Model based on five tumour immune microenvironment-related genes for predicting hepatocellular carcinoma immunotherapy outcomes

Abstract

Background Although the tumour immune microenvironment is known to significantly influence immunotherapy outcomes, its association with changes in gene expression patterns in hepatocellular carcinoma (HCC) during immunotherapy and its effect on prognosis have not been clarified. Methods A total of 365 HCC samples from The Cancer Genome Atlas liver hepatocellular carcinoma (TCGA-LIHC) dataset were stratified into training datasets and verification datasets. In the training datasets, immune-related genes were analysed through univariate Cox regression analyses and least absolute shrinkage and selection operator (LASSO)-Cox analyses to build a prognostic model. The TCGA-LIHC, GSE14520, and Imvigor210 cohorts were subjected to time-dependent receiver operating characteristic (ROC) and Kaplan–Meier survival curve analyses to verify the reliability of the developed model. Finally, single-sample gene set enrichment analysis (ssGSEA) was used to study the underlying molecular mechanisms. Results Five immune-related genes (LDHA, PPAT, BFSP1, NR0B1, and PFKFB4) were identified and used to establish the prognostic model for patient response to HCC treatment. ROC curve analysis of the TCGA (training and validation sets) and GSE14520 cohorts confirmed the predictive ability of the five-gene-based model (AUC > 0.6). In addition, ROC and Kaplan–Meier analyses indicated that the model could stratify patients into a low-risk and a high-risk group, wherein the high-risk group exhibited worse prognosis and was less sensitive to immunotherapy than the low-risk group. Functional enrichment analysis predicted potential associations of the five genes with several metabolic processes and oncological signatures. Conclusions We established a novel five-gene-based prognostic model based on the tumour immune microenvironment that can predict immunotherapy efficacy in HCC patients.

LPCAT1 overexpression promotes the progression of hepatocellular carcinoma

“…According to American Cancer Statistics 2021, there will be approximately 40,000 new cancer cases and 30,000 deaths per year, with a 5-year relative survival rate of only 20% [3]. HCC is a complex and multistage disease that may be explained by genetic and epigenetic changes [4][5][6][7][8]. Despite the development of surgery and combined treatment, as well as progress in early diagnosis and interventional therapy, most patients are still diagnosed in the advanced stage of HCC with a low 5-year survival rate and poor prognosis [9][10][11].…”

A New Risk Score Based on Eight Hepatocellular Carcinoma- Immune Gene Expression Can Predict the Prognosis of the Patients

“…According to the survival prediction of patients with prognostic biomarkers, individualized treatment can be better developed in clinical practice (15,16). Compared with a single gene, a multigenebased model has been shown to be more robust and precise in diagnosis and prognosis in many cancers (17,18). Thus, it provides new options for prognostic prediction and treatment of patients.…”

Biomarkers and Future Perspectives for Hepatocellular Carcinoma Immunotherapy

“…Importantly, however, although the differences in the above-mentioned clinical trial data were reported to be statistically significant, this gene signature does not adequately distinguish between responders and nonresponders. Recently, a five-gene immune-related signature ( LDHA , PPAT , BFSP1 , NR0B1 , and PFKFB4 ) was identified and used to establish a prognostic model for responses to HCC treatment that could stratify patients who were sensitive to immunotherapy ( 93 ). Other studies using different gene combination strategies have also reported their potential to predict ICI responses by reflecting the characteristics of the immune microenvironment ( 94 , 95 ).…”