ArticleJCI insight2020
Prognostic and predictive value of an immune infiltration signature in diffuse lower-grade gliomas.
Article in JCI insight, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Limitations of nomogram models in predicting survival outcomes for glioma patients.Frontiers in immunology · 2025Pooled it
- Leveraging single-cell foundation models for accurate survival outcome prediction.Bioinformatics advances · 2026Article
- Explainable Machine Learning Models for Glioma Subtype Classification and Survival Prediction.Cancers · 2025Article
- Article
- Autonomic nervous system development-related signature as a novel predictive biomarker for immunotherapy in pan-cancers.Frontiers in immunology · 2025Article
- Revealing the role of SPP1Cell & bioscience · 2024Article
- Exploring the prognostic potential of m6A methylation regulators in low-grade glioma: implications for tumor microenvironment modulation.European journal of medical research · 2024Article
- Leveraging a disulfidptosis‑related lncRNAs signature for predicting the prognosis and immunotherapy of glioma.Cancer cell international · 2023Article
- Depiction of neuroendocrine features associated with immunotherapy response using a novel one-class predictor in lung adenocarcinoma.Discover oncology · 2023Article
- Ferroptosis-related NFE2L2 and NOX4 Genes are Potential Risk Prognostic Biomarkers and Correlated with Immunogenic Features in Glioma.Cell biochemistry and biophysics · 2023Review
- Novel Cuproptosis-Related Gene Signature for Precise Identification of High-Risk Populations in Low-Grade Gliomas.Mediators of inflammation · 2023Article
- Article
- Article
- A Novel Classification Model for Lower-Grade Glioma Patients Based on Pyroptosis-Related Genes.Brain sciences · 2022Article
- APOLLO: An accurate and independently validated prediction model of lower-grade gliomas overall survival and a comparative study of model performance.EBioMedicine · 2022Article
- The immunology of low-grade gliomas.Neurosurgical focus · 2022Review
- Methylation-based reclassification and risk stratification of skull-base chordomas.Frontiers in oncology · 2022Article
- Identification of a Nomogram with an Autophagy-Related Risk Signature for Survival Prediction in Patients with Glioma.International journal of general medicine · 2022Article
- FCGR3A Is a Prognostic Biomarker and Correlated with Immune Infiltrates in Lower-Grade Glioma.Journal of oncology · 2022Article
- Construction and validation of a glioblastoma prognostic model based on immune-related genes.Frontiers in neurology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
BACKGROUNDLower-grade gliomas (LGGs) vary widely in terms of the patient's overall survival (OS). There is no current, valid method that could exactly predict the survival. The effects of intratumoral immune infiltration on clinical outcome have been widely reported. Thus, we aim to develop an immune infiltration signature to predict the survival of LGG patients.METHODSWe analyzed 1216 LGGs from 5 public data sets, including 2 RNA sequencing data sets and 3 microarray data sets. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to select an immune infiltration signature and build a risk score. The performance of the risk score was assessed in the training set (329 patients), internal validation set (140 patients), and 4 external validation sets (405, 118, 88, and 136 patients).RESULTSAn immune infiltration signature consisting of 20 immune metagenes was used to generate a risk score. The performance of the risk score was thoroughly verified in the training and validation sets. Additionally, we found that the risk score was positively correlated with the expression levels of TGF-β and PD-L1, which were important targets of combination immunotherapy. Furthermore, a nomogram incorporating the risk score, patient's age, and tumor grade was developed to predict the OS, and it performed well in all the training and validation sets (C-index: 0.873, 0.881, 0.781, 0.765, 0.721, and 0.753).CONCLUSIONThe risk score based on the immune infiltration signature has reliable prognostic and predictive value for patients with LGGs and is a potential biomarker for the cotargeting immunotherapy.FUNDINGThis work was supported by The National Natural Science Foundation of China (grant nos. 81472370 and 81672506), the Natural Science Foundation of Beijing (grant no. J180005), the National High Technology Research and Development Program of China (863 Program, grant no. 2014AA020610), and the National Basic Research Program of China (973 Program, grant no. 2014CB542006).
Indexed as
Identifiers
What OpenQuestion holds
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.