ArticleComputational intelligence and neuroscience2022
Analyzing Prognostic Hub Genes in the Microenvironment of Cutaneous Melanoma by Computer Integrated Bioinformatics.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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1 citing paper in PubMed.
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cutaneous melanoma (CM) is attracting increasing attention due to high mortality. In response to this, we synthetically analyze the CM dataset from the TCGA database and explore microenvironment-related genes that effectively predict patient prognosis. Immune/stromal scores of cases are calculated using the ESTIMATE algorithm and are significantly associated with overall patient survival. Then, differentially expressed genes are identified by comparing the immune score and stromal score, also prognostic genes are subsequently screened. Functional analysis shows that these genes are enriched in different activities of immune system. Moreover, 19 prognosis-related hub genes are extracted from the protein-protein interaction network, of which four unreported genes (IL7R, FLT3, C1QC, and HLA-DRB5) are chosen for validation. A significant negative relationship is found between the expression levels of the 4 genes and pathological stages, notably
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