BIOS-03. COPY NUMBER VARIATION (CNV) AND CLINICAL OUTCOMES IN IDH-WILDTYPE VERSUS IDH-MUTANT GLIOMA

Abstract

Abstract Genomic classification of gliomas has the potential for improved prognostication and treatment guidance. However, much work remains to elucidate the full potential of genomics in glioma characterization. IDH mutant gliomas generally carry an improved survival compared to their wild-type counterparts, but their clinical course is significantly more variable and challenging to predict. The goal of this study is to characterize tumor genetic/genomic parameters associated with progression-free survival (PFS) and overall survival (OS) of both IDH-wildtype and IDH-mutant gliomas and compare the two subtypes for further stratification. We collected data for 203 patients diagnosed with IDH-wildtype gliomas (WHO Grade IV) and 88 patients with IDH-mutant gliomas (WHO Grade II-IV) from the Emory Healthcare system. Microarray single nucleotide polymorphism-copy number analysis was performed to detect total CNVs which are associated with tumor mutational burden. We analyzed total CNV based on the median, quartiles, and optimal cut points via the ideal cutpoint calculator, Cutoff Finder. We then estimated the correlation between % total CNV, PFS, and OS using the Pearson correlation coefficient. For IDH-wildtype gliomas, the mean CNV was 18.69 (standard deviation (SD): 9.62), and the median was 16.00 (IQR: 1-57). The optimal cutoff was defined as 39 for PFS analysis and 20.5 for OS analysis. For IDH-mutant gliomas, the mean CNV was 12.8 (SD: 11.36), and the median was 8.5 (IQR: 5 – 17.5). The optimal cutoff was defined as 10.5 for OS analysis and 7.5 for PFS analysis. Overall, higher CNV was associated with lower PFS and OS in both groups. However, the results were only statistically significant for OS at the optimal cutoff (20.5) for IDH-wildtype gliomas (p-value = 0.0379), and for PFS at the optimal cutoff (7.5) for IDH-mutant gliomas (p-value = 0.0420). These findings suggest that CNV may be useful as a potential prognosis factor for both tumor subtypes in different contexts.