Glioma Treatment Response Research Articles

Glioma monitoring via longitudinal intracranial cerebrospinal fluid cell-free DNA.

2053 Background: Current methods for glioma treatment response assessment are limited. This study aimed to assess the technical and clinical feasibility of molecular profiling using intracranial CSF from patients with gliomas during their disease course. Methods: Adults with gliomas were recruited for longitudinal intracranial CSF collection using 1) Ommaya reservoirs, from which CSF would be sampled on at least two separate occasions, or 2) CSF collection from other clinically indicated CSF access devices, such as ventriculoperitoneal (VP) shunts. Patients were followed until their last visit or present time for ongoing participants. For this initial cfDNA feasibility study, CSF was collected from Ommaya reservoirs in four patients and from an existing VP shunt in one patient. cfDNA was then extracted and analyzed using two sequencing platforms, PredicineCARE for cancer variant profiling and PredicineSCORE for low-pass whole genome sequencing (LP-WGS). This analysis generated genomic aberration profiles and genome-wide copy number burden (CNB) score. Results: Five patients (2 females, 3 males; median age: 40 years, range 32-64 years) underwent longitudinal intracranial CSF collection via Ommaya reservoirs (n=4) or VP shunt (n=1). In total, thirty-five CSF samples were obtained (median volume: 3.80 mL; 0.5-5 mL), with 30 samples (85.7%) yielding sufficient cfDNA for variant profiling and LP-WGS. Our initial findings suggest that tumor fraction increased by 6.28x and 2.87x with radiographic progression in two patients. Tumor fraction decreased by 0.08x and 0.04x in two patients with paired immediate pre-versus-post chemoradiation samples. Despite ongoing pseudoprogression in one patient, tumor fraction decreased to unmeasurable levels from a post-resection baseline of 0.26. Patient-specific tumor-associated variant allelic frequencies (VAFs), including TP53, PTEN, TERT, and CDKN2A/B, decreased within individual patients after resection and chemoradiation. In two patients with isocitrate dehydrogenase (IDH) mutant gliomas, decreasing IDH1 VAF after resection correlated with decreased CSF D-2-hydroxyglutarate (D-2-HG) levels (0.64x and 0.62x, respectively, for the first patient, and 0.01x and 0.07x for the other patient). Both CSF IDH1 VAF and CSF D-2-HG increased in the patient who had radiographic progression (2.56x and 9.21x, respectively). Moreover, CNB decreased below the limit of quantification during treatment and increased above the limit at progression. Conclusions: Longitudinal CSF cfDNA can feasibly be obtained via CSF access devices in patients with gliomas during their disease course. Ongoing studies will evaluate hypotheses generated in this case series regarding how longitudinal CSF cfDNA could be utilized to sensitively detect changes in disease burden. Clinical trial information: NCT04692337 ; NCT04692324 .

Abstract 2294: Monitoring glioma treatment response through longitudinal analysis of cell-free DNA in cerebrospinal fluid: Insights from a comprehensive study using next-generation sequencing

Abstract Background: Assessing treatment response in gliomas with high fidelity remains challenging. Cell-free DNA (cfDNA) is increasingly recognized as a liquid biomarker in plasma and cerebrospinal fluid (CSF), showing promise in optimizing therapeutic regimens for various cancers. While CSF has been explored as a source of cfDNA for gliomas, understanding the dynamics of cfDNA abundance and sequencing changes during treatment and recurrence is essential. Leveraging our biobank of longitudinal CSF specimens obtained through CSF access devices, we aimed to determine the potential utility of CSF cfDNA as a monitoring tool for treatment response in glioma patients. Materials and methods: Longitudinal CSF specimens were collected through Ommaya reservoirs (NCT04692337) or ventriculoperitoneal shunts (NCT04692324) from patients with brain tumors, including gliomas. cfDNA was extracted from 1-5 mL of CSF based on available sample volumes and quantified using Qubit. Next-Generation sequencing using PredicineCARE or PredicineSCORE low-pass whole genome sequencing (LPWGS) was performed based on the available cfDNA. Results: CSF collected before versus after resection showed an increase in quantified cfDNA (2.97x, range: 1.58-5.26x), indicating the impact of increased parenchymal disruption and closer contact with CSF. Subsequently, CSF cfDNA decreased during chemoradiation and adjuvant treatment and increased at recurrence, even in patients co-enrolled in immunotherapy trials for IL-7 agonists and pembrolizumab. Notably, copy number burden (CNB) increased at recurrence in three patients with known disease progression and decreased throughout immunotherapy treatment in one patient despite concerns of pseudoprogression. In a patient with a hypermutated glioblastoma, CSF cfDNA revealed over 59 genomic alterations, including MAP2K1, KIT, and PDGFRA. Another patient with a progressing EGFR-amplified GBM showed over 200 new variants in the final sample, with EGFR copy number increasing from 2 to over 30. Conclusion: Analysis of cfDNA throughout a patient’s disease course, encompassing resection and treatment with standard-of-care and experimental therapies, may aid in disease monitoring and treatment response. Further evaluation in a larger patient cohort is needed to determine the sensitivity of changes in mutations, CNB, and cfDNA quantity for glioma disease burden. Citation Format: Riviere-Cazaux Cecile, Xiaoxi Dong, Chao Dai, Wei Mo, Pan Du, Shidong Jia, Terence Burns. Monitoring glioma treatment response through longitudinal analysis of cell-free DNA in cerebrospinal fluid: Insights from a comprehensive study using next-generation sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2294.

