ArticleiScience2024
Machine learning unveils immune-related signature in multicenter glioma studies.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Lactate Metabolism-Immune Regulation-Related Gene Signature in Lower-Grade Gliomas: Prognostic Model Development and Immune Characterization.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Development and validation of a robust cuproptosis related signature for primary glioma via machine learning aided by loop training and validation.Discover oncology · 2026Article
- Comprehensive analysis of immune escape-related prognostic signature in high-grade glioma.Discover oncology · 2025Article
- Expression graph network framework for biomarker discovery.Briefings in bioinformatics · 2025Article
- Machine learning derived development and validation of extracellular matrix related signature for predicting prognosis in adolescents and young adults glioma.Scientific reports · 2025Article
- Article
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor, showed stable and powerful predictive performance for overall and progression-free survival, surpassing traditional clinical variables. The risk score correlated significantly with the immune microenvironment, indicating potential sensitivity to immunotherapy. High-risk groups exhibited distinct chemotherapy drug sensitivity. Seven signature genes, including IGFBP2 and TNFRSF12A, were validated by qRT-PCR, with higher expression in tumors and prognostic relevance. TNFRSF12A, upregulated in GBM, demonstrated inhibitory effects on glioma cell proliferation, migration, and invasion. CIPS emerges as a robust tool for enhancing individual glioma patient outcomes, while IGFBP2 and TNFRSF12A pose as promising tumor markers and therapeutic targets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.