Identification and validation of a novel prognosis prediction model in adrenocortical carcinoma by integrative bioinformatics analysis and statistics and machine learning
Abstract:Background: Adrenocortical carcinoma (ACC) is a rare malignancy with poor prognosis. Thus, we aimed to establish a gene signature to predict the prognosis for ACC. Methods: Firstly, “WGCNA” package was used to construct a co-expression network and screen key module. Secondly, survival associated genes were identified by performing survival analysis. Thirdly, regression models were constructed by using the Ridge, ELASTIC-NET, and LASSO methods. Time-dependent ROC analysis, Cox regression analysis, GSEA, DCA and… Show more
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