ArticleJournal of cancer research and clinical oncology2023
An alternative extension of telomeres related prognostic model to predict survival in lower grade glioma.
Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 3 citations in OpenAlex.
- Evaluating a Glioma Transcriptomic Signature Against a Clinical Reference Model and a Random-Signature Null Distribution: A Leakage-Controlled Internal Audit and a Survey of the Field.Diagnostics (Basel, Switzerland) · 2026Article
- Identification of alternative lengthening of telomeres-related genes prognosis model in hepatocellular carcinoma.BMC cancer · 2024Article
- Prognosis Individualized: Survival predictions for WHO grade II and III gliomas with a machine learning-based web application.NPJ digital medicine · 2023Article
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9 authors at 2 institutions in 1 country.
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Abstract
objectiveThe alternative extension of the telomeres (ALT) mechanism is activated in lower grade glioma (LGG), but the role of the ALT mechanism has not been well discussed. The primary purpose was to demonstrate the significance of the ALT mechanism in prognosis estimation for LGG patients.
methodGene expression and clinical data of LGG patients were collected from the Chinese Glioma Genome Atlas (CGGA) and the Cancer Genome Atlas (TCGA) cohort, respectively. ALT-related genes obtained from the TelNet database and potential prognostic genes related to ALT were selected by LASSO regression to calculate an ALT-related risk score. Multivariate Cox regression analysis was performed to construct a prognosis signature, and a nomogram was used to represent this signature. Possible pathways of the ALT-related risk score are explored by enrichment analysis.
resultThe ALT-related risk score was calculated based on the LASSO regression coefficients of 22 genes and then divided into high-risk and low-risk groups according to the median. The ALT-related risk score is an independent predictor of LGG (HR and 95% CI in CGGA cohort: 5.70 (3.79, 8.58); in TCGA cohort: 1.96 (1.09, 3.54)). ROC analysis indicated that the model contained ALT-related risk score was superior to conventional clinical features (AUC: 0.818 vs 0.729) in CGGA cohorts. The results in the TCGA cohort also shown a powerful ability of ALT-related risk score (AUC: 0.766 vs 0.691). The predicted probability and actual probability of the nomogram are consistent. Enrichment analysis demonstrated that the ALT mechanism was involved in the cell cycle, DNA repair, immune processes, and others.
conclusionALT-related risk score based on the 22-gene is an important factor in predicting the prognosis of LGG patients.
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