ArticleComputational and mathematical methods in medicine2022
The Cuproptosis-Related Long Noncoding RNA Signature Predicts Prognosis and Tumour Immune Analysis in Osteosarcoma.
Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- LncRNA NKILA as a key regulator in cancer pathogenesis: insights into its mechanisms and clinical implications.Cancer cell international · 2026Review
- Musculoskeletal disorders: does cuproptosis hold the key?Frontiers in cell and developmental biology · 2026Review
- Integrating gene demethylation and immune modulation: PD-1 nanovesicles as a dual-action therapy for NSCLC.Materials today. Bio · 2025Article
- A predictive model based on program cell death genes for prognosis and therapeutic response in early stage hepatocellular carcinoma.Scientific reports · 2025Article
- Cuproptosis and its potential role in musculoskeletal disease.Frontiers in cell and developmental biology · 2025Review
- Construction of a cuproptosis-tricarboxylic acid cycle-associated lncRNA model to predict the prognosis of non-small cell lung cancer.Translational cancer research · 2024Article
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5 authors at 2 institutions in 1 country.
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Abstract
Background: Cuprotopsis is a type of programmed cell death discovered in recent years. Long noncoding RNAs (lncRNAs) play an important regulatory role in programmed cell death. The effect of cuproptosis-related lncRNAs on osteosarcoma is unknown. Our work, based on cuproptosis-related lncRNAs, proposes a gene signature to assess the prognosis of patients with osteosarcoma. Methods: Osteosarcoma gene expression data from The Cancer Genome Atlas (TCGA), clinical features of osteosarcoma and RNA sequencing data of normal adipose tissue were obtained from the UCSC Xena database. A cuproptosis-related lncRNA risk model was established to calculate the risk score. At the same time, cluster analysis, clinicopathological analysis, functional enrichment analysis, and prediction of compounds with potential therapeutic value were evaluated. We analyzed whether there was a correlation between the risk score and tumour immunity. RT-qPCR was used to verify the expression level of lncRNA. Results: Nine lncRNAs (AC124798.1, AC006033.2, AL450344.2, AL512625.2, LINC01060, LINC00837, AC004943.2, AC064836.3, and AC100821.2) were identified to create a risk model and indicate the prognosis of patients with osteosarcoma. The high-risk group had a worse prognosis than the low-risk group. Analysis of clinicopathological features, principal component analysis, receiver operating characteristic curve, c-index curve, and comparative analysis of models proved that the model is reliable. Functional enrichment analysis suggests that the risk score may correlate with cell energy metabolism and tumour-related biological function. Three potentially therapeutic compounds have been predicted. These analyses may be beneficial to the treatment of osteosarcoma in the future. RT-qPCR verified the expression level of three lncRNA (LINC01060, NKILA, and SNHG8). Conclusions: Cuproptosis-related lncRNAs have a strong relationship with osteosarcoma patients. Nine lncRNA models can effectively forecast the prognosis of osteosarcoma and may play a significant role in the individualized treatment of osteosarcoma patients in the future.
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