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Molecular signature incorporating the immune microenvironment enhances thyroid cancer outcome prediction

Authors :
George J. Xu
Matthew A. Loberg
Jean-Nicolas Gallant
Quanhu Sheng
Sheau-Chiann Chen
Brian D. Lehmann
Sophia M. Shaddy
Megan L. Tigue
Courtney J. Phifer
Li Wang
Mario W. Saab-Chalhoub
Lauren M. Dehan
Qiang Wei
Rui Chen
Bingshan Li
Christine Y. Kim
Donna C. Ferguson
James L. Netterville
Sarah L. Rohde
Carmen C. Solórzano
Lindsay A. Bischoff
Naira Baregamian
Aaron C. Shaver
Mitra Mehrad
Kim A. Ely
Daniel W. Byrne
Thomas P. Stricker
Barbara A. Murphy
Jennifer H. Choe
Luciane T. Kagohara
Elizabeth M. Jaffee
Eric C. Huang
Fei Ye
Ethan Lee
Vivian L. Weiss
Source :
Cell Genomics, Vol 3, Iss 10, Pp 100409- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Summary: Genomic and transcriptomic analysis has furthered our understanding of many tumors. Yet, thyroid cancer management is largely guided by staging and histology, with few molecular prognostic and treatment biomarkers. Here, we utilize a large cohort of 251 patients with 312 samples from two tertiary medical centers and perform DNA/RNA sequencing, spatial transcriptomics, and multiplex immunofluorescence to identify biomarkers of aggressive thyroid malignancy. We identify high-risk mutations and discover a unique molecular signature of aggressive disease, the Molecular Aggression and Prediction (MAP) score, which provides improved prognostication over high-risk mutations alone. The MAP score is enriched for genes involved in epithelial de-differentiation, cellular division, and the tumor microenvironment. The MAP score also identifies aggressive tumors with lymphocyte-rich stroma that may benefit from immunotherapy. Future clinical profiling of the stromal microenvironment of thyroid cancer could improve prognostication, inform immunotherapy, and support development of novel therapeutics for thyroid cancer and other stroma-rich tumors.

Details

Language :
English
ISSN :
2666979X
Volume :
3
Issue :
10
Database :
Directory of Open Access Journals
Journal :
Cell Genomics
Publication Type :
Academic Journal
Accession number :
edsdoj.fc1b6ef5686b46cf86fe3857f3b602c5
Document Type :
article
Full Text :
https://doi.org/10.1016/j.xgen.2023.100409