PATH-19. TERT PROMOTER MUTATION, NOT H3K27M MUTATION IS A PROGNOSTIC FACTOR FOR ADULT THALAMIC GLIOMAS

Purpose Thalamic diffuse glioma is classified as WHO grade 4 as Diffuse midline glioma, H3K27M mutation if H3K27M mutation was found regardless of its histological findings, but the significance of H3K27M mutation is not clear compared with pediatric cases. We aimed to find genetic prognostic factors in adult thalamic diffuse gliomas. METHODS Pathological diagnosis, genetic abnormalities, and clinical course of adult newly diagnosed thalamic gliomas diagnosed and treated at our institution from July 2007 to March 2020 were retrospectively analyzed. RESULTS The number of cases was 41 (24 males, 17 females), median age was 47 years (20-75 years). Tumor localization was 20 cases on the left, 14 cases on the right, and 7 cases on both sides. The pathological diagnosis was GBM 15 cases, DMG 15 cases, AA-IDH WT 7 cases, DA-IDH WT 4 cases, all of which were IDH wild type, and none of them had IDH mutation and 1p/19q co-deletion. H3K27M mutations were found in 15 cases and TERT promoter mutations were found in 12 cases, both of which were completely mutually exclusive. Tumor resection and biopsy was performed in 33 and 8 cases, respectively, and the median removal rate was 95% for those who underwent tumor resection. The median PFS and OS of all cases were 14.3 months and 38 months, respectively, and the median OS by pathological diagnosis was GBM 12.4 months, DMG 47.4 months, AA-IDH WT 37.3 months, DA-IDH WT not reached. The median OS in the H3K27M mutant group (47.4 months) was significantly better (p=0.02) than that in the TERT promoter mutation group (13.5 months). CONCLUSION There was no IDH mutation in adult thalamic gliomas, the H3K27M mutation and the TERT promoter mutation were mutually exclusive. The H3K27M mutation was not a prognostic factor, but the TERT promoter mutation was the strongest prognostic factor.

PATH-36. INTRATUMOR HETEROGENEITY AND BIOINFORMATIC DIFFERENCES INFLUENCE MENINGIOMA MOLECULAR CLASSIFICATION

Molecular alterations such as CDKN2A inactivation and TERT promoter mutation are new criteria for grade 3 meningiomas in the 5th edition of the WHO Classification of Tumors of the Central Nervous System. However, consensus approaches to identify copy number variants (CNVs) and short somatic variants in meningiomas are lacking. Here, we performed integrated DNA methylation profiling, RNA-sequencing, and targeted DNA mutational profiling on 10 stereotactically-collected, regionally-distinct samples from 4 meningiomas. Targeted DNA sequencing revealed numerous private short somatic variants from multiple sites within individual meningiomas, including a TERT promoter mutation in only 1 of 2 samples from the same tumor. DNA methylation profiling revealed differences in biologic groups and immune cell enrichment between regionally-distinct samples within individual meningiomas. CNV status was evaluated using DNA methylation profiling and RNA sequencing on 14 stereotactically-collected, regionally-distinct samples from 2 meningiomas. Phylogenetic architectures from DNA methylation profiling and targeted DNA sequencing were highly concordant and shared 99.12% of CNVs while RNA sequencing identified only 39% of the CNVs called from DNA based approaches. Finally, CNV analysis based on single-cell RNA sequencing revealed partially overlapping CNVs across meningioma cells within an individual tumor, suggesting subclonal populations may influence CNV-based meningioma molecular classification and underlie limitations in defining CNVs from bulk RNA-sequencing. In sum, these data highlight the relative strengths and weaknesses of various approaches for molecular analysis of meningiomas complicated by intratumor heterogeneity due to non-tumor cells and subclonal populations of meningioma cells. Future efforts to incorporate molecular analysis into the diagnostic paradigm for meningiomas may require orthogonal validation across multiple platforms or image-guided meningioma sampling to select the most aggressive regions for molecular profiling.

