ArticleEuropean journal of medical research2023
Combining bulk and single-cell RNA-sequencing data to develop an NK cell-related prognostic signature for hepatocellular carcinoma based on an integrated machine learning framework.
Article in European journal of medical research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence networks for assessing the prognosis of gastrointestinal cancer to immunotherapy based on genetic mutation features: a systematic review and meta-analysis.BMC gastroenterology · 2025Pooled it
- CMA-associated cellular state remodeling defines prognostic heterogeneity and identifies ARRDC3 as a protective functional gene in small cell lung cancer.Frontiers in cell and developmental biology · 2026Article
- Integrated Machine Learning and Multi-Omics Identifies a Novel Molecular Signature for Improving the Prognosis of Hepatocellular Carcinoma.Journal of hepatocellular carcinoma · 2026Article
- Single-cell sequencing combined with bulk RNA seq reveals the roles of natural killer cell in prognosis and immunotherapy of hepatocellular carcinoma.Scientific reports · 2025Article
- Habitat radiomics based on CT images to predict survival and immune status in hepatocellular carcinoma, a multi-cohort validation study.Translational oncology · 2025Article
- A comprehensive analysis to reveal the underlying molecular mechanisms of natural killer cell in thyroid carcinoma based on single-cell RNA sequencing data.Discover oncology · 2025Article
- Uncovering the heterogeneity of NK cells on the prognosis of HCC by integrating bulk and single-cell RNA-seq data.Frontiers in oncology · 2025Article
- Overcoming resistance to PD-1 and CTLA-4 blockade mechanisms and therapeutic strategies.Frontiers in immunology · 2025Review
- Deep Immunoprofiling of Large-Scale Tuberculosis Dataset at Single Cell Resolution Reveals a CD81Cells · 2024Article
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- Macrophage-related Genomic Signatures Predict HCC Prognosis and Therapy Response.Cancer genomics & proteomicsArticle
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6 authors.
Funding
Abstract
backgroundThe application of molecular targeting therapy and immunotherapy has notably prolonged the survival of patients with hepatocellular carcinoma (HCC). However, multidrug resistance and high molecular heterogeneity of HCC still prevent the further improvement of clinical benefits. Dysfunction of tumor-infiltrating natural killer (NK) cells was strongly related to HCC progression and survival benefits of HCC patients. Hence, an NK cell-related prognostic signature was built up to predict HCC patients' prognosis and immunotherapeutic response.
methodsNK cell markers were selected from scRNA-Seq data obtained from GSE162616 data set. A consensus machine learning framework including a total of 77 algorithms was developed to establish the gene signature in TCGA-LIHC data set, GSE14520 data set, GSE76427 data set and ICGC-LIRI-JP data set. Moreover, the predictive efficacy on ICI response was externally validated by GSE91061 data set and PRJEB23709 data set.
resultsWith the highest C-index among 77 algorithms, a 11-gene signature was established by the combination of LASSO and CoxBoost algorithm, which classified patients into high- and low-risk group. The prognostic signature displayed a good predictive performance for overall survival rate, moderate to high predictive accuracy and was an independent risk factor for HCC patients' prognosis in TCGA, GEO and ICGC cohorts. Compared with high-risk group, low-risk patients showed higher IPS-PD1 blocker, IPS-CTLA4 blocker, common immune checkpoints expression but lower TIDE score, which indicated low-risk patients might be prone to benefiting from ICI treatment. Moreover, a real-world cohort, PRJEB23709, also revealed better immunotherapeutic response in low-risk group.
conclusionsOverall, the present study developed a gene signature based on NK cell-related genes, which offered a novel platform for prognosis and immunotherapeutic response evaluation of HCC patients.
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