Related Experiment Video
Updated: Jun 14, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Identification of a nomogram predicting overall survival based on ADAP2-related apoptosis genes in gliomas
Chao Zhang1, Jiajun Wang1, Zihui Niu1
1Department of Neurosurgery, The Affliated Chuzhou Hospital of Anhui Medical University, The First People's Hospital of Chuzhou, Chuzhou 239000, China.
Background:
Apoptosis continues to be a pivotal area of investigation in glioma research. ADAP2 mediates the malignant progression of gliomas through the inhibition of apoptosis and predicts the overall survival(OS) of glioma patients based on prognostic modeling of the apoptotic gene set.
Methods:
The study encompassed 686 glioma patients, with 413 allocated to the training group and 273 to the validation group. Differential expression of ADAP2 across various glioma subtypes was assessed through bioinformatics analysis and Western blotting. The correlation between ADAP2 and apoptosis was examined using Gene Set Enrichment Analysis (GSEA). Multivariate Cox regression analysis and LASSO dimension reduction analysis were employed to identify apoptosis-related genes with prognostic significance in glioma patients and to construct a nomogram. Biological functions and mechanisms associated with risk scores were explored via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and GSEA analyses, with validation through Western blotting, flow cytometry, and AM/PI staining.
Results:
ADAP2 was found to be enriched in more aggressive glioma subtypes and was closely linked to glioma cell apoptosis, modulating this process via the NF-κB and P53 signaling pathway. A nomogram for OS in glioma patients was constructed using thirteen apoptosis-related genes. Additionally, ROC curves, calibration curves, and C-indices confirmed the robust applicability of the nomogram.
Conclusion:
ADAP2 functions as a prognostic biomarker for glioma patients, regulating glioma cell apoptosis through the NF-κB and P53 signaling pathway. Moreover, prognostic models based on apoptosis-related genes can accurately predict OS for glioma patients at 1, 2, 3, 5, and 10 years.
More Related Videos
06:32Evaluation of Biomarkers in Glioma by Immunohistochemistry on Paraffin-Embedded 3D Glioma Neurosphere Cultures
Published on: January 9, 2019
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024