching for potential immunotherapy targets will aid the early diagnosis and treatment of HCC. Methods Firstly, detailed HCC data were downloaded from The Cancer Genome Atlas database. GDCRNATools was used for the comprehensive analysis of RNA sequencing data. Subsequently, the CIBERSORT package was used to estimate infiltration scores of 22 types of immune cells in complex samples. Furthermore, hub genes were identified via weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis. In addition, multiple databases were used to validate the expression of hub gene in the tumor tissue. Finally, prognostic, diagnostic and immunohistochemical analysis of key hub genes was performed. Results In the present study, 9 hub genes were identified using WGCNA and PPI network analysis. Furthermore, the expression levels of 9 genes were positively correlated with the infiltration levels of CD8-positive T (CD8+ T) cells. In multiple dataset validations, the expression levels of CCL5, CXCR6, CD3E, and LCK were decreased in cancer tissues. In addition, survival analysis revealed that patients with LCK low expression had a poor survival prognosis (P < 0.05). Immunohistochemistry results demonstrated that CCL5, CD3E and LCK were expressed at low levels in HCC cancer tissues. Conclusion The identification of CCL5, CXCR6, CD3E and LCK may be helpful in the development of early diagnosis and therapy of HCC. LCK may be a potential prognostic biomarker for immunotherapy for HCC.
topic Hepatocellular carcinoma
CD8+ T cells
LCK
Weighted gene co-expression network analysis
Diagnosis and prognosis
url https://doi.org/10.1186/s13000-021-01118-y
work_keys_str_mv AT yinghuihou identificationofimmuneinfiltratingcellrelatedbiomarkersinhepatocellularcarcinomabasedongenecoexpressionnetworkanalysis
AT guizhizhang identificationofimmuneinfiltratingcellrelatedbiomarkersinhepatocellularcarcinomabasedongenecoexpressionnetworkanalysis
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