Abstract
Background: Immune checkpoint inhibitor (ICI) therapy has been proved to be a promising therapy to many types of solid tumors. However, effective biomarker for estimating the response to ICI therapy and prognosis of hepatocellular carcinoma (HCC) patients remains underexplored. The aim of this study is to build a novel immune-related prognostic index based on transcriptomic profiles.Methods: Weighted gene co-expression network analysis (WGCNA) was conducted to identify immune-related hub genes that are differentially expressed in HCC cohorts. Next, univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to detect hub genes associated to overall survival (OS). To validate the immune-related prognostic index, univariate and multivariate Cox regression analysis were performed. CIBERSORT and ESTIMATE were used to explore the tumor microenvironment and immune infiltration level.Results: The differential expression analysis detected a total of 148 immune-related genes, among which 25 genes were identified to be markedly related to overall survival in HCC patients. LASSO analysis yielded 10 genes used to construct the immune-related gene prognostic index (IRGPI), by which a risk score is computed to estimate low vs. high risk indicating the response to ICI therapy and prognosis. Further analysis confirmed that this immune-related prognostic index is an effective indicator to immune infiltration level, response to ICI treatment and OS. The IRGPI low-risk patients had better overall survival (OS) than IRGPI high-risk patients on two independent cohorts. Moreover, we found that IRGPI high-risk group was correlated with high TP53 mutation rate, immune-suppressing tumor microenvironment, and these patients acquired less benefit from ICI therapy. In contrast, IRGPI-low risk group was associated with low TP53 and PIK3CA mutation rate, high infiltration of naive B cells and T cells, and these patients gained relatively more benefit from ICI therapy.
Highlights
Liver cancer remains a global health challenge, with an estimated incidence of more than 1 million cases by 2025 (Llovet et al, 2021) around the world
According to the Pearson correlation coefficient between a module and sample feature, we found green, yellow, and magenta modules were closely correlated with Hepatocellular carcinoma (HCC) tumors, the genes in these two modules were selected for further analysis
Immune checkpoint inhibitor has been proven to be an effective treatment for HCC
Summary
Liver cancer remains a global health challenge, with an estimated incidence of more than 1 million cases by 2025 (Llovet et al, 2021) around the world. Hepatocellular carcinoma (HCC) is the most common form of liver cancer and accounts for 90% cases, and its increasing mortality rate is receiving growing concern. Conventional treatment, such as surgery, radiotherapy, and chemotherapy, do not significantly prolong overall survival (OS) of HCC patients (Ghouri et al, 2017). Immunotherapy is emerged as an effective therapy in the field of cancer treatment in recent years, and among them the most impressive is immune checkpoint blockade (Mellman et al, 2011). Effective biomarker for estimating the response to ICI therapy and prognosis of hepatocellular carcinoma (HCC) patients remains underexplored. The aim of this study is to build a novel immune-related prognostic index based on transcriptomic profiles
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