Galanis, Evanthia

PURPOSE Integrating external control data into clinical trial designs and analyses has the potential to accelerate drug development processes. We reanalyzed the three experimental arms of the Individual Screening Trial of Innovative Glioblastoma Therapy (INSIGhT), a randomized phase II platform trial in newly diagnosed O 6 -methylguanine-DNA methyltransferase-unmethylated glioblastoma (ClinicalTrials.gov identifier: NCT02977780 ). To evaluate the validity of using external data sets, we compared treatment effect estimates based on internal INSIGhT control data and matched external control data. METHODS The three experimental arms of INSIGhT (abemaciclib [n = 72], neratinib [n = 80], and CC-115 [n = 12]) did not improve survival compared with internal controls (standard chemoradiation [n = 70]). We derived external control patient-level data from multiple real-world and clinical trial data sets. We applied propensity score matching and Cox proportional hazards models to estimate treatment effects with external controls. Additionally, using this glioblastoma (GBM) data collection, we specified simulation scenarios to evaluate trial designs that integrate external controls. RESULTS After matching to external controls, no survival benefit was observed for patients receiving abemaciclib (hazard ratio [HR], 1.00 [95% CI, 0.75 to 1.34]), neratinib (HR, 0.93 [95% CI, 0.70 to 1.24]), or CC-115 (HR, 0.88 [95% CI, 0.41 to 1.88]). Simulations, together with the INSIGhT data and a collection of GBM data sets, allowed us to examine efficiencies and risks of clinical trial designs that leverage external control data. CONCLUSION The use of carefully matched external controls, to replace or augment the internal controls of INSIGhT, produced treatment effect estimates that were similar to previously published analyses. Single-arm trial designs and hybrid randomized designs incorporating propensity score–matched external control data evaluated treatment effects in the early-phase testing of experimental therapies in newly diagnosed GBM. The validity of this approach and risks of bias depended on the availability of comprehensive and accurate data on all potential confounders, in the absence of unmeasured confounding.

PURPOSE GBM AGILE (ClinicalTrials.gov identifier: NCT03970447 ) is a phase II/III Bayesian adaptive platform registration trial testing multiple arms against a common control; the primary end point is overall survival (OS). Regorafenib, a multikinase inhibitor, showed OS benefit in recurrent (RD) glioblastoma in the phase II REGOMA trial and entered GBM AGILE as the first investigational arm. METHODS Patient subtypes included in the regorafenib arm of GBM AGILE were newly diagnosed unmethylated (NDU) and RD glioblastoma. Prospective defined sets of subtypes, or arm signatures, were NDU, RD, and all (NDU + RD). As the first investigational arm in GBM AGILE, regorafenib was equally randomized to the control arm. Treatment in the control arm is temozolomide + radiotherapy (in newly diagnosed) or lomustine (in RD). Efficacy was assessed by OS hazard ratio (HR), arm/control, and demonstrated when the Bayesian probability of benefit (HR <1.00) was ≥98%. Analysis was performed monthly for limited efficacy, which occurs when the Bayesian predictive power is <25% for all signatures, and determines stopping enrollment. Follow-up continued for 12 months after accrual stopped. RESULTS When the predictive power was <25% in all predefined signatures for regorafenib, accrual stopped for limited efficacy. The final analysis did not demonstrate OS improvement in the regorafenib arm in RD nor NDU glioblastoma. Median HRs were 1.05 (NDU), 1.07 (RD), and 1.07 (all) with final probabilities of benefit (HR <1.00) of 0.421 (NDU), 0.312 (RD), and 0.296 (all). Regorafenib was associated with increased toxicity relative to control. CONCLUSION GBM AGILE did not show superiority of regorafenib over control in RD (lomustine) or NDU (temozolomide + radiotherapy) glioblastoma, yet caused increased toxicities. Regorafenib has been removed from National Comprehensive Cancer Network guidelines as a treatment option for RD.

