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ORIGINAL RESEARCH article

Front. Immunol.

Sec. Cancer Immunity and Immunotherapy

Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1595539

This article is part of the Research TopicTargeting Cell Death Pathways for Enhanced Cancer Immunotherapy: Specific Involve in Necroptosis, Pyroptosis, Ferroptosis, Cuproptosis, Autophagy, Apoptosis, and ICD ResearchView all 14 articles

Prognostic Model Construction and Immune Microenvironment Analysis of Pyroptosis-Related Genes in Hepatocellular Carcinoma Based on Single-Cell RNA Sequencing

Provisionally accepted
Haoming  ShenHaoming Shen1Yizhi  PengYizhi Peng1Qingqing  XieQingqing Xie2Yuxi  RenYuxi Ren1Junping  HuJunping Hu3Peifang  QinPeifang Qin3Yuanxiong  ChenYuanxiong Chen3Hao  ZengHao Zeng3Yifan  SunYifan Sun3*
  • 1Department of Clinical Laboratory, Hunan Cancer Hospital, Changsha, Anhui Province, China
  • 2third affiliated hospital of Guangxi University of Chinese Medicine, Liuzhou, Guangxi Zhuang Region, China
  • 3eighth affiliated hospital of guangxi medical university Guigang, China, Guigang, China

The final, formatted version of the article will be published soon.

Background: Hepatocellular carcinoma (HCC) prognosis continues to be challenging due to tumor heterogeneity and dynamic immunosuppressive microenvironments. Although pyroptosis plays a critical role in tumor-immune interactions, its prognostic significance in HCC at single-cell resolution has not been systematically investigated. Methods: We analyzed a publicly available single-cell RNA sequencing (scRNA-seq) data from 10 HCC tumors and paired adjacent tissue samples (60,496 cells) to elucidate pyroptosis-related gene (PRG) profiles. Differential expression and functional pathway analyses revealed PRG expression dynamics across cell subtypes. A LASSO-Cox prognostic model was developed using data from the liver hepatocellular carcinoma (LIHC) cohort of The Cancer Genome Atlas (TCGA) (n=365); the model was externally validated with International Cancer Genome Consortium (ICGC) datasets (n=231). Biological validation comprised reverse transcription quantitative polymerase chain reaction (RT-PCR) in HCC cell lines and immunohistochemical analysis of clinical specimens. Results: The scRNA-seq atlas identified 10 cellular clusters with enriched expression of 29 PRGs, primarily in natural killer cells, T lymphocytes, monocytes, and macrophages. The prognostic model developed in this study stratified patients into high-risk and low-risk categories based on eight significant genes, achieving area under the curve (AUC) values of 0.73, 0.65, and 0.69 for overall survival at one-year, two-year, and three-year intervals, respectively. Furthermore, external validation using data from the ICGC confirmed the prognostic model's discriminative ability. Notably, high-risk patients demonstrated enhanced sensitivity to immunotherapy, as indicated by decreased tumor immune dysfunction and exclusion (TIDE) scores and increased expression of the immune checkpoints PD-1 and CTLA4. Conclusions: This study established a scRNA-seq-derived prognostic model based on PRGs, which offers insights into HCC immune landscape remodeling. The risk score and nomogram integrate tumor stages and pyroptosis-associated signatures, providing a clinical tool for personalized prognosis and therapeutic targeting.

Keywords: Hepatocellular Carcinoma, biomarkers, pyroptosis, single-cell RNA sequencing, Prognostic model

Received: 18 Mar 2025; Accepted: 31 Jul 2025.

Copyright: © 2025 Shen, Peng, Xie, Ren, Hu, Qin, Chen, Zeng and Sun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Yifan Sun, eighth affiliated hospital of guangxi medical university Guigang, China, Guigang, China

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