Understanding the differences in adolescent and young adult (AYA) gliomas and older adult (OA) gliomas based on functional molecular subgroups

Authors:

Catherine Bi, Ashwin Subramaniam, Joanne Xiu, Amy Heimberger, Sharon Michelhaugh, Sandeep Mittal, Ashley Sumrall, Deepa Subramaniam

BACKGROUND

Gliomas in the AYA population (15–39 years of age) have unique biological characteristics and need to be better characterized.

METHODS

Glioma tumors in AYA subjects and subjects >65 years of age (OA) were analyzed by next generation sequencing using a 592 gene panel. Pathogenic mutations were classified into five functional groups, viz. metabolic pathways genes (IDH1/2, FH), tumor suppressor genes (TP53, RB1, APC, NF1/2, PTEN, TSC1/2), genes involved in DNA repair (MMR genes, BRCA1/2, POLE, ARID1A, CHEK2, ATM, BLM, BRIP1, WRN, BARD1, POT1, MUTYH), oncogenes (BRAF, NRAS, HRAS, EGFR, PDGFRA, FGFR1, NOTCH1, MYCN), and genes involved in transcriptional regulation (SETD2, H3F3A, KMTD2A/2C/2D, KDM6A, PIK3CA). Mutation frequency in AYA tumors and OA tumors were compared using Chi-squared analysis (Pearson’s score χ2; likelihood ratio LR).

RESULTS

720 unique gliomas tumors were analyzed: 118 AYA, 602 OA; 420 males, 300 females. When both groups are considered together, glioblastoma was the most common histology (75%), followed by grade 3 astrocytoma (13%), glioma NOS (3.8%), oligodendrogliomas (3%), low grade gliomas (2.9%) and other (2.3%). AYA tumors harbored more metabolic pathway gene mutations (χ2 137.7, p< 0.0001) driven primarily by IDH1 mutations, while OA tumors had a higher mutation frequency in oncogenes (χ2 9.22, p=0.0024) driven by EGFR mutations (LR 27.567) and tumor suppressor genes (χ2 40.35, p< 0.0001) driven by NF1 (LR 18.147) and PTEN (LR 66.216). No significant differences were noted in mutation frequency in DNA repair or transcriptional regulation genes. However, AYA glioblastoma tumors had a significant increase in mutations in genes involved in chromatin remodeling, (χ2 11.43, p=0.0007) even after excluding H3F3A.

CONCLUSIONS

Functional genomic classification of AYA tumors may help develop better targeted therapies, especially focused on genes involved in metabolic pathways and transcriptional regulation.

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