Citations

Abstract Glioblastoma (GBM), isocitrate dehydrogenase wild-type (IDHwt) and central nervous system diffuse large B-cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. Deep learning on T1 postcontrast and T2-weighted MRI sequences were used to differentiate GBM and CNS-DLBCL. A three-stage temporal study design was utilized. Model development was performed on 146 patients with CNS-DLBCL and 146 age-matched, sex-matched, and MRI year–matched patients with GBM diagnosed at Mayo Clinic between 1998 and 2019. Models were tested on independent temporal test cohorts. Initial testing included 240 independent GBM diagnosed at Mayo Clinic between 1998 and 2019. The prospective test cohort included 37 patients with CNS-DLBCL and 256 patients with GBM diagnosed at Mayo Clinic after January 1, 2020, and 36 patients with CNS-DLBCL diagnosed at an external institution. Of the patients diagnosed at Mayo Clinic, 47% had MRIs generated from non-Mayo institutions. Two different model approaches were compared: (i) ensemble approach using area under the receiver operating characteristic curve (AUC) and cross-validation for model selection and (ii) loss approach minimizing cross-entropy loss and cross-validation to evaluate prediction performance. The AUCs on the prospective test cohort were 0.84 [95% confidence interval (CI), 0.78–0.90] and 0.83 (95% CI, 0.77–0.88) for the ensemble and loss approaches, respectively. Stability of ensemble prediction improved with the increasing number of models. Stratified AUC analysis demonstrated consistent performance across sex and age. We utilized a robust temporal study design and applied 2 different analytic approaches to develop a classification model. The findings confirm the feasibility of using MRI-based deep learning models to differentiate GBM from CNS-DLBCL. Significance: GBM, IDHwt and CNS-DLBCL are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Noninvasive tools are needed to aid in differential diagnosis. We developed MRI-based deep learning models to differentiate GBM, IDHwt from CNS-DLBCL using a rigorous three-stage temporal design that included prospective validation. The model AUC on a prospective cohort was 0.84.

Abstract Background Isocitrate dehydrogenase (IDH)-mutant gliomas are infiltrative tumors with limited treatment options at recurrence. Early studies suggest IDH inhibition has therapeutic activity. We evaluated clinical outcomes associated with IDH-1 inhibitor ivosidenib in recurrent IDH-1-mutant gliomas and molecular predictors of response. Methods We retrospectively analyzed adults treated with ivosidenib from January 2021 to August 2025 with predominantly recurrent, pretreated CNS WHO grade 2-4 astrocytoma IDH-mutant or grade 2-3 oligodendroglioma, IDH-mutant and 1p/19q codeleted. Prior anticancer treatments, toxicities, enhancement status at ivosidenib initiation, and genomic alterations were collected. The primary endpoint was progression-free survival (PFS); secondary analyses evaluated associations between PFS, genomic complexity, and CDKN2A/B homozygous deletion. Results Ninety-two adults, median age 43, were included: 61 astrocytomas and 31 oligodendrogliomas, mostly grade 2. Before ivosidenib, 69 had surgery, 64 chemotherapy, and 64 radiation. Median time from diagnosis to ivosidenib was 4.8 years, with median of two prior progressions. Median treatment duration was 5.8 months. Median PFS was 15.2, 4.6, and 2.1 months for astrocytoma grades 2-4, 14.0 and 6.9 months for oligodendroglioma grades 2-3. Increasing genomic complexity was associated with shorter PFS in univariate analysis. Patients without CDKN2A/B homozygous deletion had median PFS of 19.2 months. Two patients with homozygous deletion had median PFS of 0.6 months. Conclusions In this retrospective analysis of predominantly recurrent IDH-1-mutant glioma, ivosidenib was associated with longer PFS in lower-grade, non-enhancing tumors that received little or no prior anticancer treatment and less complex genomic profiles. These findings support a context-dependent benefit of IDH inhibition in recurrent disease.

