Dataset Information


Genomic and Transcriptomic Characterization of Papillary Microcarcinomas With Lateral Neck Lymph Node Metastases.

ABSTRACT: CONTEXT:Most papillary microcarcinomas (PMCs) are indolent and subclinical. However, as many as 10% can present with clinically significant nodal metastases. OBJECTIVE AND DESIGN:Characterization of the genomic and transcriptomic landscape of PMCs presenting with or without clinically important lymph node metastases. SUBJECTS AND SAMPLES:Formalin-fixed paraffin-embedded PMC samples from 40 patients with lateral neck nodal metastases (pN1b) and 71 patients with PMC with documented absence of nodal disease (pN0). OUTCOME MEASURES:To interrogate DNA alterations in 410 genes commonly mutated in cancer and test for differential gene expression using a custom NanoString panel of 248 genes selected primarily based on their association with tumor size and nodal disease in the papillary thyroid cancer TCGA project. RESULTS:The genomic landscapes of PMC with or without pN1b were similar. Mutations in TERT promoter (3%) and TP53 (1%) were exclusive to N1b cases. Transcriptomic analysis revealed differential expression of 43 genes in PMCs with pN1b compared with pN0. A random forest machine learning-based molecular classifier developed to predict regional lymph node metastasis demonstrated a negative predictive value of 0.98 and a positive predictive value of 0.72 at a prevalence of 10% pN1b disease. CONCLUSIONS:The genomic landscape of tumors with pN1b and pN0 disease was similar, whereas 43 genes selected primarily by mining the TCGA RNAseq data were differentially expressed. This bioinformatics-driven approach to the development of a custom transcriptomic assay provides a basis for a molecular classifier for pN1b risk stratification in PMC.


PROVIDER: S-EPMC6733494 | BioStudies | 2019-01-01

REPOSITORIES: biostudies

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