LASSO Cox regression and multivariate Cox regression identified a 13-TF prognostic signature comprised of CREB3元, NR0B1, CENPA, FOXM1, E2F2, MYBL2, HOXC11, ZIC2, ZNF282, DNMT1, TCF3, ELK4, and KLF6. Furthermore, Gene Set Enrichment Analysis (GSEA) was performed to analyze the significance of the TFs constituting the prognostic signature. ![]() Then, multivariate analysis was used to reveal the independent prognostic factors. The univariate Cox regression analysis was applied to identify the survival-related TFs and the LASSO Cox regression was conducted to construct the TF signature based on these survival-associated TFs candidates. The gene expression profile and clinical information for ACC patients were downloaded from The Cancer Genome Atlas (TCGA, training set) and Gene Expression Omnibus (GEO, validation set) datasets after obtained 1,639 human TFs from a previously published study. This study aimed to construct a TF-based prognostic signature for the prediction of survival of ACC patients. ![]() Transcription factors (TFs) deregulation is found to be involved in adrenocortical tumorigenesis and cancer progression. ![]() Adrenocortical carcinoma (ACC) is a rare endocrine cancer that manifests as abdominal masses and excessive steroid hormone levels and is associated with poor clinical outcomes.
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