The wide uptake of "liquid biopsy" diagnostics in the care of advanced cancer patients highlights the desire for improved access to tumor allowing accurate tumor genotyping (1). Genotyping of plasma cfDNA is now routine for detection of EGFR driver mutations at diagnosis of NSCLC, or for detection of the EGFR T790M mutation after TKI resistance, and is an emerging approach for the detection of other drivers (HER2 or BRAF mutations, ALK or ROS1 fusions…) (2) or the estimation of tumor mutation burden (TMB) (3). However, the most sensitive plasma genotyping platforms still have a sensitivity of only 70%-80%, such that a negative result requires tissue biopsy confirmation.
Name: Molecular analysis of surnatant
Description: to investigate the sensitivity of sfDNA genotyping in various clinical settings and to compare it to cell block
Measure: main aim of the study Time: 18 monthsDescription: To assess the feasibility of TMB estimation on this specimen
Measure: TMB estimation Time: 18 monthsDescription: To compare the sensitivity of plasma genotyping to cell block
Measure: sensitivity of plasma Time: 18 monthsDescription: To investigate the concordance between plasma and supernatant for mutation detection and TMB estimation
Measure: concordance between plasma and supernatant Time: 18 monthsDescription: To calculate the rate of patients with at least one additional mutation detected on supernatant compared to cell block
Measure: mutation rate Time: 18 monthsDescription: To compare the sensitivity of supernatant and plasma to cell block for the detection of specific alterations (EGFR, HER2, BRAF, PIK3CA, KRAS, MET mutations, ALK, ROS1, NTRK, RET fusions)
Measure: Sensitivity of supernatant and plasma Time: 18 monthsDescription: To compare the turnaround time of supernatant, plasma and cell block for genotyping
Measure: Turnaround time of supernatant Time: 18 monthsCohort
There is one SNP
Genotyping of plasma cfDNA is now routine for detection of EGFR driver mutations at diagnosis of NSCLC, or for detection of the EGFR T790M mutation after TKI resistance, and is an emerging approach for the detection of other drivers (HER2 or BRAF mutations, ALK or ROS1 fusions…) (2) or the estimation of tumor mutation burden (TMB) (3). --- T790M ---