ArticleJournal of oncology2022
Subtype Classification and Prognosis Signature Construction of Osteosarcoma Based on Cellular Senescence-Related Genes.
Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 11 citations in OpenAlex.
- Decoding osteosarcoma from heterogeneity to precision therapy.Discover oncology · 2025Review
- Exploratory Analysis of Molecular Subtypes in Early-Stage Osteosarcoma: Identifying Resistance and Optimizing Therapy.Cancers · 2025Article
- Unveiling a novel model of cell senescence-related genes for prognostic assessment and immunotherapeutic insights in gastric cancer.Scientific reports · 2025Article
- Review
- Targeting myeloid-derived suppressor cells in the tumor microenvironment: potential therapeutic approaches for osteosarcoma.Oncology research · 2025Review
- Identification of a novel cellular senescence-related lncRNA signature for prognosis and immune response in osteosarcoma.Translational cancer research · 2024Article
- Advances in prognostic models for osteosarcoma risk.Heliyon · 2024Review
- Article
- Comprehensive analysis of splicing factor SRs-related gene characteristics: predicting osteosarcoma prognosis and immune regulation status.Frontiers in oncology · 2024Article
- Managing the immune microenvironment of osteosarcoma: the outlook for osteosarcoma treatment.Bone research · 2023Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Cellular senescence (CS) is an alternative procedure that replaces or reinforces inadequate apoptotic responses and is used as an influencing factor for a variety of cancers. The value of CS gene in evaluating the immunotherapy response and clinical outcome of osteosarcoma (OS) has not been reported, and an accurate risk model based on CS gene has not been developed for OS patients. Methods: 279 CS genes were obtained from CellAge. Univariate Cox regression analysis was used to screen the CS gene which was significantly related to the prognosis of OS samples in TARGET data set. The prognosis, clinicopathological features, immune infiltration, gene expression at immune checkpoints, tumor immune dysfunction and exclusion (TIDE) score, and chemotherapy resistance of OS were analyzed among clusters. Least absolute shrinkage and selection operator (Lasso) Cox regression analysis to build cellular senescence-related gene signature (CSRS). Univariate and multivariate Cox regression analysis of CSRS and clinical parameters were carried out, and the parameters with independent prognostic value were used to construct nomogram. Results: Based on 30 CS genes related to OS prognosis, OS samples were divided into three clusters: C1, C2, and C3. C3 showed the lowest survival rate and metastasis rate and the highest immune score and stromal score and was more likely to respond to immune checkpoint blockade (ICB) treatment. A CSRS scoring system including four CS genes (MYC, DLX2, EPHA3, and LIMK1) was constructed, which could distinguish the survival outcome, tumor microenvironment (TME) status, and ICB treatment response of patients with different CSRS score. Nomogram constructed by CSRS score and metastatic has a high prognostic value for OS. Conclusions: Our study identified a molecular classification determined by CS-related genes and developed a new CSRS that has potential value in OS immunotherapy response and clinical outcome prediction.
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Registered trials
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