Patil, Vikas S.

4157 Background: IDH1/2 mutations occur in ~25% of cholangiocarcinomas (CCAs). Preclinical studies suggest synergy between PARP inhibition and PD-L1 blockade. We previously conducted a phase II trial of olaparib plus durvalumab in advanced IDH -mutant CCA. We report matched baseline tissue and serial cell-free DNA (cfDNA)-based correlative analysis of pts samples. The primary objective was to develop a cfDNA methylome signature as a non-invasive biomarker. Methods: This single-arm, open-label phase II study (NCT03991832) enrolled patients with unresectable/metastatic IDH -mutant CCA and ≤2 prior lines of systemic therapy. Patients received olaparib 300 mg orally twice daily and durvalumab 1500 mg IV every 4 weeks. Blood samples were collected at baseline and monthly while on treatment for planned correlatives to examine R2HG, S2HG, and artemin levels using HPLC (High-Performance Liquid Chromatography). Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) was performed on pts cfDNA samples and case-matched IDH -wildtype pts. Formalin-fixed, paraffin-embedded blocks of baseline tumor biopsies were used for multispectral fluorescent IHC (FL-IHC) using a 6-marker panel composed of pan-cytokeratin, CD4, CD8, CD163, PD-L1, and CD68. Results: Ten patients were enrolled (median age 63.5 y; 50% female; 90% received prior platinum). Median treatment duration was 1.95 mo (range 1.8–13.5). No complete or partial responses were observed. DCR was 30% (3 patients with stable disease); one patient remained on therapy for 13.5 mo before progression. Median PFS was 1.97 mo (95% CI 1.73–3.93). HPLC from baseline plasma showed lower baseline artemin levels correlated with stable disease (p=0.038), while R2HG/S2HG ratios showed no association with outcome. FL-IHC showed enriched immune cell populations, specifically CD4 + T cells (p=0.0032) and a trend for CD68 + macrophages (p=0.062), in the tumor stroma compared with tumor core. 54 plasma samples (from 8 patients) were profiled with cfMeDIP-seq along with 8 IDH -wildtype controls. Using top 100 differentially methylated regions, the circulating tumour DNA methylome exhibited a highly specific signature, accurately discriminating IDH -mutant and IDH -wildtype CCA regardless of treatment status. The specific differentially methylated gene pathways between groups were comprehensively examined in both on-treatment and baseline plasma samples. Conclusions: Advanced IDH -mutant CCA harbors an immune-excluded phenotype, which may underlie primary resistance to immunotherapy. Plasma cfDNA methylome signature can accurately discriminate CCA with IDH mutations. Clinical trial information: NCT03991832 .

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 Brain metastases (BM) are the most common intracranial tumor, with a poor prognosis of 10-16 months, and lung adenocarcinoma (LUAD) is the most common source. Currently, we cannot reliably predict which patients will develop BMs clinically, so most are detected after they develop and growing to cause deficits. Here, we use tumor DNA methylomes to predict which patients are likely to develop BM through the course of disease and we use both cerebrospinal fluid (CSF) and plasma methylomes for BM liquid biopsy, enabling their early detection and treatment. METHODS DNA methylomes were acquired from 419 tumor and plasma samples from 363 LUAD and BM patients. We built DNA methylation-based models that predict BM development and that also identify BMs non-invasively from CSF and plasma in discovery data subsets. A nomogram was built that predicts BM risk using methylation scores and clinical stage together. Models were evaluated in independent validation sets. RESULTS Our model predicting BM development was accurate (Univariable Cox: HR=5.7, 95% CI=1.9-17.2), p=0.0023), independent of clinical factors (Multivariable Cox: HR=8.9, 95% CI=2.0-40.5, p=0.0046), and more predictive than cancer staging used currently clinically (AUC=0.81 versus 0.65). Our combinatorial nomogram using methylation and staging data together showed enhanced BM prediction (Univariable Cox: HR=17.2, 95% CI=4.1-71.3, p<0.0001; AUROC=0.82). Our models identifying BM through biofluid methylomes accurately distinguished BM from differential diagnoses of gliomas and lymphomas in plasma (AUROC=0.80, 95% CI=0.68-0.93) and with greater accuracy in CSF (AUROC=0.93, 95% CI=0.71-1.0). CONCLUSION Overall, we show the first approaches for robust molecular prediction of BM development and for reliable liquid biopsy of BM. This work is expected to transform cancer management by identifying high-risk lung cancer patients after initial treatment for inclusion in screening protocols using neuroimaging and liquid biopsy, to identify BM development early with less advanced disease and more optimal therapeutic outcomes.

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.

