ArticleFrontiers in molecular biosciences2021
Development of a Machine Learning-Based Autophagy-Related lncRNA Signature to Improve Prognosis Prediction in Osteosarcoma Patients.
Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Machine Learning Models for the Identification of Prognostic and Predictive Cancer Biomarkers: A Systematic Review.International journal of molecular sciences · 2023Pooled it
- Metabolic-immune crosstalk in osteosarcoma: mechanisms and therapeutic opportunities.Frontiers in immunology · 2026Review
- Bridging technology and medicine: artificial intelligence in targeted anticancer drug delivery.RSC advances · 2025Review
- Construction of a diagnostic model utilizing m7G regulatory factors for the characterization of diabetic nephropathy and the immune microenvironment.Scientific reports · 2025Article
- Article
- Review
- 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
- Integrating bioinformatics and machine learning to uncover lncRNA LINC00269 as a key regulator in Parkinson's disease via pyroptosis pathways.European journal of medical research · 2024Article
- Autophagy and machine learning: Unanswered questions.Biochimica et biophysica acta. Molecular basis of disease · 2024Review
- A telomere-related signature for predicting prognosis and assessing immune microenvironment in osteosarcoma.Frontiers in pharmacology · 2024Article
- A novel ferroptosis-related microRNA signature with prognostic value in osteosarcoma.Acta biochimica et biophysica Sinica · 2023Article
- A Disulfidptosis-Related Gene Signature Associated with Prognosis and Immune Cell Infiltration in Osteosarcoma.Bioengineering (Basel, Switzerland) · 2023Article
- Construction of a Diagnostic mBiomolecules · 2023Article
- Managing the immune microenvironment of osteosarcoma: the outlook for osteosarcoma treatment.Bone research · 2023Review
- Identification of a novel MYC target gene set signature for predicting the prognosis of osteosarcoma patients.Frontiers in oncology · 2023Article
- Screening and verification of prognostic lncRNA markers related to immune infiltration in the metastasis of osteosarcoma.Translational cancer research · 2022Article
- Immune Microenvironment in Osteosarcoma: Components, Therapeutic Strategies and Clinical Applications.Frontiers in immunology · 2022Review
- A cuproptosis-related genes signature associated with prognosis and immune cell infiltration in osteosarcoma.Frontiers in oncology · 2022Article
- Identification of Autophagy- and Ferroptosis-Related lncRNAs Functioned through Immune-Related Pathways in Head and Neck Squamous Carcinoma.Life (Basel, Switzerland) · 2021Article
- Identification of a N6-Methyladenosine (m6A)-Related lncRNA Signature for Predicting the Prognosis and Immune Landscape of Lung Squamous Cell Carcinoma.Frontiers in oncology · 2021Article
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOsteosarcoma is a frequent bone malignancy in children and young adults. Despite the availability of some prognostic biomarkers, most of them fail to accurately predict prognosis in osteosarcoma patients. In this study, we used bioinformatics tools and machine learning algorithms to establish an autophagy-related long non-coding RNA (lncRNA) signature to predict the prognosis of osteosarcoma patients.
methodsWe obtained expression and clinical data from osteosarcoma patients in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We acquired an autophagy gene list from the Human Autophagy Database (HADb) and identified autophagy-related lncRNAs by co-expression analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the autophagy-related lncRNAs were conducted. Univariate and multivariate Cox regression analyses were performed to assess the prognostic value of the autophagy-related lncRNA signature and validate the relationship between the signature and osteosarcoma patient survival in an independent cohort. We also investigated the relationship between the signature and immune cell infiltration.
resultsWe initially identified 69 autophagy-related lncRNAs, 13 of which were significant predictors of overall survival in osteosarcoma patients. Kaplan-Meier analyses revealed that the 13 autophagy-related lncRNAs could stratify patients based on their outcomes. Receiver operating characteristic curve analyses confirmed the superior prognostic value of the lncRNA signature compared to clinically used prognostic biomarkers. Importantly, the autophagy-related lncRNA signature predicted patient prognosis independently of clinicopathological characteristics. Furthermore, we found that the expression levels of the autophagy-related lncRNA signature were significantly associated with the infiltration levels of different immune cell subsets, including T cells, NK cells, and dendritic cells.
conclusionThe autophagy-related lncRNA signature established here is an independent and robust predictor of osteosarcoma patient survival. Our findings also suggest that the expression of these 13 autophagy-related lncRNAs may promote osteosarcoma progression by regulating immune cell infiltration in the tumor microenvironment.
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