Ida, Cristine

Abstract Sequencing efforts have identified key oncogenic drivers and transcriptomic subtypes of high-grade gliomas (HGGs), but this knowledge has not resulted in individualized therapy or improved patient outcomes. Here, we used a functional genomics approach combining integrated genomic/transcriptomic analyses with patient-derived 3D micro-cancers (mCancers) to rapidly identify individualized therapeutic vulnerabilities and determine predictive response biomarkers. 30 primary/recurrent HGGs, including 20 glioblastomas, 5 astrocytomas, and 5 oligodendrogliomas, were included for drug testing. mCancers recapitulated the structural and molecular alterations, cellularity, and heterogeneity, of parental patient tumors. A total of 119 single-agent drugs and 183 drug combinations were tested, while a pre-selected drug panel comprising 25 glioma-relevant treatment strategies was tested across all cases. In general, mCancer efficacy corresponded well to historical responses to previously tested agents (EGFR, HDAC inhibitors, etc.). Combined, strong efficacy (i.e. >70% growth inhibition at Cmax) of single treatments targeting deregulated receptor tyrosine kinase (RTK), p53/apoptosis, cell cycle, DNA damage repair, IDH, or telomere maintainance pathways, was observed in 14 out of 30 cases. Surprisingly, transcriptional signatures, but not specific genetic alterations, were found to stratify drug responses. For example, mCancers enriched for the most aggressive mesenchymal (MES) and glycolytic/plurimetabolic (GPM) transcriptional subtypes exhibited stronger response to the BET inhibitor JQ1 (and other clinical BET inhibitors) and the DNA-PKcs/mTOR dual inhibitor CC-115. This therapeutic vulnerability was associated with enrichment of YAP/TAZ signaling, and the glioblastoma stem cell G-STEM signature. Notably, individual combination strategies were effective across tumors, with strong responses ranging from 38% to 77% of all tumors tested. Overall, this study underscores the value of functional genomics in identifying novel vulnerabilities of HGGs and associated response biomarkers. It also highlights the need for further clinical validation of several novel therapies and especially drug combination strategies with strong efficacy in the ex vivo setting.

Abstract Glioblastoma (GBM), IDH-wildtype (WT) is currently defined as an IDH-WT and H3-WT diffuse astrocytic glioma with molecular diagnostic features including whole +7/−10, TERT promoter (TERTp) mutation, and EGFR amplification and/or morphological diagnostic features such as necrosis and microvascular proliferation. To further understand the diversity of copy number signatures of GBM, IDHWT and evaluate the diagnostic utility of other recurrent copy number changes, we analyzed paired chromosomal microarray and next-generation sequencing mutational profiling data from 418 adult IDH-WT and H3-WT tumors with GBM morphological diagnostic features. The most common molecular features were TERTp mutations (85%), CDKN2A/B heterozygous/homozygous deletion (78%/66%), +7/-10 (63%), EGFR amplification (41%), +19 (36%), PTEN mutations (35%), partial -13 (33%), partial -14 (33%), +20 (32%), TP53 mutations (32%), and partial -22 (29%). At least one molecular diagnostic biomarker was present in 92% (n=385) of cases, and 29% (n=121) of cases had all three. The +7/-10 biomarker was the most frequent chromosomes 7/10 copy number change (68%, n=265). Other +7/-10 patterns were seen in 30% (n=125) of cases and included isolated +7 or -10, combinations of +7 and -10 with partial +7, partial -10 or 10 copy neutral loss of heterozygosity (cnLOH). Overall, 93% (390/418) of cases had whole and other chromosome 7/10 copy number changes. In comparison to tumors with +7/-10, tumors with other +7/-10 patterns were significantly enriched for partial 13 loss (Bonferroni adjusted p=0.04) but were not associated with significant difference in patient overall survival (p=0.30, 158/418 had available survival data). Our findings reiterate and expand the spectrum of copy number changes associated with GBM, IDH-WT. The similar overall survival rates between cases with the +7/-10 biomarker and those with other +7/-10 patterns suggest that other +7/-10 patterns may be functionally equivalent to +7/-10 and diagnostically relevant as a molecular diagnostic biomarker for this tumor type.

Abstract INTRODUCTION Prior to 2021, (classic) glioblastoma (GBM) required absence of IDH mutation and histologic features of hypercellularity, nuclear atypia, microvascular proliferation (MVP), and necrosis. Absence of histologic features can be a result of undersampling, with molecular, radiologic, and clinical features consistent with GBM. Accordingly, WHO 2021 defined molecular glioblastoma as diffuse glioma IDHwt, H3wt, with one or more of MVP, necrosis, TERT promoter mutation, EGFR gene amplification (EGFRamp), and/or +7/−10. We hypothesized that there is clinical and radiographic heterogeneity among tumors defined as molecular GBM. METHODS We identified 121 patients that met the criteria for molecular GBM. 121 Classic GBM, defined as IDHwt with hypercellularity, MVP or necrosis, were matched to molecular GBM cases by age, sex, and diagnosis date. All cases were reviewed for relevant histologic features and molecular features. Examined clinical variables included: first symptom, time from first symptom to date of pathological diagnosis, date of first MRI, tumor location, radiographic features of enhancement, diffusion or mass effect, time to progression and overall survival. Clinical, radiologic, and molecular features were compared between classic and molecular GBM. RESULTS Currently,160 cases have been reviewed. Preliminary results show that there is a longer time from first symptom to diagnosis for molecular GBM. Molecular GBM is significantly more likely to be discovered coincidentally, and without enhancement or radiographic necrosis. Classic GBM is significantly more likely to present with focal neurologic deficit as first symptom, regional mass effect on index imaging and have monosomy 10. CONCLUSION While pathologic undersampling accounts for a significant proportion of molecular GBM, our data suggest that there are significant clinical, radiographic, and outcome differences between classical and molecular GBM. Final analysis of the entire cohort will help better define this clinical spectrum.