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 &lt; .001). mGBM more often presented with seizures (51% vs 26%, p &lt; .001), gliomatosis pattern (12% vs 2%, p = .005), basal ganglia involvement (17% vs 0%, p &lt; .001). Contrast enhancement appeared on MRI for 98% (96/98) of hGBM and 50% (54/107) of mGBM (p &lt; .001). mGBM with non-enhancing MRI were rarely multifocal (2% vs 30%, p &lt; .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 &lt; .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 Background DNA methylation profiling can be used to robustly predict postsurgical outcomes and response to radiotherapy (RT) for meningioma patients. To allow for seamless integration of these complementary models into clinical practice, a practical framework is needed. Methods We leveraged a cohort of nearly 2000 surgically-treated meningiomas with DNA methylation profiling and clinical outcomes data. Existing methylation-based prediction models were dichotomized to yield four risk groups: low and high recurrent risk, each with RT sensitive and resistant subgroups. Risk groups were correlated with progression-free survival in the context of existing biomarkers including extent of resection and WHO grade. Results We first demonstrated that all risk groups benefit from gross total resection. All “high-risk, RT sensitive” tumors (n = 306, 15.7%) also benefited from adjuvant RT: after GTR, median PFS increased from 4.68 (4.13-9.48) years to not reached (P = .003); after subtotal resection (STR), from 2.12 (1.59-3.02) to 4.09 (3.41-not reached) years (P = .004). “Low-risk, RT sensitive cases” (n = 1207, 61.8%) also benefited from RT after STR (median PFS 7.39 (6.66-12.8) vs. 16.53 (10.35-not reached) years, P = .03), suggesting that RT be considered in these patients. Neither “low-risk RT resistant” (n = 84, 4.3%) nor “high-risk RT resistant” (n = 356, 18.2%) cases benefited from RT, and the latter group was associated with universally poor outcomes. Conclusions We identify methylation-defined risk groups of meningioma for which additional benefit is gained from adjuvant RT, leading to a clinical decision-making framework for straightforward integration of molecular models into clinical practice.

Abstract BACKGROUND Poly(ADP-ribose) polymerase inhibitors (PARPi), initially developed for BRCA-mutant tumors, are now being explored in gliomas to target DNA repair defects. In this retrospective analysis, we report our institutional experience using PARPi with temozolomide for glioma treatment. METHODS The medical record was retrospectively reviewed at our institution for neuro-oncology patients treated with off-label PARPi combined with temozolomide for &gt; 1 month between 1/1/2010 and 5/1/2025. RESULTS Nineteen patients (median age 45, 47% female) were included. PARPi included olaparib (n = 18) and niraparib (n = 1). Tumor types were glioblastoma (GBM, n = 7), Grade 4 IDH-mutant astrocytoma (G4A, n = 4), Grade 3 astrocytoma (G3A, n = 2), Grade 3 oligodendroglioma (G3O, n = 3), Grade 2 oligodendroglioma (G2O, n = 2), and IDH1-mutant brainstem glioma (BG, n = 1; IDH status determined per CSF 2-hydroxyglutarate without surgically confirmed histologic subtyping). Patients were heavily pre-treated. One patient lost to follow-up was censored at last contact. Patients had KPS ≥ 70 in all but one case (KPS 60) and multiple prior progressions (treatment was initiated at 4th recurrence or higher in 16/19 patients). Median time from drug initiation to progression, drug initiation to death, and overall survival were as follows (months): GBM (3.0, 6.5, 34.9), G4A (1.4, 3.9, 80.3), G3A (3.4, 4.2, 83.3), G3O (3.8, 17.2, 121.2), G2O (3.0, 3.5, 159.9), BG (4, 5.5, 164.8). CONCLUSIONS This retrospective analysis supports the tolerability of combining PARPi with temozolomide in a real-world, heavily pretreated glioma population. Despite limited evidence of durable tumor control, the regimen provided transient disease stability in patients with few remaining options. These findings may inform treatment in compassionate or salvage settings particularly when alkylator treatment is considered, and highlight the need for prospective trials to identify response biomarkers and assess clinical utility.

