ArticleThe Journal of international medical research2020
Identification of prognostic immune genes in laryngeal cancer.
Article in The Journal of international medical research, 2020. 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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Who cites it
3 citing papers in PubMed.
- Identifying key pathogenic mechanisms and potential intervention targets for recurrence after laryngeal cancer treatment through bioinformatics screening.Translational cancer research · 2024Article
- An Improvised Deep-Learning-Based Mask R-CNN Model for Laryngeal Cancer Detection Using CT Images.Sensors (Basel, Switzerland) · 2022Article
- DIAPH2, PTPRD and HIC1 Gene Polymorphisms and Laryngeal Cancer Risk.International journal of environmental research and public health · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveIn this study, we aimed to identify prognostic immune-related genes and establish a prognostic model for laryngeal cancer based on these genes.
methodsTranscriptome profiles and clinical data of patients with laryngeal cancer were downloaded from The Cancer Genome Atlas database. Integrated bioinformatics analyses were performed to identify genes associated with prognosis.
resultsThirty prognostic immune-related genes for laryngeal cancer were identified. We constructed a regulatory network of prognosis comprising transcription factors and immune-related genes. Multivariate Cox regression analyses identified 15 immune-related genes in the network that were used to establish the prognostic model. The model exhibited excellent prognostic prediction ability with a high area under the curve value (0.916). The calculated risk score based on expression of the 15 immune-related genes was shown to be an independent prognostic factor for laryngeal cancer.
conclusionWe identified prognostic immune-related genes and established a prognostic model for laryngeal cancer, which might help identify novel predictive biomarkers and therapeutic targets of laryngeal cancer.
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