Expression of let-7i and miR-192 is associated with resistance to cisplatin-based chemoradiotherapy in patients with larynx and hypopharynx cancer.

Biomarker Chemoradiotherapy Head and neck cancer Hypopharynx Larynx Predictive microRNA

Journal

Oral oncology
ISSN: 1879-0593
Titre abrégé: Oral Oncol
Pays: England
ID NLM: 9709118

Informations de publication

Date de publication:
22 Jun 2020
Historique:
received: 04 03 2020
revised: 18 05 2020
accepted: 07 06 2020
pubmed: 26 6 2020
medline: 26 6 2020
entrez: 26 6 2020
Statut: aheadofprint

Résumé

The majority of patients with locally advanced larynx or hypopharynx squamous cell carcinoma are treated with organ-preserving chemoradiotherapy (CRT). Clinical outcome following CRT varies greatly. We hypothesized that tumor microRNA (miRNA) expression is predictive for outcome following CRT. Next-generation sequencing (NGS) miRNA profiling was performed on 37 formalin-fixed paraffin-embedded (FFPE) tumor samples. Patients with a recurrence-free survival (RFS) of less than 2 years and patients with late/no recurrence within 2 years were compared by differential expression analysis. Tumor-specific miRNAs were selected based on normal mucosa miRNA expression data from The Cancer Genome Atlas database. A model was constructed to predict outcome using group-regularized penalized logistic ridge regression. Candidate miRNAs were validated by RT-qPCR in the initial sample set as well as in 46 additional samples. Thirteen miRNAs were differentially expressed (p < 0.05, FDR < 0.1) according to outcome group. Initial class prediction in the NGS cohort (n = 37) resulted in a model combining five miRNAs and disease stage, able to predict CRT outcome with an area under the curve (AUC) of 0.82. In the RT-qPCR cohort (n = 83), 25 patients (30%) experienced early recurrence (median RFS 8 months; median follow-up 42 months). Class prediction resulted in a model combining let-7i-5p, miR-192-5p and disease stage, able to discriminate patients with good versus poor clinical outcome (AUC:0.80). The combined miRNA expression and disease stage prediction model for CRT outcome is superior to using either factor alone. This study indicates NGS miRNA profiling using FFPE specimens is feasible, resulting in clinically relevant biomarkers.

Identifiants

pubmed: 32585557
pii: S1368-8375(20)30287-6
doi: 10.1016/j.oraloncology.2020.104851
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104851

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Dennis Poel (D)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, the Netherlands; Department of Medical Oncology, Radboud University Medical Center, Nijmegen, the Netherlands.

François Rustenburg (F)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Neurosurgery, Cancer Center Amsterdam, the Netherlands.

Daoud Sie (D)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Center Amsterdam, the Netherlands.

Hendrik F van Essen (HF)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Center Amsterdam, the Netherlands.

Paul P Eijk (PP)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Center Amsterdam, the Netherlands.

Elisabeth Bloemena (E)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Center Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Maxillofacial Surgery/Oral Pathology, Academic Center for Dentistry Amsterdam (ACTA), the Netherlands.

Teresita Elhorst Benites (T)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, the Netherlands.

Madeleine C van den Berg (MC)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, the Netherlands.

Marije R Vergeer (MR)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Radiation Oncology, Cancer Center Amsterdam, the Netherlands.

René C Leemans (RC)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Otolaryngology-Head and Neck Surgery, Cancer Center Amsterdam, the Netherlands.

Tineke E Buffart (TE)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, the Netherlands; Antoni van Leeuwenhoek Hospital, Department of Gastrointestinal Oncology, Amsterdam, the Netherlands.

Bauke Ylstra (B)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Pathology, Cancer Center Amsterdam, the Netherlands.

Ruud H Brakenhoff (RH)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Otolaryngology-Head and Neck Surgery, Cancer Center Amsterdam, the Netherlands.

Henk M Verheul (HM)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, the Netherlands; Department of Medical Oncology, Radboud University Medical Center, Nijmegen, the Netherlands.

Jens Voortman (J)

Amsterdam UMC, Vrije Universiteit Amsterdam, Department of Medical Oncology, Cancer Center Amsterdam, the Netherlands. Electronic address: j.voortman@amsterdamumc.nl.

Classifications MeSH