Abstract BACKGROUND The IDH inhibitor vorasidenib was FDA-approved for treatment of IDH-mutant grade 2 gliomas in August 2024. We evaluated vorasidenib in patients with grade 3 and 4 IDH-mutant gliomas who would not have been eligible for the INDIGO trial. METHODS Retrospective review of patients with grade 3 or 4 IDH-mutant gliomas treated with vorasidenib between 9/1/24 and 5/31/25. Prior treatments, radiographic response, adverse events and seizure control were collected for each patient. RESULTS Thirty-two patients (median age 39.5, 46.9% female) met inclusion criteria. Tumor types included grade 3 oligodendroglioma (11, 34.4%), grade 3 astrocytoma (13, 40.6%) and grade 4 astrocytoma (8, 25%). Thirty patients had contrast-enhancement; 2 patients had non-enhancing tumor. Prior treatments included surgical resection (30, 93.8%), radiation (27, 84.4%), cytotoxic chemotherapy (25, 78.1%), bevacizumab (5, 15.6%), pembrolizumab (3, 9.4%), and ivosidenib (8, 25%). Four patients (12.5%) were naïve to systemic treatment at the time of vorasidenib initiation. Median duration of vorasidenib was 101.5 days (range 18-255) with 19 patients still on vorasidenib at the time of last follow-up. Seventeen patients (53.1%) had stable disease, 11 (34.4%) had progressive disease, 2 (6.3%) did not yet have response assessment, and 2 (6.3%) died. Grade 1 transaminitis occurred in 12 patients with no high grade transaminitis. Two patients developed lymphopenia; both were heavily pre-treated with multiple alkylating agents; no other hematologic toxicity was noted. One patient developed myalgias leading to vorasidenib discontinuation. Nine patients had fatigue, 4 headaches, 2 nausea, 2 decreased appetite. In patients with a history of epilepsy, there were no reported seizures. CONCLUSIONS Vorasidenib was well-tolerated in this heavily pre-treated cohort of grade 3–4 IDH-mutant gliomas, with low-grade transaminitis and fatigue being the most common toxicities. Preliminary results show disease stability in 53.1% of patients after a median of 3.5 months. Conclusions are limited by short-interval follow-up.

Abstract Glioblastoma (GBM) diagnosis integrates morphology and tumor molecular alterations. Patients with classic morphology are designated as histologic GBM (hGBM). Patients without classic morphology harboring TERT promoter mutation (TERTp), or epidermal growth factor receptor amplification (EGFRamp), or combined gain of chromosome 7 and loss of 10 (+7/-10) designate molecular GBM (mGBM). We compared radiographic features, genomic alterations, and clinical outcome between hGBM and mGBM. 109 mGBM Mayo Clinic cases diagnosed between 1993-2021 were matched to 101 cGBM by age, sex, year of diagnosis, and TERT promoter (TERTp) status. Clinical and radiographic data abstraction was blinded. Progression-free and overall survival were compared across groups in the subset of patients who received standard of care. Contrast enhancement was present on index MRI (MRI at diagnosis) for 98% (96/98) hGBM and 50% (54/107) mGBM (p&lt;0.0001) patients. mGBM tumors harbored fewer total copy number alterations (median of 16.5 vs 20, p=0.029) and were less likely to have CDKN2A/B homozygous deletion (56% vs 77%, p=0.005). Among the 87 mGBM and 82 hGBM receiving standard of care, median overall survival was longer for mGBM versus hGBM (2.24 vs 1.62 years, p=0.016). mGBM patients with +7/-10 (HR=2.60, p=0.035) or CDKN2A/B (HR=3.61, p=0.002) had poorer overall survival compared to mGBM patients without the corresponding alteration. On index MRI mGBM patients without contrast enhancement had better overall survival compared to hGBM (HR=0.50; p=0.003) whereas there was no survival difference between mGBM with enhancement and hGBM. mGBM with enhancement on index MRI likely represent undersampled, or early / evolving hGBM. mGBM patients with non-enhancing MRI, younger than 60, with long symptom profile including seizures, and some combination of non-anaplastic morphology, TERTp only, no homozygous deletion of CDKN2A/B, and low copy number complexity may represent other IDHwt glioma entities. Caution is advised in counseling, management, discussing prognosis, and inclusion in clinical trials.

