Four circadian rhythm-related genes predict incidence and prognosis in hepatocellular carcinoma

Circadian dysregulation can be involved in the development of malignant tumors, though its relationship with the progression of hepatocellular carcinoma is not yet fully understood. We identified genes related to circadian rhythms from the Cancer Genome Atlas (TCGA), measured gene expression, and co...

Full description

Saved in:
Bibliographic Details
Published inFrontiers in oncology Vol. 12; p. 937403
Main Authors Wu, Zhenyu, Hu, Hao, Zhang, Qiang, Wang, Tengfei, Li, Huixing, Qin, Yugang, Ai, Xiangnan, Yi, Wen, Wei, Xiaojun, Gao, Wei, Ouyang, Caiguo
Format Journal Article
LanguageEnglish
Published Frontiers Media S.A 10.11.2022
Subjects
Circadian clock
gene signature
immune
liver cancer
Oncology
overall survival
Online AccessGet full text

Cover

More Information
Summary:Circadian dysregulation can be involved in the development of malignant tumors, though its relationship with the progression of hepatocellular carcinoma is not yet fully understood. We identified genes related to circadian rhythms from the Cancer Genome Atlas (TCGA), measured gene expression, and conducted genomic difference analysis to construct a circadian rhythm-related signature. The resulting prognosis model proved to be an effective biomarker, as demonstrated by Kaplan-Meier survival analysis for both the training (n = 370, P = 2.687e-10) and external validation cohorts (n = 230, P = 1.45e-02). Further, we found that patients considered ‘high risk’, with an associated poor prognosis, displayed elevated levels of immune checkpoint genes and immune filtration. We also conducted functional enrichment, which indicated that the risk model showed a significant positive correlation with certain malignant phenotypes, including G2M checkpoint, MYC targets, and the MTORC1 signaling pathway. In summary, we identified a novel circadian rhythm-related signature allowing assessment of prognosis for hepatocellular carcinoma patients, and further can be used to predict immune infiltration sensitivity.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Reviewed by: Yu-gang Huang, Hubei University of Medicine, China; Dongyin Guan, Baylor College of Medicine, United States
Edited by: Cheng Zhang, Anhui Medical University, China
This article was submitted to Molecular and Cellular Oncology, a section of the journal Frontiers in Oncology
These authors have contributed equally to this work
ISSN:2234-943X
2234-943X
DOI:10.3389/fonc.2022.937403