Integrating ctDNA Analysis and Radiomics for Dynamic Risk Assessment in Localized Lung Cancer
Menée sur 418 patients atteints d'un cancer du poumon non à petites cellules traité par chimioradiothérapie, cette étude évalue la performance d'un modèle, basé sur l'analyse de l'ADN tumoral circulant, des caractéristiques tumorales et des données radiomiques, pour prédire le risque de progression de la maladie
The complementarity and clinical utility of combining liquid biopsies and radiomic image analysis has not been demonstrated. ctDNA minimal residual disease after chemoradiotherapy (CRT) for non–small cell lung cancer (NSCLC) is highly prognostic, but on-treatment biomarkers are needed to enable response-adapted therapies. In this study, we analyzed 418 patients with NSCLC undergoing CRT to develop and validate a novel dynamic risk model that accurately predicts ultimate progression-free survival during treatment. We optimize tissue-free variant calling from plasma samples to facilitate ctDNA monitoring and demonstrate the importance of accounting for persistent clonal hematopoiesis variants. We show that mid-CRT ctDNA concentration is prognostic for disease progression and integrate additional pre-CRT risk factors, including radiomics, into a combined model that improves outcome prediction. Our results suggest that tumor features, radiomics, and mid-CRT ctDNA analysis are complementary and can identify patients at high and low risk of progression to potentially enable response-adapted therapies
Cancer Discovery , article en libre accès 2025