Abstract 383P
Background
Glioma is a common type of brain tumour with a poor prognosis, and its median survival is fewer than 15 months. Accurate molecular profiling may improve outcomes by providing tailored treatments. There are different types of glioma biomarkers, such as point mutations, promoter methylation, and large-scale copy-number variation, which are usually measured by different platforms. To fulfil the clinical requirement of molecular classification of gliomas, we designed an economical and fast assay which can detect biomarkers of multiple types simultaneously, and validated the assay technically and clinically.
Methods
Our assay is based on a mass spectrometry (MS) platform which detects mutations in IDH1-R132, IDH2-R172, TERT-C228T/C250T, H3F3A/HIST1H3B-K27M, and BRAF-V600E, along with MGMT promoter methylation, and chromosomal 1p/19q co-deletion. For technical validation, 60 samples were tested and the results were compared with standard results from NGS/qPCR, FISH, and pyrosequencing. For clinical validation, 1398 real-world samples were curated to evaluate the utility of the assay by assessing the concordance between clinical diagnosis and molecular classification results.
Results
The MS-based assay was validated by the high concordance (greater than 95%) with standard methods. With similar accuracy, the assay takes only half the turnaround time and cost of NGS. Of 1398 cases diagnosed as glioma, our assay correctly subtyped 612 of 646 glioblastomas and 275 of 287 oligodendrogliomas, clinically validated with 95% concordance. 89 cases of 1p/19q co-deletions, 241 positive cases of MGMT promoter methylation, one case of K27M mutation, 19 cases of V600E mutation were detected from 612 consistent glioblastoma samples. Among 34 misclassified glioblastoma samples, 7 cases were detected as co-occurrence of wild-type TERT and IDH mutations, which were suspected as secondary glioblastomas, according to the 2016 WHO classification criteria.
Conclusions
A MS-based assay for molecular profiling of gliomas was designed and validated on more than a thousand real-world clinical samples. The assay is time- and cost-effective, as well as highly accordant with other standard methods and clinical diagnosis.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.