We verified the analytical performance of the Abbott RealTime SARS-CoV-2 assay on the m2000 system and compared its clinical performance to the CDC 2019-nCoV Real-Time PCR Diagnostic Panel and the ThermoFisher TaqPath RT-PCR COVID-19 kit. We also performed a bridging study comparing the RealTime SARS-CoV-2 assay with the new Abbott Alinity m SARS-CoV-2 assay. A number of standards, reference materials, and commercially available controls were used for the analytical verification to confirm the limit of detection, linearity, and reproducibility. We used nasopharyngeal (NP) swab specimens collected in saline for the clinical verification and bridging studies. Overall, we found 91.2% positive percent agreement (PPA) (95% CI 76.2 to 98.14%) and a 100% negative percent agreement (NPA) (95% CI 97.97 to 100%) between the results of the RealTime SARS-CoV-2 and CDC tests with 217 NP specimens (P=0.13). We found a PPA of 100% (95% CI 90.26 to 100%) and a NPA of 95.15% (95% CI 83.47 to 99.4%) between the results of the RealTime and TaqPath tests with 77 NP specimens (P=0.24). Finally, we tested 203 NP swab specimens for SARS-CoV-2 on the m2000 on the Alinity m systems. The PPA and NPA were 92.2% (95% CI, 85.3 to 96.59%) and 92% (95% PI, 84.8 to 96.5%), respectively (P=0.4). Although cycle number (Cn) values obtained for the concordant positive samples were highly correlated (R2, 0.95), the Cn values were on average 14.14 higher on the Alinity m system due to the unread cycles with the RealTime SARS-CoV-2 assay.

Background Giant cell glioblastoma (gcGBM) is a rare histologic subtype of glioblastoma characterized by numerous bizarre multinucleate giant cells and increased reticulin deposition. Compared with conventional isocitrate dehydrogenase (IDH)-wildtype glioblastomas, gcGBMs typically occur in younger patients and are generally associated with an improved prognosis. Although prior studies of gcGBMs have shown enrichment of genetic events, such as TP53 alterations, no defining aberrations have been identified. The aim of this study was to evaluate the genomic profile of gcGBMs to facilitate more accurate diagnosis and prognostication for this entity. Methods Through a multi-institutional collaborative effort, we characterized 10 gcGBMs by chromosome studies, single nucleotide polymorphism microarray analysis, and targeted next-generation sequencing. These tumors were subsequently compared to the genomic and epigenomic profile of glioblastomas described in The Cancer Genome Atlas (TCGA) dataset. Results Our analysis identified a specific pattern of genome-wide massive loss of heterozygosity (LOH) driven by near haploidization in a subset of glioblastomas with giant cell histology. We compared the genomic signature of these tumors against that of all glioblastomas in the TCGA dataset (n=367) and confirmed that our cohort of gcGBMs demonstrated a significantly different genomic profile. Integrated genomic and histologic review of the TCGA cohort identified three additional gcGBMs with a near haploid genomic profile. Conclusions Massive LOH driven by haploidization represents a defining molecular hallmark of a subtype of gcGBM. This unusual mechanism of tumorigenesis provides a diagnostic genomic hallmark to evaluate in future cases, may explain reported differences in survival, and suggests new therapeutic vulnerabilities.

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