A liquid biopsy signature for predicting early recurrence in patients with gastric cancer
Menée à l'aide de données du projet "The Cancer Genome Atlas" ainsi que d'échantillons sanguins et d'échantillons tumoraux prélevés sur des patients atteints d'un cancer gastrique, cette étude identifie une signature, basée sur l'expression de 8 microARNs et la présence d'une instabilité des microsatellites, pour prédire le risque de récidive
Background : Gastric cancer (GC) patients who experience recurrence within the first year following surgery (early recurrence [ER]) exhibit worse prognosis. Herein, we established a microRNA-based liquid biopsy assay to predict ER in GC patients.
Methods : A comprehensive biomarker discovery was performed by analysing miRNA expression profiling in 271 primary GC tumours. Thereafter, the expression of these biomarkers was validated in 290 GC cases, which included 218 tissues and 72 pre-treatment sera, from two independent institutions.
Results : A panel of 8 miRNAs was identified during the initial biomarker discovery, and this panel could robustly predict ER in a tissue-based clinical cohort (area under the curve [AUC]: 0.81). Furthermore, a model combining the miRNA panel, microsatellite instability (MSI) status and tumour size exhibited superior predictive performance (AUC: 0.86), and was defined as a Prediction of Early Recurrence in GC (PERGC) signature, which was successfully validated in another independent cohort (AUC: 0.82). Finally, the PERGC signature was translated into a liquid biopsy assay (AUC: 0.81), and a multivariate regression analysis revealed this signature to be an independent predictor for ER (odds ratio: 11.20).
Conclusion : We successfully established a miRNA-based liquid biopsy signature that robustly predicts the risk of ER in GC patients.
British Journal of Cancer , résumé, 2023