ArticleFrontiers in immunology2022
Integration of single-cell RNA sequencing and bulk RNA sequencing to reveal an immunogenic cell death-related 5-gene panel as a prognostic model for osteosarcoma.
Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 24 citations in OpenAlex.
- Integrative single-cell analysis reveals immunogenic cell death-associated heterogeneity and identifies a robust prognostic signature in osteosarcoma with experimental validation.Frontiers in pharmacology · 2026Article
- Computational pathology approach for assessment of prognosis and immunotherapy response in pan-gastrointestinal cancer.Journal of translational medicine · 2025Article
- Constructing a Pan-Cancer Prognostic Model via Machine Learning Based on Immunogenic Cell Death Genes and Identifying NT5E as a Biomarker in Head and Neck Cancer.Current issues in molecular biology · 2025Article
- From cells to clinic: Single-cell transcriptomics shaping the future of orthopedics.Journal of orthopaedic translation · 2025Review
- Development of a prognostic model for osteosarcoma based on macrophage polarization-related genes using machine learning: implications for personalized therapy.Clinical and experimental medicine · 2025Article
- Based on single-cell and transcriptome data, ferroptosis and the immunological landscape in osteosarcoma were discovered.Discover oncology · 2025Article
- Immunogenic cell death signature predicts survival and reveals the role of VEGFA + Mast cells in lung adenocarcinoma.Scientific reports · 2025Article
- LncRNA-associated ceRNA Network Revealing the Potential Regulatory Roles of Ferroptosis and Immune Infiltration in Osteosarcoma as well as Construction of the Prognostic Model.Current medicinal chemistry · 2025Article
- Unraveling the PANoptosis Landscape in Osteosarcoma: A Single-Cell Sequencing and Machine Learning Approach to Prognostic Modeling and Tumor Microenvironment Analysis.International journal of genomics · 2025Article
- Immunogenic cell death-related cancer-associated fibroblast clusters and prognostic risk model in cervical cancer.APL bioengineering · 2024Article
- Article
- A novel prognostic signature related to programmed cell death in osteosarcoma.Frontiers in immunology · 2024Article
- Develop a Novel Signature to Predict the Survival and Affect the Immune Microenvironment of Osteosarcoma Patients: Anoikis-Related Genes.Journal of immunology research · 2024Article
- Single-cell RNA sequencing reveals the communications between tumor microenvironment components and tumor metastasis in osteosarcoma.Frontiers in immunology · 2024Article
- Integrated analysis of single-cell and bulk RNA-seq establishes a novel signature for prediction in gastric cancer.World journal of gastrointestinal oncology · 2023Article
- By integrating single-cell RNA-seq and bulk RNA-seq in sphingolipid metabolism, CACYBP was identified as a potential therapeutic target in lung adenocarcinoma.Frontiers in immunology · 2023Article
- Article
- Development and validation of immunogenic cell death-applied prediction model for esophageal carcinoma.American journal of cancer research · 2023Article
- Molecular characterization of immunogenic cell death indicates prognosis and tumor microenvironment infiltration in osteosarcoma.Frontiers in immunology · 2022Article
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10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Despite the comparatively low prevalence of osteosarcoma (OS) compared to other cancer types, metastatic OS has a poor overall survival rate of fewer than 30%. Accumulating data has shown the crucial functions of immunogenic cell death (ICD) in various cancers; nevertheless, the relationship between ICD and OS was not previously well understood. This research aims to determine the function of ICD in OS and construct an ICD-based prognostic panel. Methods: Single cell RNA sequencing data from GSE162454 dataset distinguished malignant cells from normal cells in OS. The discrepancy in ICD scores and corresponding gene expression was intensively explored between malignant cells and normal cells. Using the RNA sequencing data of the TARGET-OS, GSE16091, GSE21257, and GSE39058 datasets, the molecular subtype of OS was determined by clustering seventeen ICD-related genes obtained from the literature. Differentially expressed genes (DEGs) between different molecular subtypes were identified to develop a novel ICD-associated prognostic panel. Results: The malignant cells had a remarkable decrease in the ICD scores and corresponding gene expression compared with normal cells. A total of 212 OS patients were successfully stratified into two subtypes: C1 and C2. C1-like OS patients were characterized by better prognostic outcomes, overexpression of ICD genes, activation of the ICD pathway, high inflitration abundance of immunocytes, and low expression levels of immune checkpoint genes (ICGs); however, the reverse is true in C2-like OS patients. Utilizing the limma programme in R, the DEGs between two subtypes were determined, and a 5-gene risk panel consisting of BAMBI, TMCC2, NOX4, DKK1, and CBS was developed through LASSO-Cox regression analysis. The internal- and external-verification cohorts were employed to verify the efficacy and precision of the risk panel. The AUC values of ROC curves indicated excellent prognostic prediction values of our risk panel. Conclusions: Overall, ICD represented a protective factor against OS, and our 5-gene risk panel serving as a biomarker could effectively evaluate the prognostic risk in patients with OS.
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