ArticleJournal of oncology2021
Construction of a Prognostic Gene Signature Associated with Immune Infiltration in Glioma: A Comprehensive Analysis Based on the CGGA.
Article in Journal of oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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
10 citing papers in PubMed, 14 citations in OpenAlex.
- Review
- Article
- The Abundance of Tumor-Infiltrating CD8Biomedicines · 2022Article
- Identification of Prognostic Genes in Gliomas Based on Increased Microenvironment Stiffness.Cancers · 2022Article
- Article
- Considering Computational Mathematics IGHG3 as Malignant Melanoma Is Associated with Immune Infiltration of Malignant Melanoma.BioMed research international · 2022Article
- Identification and Validation of a Gene Signature for Lower-Grade Gliomas Based on Pyroptosis-Related Genes to Predict Survival and Response to Immune Checkpoint Inhibitors.Journal of healthcare engineering · 2022Article
- A Novel Defined Pyroptosis-Related Gene Signature for Predicting Prognosis and Treatment of Glioma.Frontiers in oncology · 2022Article
- Article
- Review
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTumor microenvironment (TME) is closely related to the progression of glioma and the therapeutic effect of drugs on this cancer. The aim of this study was to develop a signature associated with the tumor immune microenvironment using machine learning.
methodsWe downloaded the transcriptomic and clinical data of glioma patients from the Chinese Glioma Genome Atlas (CGGA) databases (mRNAseq_693). The single-sample Gene Set Enrichment Analysis (ssGSEA) database was used to quantify the relative abundance of immune cells. We divided patients into two different infiltration groups via unsupervised clustering analysis of immune cells and then selected differentially expressed genes (DEGs) between the two groups. Survival-related genes were determined using Cox regression analysis. We next randomly divided patients into a training set and a testing set at a ratio of 7 : 3. By integrating the DEGs into least absolute shrinkage and selection operator (LASSO) regression analysis in the training set, we were able to construct a 15-gene signature, which was validated in the testing and total sets. We further validated the signature in the mRNAseq_325 dataset of CGGA.
resultsWe identified 74 DEGs associated with tumor immune infiltration, 70 of which were significantly associated with overall survival (OS). An immune-related gene signature was established, consisting of 15 key genes: adenosine triphosphate (ATP)-binding cassette subfamily C member 3 (
conclusionWe constructed a stable gene signature associated with immune infiltration to predict the survival rates of glioma patients.
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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.