Immunogenic profiling of metastatic uveal melanoma discerns a potential signature related to prognosis

AbstractBackgroundUveal melanoma (UM) is an aggressive intraocular malignant tumor. The present study aimed to identify the key genes associated with UM metastasis and established a gene signature to analyze the relationship between the signature and prognosis and immune cell infiltration. Later, a predictive model combined with clinical variables was developed and validated.MethodsTwo UM gene expression profile chip datasets were downloaded from TCGA and GEO databases. Immune-related genes (IRGs) were obtained from IMPORT database. First, these mRNAs were intersected with IRGs, and weighted gene co-expression network analysis (WGCNA) was used to identify the co-expression of genes primarily associated with metastasis of UM. Univariate Cox regression analysis screened the genes related to prognosis. LASSO-Cox established a risk score to distinguish high-risk group and low-risk group. Then the GSEA enrichment pathway and immune cell infiltration of the two groups were compared. And combined with clinical variables, a predictive model was constructed. The time-dependent receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) curve were used to verify the stability and accuracy of the final predictive model, and a nomogram was then drawn.ResultsThe MEblack, MEpurple, and MEblue modules were significantly associated with the metastasis of UM patients (P value  <  0.001, = 0.001, = 0.022, respectively). Four genes (UBXN2B,...
Source: Journal of Cancer Research and Clinical Oncology - Category: Cancer & Oncology Source Type: research