Abstract The 2021 WHO classification redefined glioblastoma IDH-wildtype (GBM), integrating histopathological and tumor molecular features. Diffuse astrocytic glioma lacking histologic features of necrosis and microvascular proliferation are classified as (molecular) GBM if the tumor is IDH- and H3-wildtype and has one or more additional tumor molecular alterations: TERT promoter mutation, EGFR amplification, or +7/-10. Due to the absence of histopathological features of classic GBM and presentation without enhancement on MRI in approximately 50% of cases, molecular GBM frequently resemble low-grade IDH-mutant gliomas. We hypothesized that MRI-based deep learning models could distinguish IDH-mutant glioma from molecular GBM. We retrospectively identified 97 individuals with molecular GBM, who were matched to 97 individuals with IDH-mutant glioma by age, sex, year of diagnosis, and enhancement on MRI. Of the 97 IDH-mutant gliomas, 51% were 1p/19q codeleted, 42% grade 2, 47% grade 3, and 10% grade 4. Preoperative postcontrast T1-weighted (T1C) and T2-weighted (T2) MRI sequences were used to train a 3D-DenseNet121 model. The model was validated on an independent prospective set of 150 IDH-mutant gliomas and 71 molecular GBM. The MRI-based deep learning model achieved an area under the receiver operator curve (AUC) of 0.75 (95% CI: 0.68-0.82) in the prospective validation set. Sex-stratified AUCs were 0.72 (95% CI: 0.59-0.85) for females and 0.76 (95% CI: 0.68-0.85) for males. Age stratified AUCs were 0.71 (95% CI: 0.60-0.83) for patients under 55 years of age and 0.64 (95% CI: 0.50-0.79) for patients older than 55. These results suggest that discriminative MRI features of IDH-mutant glioma and molecular GBM exist and can be identified from deep learning models. However, radiographic ambiguity exists and underscores the need for further optimization of the deep learning architecture or by integrating additional non-invasive modalities. For example, future work entails integrating germline variants into the model, including rs55705857, which is a causal variant for IDH-mutant glioma. With further validation and integration of multi-modal data, a noninvasive tool may support more personalized decision-making.

Abstract BACKGROUND The Response Assessment in Neuro-Oncology (RANO) was recently updated to RANO 2.0, which no longer requires follow-up imaging to confirm progression in recurrent glioma patients recieving immunotherapy, as previously recommended by iRANO. This study evaluates the utility of RANO 2.0 to determine whether radiographic progression on initial post-treatment MRI is sufficient to guide timely discontinuation of ineffective therapy. METHODS This retrospective study, conducted at Mayo Clinic, included patients ≥18 years receiving ≥2 cycles of off-label pembrolizumab for recurrent glioma between 1/1/2014 – 5/1/2025. Radiographic response was assessed using the first MRI performed ≥30 days after pembrolizumab initiation. Progression was defined as a ≥25% increase in the product of perpendicular diameters of the lesion, clear progression of non-measurable disease, new lesion appearance, clinical deterioration, or death. For suspected pseudo-progression, sequential MRIs were reviewed; if progression was confirmed, the original date was used. RESULTS Sixty-two patients were included (mean age: 46.1 years; 64.5% male), receiving pembrolizumab for a median duration of 2.8 (1.4 – 19.4) months. Median time to initial radiographic response assessment was 1.6 (1.1 – 3.5) months, and progression-free survival was 2.3 (0.7 – 15.2) months. Thirty-seven (59.7%) patients were identified with progression at initial evaluation. Among them, 11 were initially suspected of pseudo-progression, and continued pembrolizumab: 3 received additional radiation, 2 initiated bevacizumab, while 6 remained on their prior regimens [pembrolizumab only (3); pembrolizumab with bevacizumab (3)]. However, all were subsequently confirmed to have true progression, with a median delay of 1.4 (0.7 – 7.1) months until pembrolizumab discontinuation. No true pseudo-progression cases were observed. CONCLUSIONS Our findings support the clinical applicability of RANO 2.0 in recurrent glioma patients receiving pembrolizumab. Initial radiographic progression reliably predicted true progression, suggesting limited value in confirmatory follow-up imaging. Early recognition of treatment failure may reduce delays in initiating salvage therapies, along with associated toxicity and cost.