1. Deep learning prediction of BRAF-RAS gene expression signature identifies noninvasive follicular thyroid neoplasms with papillary-like nuclear features
- Author
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Alexander T. Pearson, James M. Dolezal, Anna Trzcinska, Xavier M. Keutgen, Nishant Agrawal, Peter Angelos, Sara Kochanny, Elizabeth A. Blair, Chih-Yi Liao, and Nicole A. Cipriani
- Subjects
Proto-Oncogene Proteins B-raf ,0301 basic medicine ,Pathology ,medicine.medical_specialty ,Carcinoma, Papillary, Follicular ,Article ,Pathology and Forensic Medicine ,Thyroid carcinoma ,03 medical and health sciences ,Deep Learning ,0302 clinical medicine ,Text mining ,Follicular phase ,Gene expression ,medicine ,Humans ,Neoplasm ,Thyroid Neoplasms ,Nuclear atypia ,Head and neck cancer ,business.industry ,Gene Expression Profiling ,fungi ,Thyroid ,Diagnostic markers ,medicine.disease ,Gene Expression Regulation, Neoplastic ,Thyroid diseases ,Tumor Subtype ,030104 developmental biology ,medicine.anatomical_structure ,030220 oncology & carcinogenesis ,Mutation ,ras Proteins ,Transcriptome ,business - Abstract
Noninvasive follicular thyroid neoplasms with papillary-like nuclear features (NIFTP) are follicular-patterned thyroid neoplasms defined by nuclear atypia and indolent behavior. They harbor RAS mutations, rather than BRAFV600E mutations as is observed in papillary thyroid carcinomas with extensive follicular growth. Reliably identifying NIFTPs aids in safe therapy de-escalation, but has proven to be challenging due to interobserver variability and morphologic heterogeneity. The genomic scoring system BRS (BRAF-RAS score) was developed to quantify the extent to which a tumor’s expression profile resembles a BRAFV600E or RAS-mutant neoplasm. We proposed that deep learning prediction of BRS could differentiate NIFTP from other follicular-patterned neoplasms. A deep learning model was trained on slides from a dataset of 115 thyroid neoplasms to predict tumor subtype (NIFTP, PTC-EFG, or classic PTC), and was used to generate predictions for 497 thyroid neoplasms within The Cancer Genome Atlas (TCGA). Within follicular-patterned neoplasms, tumors with positive BRS (RAS-like) were 8.5 times as likely to carry an NIFTP prediction than tumors with negative BRS (89.7% vs 10.5%, P
- Published
- 2021
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