Background: Glioblastoma poses an inevitable threat to patients despite aggressive therapy regimes. It displays a great level of molecular heterogeneity and numerous substitutions in several genes have been documented. Next-generation sequencing techniques have identified various molecular signatures that have led to a better understanding of the molecular pathogenesis of glioblastoma. In this limited study, we sought to identify genetic variants in a small number of rare patients with aggressive glioblastoma. Methods: Five tumor tissue samples were isolated from four patients with rapidly growing glioblastoma. Genomic DNA was isolated and whole exome sequencing was used to study protein-coding regions. Generated FASTQ files were analyzed and variants were called for each sample. Variants were prioritized with different approaches and functional annotation was applied for the detrimental variants. Results: A total of 49,780 somatic variants were identified in the five glioblastoma samples studied, with the majority as missense substitutions. The top ten genes with the highest number of substitutions were MUC3A, MUC4, MUC6, OR4C5, PDE4DIP, AHNAK2, OR4C3, ZNF806, TTN, and RP1L1. Notably, variant prioritization after annotation indicated that the MTCH2 (Chr11: 47647265 A>G) gene sequence change was putative deleterious in all of the aggressive tumor samples. Conclusion: The MTCH2 (Chr11: 47647265 A>G) gene substitution was identified as putative deleterious in highly aggressive glioblastomas, which merits further investigation. Moreover, a high tumor mutation burden was observed, with a signature of the highest substitutions in MUC3A, MUC4, MUC6, OR4C5, PDE4DIP, AHNAK2, OR4C3, ZNF806, TTN, and RP1L1 genes. The findings provide critical, initial data for the further rational design of genetic screening and diagnostic approaches against aggressive glioblastoma.
CITATION STYLE
Khan, I., Işık, E. B., Mahfooz, S., Khan, A. M., & Hatiboglu, M. A. (2023). Identification of Genetic Alterations in Rapid Progressive Glioblastoma by Use of Whole Exome Sequencing. Diagnostics, 13(6). https://doi.org/10.3390/diagnostics13061017
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