Liu, Jeff

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.

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 Pediatric, adolescent and young adult patients (Ped/AYA; 0–39 years) with meningiomas are underrepresented in neuro-oncology research, despite meningiomas being the second most common primary brain tumor in this age group. While DNA methylation-based models have advanced classification and prognostication in adults, their utility in younger populations remains uncertain. To address this gap, we aimed to evaluate the performance of current DNA methylation-based classification and recurrence prediction models in Ped/AYA patients with meningiomas and identify age-associated molecular differences. As part of this study, we analyzed 1,568 meningioma samples with DNA methylation and clinical data, including subsets with whole-exome and RNA sequencing. Patients were grouped into Ped/AYA (≤39 years, n = 213) and adult (>39 years, n = 1,355) cohorts. We assessed classifier performance, performed subgroup-specific model retraining, and compared molecular profiles across age groups. Our results showed that molecular classification differed significantly between age groups, with Ped/AYA tumors less frequently belonging to the most aggressive Proliferative Molecular Group. The DNA methylation-based recurrence model performed well in adults (AUC = 0.83) but poorly in the Ped/AYA cohort (AUC = 0.57). However, retraining the model on only younger patients improved performance (AUC = 0.75). In addition, Ped/AYA tumors exhibited significantly fewer chromosomal alterations, including lower frequencies of 1p, 6q, and 14q loss (p<0.05). Taken together, these findings indicate that predominantly adult-trained methylation models underperform in younger meningioma patients due to both biological divergence and exclusion from training datasets. Our findings underscore the need for age-specific molecular tools to improve prognostication and support personalized care across the lifespan in neuro-oncology.

Abstract Brain metastases (BMs) are a common and often fatal progression of systemic cancers, affecting up to 25% of patients. Despite advances in surgical resection and radiotherapy, the median survival remains limited to 10–16 months. While genomic profiling has enabled the development of targeted therapies, there remains a paucity of prognostic tools for clinical use. To address this, we explored the utility of DNA methylation profiling—an epigenetic marker increasingly recognized for its diagnostic and prognostic value. We profiled fresh-frozen tissue from 327 surgically resected BM samples of lung, breast, melanoma, and gastrointestinal (GI) origin using the Illumina Infinium MethylationEPIC BeadChip array. Unsupervised analysis via partitioning around medoids (PAM) clustering identified five robust groups. Four of these correlated closely with primary tumor origin. However, a distinct “Poly-Origin Cluster” emerged, comprising tumors from multiple primary sites with a shared epigenetic signature. Poly-Origin tumors showed improved survival outcomes compared to origin-aligned clusters (20.2 vs. 10.1 months, p=0.0018), independent of clinical covariates. Notably, these tumors were enriched for immune cell infiltration—including CD14+ macrophages, CD19+ B-cells, and CD56+ NK cells—based on deconvolution analysis, and exhibited reduced genomic instability as measured by copy number variation. These tumors were enriched for pathways related to cell signaling. We validated the prognostic significance of the Poly-Origin methylation signature in a publicly available independent cohort (n=96), and found that high signature concordance correlated with extended survival. Finally, we demonstrated the feasibility of detecting this signature in plasma-derived cell-free DNA using cfMeDIP-seq, with high classification accuracy (AUC = 0.98). These findings reveal a clinically meaningful subtypes of BM not captured by tissue origin or mutation status alone. Our work suggests that DNA methylation profiling may be a powerful tissue- and liquid biopsy–based tool that holds promise as a non-invasive prognostic biomarker in the management of brain metastasis.

Abstract A major barrier in understanding adult diffuse gliomas lies in the inability to track tumor evolution in real time. To address this, we employed a novel method known as continuous lineage tracing, which integrates CRISPR/Cas9-based expressed DNA barcoding with single-cell RNA sequencing, enabling a phylogenetic approach to studying tumor development. Patient-derived glioma-initiating cell lines were engineered with expressed barcodes targeted by CRISPR/Cas9 and implanted into mice to create intracranial xenografts. Tumors underwent single-cell RNA sequencing; expressed barcodes were used to infer clonal relationships, and transcriptomic profiles enabled cell state classification. Phylogenetic lineage trees were reconstructed using lineage inference algorithms to characterize cell fitness, expansion, and plasticity. Our analysis uncovered extensive intra-clonal cell state heterogeneity, indicating active phenotype switching prior to therapy. We identified consistent transcriptional programs associated with tumor engraftment and in vivo clonal advantage. Lineage tracing revealed gene expression signatures linked to key phenotypes: fitness, enriched for neural-mesenchymal and injury-response pathways; expansion, associated with RNA splicing; and plasticity, correlated with cell cycle and DNA repair programs. Glioma stem cells appeared to span a transcriptional continuum from undifferentiated, high-fitness states to more differentiated, low-fitness states, with high-fitness cells potentially representing transitional phenotypes. We then validated these findings in a cohort of 185 surgically resected gliomas with matched bulk RNA and proteomic data. Phylogenetic gene signatures differed markedly between IDH-mutant and IDH-wildtype tumors. When stratified by tumor type, both fitness and expansion signatures were significantly associated with overall survival in GBM (median 12.6 months, p=0.041) and oligodendrogliomas (median 66 months, p=0.027). This study demonstrates the utility of continuous lineage tracing to reconstruct tumor evolution and identify transcriptional programs linked to tumor growth and prognosis. Our approach provides a powerful framework for dissecting glioma biology and identifying potential therapeutic vulnerabilities.

Abstract INTRODUCTION Recurrent IDH-mutant gliomas pose a significant therapeutic challenge, with limited treatment options following progression after standard therapy. Combining PARP inhibitors with immune checkpoint blockade has been proposed as a synergistic strategy in IDH-mutant high-grade gliomas, leveraging vulnerabilities in homologous recombination repair and increased PD-L1 expression following PARP inhibition. OBJECTIVE This phase II trial (NCT03991832) evaluated the combination of the PARP inhibitor olaparib and the PD-L1 inhibitor durvalumab in patients with recurrent IDH-mutant glioma. We also investigated the potential of the plasma tumor methylome as a non-invasive biomarker of treatment response. METHODS Twenty-nine patients (median age 40.5 years; 41% female) were enrolled between January 2020 and February 2023. All patients received olaparib (300 mg twice daily) and durvalumab (1,500 mg IV every four weeks) until radiographic or clinical progression. Plasma samples were collected at baseline and monthly, and cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) was performed. RESULTS The objective response rate was 10%, and median overall survival was 9.3 months. Longitudinal cfMeDIP-seq profiling enabled development of a circulating methylome classifier that accurately distinguished responders from non-responders. Integration with matched tumor transcriptomic and methylation data revealed enrichment of immune and DNA repair pathways in responders. Whole-exome sequencing identified no consistent mutational correlates. Spatial transcriptomic analysis demonstrated a more interactive, immune-rich tumor microenvironment and reduced malignant cell state diversity in responders. CONCLUSION This study supports the safety of combined PARP and PD-L1 blockade in recurrent IDH-mutant glioma and highlights the plasma methylome as a promising non-invasive biomarker of therapeutic response.