Epithelial-to-mesenchymal transition is a prognostic marker for patient outcome in advanced stage HNSCC patients treated with chemoradiotherapy.
Chemoradiotherapy
Epithelial to mesenchymal transition
HNSCC
Head and neck cancer
Prognostic biomarkers
RNA-Seq
Journal
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
ISSN: 1879-0887
Titre abrégé: Radiother Oncol
Pays: Ireland
ID NLM: 8407192
Informations de publication
Date de publication:
06 2020
06 2020
Historique:
received:
17
01
2020
revised:
06
05
2020
accepted:
08
05
2020
pubmed:
16
5
2020
medline:
15
4
2021
entrez:
16
5
2020
Statut:
ppublish
Résumé
The prognosis of patients with HPV-negative advanced stage head and neck squamous cell carcinoma (HNSCC) remains poor. No prognostic markers other than TNM staging are routinely used in clinic. Epithelial-to-mesenchymal transition (EMT) has been shown to be a strong prognostic factor in other cancer types. The purpose of this study was to determine the role of EMT in HPV-negative HNSCC outcomes. Pretreatment tumor material from patients of two cohorts, totalling 174 cisplatin-based chemoradiotherapy treated HPV-negative HNSCC patients, was RNA-sequenced. Seven different EMT gene expression signatures were used for EMT status classification and generation of HNSCC-specific EMT models using Random Forest machine learning. Mesenchymal classification by all EMT signatures consistently enriched for poor prognosis patients in both cohorts of 98 and 76 patients. Uni- and multivariate analyses show important HR of 1.6-5.8, thereby revealing EMT's role in HNSCC outcome. Discordant classification by these signatures prompted the generation of an HNSCC-specific EMT profile based on the concordantly classified samples in the first cohort (cross-validation AUC > 0.98). The independent validation cohort confirmed the association of mesenchymal classification by the HNSCC-EMT model with poor overall survival (HR = 3.39, p < 0.005) and progression free survival (HR = 3.01, p < 0.005) in multivariate analysis with TNM. Analysis of an additional HNSCC cohort from PET-positive patients with metastatic disease prior to treatment further supports this relationship and reveals a strong link of EMT to the propensity to metastasize. EMT in HPV-negative HNSCC co-defines patient outcome after chemoradiotherapy. The generated HNSCC-EMT prediction models can function as strong prognostic biomarkers.
Sections du résumé
BACKGROUND
The prognosis of patients with HPV-negative advanced stage head and neck squamous cell carcinoma (HNSCC) remains poor. No prognostic markers other than TNM staging are routinely used in clinic. Epithelial-to-mesenchymal transition (EMT) has been shown to be a strong prognostic factor in other cancer types. The purpose of this study was to determine the role of EMT in HPV-negative HNSCC outcomes.
METHODS
Pretreatment tumor material from patients of two cohorts, totalling 174 cisplatin-based chemoradiotherapy treated HPV-negative HNSCC patients, was RNA-sequenced. Seven different EMT gene expression signatures were used for EMT status classification and generation of HNSCC-specific EMT models using Random Forest machine learning.
RESULTS
Mesenchymal classification by all EMT signatures consistently enriched for poor prognosis patients in both cohorts of 98 and 76 patients. Uni- and multivariate analyses show important HR of 1.6-5.8, thereby revealing EMT's role in HNSCC outcome. Discordant classification by these signatures prompted the generation of an HNSCC-specific EMT profile based on the concordantly classified samples in the first cohort (cross-validation AUC > 0.98). The independent validation cohort confirmed the association of mesenchymal classification by the HNSCC-EMT model with poor overall survival (HR = 3.39, p < 0.005) and progression free survival (HR = 3.01, p < 0.005) in multivariate analysis with TNM. Analysis of an additional HNSCC cohort from PET-positive patients with metastatic disease prior to treatment further supports this relationship and reveals a strong link of EMT to the propensity to metastasize.
CONCLUSIONS
EMT in HPV-negative HNSCC co-defines patient outcome after chemoradiotherapy. The generated HNSCC-EMT prediction models can function as strong prognostic biomarkers.
Identifiants
pubmed: 32413532
pii: S0167-8140(20)30266-8
doi: 10.1016/j.radonc.2020.05.013
pii:
doi:
Substances chimiques
Biomarkers, Tumor
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
186-194Informations de copyright
Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.