ArticleGenes & genomics2022
Establishment and validation of five autophagy-related signatures for predicting survival and immune microenvironment in glioma.
Article in Genes & genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Autophagy in brain tumors: molecular mechanisms, challenges, and therapeutic opportunities.Journal of translational medicine · 2025Review
- Artificial Intelligence Algorithm-Based Intraoperative Magnetic Resonance Navigation for Glioma Resection.Contrast media & molecular imaging · 2022Article
- CAMK1D Inhibits Glioma Through the PI3K/AKT/mTOR Signaling Pathway.Frontiers in oncology · 2022Article
- Procollagen C-protease enhancer protein is a prognostic factor for glioma and promotes glioma development by regulating multiple tumor-related pathways and immune microenvironment.International journal of immunopathology and pharmacologyArticle
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGliomas, especially Glioblastoma multiforme, are the most frequent type of primary tumors in central nervous system. Increasing researches have revealed the relationship between autophagy and tumor, while the molecular mechanism of autophagy in glioma is still rarely reported.
objectiveOur research aims to conform the autophagy-related genes (ARGs) implicated in the development and progression of glioma and improve our understanding of autophagy in glioma.
methods20 candidate ARGs were screened through the protein-protein interaction network. We also downloaded the publicly accessible glioma data for 665 individuals from TCGA and 970 individuals from CGGA with RNA sequences and clinicopathological information. Subsequently, univariate and multivariate Cox regression analysis identified 5 key ARGs among the 20 candidate genes as key prognostic genes for survival, GSEA and immune response analysis.
resultsATG5, BCL2L1, CASP3, CASP8, GAPDH were identified as key ARGs in our research. Further studies showed that the high-risk population was linked to a dismal prognosis and suggested an immune-inhibitory microenvironment. GSEA results demonstrated that high risk population was closely related to DNA repair, hypoxia pathways, implicated in immunosuppression and carcinogenesis. Through CMap, we finally identified 14 candidate drugs for the ARG high risk population.
conclusionsThis study established and verified an ARG risk model, which can serve as an independent predictor for prognosis, reflect on the strength of the immune response and predict the potential drugs in glioma. Our findings offer new understandings of ARG molecular mechanism and promising therapeutic targets for glioma treatment.
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