IDH1 and IDH2 somatic mutations have been identified in solid tumors and blood malignancies. The development of inhibitors of mutant IDH1 and IDH2 in the past few years has prompted the development ...of a fast and sensitive assay to detect IDH1R132, IDH2R140 and IDH2R172 mutations to identify patients eligible for these targeted therapies. This study aimed to compare two new multiplexed PCR assays – an automated quantitative PCR (qPCR) on the PGX platform and a droplet digital PCR (ddPCR) with next‐generation sequencing (NGS) for IDH1/2 mutation detection. These assays were evaluated on 102 DNA extracted from patient peripheral blood, bone marrow and formalin‐fixed paraffin‐embedded tissue samples with mutation allelic frequency ranging from 0.6% to 45.6%. The ddPCR assay had better analytical performances than the PGX assay with 100% specificity, 100% sensitivity and a detection limit down to 0.5% on IDH1R132, IDH2R140 and IDH2R172 codons, and a high correlation with NGS results. Therefore, the new highly multiplexed ddPCR is a fast and cost‐effective assay that meets most clinical needs to identify and follow cancer patients in the era of anti‐IDH1/2‐targeted therapies.
This study presents the first evaluation of two new highly multiplexed PCR assays as compared with next‐generation sequencing (NGS): an automated qPCR on the PGX platform and an allele‐specific droplet digital PCR (ddPCR) assay, both designed to detect most IDH1 and IDH2 hotspot mutations. The ddPCR assay was the best assay in terms of sensitivity, specificity, robustness, cost and timeliness, regardless of patient sample processing. It is, therefore, an appealing alternative to NGS to screen patients eligible for IDH1/2 targeted therapies.
Several fusion genes such as BCR::ABL1, FIP1L1::PDGFRA, and PML::RARA are now efficiently targeted by specific therapies in patients with leukemia. Although these therapies have significantly ...improved patient outcomes, leukemia relapse and progression remain clinical concerns. Most myeloid next-generation sequencing (NGS) panels do not detect or quantify these fusions. It therefore remains difficult to decipher the clonal architecture and dynamics of myeloid malignancy patients, although these factors can affect clinical decisions and provide pathophysiologic insights. An asymmetric capture sequencing strategy (aCAP-Seq) and a bioinformatics algorithm (HmnFusion) were developed to detect and quantify MBCR::ABL1, μBCR::ABL1, PML::RARA, and FIP1L1::PDGFRA fusion genes in an NGS panel targeting 41 genes. One-hundred nineteen DNA samples derived from 106 patients were analyzed by conventional methods at diagnosis or on follow-up and were sequenced with this NGS myeloid panel. The specificity and sensitivity of fusion detection by aCAP-Seq were 100% and 98.1%, respectively, with a limit of detection estimated at 0.1%. Fusion quantifications were linear from 0.1% to 50%. Breakpoint locations and sequences identified by NGS were concordant with results obtained by Sanger sequencing. Finally, this new sensitive and cost-efficient NGS method allowed integrated analysis of resistant chronic myeloid leukemia patients and thus will be of interest to elucidate the mutational landscape and clonal architecture of myeloid malignancies driven by these fusion genes at diagnosis, relapse, or progression.
