Evidence map›Paper›PMID 41200185›Full record

ArticleFrontiers in immunology2025

Identification of immunogenic cell death signature genes in hepatocellular carcinoma: from single-cell transcriptomics to

Hongliang Liu, Zhenni Sun, Xi Wang, Bin Zhou, Lichao Cha

Abstract read
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Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hongliang Liu *Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
Zhenni Sun *Department of Oncology, Qingdao Municipal Hospital, Qingdao, China.
Xi WangDepartment of Oncology, Women and Children's Hospital Affiliated to Qingdao University, Qingdao, China.
Bin ZhouDepartment of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
Lichao ChaDepartment of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) lacks reliable prognostic biomarkers for immunotherapy. Immunogenic cell death (ICD) represents a promising therapeutic target, but its comprehensive characterization in HCC remains unexplored. Methods: We performed multi-omics integration of single-cell RNA sequencing data from 7 HCC samples (GSE112271, 44,461 cells) with bulk transcriptomics from three independent cohorts (TCGA-HCC [n=371], GSE14520 [n=242], ICGC [n=445]). ICD activity was quantified using ssGSEA. We identified HCC-specific ICD-related (HCC-ICDR) genes via WGCNA and optimized a prognostic model by benchmarking machine learning algorithms. Experimental validation included functional assays using CLIC1 and NAP1L1 overexpression in HepG2 cells. Results: The ICD-based risk score (ICDRS) demonstrated superior prognostic accuracy (C-index=0.839), validated across cohorts. Single-cell profiling revealed macrophages exhibited the highest ICD activity. High-risk patients displayed immunosuppressive microenvironments with enriched Tregs, M0 macrophages, and neutrophils, alongside hyperactivated DNA repair and MYC signaling. Low-risk patients showed anti-tumor immunity with increased CD8+ T cells and M1 macrophages. ICDRS predicted differential therapeutic vulnerabilities: low-risk patients showed enhanced sensitivity to standard immunotherapy-compatible treatments including sorafenib and doxorubicin, while high-risk patients demonstrated preferential sensitivity to EGFR-targeted therapies. Experimental validation confirmed CLIC1 and NAP1L1 significantly promoted HCC malignant behaviors. Conclusions: We established the comprehensive ICD-based prognostic framework for HCC, revealing novel tumor-immune interactions and therapeutic vulnerabilities. This model provides robust stratification for immunotherapy selection and advances precision medicine in HCC management. Future clinical translation includes prospective validation and development of companion diagnostics, offering potential pathways for personalized HCC treatment implementation.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularImmunogenic Cell DeathLiver NeoplasmsMachine LearningTranscriptomeGene Expression ProfilingGene Expression Regulation, NeoplasticHep G2 CellsHumansPrognosisSingle-Cell AnalysisTumor MicroenvironmentBiomarkers, Tumorhepatocellular carcinomaimmunogenic cell deathmachine learningmulti-omics integrationprecision medicinetumor microenvironment

Identifiers

PMID41200185
PMCPMC12585982

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.