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OA06 - Prognostic & Predictive Biomarkers (ID 452)
- Event: WCLC 2016
- Type: Oral Session
- Track: Biology/Pathology
- Presentations: 1
OA06.02 - Mutational Load Predicts Survival in LDCT Screening-Detected Lung Cancers (ID 5577)
14:20 - 15:50 | Author(s): M. Dugo
The issue of overdiagnosis in low-dose computed tomography (LDCT) screening trials for lung cancer has to be addressed by the development of complementary biomarkers able to improve detection of aggressive disease. We previously identified a 24 plasma miRNA signature endowed with good performance in terms of sensitivity and specificity in subjects enrolled in independent LDCT screening trials. However, the relationship between circulating miRNAs in plasma and the molecular heterogeneity of the patients’ tumors needs to be considered. Linking tumor genomics to circulating miRNA profiles represent an attractive approach. In fact a plasma miRNA assay able to classify molecular subclasses of tumors could constitute a sort of “liquid biopsy” endowed with not only diagnostic but also prognostic and, potentially, therapeutic value.
We evaluated the mutation profile by targeted Next-Generation Sequencing (NGS) analysis (Cancer Hotspot Panel v.2) in 94 Low Dose Computed Tomography (LDCT) screening-detected lung tumors resected from subjects participating in 3 screening trials for lung cancer. Mutation profile was associated with clinicopathologic, survival features and with a plasma MSC risk level of patients. The mutational profile obtained was compared with the mutations of a selected dataset of clinically detected lung tumors through The Cancer Genome Atlas (TCGA).
We showed alterations in the main genetic drivers in 79% of screening lung tumors whereas 21% of tumor samples had no alteration within these amplicons. Significant associations between TP53, squamous histology and smoking intensity as well as KRAS mutations with worse OS were detected. EGFR alterations were present in 4 tumors from heavy smokers. The 5-year overall survival (OS) of screening patients with and without mutations in the tumors was 64% and 100%, respectively (p=0.019). By combining the mutational status with the MSC risk profile, patients were stratified into 3 groups with 5-year OS ranging from 41% to 96% (p<0.0001) and the prognostic value was significant even when controlling for stage (p=0.017). A similar mutational profile and mutation frequency was observed in screening- and in clinical (TCGA) tumors, whereas difference in 5-year OS between subjects with and without mutations was exclusively detected in screening patients.
The mutation profile of screening-detected tumors, while similar to that of clinically-detected tumors, was a strong predictor of OS. The combination of tumor mutational status with a circulating miRNA-based risk classifier predicts tumor aggressiveness and clinical outcome and may find rapid application in LDCT screening programs by reducing the number of unnecessary interventions and helping plan targeted treatment
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