Abstract INTRODUCTION While TERT promoter mutation (TPM) has been established as a marker of clinically aggressive meningiomas, this alteration is rare and found in less than 5% of all cases. However, a larger subset of meningiomas may exhibit aberrant TERT expression in the absence of TPMs. This study investigated the effect of TERT gene expression on clinical outcome in meningioma patients. METHODS Clinical and molecular data were retrospectively collected on 1241 meningiomas, split into a Toronto discovery cohort and a multi-institutional validation cohort. Sanger sequencing and bulk RNA sequencing were used to determine TPM status and TERT gene expression. The effect of TERT expression on progression-free survival (PFS) was assessed using Kaplan-Meier and Cox regression analysis. RESULTS While meningiomas with TPM showed expectedly higher TERT gene expression compared to wildtype (TP-WT) cases (p<0.0001), TERT expression was still detected in 28.7% (157/547) of TP-WT meningiomas. Meningiomas with TERT expression showed significantly worse PFS compared to meningiomas without any TERT expression. In fact, WHO grade 1 meningiomas with TERT expression had PFS outcomes resembling WHO grade 2 meningiomas lacking TERT expression (p=0.59). In turn, WHO grade 2 meningiomas with TERT expression had clinical outcomes similar to WHO grade 3 meningiomas without TERT expression (p=0.42). Furthermore, the proportion of meningiomas expressing TERT as well as overall TERT expression levels increased with increasing WHO grade. Multivariable analysis showed that TERT expression was significantly associated with worse PFS even when controlling for other known predictors of clinical outcome including TPM, CDKN2A/B loss, 1p/22q status and WHO grade (HR 1.85 [95% CI 1.33-2.57], p=0.00024). CONCLUSION TERT expression is a novel independent biomarker of outcome for meningiomas identifiable in up to one-third of cases that may be utilized to reclassify tumours to a higher WHO grade.

2030 Background: Brain metastases (BM) are common and arise in 30% of lung adenocarcinoma (LUAD) patients. Patients with LUAD that develop BM have significantly poorer outcomes, with a 10-16 month median overall survival. Unfortunately, current clinical practice for BM prediction is limited and so BM are typically detected after they develop and grow to cause neurological symptoms. Once BM are detected, currently neurosurgical tumor biopsies are performed to enable BM diagnosis via neuropathological evaluation. The aims of this study were to develop DNA methylation-based models that predict LUAD BM and non-invasively detect BM in blood to enable early diagnosis and treatment. Methods: DNA methylomes were acquired from 402 tumor tissue and plasma samples in a cohort of 346 LUAD and BM patients. Machine learning models were built using DNA methylation signatures that stratify BM risk in tissue and detect BM in plasma. Models were evaluated in independent validation datasets. A predictive nomogram was developed using the BM prediction model together with clinical factors to provide composite patient-specific scores reflecting BM risk. Results: The methylation-based BM predictor accurately stratified BM risk in a univariable Cox model using validation set data (HR = 5.65, 95%CI 1.85–17.2, p = 0.0023). Model utility was independent of the predictive value of clinical factors in a multivariable Cox model using validation set data (Table 1: HR = 8.92, 95%CI 1.97–40.5, p = 0.0046). The 5-year model accuracy was 0.81 and significantly higher than a similarly built cancer stage-based model (0.65), demonstrating utility over current practice. The combinatorial clinical-methylomic predictive nomogram had enhanced utility with an accuracy of 0.82 univariable Cox HR of 17.2 (95%CI 4.13–71.3, p < 0.0001), demonstrating comprehensive patient-specificity. The plasma-based model accurately classified BM from gliomas and lymphomas (AUROC=0.80), as typical clinical differential diagnoses, in validation set data. The models were validated further in additional external data. Conclusions: DNA methylation-based modeling of BM can accurately predict LUAD patients at risk for BM development and can non-invasively detect BM that develop. Future treatment approaches may tailor initial LUAD treatment and ongoing cancer surveillance to a patient’s BM risk, allowing for the potential to prevent and treat BM early. DNA methylation-based BM prediction is independent of clinical factors in a multivariable Cox proportional hazards model. Variable HR 95% CI p Methylome risk score 8.92 1.97–40.5 0.005 Age Years 0.96 0.92–1.02 0.177 Smoking Pack-years 0.99 0.95–1.03 0.496 EGFR Mutant vs wildtype 0.92 0.25–3.34 0.895 T T2 vs T1 1.58 0.41–6.04 0.505 T3−4 vs T1 1.49 0.28–7.98 0.642 N N1 vs N0 1.05 0.31–3.58 0.943 N2−3 vs N0 1.00 0.27–3.69 0.995 M M1 vs M0 145 12.2–1730 <0.001