ABSTRACT IDH-mutant astrocytomas maintain telomeres through the alternative lengthening of telomeres (ALT) pathway, producing extreme inter-arm telomere length heterogeneity, yet how this heterogeneity shapes structural genome evolution remains unknown. Using Oxford Nanopore long-read sequencing of 20 IDH-mutant astrocytomas, we profiled structural variants (SVs), copy number variants, extrachromosomal DNA (ecDNA) and measured allele-specific telomere lengths from individual long reads. We identified pervasive complex rearrangements, including chromothripsis and foldback events consistent with breakage-fusion-bridge cycles, and widespread ecDNAs. SV breakpoints were enriched at telomeric and centromeric regions regardless of local telomere length, revealing constitutive structural fragility. Arm-level telomere length analysis uncovered a dual-mode model: arms with short telomeres preferentially harbored breakage-associated events, while arms with long ALT-maintained telomeres were enriched for ecDNA and amplification-associated events. These findings identify chromosome-arm-specific telomere length as a determinant of structural genome evolution in ALT-driven tumors.

Abstract Background: Alternative lengthening of telomeres (ALT) is common in isocitrate dehydrogenase (IDH) mutant astrocytomas, but how telomere length variability contributes to genome instability remains unclear. We hypothesized that chromosome arm–specific telomere heterogeneity underlies distinct patterns of somatic structural variation (SV), copy-number alteration (CNA), and extrachromosomal DNA (ecDNA) formation. Methods: Oxford Nanopore long-read whole-genome sequencing (∼20–40x coverage) was performed in a clinical cohort of n = 20 IDH-mutant astrocytomas. Somatic SVs were called with Severus and filtered to a high-confidence tumor-specific set. CNAs were inferred by read-depth segmentation (DNAcopy) and further refined using a long-read CNA framework (Wakhan). Chromosome arm–specific telomere length was estimated with Telogator, and SV breakpoints were annotated for enrichment near subtelomeric and pericentromeric regions. Associations between arm-level telomere length and SV/CNA features (rate and proportion) were tested using linear mixed-effects models with patient as a random effect. High-level amplification regions were defined directly from CNA segments with high copy number, and ecDNA-like circular amplicons were subsequently reconstructed from amplified intervals using Decoil. Results: IDH-mutant astrocytomas displayed pronounced SV heterogeneity, with complex breakends (BNDs) dominating the somatic SV landscape. SVs were spatially patterned, as deletions and insertions preferentially accumulated near subtelomeric and pericentromeric domains, implicating chromosome ends and repeat-rich regions as recurrent substrates for rearrangement. At the tumor level, markedly shortened telomeres were associated with increased SV burden and CNA burden, consistent with telomere attrition as a correlate of genome-wide structural instability in highly rearranged genomes. At higher resolution, telomere length varied substantially across chromosome arms and classified distinct structural outcomes: arms with shorter telomeres were enriched for complex insertional SVs, whereas arms with relatively elongated telomeres more frequently carried focal high-level amplifications and ecDNA-like circular amplicons. Conclusions: These findings reveal a link between arm-specific telomere heterogeneity and the emergence of structural and amplification architectures in IDH-mutant astrocytomas. Telomere remodeling may influence where rearrangements and ecDNA structures arise, offering potential biomarkers of genome instability and tumor evolution. Generative AI was used to improve language clarity; all content was verified by the authors. Citation Format: Maryam Jehangir, Kristen Drucker, T. Rhyker Ranallo-Benavidez, Thomas M. Kollmeyer, Ayse Keskus, Daniel Lachance, Jeanette E. Eckel-Passow, Ofer Shoshani, Mikhail Kolmogorov, Robert B. Jenkins, Floris P. Barthel. Telomere length heterogeneity shapes structural and amplification landscapes in IDH-mutant astrocytoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr PR009.

