Fusion Gene Detection and Quantification by Asymmetric Capture Sequencing (aCAP-Seq).

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.

Investigation of Kingella kingae Invasive Infection Outbreaks in Day Care Facilities: Assessment of a Rapid Genotyping Tool Targeting the DNA Uptake Sequence.

Outbreaks of Kingella kingae invasive infections have recently been reported in day care centers. Pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) revealed that although the invasive strains had widespread dissemination in the day care population, less virulent strains were also circulating in the facilities. However, these typing tools are costly, time-consuming, and labor-intensive and provide delayed results. A study was conducted to assess the performance of a rapid and cost-effective genotyping tool targeting the DNA uptake sequence (DUS) in the investigation of outbreaks of K. kingae disease. DUS typing (DUST) patterns of each strain from 7 different clusters were compared to distinguish genotypically linked strains from others. PFGE and, when available, MLST results were used as gold standards. DUST was assessed on 80 K. kingae isolates from Nir-Itzhak (n = 14), Tel-Nof (n = 14), Palmahim (n = 5), Umm-al-Fahm (n = 7), Eilat (n = 8), Nevatim (n = 15) in Israel and Paris, France (n = 17). A unique DUST pattern was involved in the Nir-Itzhak, Palmahim, Umm-al-Fahm, and Paris episodes. Two DUST patterns were found in Eilat, whereas at least 3 were identified in the Tel-Nof and Nevatim episodes. In total, 11 (13.8%) children carried a K. kingae isolate that differed from the outbreak strain. These results were concordant with those obtained with the traditional PFGE and MLST methods. DUST appears to be sensitive and specific in distinguishing the invasive outbreak strain from others in asymptomatic carriers and could be useful to limit unnecessary exposure of the entire day care population to selective antibiotic pressure.