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Machine Learning Identifies Glycosphingolipid Signature Linking Immune Dysregulation and Clinical Prognosis in Uveal Melanoma

2025-11-13

Abstract excerpt

<title>Abstract</title> <p> Purpose To investigate glycosphingolipid biosynthesis (GSB) dysregulation in uveal melanoma (UVM) and develop a machine learning-driven prognostic signature bridging GSB activity, tumor microenvironment, and clinical outcomes. Methods Using TCGA and GEO cohorts, GSB activity was quantified via Gene Set Variation Analysis (GSVA). Differential expression analysis, least absolute shrinka...

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Literature Corpus work
b4830039-7fb8-5926-9ee3-d303dcbbb47e
DOI
10.21203/rs.3.rs-7815940/v1
Open publication

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Machine Learning Identifies Glycosphingolipid Signature Linking Immune Dysregulation and Clinical Prognosis in Uveal MelanomaDOI 10.21203/rs.3.rs-7815940/v1
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