Ontology highlight
ABSTRACT: Context
Thyroid cancer recurrence is associated with increased mortality and adverse outcomes. Recurrence risk is currently predicted using clinical tools, often restaging patients after treatment. Detailed understanding of recurrence risk at disease onset could lead to personalized and improved patient care.Objective
We aimed to perform a comprehensive bioinformatic and experimental analysis of 3 levels of genetic change (mRNA, microRNA, and somatic mutation) apparent in recurrent tumors and construct a new combinatorial prognostic risk model.Methods
We analyzed The Cancer Genome Atlas data (TCGA) to identify differentially expressed genes (mRNA/microRNA) in 46 recurrent vs 455 nonrecurrent thyroid tumors. Two exonic mutational pipelines were used to identify somat
SUBMITTER: Nieto HR
PROVIDER: S-EPMC9016467 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature