Development and Validation of a Novel Immune-Gene Pairs Prognostic Model Associated with CTNNB1 Alteration in Hepatocellular Carcinoma
Junyu Huo, Liqun Wu, Yunjin Zang
Affiliated Hospital of Qingdao University, Qingdao, Shandong, China (mainland)
Med Sci Monit 2020; 26:e925494
Available online: 2020-07-23
Immunotherapy is one of the research hotspots in the field of hepatocellular carcinoma (HCC). Successive clinical trials have shown that patients with CTNNB1 mutations are resistant to immunotherapy, but the mechanism is still unclear.
MATERIAL AND METHODS: We identified differentially expressed immune genes (DEIGs) in patients with and without CTNNB1 mutations in the Cancer Genome Atlas (TCGA) database and then paired them to explore any correlation with prognosis. Univariate Cox regression analysis and Lasso regression analysis were used to develop the prognostic model. We first divided the TCGA cohort into 29 subgroups for internal validation and then used the International Cancer Genome Consortium (ICGC) cohort to conduct external validation. We also used a CIBERSORT algorithm to quantify immune infiltration of the different risk groups.
RESULTS: The novel prognostic model consisted of 45 immune-gene pairs with general applicability. It was more accurate than the traditional prognostic signature, which is based on gene expression by comparison of area under the receiver operating characteristic curve (AUC) values. The infiltration proportion of B cells, CD8 T lymphocytes, activated natural killer cells, and M1 macrophages in the low-risk group was greater in the high-risk group, while the infiltration proportion of M0 and M2 macrophages was greater in the high-risk group.
CONCLUSIONS: In this study, a novel approach was proposed for evaluating HCC prognosis, which may be useful in evaluatingthe intensity of the immune response in the HCC microenvironment.
Keywords: Carcinoma, Hepatocellular, Prognosis, transcriptome