Damage-associated molecular pattern scoring system and its role in prognosis and immunotherapy in hepatocellular...

Significant interindividual differences exist in the efficacy of immunotherapy for hepatocellular carcinoma (HCC), and reliable biomarkers for predicting therapeutic response are lacking. Immunogenic cell death (ICD) participates in regulating the tumor immune microenvironment (TME) through the release of damage-associated molecular patterns (DAMPs), thereby possessing the potential to reshape the TME. DAMPs are essential for the occurrence of ICD. This study aims to address the lack of systematic evaluation of ICD-related molecular subtypes in HCC by constructing a DAMP-related molecular classification system and risk scoring model, as well as identifying hub genes regulating ICD in HCC for prognosis assessment and prediction of immunotherapy response.

Transcriptomic data and clinical information from multiple cohorts, including The Cancer Genome Atlas (TCGA)-LIHC dataset, the Gene Expression Omnibus (GEO) GSE14520 dataset, and the International Cancer Genome Consortium (ICGC)-LIRI dataset, were integrated. Unsupervised consensus clustering analysis of 40 DAMP-related genes was performed to identify molecular subtypes of HCC, followed by functional analyses and identification of activated signaling pathways in each subtype. Prognosis-related genes were screened from differentially expressed genes using univariate Cox regression analysis, and a DAMP scoring model was established through least absolute shrinkage and selection operator (LASSO) regression and stepwise Cox regression analyses. The ESTIMATE algorithm was used to evaluate TME characteristics, and the CIBERSORT algorithm was applied to analyze immune cell infiltration levels in HCC. Time-dependent receiver operating characteristic (ROC) curve analysis was used to evaluate the prognostic predictive performance of the DAMP score and compare it with clinical characteristics and previously published messenger RNA (mRNA) biomarkers. Weighted gene co-expression network analysis (WGCNA) was used to identify hub genes associated with the DAMP score. Immunohistochemistry (IHC) staining was performed to validate differential expression of hub genes between tumor and normal tissues. In vitro experiments, including cell counting kit-8 (CCK-8) assays and wound-healing assays, were conducted to investigate the role of hub genes in HCC. Flow cytometry was used to detect apoptosis levels and evaluate sensitivity to the ICD inducer 5-fluorouracil (5-FU).

Unsupervised consensus clustering analysis showed that HCC patients could be classified into 2 subgroups, namely low-DAMP-score and high-DAMP-score groups, based on the expression profiles of DAMP-related genes. Patients in the low-DAMP-score group had longer overall survival and exhibited higher immune cell infiltration, particularly CD8⁺ T-cell infiltration (all P<0.05). The DAMP score demonstrated stable prognostic stratification capability across multiple independent cohorts, with poorer survival outcomes observed in the high-DAMP-score group (all P<0.05). Time-dependent ROC analysis demonstrated high accuracy of the DAMP score in predicting 1-year and 3-year survival, outperforming commonly used clinical characteristics and 53 previously published mRNA biomarkers. Functional analyses revealed that pathways activated in the high-DAMP-score group were mainly enriched in cell proliferation-related pathways, whereas the low-DAMP-score group was associated with immune activation and metabolism-related pathways. In addition, the DAMP score was significantly negatively correlated with immune cell infiltration levels, and the proportions of multiple immune cell types differed significantly between the high- and low-DAMP-score groups (all P<0.05). The DAMP-score-related hub gene TRIP13 was significantly upregulated in HCC tissues and promoted proliferation and migration of HCC cells (all P<0.05). Silencing TRIP13 expression in HCC cells increased sensitivity to the ICD inducer 5-FU and was accompanied by increased apoptosis levels (all P<0.05).

The prognostic risk scoring model constructed based on DAMP-related genes can effectively stratify HCC patients and is closely associated with characteristics of the tumor immune microenvironment. The DAMP scoring model established in this study may be used for prognostic evaluation and prediction of immunotherapy efficacy in HCC and demonstrated stable predictive performance across multiple cohorts. As a hub gene in this DAMP scoring model, TRIP13 exerts oncogenic effects in HCC and regulates tumor cell sensitivity to the ICD inducer 5-FU. The DAMP-score-based subtype classification system and TRIP13-targeted therapy provide new molecular evidence for individualized treatment of HCC.