Subependymal giant cell astrocytomas are characterized by mTORC1 hyperactivation, a very low somatic mutation rate, and a unique gene expression profile.

Subependymal giant-cell astrocytomas (SEGAs) are slow-growing brain tumors that are a hallmark feature seen in 5-10% of patients with Tuberous Sclerosis Complex (TSC). Though histologically benign, they can cause serious neurologic symptoms, leading to death if untreated. SEGAs consistently show biallelic loss of TSC1 or TSC2. Herein, we aimed to define other somatic events beyond TSC1/TSC2 loss and identify potential transcriptional drivers that contribute to SEGA formation. Paired tumor-normal whole-exome sequencing was performed on 21 resected SEGAs from 20 TSC patients. Pathogenic variants in TSC1/TSC2 were identified in 19/21 (90%) SEGAs. Copy neutral loss of heterozygosity (size range: 2.2-46 Mb) was seen in 76% (16/21) of SEGAs (44% chr9q and 56% chr16p). An average of 1.4 other somatic variants (range 0-7) per tumor were identified, unlikely of pathogenic significance. Whole transcriptome RNA-sequencing analyses revealed 190 common differentially expressed genes in SEGA (n = 16, 13 from a prior study) in pairwise comparison to each of: low grade diffuse gliomas (n = 530) and glioblastoma (n = 171) from The Cancer Genome Atlas (TCGA) consortium, ganglioglioma (n = 10), TSC cortical tubers (n = 15), and multiple normal tissues. Among these, homeobox transcription factors (TFs) HMX3, HMX2, VAX1, SIX3; and TFs IRF6 and EOMES were all expressed >12-fold higher in SEGAs (FDR/q-value < 0.05). Immunohistochemistry supported the specificity of IRF6, VAX1, SIX3 for SEGAs in comparison to other tumor entities and normal brain. We conclude that SEGAs have an extremely low somatic mutation rate, suggesting that TSC1/TSC2 loss is sufficient to drive tumor growth. The unique and highly expressed SEGA-specific TFs likely reflect the neuroepithelial cell of origin, and may also contribute to the transcriptional and epigenetic state that enables SEGA growth following two-hit loss of TSC1 or TSC2 and mTORC1 activation.

Quantification of aneuploidy in targeted sequencing data using ASCETS.

SUMMARY: The expansion of targeted panel sequencing efforts has created opportunities for large-scale genomic analysis, but tools for copy-number quantification on panel data are lacking. We introduce ASCETS, a method for the efficient quantitation of arm and chromosome-level copy-number changes from targeted sequencing data. AVAILABILITY AND IMPLEMENTATION: ASCETS is implemented in R and is freely available to non-commercial users on GitHub: https://github.com/beroukhim-lab/ascets, along with detailed documentation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.