ArticlePhenomics (Cham, Switzerland)2024
Cellular Senescence-Related Long Non-coding RNA Signatures Predict Prognosis in Juvenile Osteosarcoma.
Article in Phenomics (Cham, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Integrative single-cell analysis revealsFrontiers in immunology · 2026Article
- PSIP1 Orchestrates Immune Escape in Osteosarcoma: Insights From Single-Cell Analysis and Implications for Immunotherapy Resistance.International journal of genomics · 2026Article
- Article
- LIG1 overexpression enhances DNA repair and immune escape leading to poor prognosis in osteosarcoma.European journal of medical research · 2025Article
- DMGAT: predicting ncRNA-drug resistance associations based on diffusion map and heterogeneous graph attention network.Briefings in bioinformatics · 2025Article
- M6A RNA modification: focusing on non-small cell lung cancer progression, therapeutic strategies and challenges.Frontiers in oncology · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteosarcoma is the most common malignant bone tumor and is frequently diagnosed in juvenile. Cellular senescence is a fundamental hallmark of osteosarcoma and plays a vital role in the initiation and progression of aging and tumorigenesis. Long non-coding RNAs (lncRNAs) are implicated in tumorigenesis. In this study, six cellular senescence-related lncRNAs with independent prognostic significance in juvenile osteosarcoma patients were identified through univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis. Prognostic significance was further confirmed by Kaplan-Meier (KM) survival curves, co-expression interaction networks, and sankey diagrams. A prognostic model of cellular senescence-related genes in juvenile osteosarcoma patients was then constructed using multivariate Cox regression analysis based on these six genes. High- and low-risk groups were identified according to the median risk score calculated by the prognostic model. The favorable prognostic significance of this model was demonstrated through survival curves, receiver operating characteristic (ROC) curves, distribution scatter plots and lncRNA expression heatmaps. Furthermore, cellular senescence-related lncRNAs were validated by enrichment analysis, immunological correlation analysis, m
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.