RBIO-03. INITIAL RESULT OF DEVELOP ROBUST DEEP LEARNING MODEL FOR DETECTING GENOMIC STATUS IN GLIOMAS AGAINST IMAGE DIFFERENCES AMONG FACILITIES

BACKGROUND The importance of detecting the genomic status of gliomas is increasingly recognized and IDH (isocitrate dehydrogenase) mutation and TERT (telomerase reverse transcriptase) promoter mutation have a significant impact on treatment decisions. Noninvasive prediction of these genomic statuses in gliomas is a challenging problem; however, a deep learning model using magnetic resonance imaging (MRI) can be a solution. The image differences among facilities causing performance degradation, called domain shift, have also been reported in other tasks such as brain tumor segmentation. We investigated whether a deep learning model could predict the gene status, and if so, to what extent it would be affected by domain shift. METHOD We used the Multimodal Brain Tumor Segmentation Challenge (BraTS) data and the Japanese cohort (JC) dataset consisted of brain tumor images collected from 544 patients in 10 facilities in Japan. We focused on IDH mutation and TERT promoter mutation. The deep learning models to predict the statuses of these genes were trained by the BraTS dataset or the training portion of the JC dataset, and the test portion of the JC dataset evaluated the accuracy of the models. RESULTS The IDH mutation predicting model trained by the BraTS dataset showed 80.0% accuracy for the validation portion of the BraTS dataset; however, only 67.3% for the test portion of the JC dataset. The TERT promoter mutation predicting model trained by the training portion of the JC dataset showed only 49% accuracy for the test portion of the JC dataset. CONCLUSION IDH mutation can be predicted by deep learning models using MRI, but the performance degeneration by domain shift was significant. On the other hand, TERT promoter mutation could not be predicted accurately enough by current deep learning techniques. In both mutations, further studies are needed.

PATH-28. RE-DEFINING CLONALITY OF THE TERT PROMOTER MUTATION WITH DEEP SEQUENCING AND MAXIMAL SAMPLING OF NEWLY DIAGNOSED AND RECURRENT GBM AND OLIGODENDROGLIOMA

TERT promoter mutation (TPM), found in over 80% of IDH-wildtype glioblastomas (GBMs) and oligodendrogliomas, leads to reactivation of telomerase and consequently tumor cell immortalization, which is potentially reversible. TERT could therefore serve as an effective target in treating tumors with TPM, if TPM is present throughout the tumor. Previous studies using a single sample or minimal sampling per tumor have shown potentially conflicting results, suggesting TPM is clonal in some cases and subclonal in others. Here we use spatially mapped tumor samples representing maximal tumor sampling to address this critical issue. Sanger sequencing was performed on 311 newly diagnosed and recurrent tumor samples from 19 IDH-wildtype GBMs and 10 oligodendrogliomas. To validate Sanger sequencing and resolve potentially ambiguous samples, deep amplicon sequencing was performed on 164 samples. To determine tumor purity and TERT expression levels, whole exome sequencing (164 samples) and RNA-Seq (129 samples) data sets were analyzed computationally. Sanger and amplicon sequencing showed that TPM was present in 305 of 311 samples (98.1%). TPM was not detected in 6 samples which had tumor purity estimates too low to be accurately determined by FACETS and lacked evidence of any driver mutation. Variant allele frequencies (VAFs) of TPM showed high positive correlation with those of clonal alterations in GBMs (r(90) = .93, p < .0001) and oligodendrogliomas (r(48) = .96, p < .0001). TPM VAFs also showed high positive correlation with tumor purity in both GBMs (r(112) = .92, p < .0001) and oligodendrogliomas (r(48) = .89, p < .0001). TPM VAF showed a moderate positive correlation with TERT expression in GBMs (r(78) = .40, p < .001) and oligodendrogliomas (r(47) = .49, p < .001). Therefore, TPM is a tumor-wide, clonal mutation in both newly diagnosed and recurrent GBMs and oligodendrogliomas. TPM VAF is moderately correlated with TERT expression.