ArticleScientific reports2022
Construction of a machine learning-based artificial neural network for discriminating PANoptosis related subgroups to predict prognosis in low-grade gliomas.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 21 citations in OpenAlex.
- Identification of PANoptosis-related hub genes in acute myocardial infarction: diagnostic potential, immune correlates, and therapeutic insights.Journal of cardiothoracic surgery · 2026Article
- From Data to Decision: Integrating Bioinformatics into Glioma Patient Stratification and Immunotherapy Selection.International journal of molecular sciences · 2026Review
- A multi-machine learning framework identifies novel PANoptosis-related biomarkers and their immune landscape in ulcerative colitis: Insights from transcriptomics and experimental validation.Frontiers in immunology · 2026Article
- Exploring the prognostic value and biomarker of TEX11 in breast cancer via PANoptosis.Breast cancer (Tokyo, Japan) · 2026Article
- PANoptosis: A novel therapeutic target in kidney disease (Review).International journal of molecular medicine · 2025Review
- A PANoptosis-Based Signature for Survival and Immune Predication in Glioblastoma Multiforme.Annals of clinical and translational neurology · 2025Article
- From pixels to prognosis: leveraging radiomics and machine learning to predict IDH1 genotype in gliomas.Neurosurgical review · 2025Article
- A potential strategy to rebuild the tumor immune microenvironment: PANoptosis.Frontiers in immunology · 2025Review
- Integrated multi-optosis model for pan-cancer candidate biomarker and therapy target discovery.Frontiers in bioinformatics · 2025Article
- Review
- PANoptosis: bridging apoptosis, pyroptosis, and necroptosis in cancer progression and treatment.Cancer gene therapy · 2024Review
- Utilizing a novel model of PANoptosis-related genes for enhanced prognosis and immune status prediction in kidney renal clear cell carcinoma.Apoptosis : an international journal on programmed cell death · 2024Article
- Identification of cross-talk pathways and PANoptosis-related genes in periodontitis and Alzheimer's disease by bioinformatics analysis and machine learning.Frontiers in aging neuroscience · 2024Article
- PANoptosis in cancer, the triangle of cell death.Cancer medicine · 2023Review
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The poor prognosis of gliomas necessitates the search for biomarkers for predicting clinical outcomes. Recent studies have shown that PANoptosis play an important role in tumor progression. However, the role of PANoptosis in in gliomas has not been fully clarified.Low-grade gliomas (LGGs) from TCGA and CGGA database were classified into two PANoptosis patterns based on the expression of PANoptosis related genes (PRGs) using consensus clustering method, followed which the differentially expressed genes (DEGs) between two PANoptosis patterns were defined as PANoptosis related gene signature. Subsequently, LGGs were separated into two PANoptosis related gene clusters with distinct prognosis based on PANoptosis related gene signature. Univariate and multivariate cox regression analysis confirmed the prognostic values of PANoptosis related gene cluster, based on which a nomogram model was constructed to predict the prognosis in LGGs. ESTIMATE algorithm, MCP counter and CIBERSORT algorithm were utilized to explore the distinct characteristics of tumor microenvironment (TME) between two PANoptosis related gene clusters. Furthermore, an artificial neural network (ANN) model based on machine learning methods was developed to discriminate distinct PANoptosis related gene clusters. Two external datasets were used to verify the performance of the ANN model. The Human Protein Atlas website and western blotting were utilized to confirm the expression of the featured genes involved the ANN model. We developed a machine learning based ANN model for discriminating PANoptosis related subgroups with drawing implications in predicting prognosis in gliomas.
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