COT-8 DEVELOPMENT OF TARGETED GENE PANEL FOR RAPID MOLECULAR DIAGNOSIS OF BRAIN TUMORS

Autor: Takuma Nakashima, Yusuke Funakoshi, Atsuhito Uneda, Shohei Nambu, Mai Kitahara, Shunsuke Yanagisawa, Makoto Ohno, Masamichi Takahashi, Yasuji Miyakita, Yoshitaka Narita, Hiromichi Suzuki
Rok vydání: 2022
Předmět:
Zdroj: Neuro-Oncology Advances. 4:iii25-iii25
ISSN: 2632-2498
DOI: 10.1093/noajnl/vdac167.098
Popis: Background Brain tumors are diagnosed based on pathological and genetic features defined by WHO classification. Although targeted gene panels are clinically available, most of them do not cover all the necessary genes for the diagnosis of brain tumors. Moreover, broad copy number analysis, which the current WHO classification requires, usually lacks in the gene panel. Another problem is that those panels demand a high burden of time and cost, which disturbs rapid diagnosis and broad application. To overcome those problems, we developed a rapid and cost-effective workflow of molecular diagnosis for brain tumors. Methods Our panel contains 109 genes of which 68 are necessary for fundamental molecular diagnosis and 41 are other common driver genes. To detect copy number changes and structural variants, which generate a fused gene, additional probes are placed on common SNPs and introns containing common breakpoints. MGMT methylation status is examined at the same time using bisulfite-converted DNA amplification. Sequencing data is analyzed using a supercomputer. Results The analysis time is within 4 days: 2 days for library preparation, 1 day for sequencing, and 12 hours for analysis. Detected driver alterations were validated by whole genome sequencing data. MGMT methylation status was correlated between the results of our workflow and pyrosequencing. Conclusions We have developed a rapid comprehensive molecular analysis workflow that detects genetic alterations and MGMT methylation. Our method allows a cost-effective molecular diagnosis with high accuracy, which would improve molecular diagnosis for brain tumors.
Databáze: OpenAIRE