Abstract There have been several attempts to predict the MGMT promoter methylation status of gliomas using deep learning (DL), with mixed results. These studies did not account for IDH mutation status and did not utilize a uniform methylation assay, introducing potential confounders in the experimental design. We assessed the performance of DL applied to brain MRI to predict the MGMT promoter methylation status of IDH-wildtype gliomas tested with a standardized assay. We included 539 IDH-wildtype gliomas tested with real-time methylation-specific PCR from 2017-2022; 205 (38%) were MGMT promoter methylated. The assay targets 8 downstream MGMT CpG sites using ACTB as control; methylation status is determined based on the difference of PCR crossing-point values: methylated if difference < 5, unmethylated if difference > 7, indeterminate otherwise. We used post-contrast T1 and T2 MRIs as inputs for our models trained using stratified 5-fold cross-validation, 400 epochs, batch size of 16, a learning rate scheduler starting at 10-3, weighted binary cross-entropy loss, and AdamW optimizer. We repeated the experiments using two 3D DL architectures (DenseNet121 and EfficientNetB0) and two image preprocessing pipelines: the BraTS protocol and one that uses padding instead of registration to an MRI atlas, keeping constant other experimental variables. For Densenet121, the best cross-validation AUROCC and F1-score (median, median absolute deviation) were 0.67 (0.06), 0.59 (0.02) using the BraTS protocol, and 0.67 (0.06), 0.58 (0.01) using padding. For EfficientNetB0, were 0.67 (0.02), 0.66 (0.01) using the BraTS protocol and 0.67 (0.01), 0.68 (0.01) using padding. Our findings suggest that it is unlikely that DL models trained on brain MRI can predict the MGMT promoter methylation of IDH-wildtype gliomas. Importantly, our study is the first to focus on an IDH-wildtype adult diffuse glioma cohort tested with a single, standardized MGMT methylation assay, eliminating the variability introduced by different assays and IDH status.

Abstract BACKGROUND The diagnosis and management of patients with brain tumors currently uses WHO defined morphologic and molecular features. However, neuro-oncology practice in low resource settings relies on histomorphology. This study aims to reclassify glioma cases diagnosed in the Department of Anatomic and Molecular Pathology Lagos University Teaching Hospital using the 2021 WHO classification. METHODS Fifty-six cases of glioma diagnosed between 2013 to 2021 were evaluated. Morphologic diagnosis was reassessed. Five-micron sections were obtained for immunohistochemistry (IHC), and genetic testing (DNA and RNA); after manual macrodissection for tumor enrichment using 10μm sections. IHC for IDH1-R132H, ATRX, BRAFV600E, P53,Ki67, and H3K27M and OncoScan chromosomal microarray analysis were performed. NGS mutation/fusion analysis and EPIC methylation array profiling are in progress. RESULTS Of 56 cases evaluated, median age was 22 years (range=1-60 years); 71% were males. The initial morphologic diagnosis include 21 pilocytic astrocytoma, 11 glioblastoma, 9 ependymoma, 7 diffuse astrocytoma, 3 anaplastic astrocytoma, 2 high-grade gliomas, 1 oligodendroglioma, 1 diffuse midline glioma, and 1 pleomorphic xanthoastrocytoma (PXA). Histomorphologic re-evaluation revealed discordant diagnosis in 29% (16/56) of cases. Of the 56 cases, 73% (41/56) had usable DNA yield and 38% (21/56) had DNA yield of ≥ 750ng. Chromosomal microarray analysis was completed for 50% (28/56) cases. The revised 2021 WHO diagnosis were: 5 glioblastoma, IDH-wildtype, 5 pilocytic astrocytoma, 4 glioma NEC, 3 posterior fossa ependymoma, group B, 3 PXAs, 3 astrocytoma, IDH-mutant, 2 pediatric low-grade glioma, 2 supratentorial ependymoma, ZFTA fusion-positive, 1 posterior fossa ependymoma, group A. In 71% (20/28) of cases, diagnosis was revised using the 2021 WHO criteria. CONCLUSION Most cases had usable DNA yield. Overall, hsitologic re-evaluation and molecular testing based on the 2021 WHO classification guidelines refined the diagnosis in 48% (27/56) of cases.