Research Paper Volume 16, Issue 2 pp 1712—1732
Malignant cell receptor-ligand subtypes guide the prediction of prognosis and personalized immunotherapy of liver cancer
- 1 Xiamen Hospital of Traditional Chinese Medicine, Xiamen Hospital, Beijing University of Chinese Medicine, Xiamen, Fujian, China
- 2 Xiamen Xianyue Hospital, Xiamen, Fujian, China
Received: June 26, 2023 Accepted: December 6, 2023 Published: January 18, 2024
https://doi.org/10.18632/aging.205453How to Cite
Copyright: © 2024 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Objective: Liver cancer is a prevalent disease with a dismal prognosis. The aim of the research is to identify subgroups based on malignant cell receptor ligand gene from single-cell RNA, which might lead to customized immunotherapy for patients with liver cancer.
Methods: Based on scRNA-seq data, we identified the receptor-ligand genes associated with prognosis and classify patients into molecular subtypes by univariate Cox regression and consensus clustering. LASSO regression was performed to construct a prognostic model, which was validated in TCGA and ICGC datasets. Immune infiltration and prediction of immunotherapy response were analyzed using ssGSEA, ESTIMATE, TIDE, and TRS score calculation. Finally, qPCR and Western blot validation of key genes and protein levels in cell lines.
Results: A risk model using 16-gene expression levels predicted liver cancer patients’ prognosis. The RiskScore associated significantly with tumor clinical characteristics and immunity, integrated with clinicopathological features for survival prediction. Differential expression of SRXN1 was verified in hepatocellular carcinoma and normal liver cells.
Conclusion: Our study utilizes single-cell analysis to investigate the communication between malignant cells and other cell types, identifying molecular subtypes based on malignant cell receptor ligand genes, offering new insights for the development of personalized immunotherapy and prognostic prediction models.
Abbreviations
HCC: Hepatocellular carcinoma; RFA: Radiofrequency ablation; MWA: Microwave ablation; KYN: Kynurenic acid; AHR: Aryl hydrocarbon receptor; TDO: Tryptophan-2,3-dioxygenase; TGFβ: Transforming growth factor-beta; IFNγ: Interferon-γ; TCGA: The Cancer Genome Atlas; ICGC: International Cancer Genome Consortium; GSEA: Gene set enrichment analysis; TME: Tumor microenvironment.