ArticleFrontiers in oncology2021
Development and Verification of a Prostate Cancer Prognostic Signature Based on an Immunogenomic Landscape Analysis.
Article in Frontiers in oncology, 2021. 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.
- S100A2 upregulates GLUT1 expression to promote glycolysis in the progression of nasopharyngeal carcinoma.Histology and histopathology · 2024Article
- Early results of the integrative epigenomic-transcriptomic landscape of colorectal adenoma and cancer.World journal of gastrointestinal oncology · 2024Article
- Screening of Differentially Expressed Genes Based on the ACRG Molecular Subtypes of Gastric Cancer and the Significance and Mechanism ofJournal of personalized medicine · 2023Article
- European Health Data Space-An Opportunity Now to Grasp the Future of Data-Driven Healthcare.Healthcare (Basel, Switzerland) · 2022Article
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Authors and funding
6 authors.
Funding
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Abstract
purposeProstate cancer (PCa) has a high incidence among older men. Until now, there are no immunological markers available to predict PCa patients' survival. Therefore, it is necessary to explore the immunological characteristics of PCa.
methodsFirst, we retrieved RNA-seq and clinical data of 499 PCa and 52 normal prostate tissue samples from the Cancer Genome Atlas (TCGA). We identified 193 differentially expressed immune-related genes (IRGs) between PCa and normal prostate tissues. Functional enrichment analyses showed that the immune system can participate in PCa initiation. Then, we constructed a correlation network between transcription factors (TFs) and IRGs. We performed univariate and multivariate Cox regression analyses and identified five key prognostic IRGs (S100A2, NOX1, IGHV7-81, AMH, and AGTR1). Finally, a predictive nomogram was established and verified by the C-index.
resultsWe successfully constructed and validated an immune-related PCa prediction model. The signature could independently predict PCa patients' survival. Results showed that high-immune-risk patients were correlated with advanced stage. We also validated the S100A2 expression
conclusionOverall, we detected five IRGs (S100A2, NOX1, IGHV7-81, AMH, and AGTR1) that can be used as independent PCa prognostic factors.
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