Xenonucleic acid technology in high-sensitivity IDH1/2 mutation detection for glioma molecular profiling.

Abstract

e14052 Background: Glioma is a life-threatening primary brain tumor that poses significant challenges for diagnosis and treatment. Certain genetic features, such as the IDH1/2 mutation status (codon 132 of IDH1 and codon 172 of IDH2), can help distinguish between different types of gliomas. IDH1/2 wild-type and mutant gliomas have different prognoses and treatment options, with patients with IDH1/2 mutations typically having a better prognosis and a better response to chemotherapy. However, current available molecular tests for IDH1/2 mutation detection have limited sensitivity, and their application to circulating cell-free DNA has not been well established. Methods: To address these challenges, we have developed a new technology that uses xenonucleic acids (XNA) to achieve high sensitivity and specificity for detecting IDH1/2 mutations. We designed and synthesized a specific XNA probe to block PCR amplification from the IDH1 wild-type allele so that the IDH1 mutant allele can be enriched by Taqman real-time PCR. Results: Our tests showed that the XNA-mediated Taqman Real-time PCR system could efficiently detect IDH1-R132H mutations at a frequency as low as 0.1% (e.g., 7 IDH1-R132H copies out of 7,425 IDH1 copies) in both synthetic DNA fragments and genomic DNA from glioma stem cell lines. Clinical verification and validation studies are ongoing using tissue biopsies and paired plasma circulating cell-free DNA (cfDNA). The results of these studies will further demonstrate the reliability and accuracy of our XNA-based detection technology and its potential impact on patient outcomes. Conclusions: Our innovative technology holds the potential to significantly enhance the diagnosis of gliomas and other cancers. It offers a cost-effective, readily available, and precise diagnostic solution that can be performed by standard pathology personnel using equipment already available in hospital pathology laboratories. We will showcase the innovative capabilities of our XNA-based detection technology and its potential to improve the diagnosis and management of gliomas.