Abstract Diffuse hemispheric glioma, H3 G34‐mutant (DHG‐H3 G34) has been primarily molecularly characterized by methylation profiling and sequencing studies. We describe an integrated histomolecular evaluation including high‐resolution copy number profiling of a series of 60 DHG‐H3 G34 to further our understanding of the spectrum of genetic changes associated with this tumor type. Cases were clinically tested using an 187‐gene mutation and fusion targeted neuro‐oncology next‐generation sequencing panel ( n = 60) and Oncoscan chromosomal microarray ( n = 26) by a single laboratory (2018–2022). A subset of cases had immunohistochemical results for OLIG2 ( n = 42), p53 ( n = 48), and ATRX ( n = 46), and methylation array data ( n = 8). Median age at testing was 21 years (range, 12–50). No significant difference was noted in clinical, histopathological, and mutational profile between pediatric and adult patients. H3‐3A G34 mutations included G34R ( n = 56; 94%), G34V ( n = 3), and a non‐canonical G34E ( n = 1). Concurrent mutations most often involved TP53 ( n = 55; 92%), ATRX ( n = 50; 83%), and PDGFRA ( n = 34; 57%). A reportedly primary tumor was confirmed to be hypermutant and had a PMS2 mutation. A single case also showed an FGFR3::FAM184B fusion. All cases with available chromosomal microarray data had unbalanced genomes, which were often complex (14/26; 54%). The most frequent recurrent copy number abnormalities were losses involving 3q, 4q, 10q, 13q, and 18q, and 17p copy‐neutral loss of heterozygosity (cnLOH) encompassing TP53 . This copy number profile was reminiscent of that seen in Grade 4 IDH‐mutant astrocytomas. Collectively, a TP53 abnormality at copy number (12/26, all cnLOH), sequence (55/60) and protein expression (46/48) level was detected in all 60 cases. In conclusion, integrated high‐resolution copy number and histomolecular analysis expanded the spectrum of genetic changes associated with DHG‐H3 G34, including the presence of universal TP53 abnormalities with frequent cnLOH—a copy number abnormality that has been largely unrecognized—for this new 2021 World Health Organization central nervous system tumor type.

Abstract In adult-type diffuse gliomas CDKN2A and/or CDKN2B (CDKN2A/B) deletions often co-occur with deletion of MTAP, suggesting that MTAP immunohistochemistry (IHC) may be a surrogate marker of CDKN2A/B status. However, the association between CDKN2A/B and MTAP deletion at the genomic level remains unknown. We assessed CDKN2A/B and MTAP deletions by chromosomal microarray in 333 adult-type diffuse gliomas and performed MTAP IHC on a subset (n = 63). CDKN2A/B and MTAP deletions were detected in 216 and 215 cases, respectively, and were concurrent in 99.5% (215/216). While most tumors with CDKN2A/B homozygous deletion (n = 148) showed concurrent MTAP homozygous deletion (108/148; 73.0%), a subset harbored MTAP heterozygous deletion (39/148; 26.4%). By analyzing the size of the chromosomal alterations, we demonstrate that initial large chromosomal 9p losses result in concurrent heterozygous deletion of CDKN2A/B and MTAP whereas smaller “second hit” deletions leading to homozygous CDKN2A/B deletion do not always encompass the MTAP locus. Discordant CDKN2A/B and MTAP tumors affect the association between MTAP IHC and copy number status of MTAP and CDKN2A/B. These findings suggest that adult-type diffuse gliomas, regardless of IDH status, follow a stereotypic pathway involving concurrent CDKN2A/B and MTAP heterozygous deletion but may diverge for CDKN2A/B and MTAP homozygous deletion.

Abstract Background Current literature suggestsisocitrate dehydrogenase (IDH)-mutant astrocytoma contains several molecular subgroups. In this study, we are interested in determining the connection between different molecular subgroups with grade and/or survival. Methods A cohort of 470 Mayo Clinic adult patients (≥18 years, 56.2% male) with primary IDH-mutant astrocytoma diagnosed by World Health Organization (WHO) 2021 criteria were examined. Results were validated in an independent cohort of 614 Mayo Clinic Neuropathology consult patients and 235 The Cancer Genome Atlas (TCGA) patients. Results The Mayo Clinic Practice cohort confirmed the association of CDKN2A/B deletion with overall survival (OS, homozygous vs hemizygous vs intact, 2.7 vs 9.6 vs 17.2 years, P < .001). Phosphatase and tensin homolog (PTEN) deletion was also associated with poor OS (7.3 vs 17.4 years, P < .001). Increased number of copy number alterations was associated with OS (continuous variable, HR = 1.027, P < .001). Carrying one or more copies of the germline risk allele at rs55705857 was associated with earlier age of onset (median age 33 vs 35 years, P = .01), and a shorter OS after adjusting for age, grade, sex and treatment (HR = 1.81, P = .007). The Mayo Clinic Neuropathology Consult cohort and TCGA were utilized to validate age of onset and survival, respectively. Unsupervised clustering of the copy number alterations identified several clinically significant groups that may define pathways to disease progression. Losses of chromosomes 11p, 13q, 1p, and 10q were all associated with reduced overall survival in the Mayo Clinic cohort. Conclusions Patients with hemizygous loss of CDKN2A/B, loss of PTEN, increased number of copy number alterations, specific chromosomal arm losses or rs55705857 germline risk allele have reduced overall survival.

