ArticleTranslational cancer research2025
Single-cell analysis revealed a diagnostic model of hepatocellular carcinoma based on cancer stem cell-related gene.
Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Single-Cell Transcriptomic Profiling Reveals Immunometabolic Reprogramming and Cell-Cell Communication in the Tumor Microenvironment of Human Hepatocellular Carcinoma.International journal of molecular sciences · 2026Article
- Integrative multi-omics identifies a diagnostic T cell signature for cutaneous squamous cell carcinoma.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Advances in the identification of novel cell signatures in benign prostatic hyperplasia and prostate cancer using single-cell RNA sequencing.Frontiers in immunology · 2025Review
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Authors and funding
7 authors.
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Abstract
Background: Cancer stem cells (CSCs) play a pivotal role in hepatocellular carcinoma (HCC) pathogenesis, driving tumor initiation, progression, metastasis, and therapeutic resistance. This study aimed to establish a reliable CSC-based signature for HCC through single-cell analysis. Methods: The study integrates single-cell RNA sequencing (scRNA-seq) data with the Dynamic Data Retrieval Tree (DDRTree) algorithm to identify and characterize CSCs in HCC. A prognostic stemness-associated gene signature was constructed using the Cancer Genome Atlas-Liver hepatocellular carcinoma (TCGA-LIHC) cohort as the training set and validated across two independent HCC datasets (GSE14520-GPL571 and GSE14520-GPL3921). Genes with significant prognostic relevance to CSC biology were prioritized for signature inclusion. The efficacy of model was assessed via survival analysis (Kaplan-Meier) and predictive accuracy evaluation [time-dependent receiver operating characteristic (ROC) curves], demonstrating robust stratification of high- versus low-risk HCC patients and strong prognostic discrimination. Results: A total of 17 CSC-related signatures in HCC were identified by copy number variation (CNV) pattern. Then, we constructed 4-CSCs-related gene predictive model by multivariate Cox regression. The model robustly stratified patients into high- and low-risk cohorts, with high-risk individuals exhibiting markedly reduced overall survival (OS). Kaplan-Meier analysis confirmed significant survival disparity between groups (P<0.001), while time-dependent ROC curves validated the model high predictive accuracy. This prognostic signature may guide the development of personalized therapeutic strategies for HCC. Conclusions: The prognostic model consisted of 4-CSC-related genes had a prognostic predictive value, providing a new perspective for precision immuno-oncology studies.
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