Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs

Abstract

BackgroundAccumulating evidence shows that immunogenic cell death (ICD) enhances immunotherapy effectiveness. In this study, we aimed to develop a prognostic model combining ICD, immunity, and long non-coding RNA biomarkers for predicting hepatocellular carcinoma (HCC) outcomes.MethodsImmune- and immunogenic cell death-related lncRNAs (IICDLs) were identified from The Cancer Genome Atlas and Ensembl databases. IICDLs were extracted based on the results of differential expression and univariate Cox analyses and used to generate molecular subtypes using ConsensusClusterPlus. We created a prognostic signature based on IICDLs and a nomogram based on risk scores. Clinical characteristics, immune landscapes, immune checkpoint blocking (ICB) responses, stemness, and chemotherapy responses were also analyzed for different molecular subtypes and risk groups.ResultA total of 81 IICDLs were identified, 20 of which were significantly associated with overall survival (OS) in patients with HCC. Cluster analysis divided patients with HCC into two distinct molecular subtypes (C1 and C2), with patients in C1 having a shorter survival time than those in C2. Four IICDLs (TMEM220-AS1, LINC02362, LINC01554, and LINC02499) were selected to develop a prognostic model that was an independent prognostic factor of HCC outcomes. C1 and the high-risk group had worse OS (hazard ratio > 1.5, p < 0.01), higher T stage (p < 0.05), higher clinical stage (p < 0.05), higher pathological grade (p < 0.05), low immune cell infiltration (CD4+ T cells, B cells, macrophages, neutrophils, and myeloid dendritic cells), low immune checkpoint gene expression, poor response to ICB therapy, and high stemness. Different molecular subtypes and risk groups showed significantly different responses to several chemotherapy drugs, such as doxorubicin (p < 0.001), 5-fluorouracil (p < 0.001), gemcitabine (p < 0.001), and sorafenib (p < 0.01).ConclusionOur study identified molecular subtypes and a prognostic signature based on IICDLs that could help predict the clinical prognosis and treatment response in patients with HCC.

Molecular biomarkers of response to sintilimab combined with lenvatinib for locally advanced hepatitis B virus-associated hepatocellular carcinoma

“…In vitro experiments have revealed that high expression of LINC01554 partially inhibits the Wnt and PI3K-Akt pathways, resulting in reduced cell invasiveness and diminished epithelialmesenchymal transition capability. Similarly, another study [21] highlighted LINC01554, along with three other RNAs (TMEM220-AS1, LINC02362, and LINC02499), as independent prognostic factors for HCC. These consistent results suggest that LINC01554 is an important potential therapeutic target.…”

Immune cell death-related lncRNA signature as a predictive factor of clinical outcomes and immune checkpoints in gastric cancer

“…He et al screened 20 lncRNAs based on 33 ICD-related genes to construct a prognostic model. The model was helpful in classifying subtypes of liver cancer based on ICD-related lncRNAs and molecules, and for predicting the prognosis of patients with liver cancer and their therapeutic response to immunotherapy ( He et al, 2022 ). Ding et al screened five lncRNAs based on 34 ICD-related genes to construct a prognostic model for gastric adenocarcinoma.…”