Abstract Background Glioblastoma IDH-wildtype (GBM) may be diagnosed histologically (hGBM) or based on molecular features when microvascular proliferation and histologic necrosis are absent (mGBM). Clinical and radiographic distinction between hGBM and mGBM remains unclear. Methods 101 hGBM cases were matched to 109 mGBM cases by age, sex, year of diagnosis, and TERT promoter mutation (TERTp) status. Clinical outcome, radiographic, and molecular features were compared across mGBM and hGBM. Results Median time from first MRI to diagnosis was longer for mGBM versus hGBM (34 vs 7 days, p < .001). mGBM more often presented with seizures (51% vs 26%, p < .001), gliomatosis pattern (12% vs 2%, p = .005), basal ganglia involvement (17% vs 0%, p < .001). Contrast enhancement appeared on MRI for 98% (96/98) of hGBM and 50% (54/107) of mGBM (p < .001). mGBM with non-enhancing MRI were rarely multifocal (2% vs 30%, p < .001). mGBM harbored fewer total copy number alterations (median 20 vs 16.5, p = .029), less often had EGFRamp (34% vs 48%, p = .051), isolated chromosome 10 loss (84% vs 96%, p = .013), and CDKN2A/B homozygous deletion (56% vs 77%, p = .005). Median overall survival was longer for mGBM (2.16 vs 1.44 years, p < .001), and for mGBM without MRI contrast enhancement versus hGBM with enhancement (3.11 vs 1.62 years, adjusted p = .003). mGBM without +7/−10 or without CDKN2A/B homozygous deletion had longer survival and time-to-progression versus hGBM with these alterations. Conclusion mGBM with MRI enhancement may represent undersampled or early/evolving hGBM. mGBM that are non-enhancing, present with seizures, prolonged time to diagnosis, absent CDKN2A/B alteration or +7/−10 may represent other IDH-wildtype entities.

Abstract Glioblastoma, IDH-wildtype (GBM), and primary central nervous system lymphoma (PCNSL) are two aggressive brain tumors with distinct treatment strategies but overlapping imaging features on MRI. Accurate preoperative differentiation remains a clinical challenge, due to their overlapping imaging features, even when advanced MRI techniques are employed. This study explored deep learning approaches leveraging multi-sequence MRI to distinguish GBM from PCNSL. Models were developed utilizing 146 PCNSL cases, which were matched to146 GBM by age, sex and year of diagnosis. A 3D-DenseNet121 convolutional neural network was trained using two analytical strategies: (i) loss-based model selection and (ii) ensemble prediction using five-fold cross-validation. Model performance was evaluated on an independent validation set of 256 GBM and 37 PCNSL from the same institution as well as 36 PCNSL cases from an external institution. All MRIs were preprocessed using the FeTS pipeline. Using the independent validation cohort, area under the receiver operating characteristic curve (AUC) and 95% confidence intervals (CI) were computed overall and stratified by demographic characteristics. Using both T1 post-contrast (T1Gd) and T2-weighted images, the loss-based model achieved AUC=0.83 (95% CI: 0.77-0.88) and the ensemble model yielded an AUC=0.82 (95% CI: 0.76-0.89). Model performance was similar across males and females; however, model performance was better for subjects older than 50 years of age versus younger than 50. When using only T1Gd images, the loss-based model dropped to AUC=0.55 (95% CI: 0.48-0.63), whereas the ensemble model had AUC=0.79 (95% CI: 0.72-0.85). Models trained with only T2 images achieved AUCs of 0.67 (95% CI: 0.60-0.73) (loss-based) and 0.75 (95% CI: 0.69-0.82) (ensemble). These results highlight the added value of the multi-sequence input. Our results confirm the feasibility of using automated deep learning models to differentiate GBM from PCNSL. Notably, the model generalized well to external MRI data, emphasizing its potential utility as a diagnostic aid in real-world clinical workflows.