Identification of a serum-based microRNA signature that detects recurrent oral squamous cell carcinoma before it is clinically evident
Menée à partir de 468 échantillons sériques prélevés sur 163 témoins et 305 patients atteints d'un carcinome épidermoïde ou in situ de la cavité buccale, cette étude identifie une signature, basée sur la présence des microARNs miR-125b-5p et miR-342-3p, pour détecter précocement la récidive d'un carcinome épidermoïde
Background : Survival rates for oral squamous cell carcinoma (OSCC) have remained poor for decades, a fact largely attributable to late-stage diagnoses and high recurrence rates. We report analysis of serum miRNA expression in samples from patients with high-risk oral lesions (HRL, including OSCC/carcinoma in situ lesions) and healthy non-cancer controls, with the aim of non-invasively detecting primary or recurrent disease before it is clinically evident.
Methods : Discovery, test, and validation sets were defined from a total of 468 serum samples (305 HRL and 163 control samples). Samples were analysed using multiple qRT-PCR platforms.
Results : A two-miRNA classifier comprised of miR-125b-5p and miR-342-3p was defined following discovery and test analyses. Analysis in an independent validation cohort reported sensitivity and specificity of ~74% for this classifier. Significantly, when this classifier was applied to serial serum samples taken from patients both before treatment and during post-treatment surveillance, it identified recurrence an average of 15 months prior to clinical presentation.
Conclusions : These results indicate this serum miRNA classifier is effective as a simple, non-invasive monitoring tool for earlier detection of recurrent disease when lesions are typically smaller and amenable to a wider array of treatment options to improve survival.
British Journal of Cancer , article en libre accès, 2023