Nassiri, Farshad

Abstract Background Meningiomas exhibit clinical heterogeneity. Radiotherapy (RT) remains the only adjuvant therapy, but tumor-control is variable, and biomarkers are limited. NRG/RTOG-0539 is the first prospective phase 2 trial to stratify meningioma patients for adjuvant RT based on clinical risk. Here, we apply modern molecular tools to this cohort and identify correlates of RT response. Methods Tumor tissue from 100 RTOG-0539 patients was profiled using DNA methylation arrays, RNA sequencing, and whole-exome sequencing. Recurrence scores, Molecular Groups, gene expression, and copy number alterations were compared across clinical groups and between RT responders and non-responders; non-response was defined as progression or death within 3 years. Results Modern grading criteria, including brain invasion, TERT mutation, CDKN2A/B deletion, and 1p/1q status, would reclassify 10% of tumors and alter treatment group assignment in 7%. Non-responders to RT exhibited more frequent 1p and 14q loss, and more copy number alterations. Transcriptomic and epigenetic profiling revealed immune-related signatures in responders and cell cycle–related pathways in non-responders, several of which overlapped with targets of vorinostat, a histone deacetylase inhibitor previously validated in aggressive meningioma models. The Proliferative Molecular Group was an independent predictor of post-RT recurrence in multivariable analysis, outperforming WHO grade. Conclusion Multi-omic analysis of the NRG/RTOG-0539 cohort shows that updated WHO grading criteria, incorporating molecular and cytogenetic features, improve risk stratification. However, molecular classification, particularly the Proliferative group, remains an independent and stronger predictor of RT response. These findings support integrating molecular biomarkers alongside modern grading frameworks to guide treatment and trial design in meningioma. Clinical Trial Information NCT00895622.

The classification and management of central nervous system (CNS) tumours have undergone substantial transformation over the past two decades, with the recognition of an expanding set of molecularly defined disease entities. Genome-wide DNA methylation profiling has emerged as an important complement to histopathology and targeted molecular testing, providing an epigenetic framework that captures tumour lineage, biological state and large-scale genomic alterations within a single assay. Accumulating evidence demonstrates that methylation-based approaches improve diagnostic precision, resolve biologically heterogeneous entities and support clinically meaningful risk stratification across a broad spectrum of CNS tumours. Methylation profiling has also increasingly been applied to outcome prediction, liquid biopsy-based analyses and the resolution of diagnostically challenging or misclassified cases. In addition, advances in multi-omic integration, computational inference from routinely acquired clinical data and evolving implementation frameworks are extending the clinical applicability of epigenetic profiling. This review synthesises the current state of DNA methylation profiling within the diagnostic and clinical framework of CNS tumours and considers how emerging technologies and practice models are shaping its ongoing integration into neuro-oncological care.

Abstract Purpose: Glioblastoma (GBM) is the most common and aggressive primary malignant brain tumor, with a median survival of only 15 months. Effective therapeutic advances remain limited, with few clinical trial patients exhibiting robust responses to experimental therapies. This has led to efforts to identify molecular biomarker signatures capable of stratifying patient responses either prognostically (pre-treatment) or diagnostically (post-treatment). This study aims to assess the robustness and reproducibility of published transcriptional GBM biomarker signatures for predicting clinical outcomes in GBM trials. Methods: We analyzed published RNA-seq data from 4 clinical trials involving oncolytic virotherapy and immune checkpoint inhibitors, as well as multiple cohorts of patients treated via the Stupp protocol. The performance of reported immune gene signatures was evaluated across all datasets using both grouped and continuous survival modeling. Intra-patient signature variation between different biopsy sites and timepoints was assessed using longitudinal, multi-site sampling collected by the Break Through Cancer Accelerating GBM Therapies TeamLab. LASSO, multivariate Cox regression, and risk scoring with FDR adjustment were used to identify novel signatures with cross-cohort utility. Key Findings: No single published signature consistently predicted survival across all analyzed trials. A post-treatment ssGSEA antitumor cytokine signature that was associated with survival in the CAN-3110 OV trial (R = 0.74, p < 0.01) was also significantly associated with improved survival in an adjuvant anti-PD1 trial (R = 0.75, p = 0.03) and neoadjuvant anti-PD1 trial (R = 0.30, p = 0.05), but not in standard-of-care controls. PAM clustering of MCP immune signatures, as reported for the DNX-2401 OV+Anti-PD1 trial, also stratified post-treatment survival in the CAN-3110 OV trial (p < 0.01), with the coldest TME subtype consistently predicting worse survival. However, the prognostic value of the most immune enriched TME subtype was inconsistent and did not extend to the Anti-PD1 trials. Furthermore, multi-site, longitudinal biopsy samples revealed marked heterogeneity in biomarker signatures between biopsies from individual patients, even when assessed at the same timepoint. We’ve identified several candidate transcriptomic signatures that show promise for generalizable prognostic value in GBM patient cohorts and are characterizing their spatiotemporal variability. Conclusions: While no individual immune signature is universally predictive in GBM immunotherapy, certain post-treatment cytokine signatures and TME stratifications are significant in multiple immunotherapy contexts, though not in standard-of-care patient cohorts. Marked spatiotemporal heterogeneity in these signatures underscores the need for composite prognostic markers resilient to sampling variance. Citation Format: Christopher M. Jannotta, C Zoe Linke, Charles A. Whittaker, Vikas Patil, Accelerating GBM Therapies TeamLab, Farshad Nassiri, Gelareh Zadeh, E Antonio Chiocca, Alexander L. Ling. Assessing biomarker reproducibility for glioblastoma patient response stratification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1055.

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 Recurrent or refractory IDH-mutant (mt) gliomas represent a population with significant unmet clinical need. The Notch ligand delta-like 3 (DLL3) is a tumor-associated antigen that is highly and homogeneously expressed in IDH-mt gliomas but absent in normal brain tissue, making it an attractive therapeutic target. Tarlatamab is a half-life extended bispecific T-cell engager that targets DLL3 and CD3 to redirect cytotoxic T cells toward DLL3-expressing tumor cells. Given the specific expression of DLL3 in IDH-mt gliomas and promising activity of tarlatamab in other DLL3-positive tumors, this study investigates the safety, efficacy, and intracranial activity of tarlatamab in this patient population. TARGID is an open-label, phase II trial enrolling adult patients with histologically confirmed IDH1 or IDH2-mt astrocytoma or oligodendroglioma following up to two prior lines of systemic therapies. The study comprises two cohorts. Cohort 1 (n=10) includes patients with resectable disease who will receive up to three cycles of tarlatamab prior to surgery; postoperative continuation is permitted. The primary endpoint for this cohort is the change in CD8+ T-cell infiltration in tumor tissue and blood. Cohort 2 (n=34) includes patients with unresectable disease and uses a Simon’s optimal two-stage design (H0: P ≤ 0.1 versus H1: P ≥ 0.25). In the 1st stage, 13 patients will be accrued. If 2 or more responses are observed, 21 additional patients will be enrolled. Tarlatamab is administered intravenously at 10 mg every two weeks, following a 1 mg priming dose on Cycle 1 Day 1. The primary endpoint is objective response rate by RANO 2.0. Exploratory endpoints include DLL3 expression, circulating biomarkers, and immune correlatives. The trial is currently in activation, with first patient enrollment anticipated in Q3 2025. The study is supported by the provision of study drug from Amgen as an investigator-initiated trial.