Title of article :
Immune Score-based Molecular Subtypes and Signature Associated with Clinical Outcome in Hepatoblastoma
Author/Authors :
Huang, Yongping Department of General Surgery - Longgang District People’s Hospital of Shenzhen, Shenzhen, Guangdong, China , Yan, Jinlong Department of General Surgery - Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, China , Liu, Ruiqi WenZhou Medical University, WenZhou, China , Tang, Guang Department of General Surgery - Longgang District People’s Hospital of Shenzhen, Shenzhen, Guangdong, China , Dong, Qi Department of General Surgery - Jiangxi Provincial Children’s Hospital, Nanchang, Jiangxi, China , Liu, Dong Department of General Surgery - Longgang District People’s Hospital of Shenzhen, Shenzhen, Guangdong, China , Yang, Xiaolan Department of General Surgery - Longgang District People’s Hospital of Shenzhen, Shenzhen, Guangdong, China , Zhang, Shouhua Department of General Surgery - Longgang District People’s Hospital of Shenzhen, Shenzhen, Guangdong, China , Tang, Dejun Department of General Surgery - Longgang District People’s Hospital of Shenzhen, Shenzhen, Guangdong, China
Pages :
12
From page :
1
To page :
12
Abstract :
Background: This study aimed to identify genes related to the immune score of hepatoblastoma, examine the characteristics of the immune microenvironment of hepatoblastoma, and construct a risk scoring system for predicting the prognosis of hepatoblastoma. Methods: Through using the gene chip data of patients with hepatoblastoma with survival data in the ArrayExpress and GEO databases, the immune score of hepatoblastoma was calculated by the ESITIMATE algorithm, and the prognostic value of immune score in patients with hepatoblastomawas studied by the survival analysis. Genes related to theimmunescore were identified by the WGCNA algorithm. According to these genes, patients with hepatoblastoma were clustered unsupervised. Finally, the risk scoring system was constructed according to the immune score-related genes. Results: The immune score calculated by the ESTIMATE algorithm had a good prognostic value in patients with hepatoblastoma. Patients with highimmunescores had better OS than those with lowimmunescores (P< 0.001). A total of 146immunescore-related genes were identified by WGCNA analysis, and univariate COX regression analysis indicated that 59 of the genes had prognostic value. According to the unsupervised clustering results of the 146immunescore-related genes, patients with hepatoblastoma could be divided into two subtypes with different prognoses, namely molecular subtype 1 and subtype 2, with molecular subtype 1 having a better prognosis. The immunocyte infiltration analysis results showed that the difference between the two subtypes was mainly in activated CD4 T cells, activated dendritic cells, CD56 bright natural killer cells, the macrophage, and regulatory T cells. According to the immune score-related genes, a risk scoring system was constructed based on a five-gene signature. After the cut-off value was determined, patients with hepatoblastoma were divided into a high-risk group and a low-risk group. The prognosis of the two groups was different. Conclusions: The immune score has a good prognostic value in patients with hepatoblastoma. Based on the different expression patterns of immunescore-related genes, hepatoblastoma can be divided into two different prognostic molecular subtypes, showing different immunocyte infiltration patterns. The established risk scoring system based on a five-gene signature has a good predictive value in patients with hepatoblastoma.
Keywords :
Hepatoblastoma , Prognosis , Immune Microenvironment , Model , Immune Cell
Journal title :
Hepatitis Monthly
Serial Year :
2021
Record number :
2699593
Link To Document :
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