677 Amide Proton Transfer-Weighted Imaging Versus Diffusion-Weighted Imaging for Monitoring Treatment Response in Glioma Patients: A Systematic Review and Meta-Analysis

Abstract Aim Monitoring treatment response in glioma (GM) patients remains a challenge, as tumour recurrence (TR) and treatment-related injury (TRI) both appear similarly on standard magnetic resonance imaging (MRI). Although diffusion-weighted MRI (DWI) is gold standard, equivocal patients still undergo invasive biopsies for diagnosis. Amide proton transfer-weighted MRI (APTw) may more accurately differentiate TR from TRI, reducing surgical intervention rates. Hence, this systematic review and meta-analysis aimed to determine how APTw compares to DWI in the identification of TR from TRI. Method A search strategy was used to select studies investigating the diagnostic ability of DWI or APTw in detecting TR from Ovid MEDLINE ®, Ovid Embase, Web of Science, Cochrane Central Register of Controlled Trials, and Thai Clinical Trials Registry. Selection criteria were applied to retrieve studies and methodologies critically appraised according to the QUADAS-2 tool. Conclusions from studies were synthesised, and the sensitivity and specificity for TR detection pooled. Results 18 studies were included in the analysis (11 DWI, 6 APTw, 1 both). For TR, APTw signal measured significantly higher, whereas apparent diffusion coefficients derived from DWI images were significantly lower. In DWI studies, combined sensitivity and specificity for TR was 84.4% (95% CI, 72.5%-91.7%) and 81.2% (95% CI, 67.9%-89.8%) accordingly. Meta-analysis was not performed for APTw due to limited study numbers. In general, studies had low methodological quality and were associated with a risk of bias. Conclusions Overall, though comparisons between DWI and APTw in monitoring GM treatment were inconclusive, this study supports the potential use of APTw in neurosurgery.

TANK shapes an immunosuppressive microenvironment and predicts prognosis and therapeutic response in glioma.

Glioma, the most prevalent malignant intracranial tumor, poses a significant threat to patients due to its high morbidity and mortality rates, but its prognostic indicators remain inaccurate. Although TRAF-associated NF-kB activator (TANK) interacts and cross-regulates with cytokines and microenvironmental immune cells, it is unclear whether TANK plays a role in the immunologically heterogeneous gliomas. TANK mRNA expression patterns in public databases were analyzed, and qPCR and IHC were performed in an in-house cohort to confirm the clinical significance of TANK. Then, we systematically evaluated the relationship between TANK expression and immune characteristics in the glioma microenvironment. Additionally, we evaluated the ability of TANK to predict treatment response in glioma. TANK-associated risk scores were developed by LASSO-Cox regression and machine learning, and their prognostic ability was tested. TANK was specifically overexpressed in glioma and enriched in the malignant phenotype, and its overexpression was related to poor prognosis. The presence of a tumor microenvironment that is immunosuppressive was evident by the negative correlations between TANK expression and immunomodulators, steps in the cancer immunity cycle, and immune checkpoints. Notably, treatment for cancer may be more effective when immunotherapy is combined with anti-TANK therapy. Prognosis could be accurately predicted by the TANK-related risk score. High expression of TANK is associated with the malignant phenotype of glioma, as it shapes an immunosuppressive tumor microenvironment. Additionally, TANK can be used as a predictive biomarker for responses to various treatments and prognosis.

Sequential and Hybrid PET/MRI Acquisition in Follow-Up Examination of Glioblastoma Show Similar Diagnostic Performance.

Both positron emission tomography (PET) and magnetic resonance imaging (MRI), including dynamic susceptibility contrast perfusion (DSC-PWI), are crucial for treatment monitoring of patients with high-grade gliomas. In clinical practice, they are usually conducted at separate time points. Whether this affects their diagnostic performance is presently unclear. To this end, we retrospectively reviewed 38 patients with pathologically confirmed glioblastoma (IDH wild-type) and suspected tumor recurrence after radiotherapy. Only patients who received both a PET−MRI (where DSC perfusion was acquired simultaneously with a FET-PET) and a separate MRI exam (including DSC perfusion) were included. Tumors were automatically segmented into contrast-enhancing tumor (CET), necrosis, and edema. To compare the simultaneous as well as the sequential DSC perfusion to the FET-PET, we calculated Dice overlap, global mutual information as well as voxel-wise Spearman correlation of hotspot areas. For the joint assessment of PET and MRI, we computed logistic regression models for the differentiation between true progression (PD) and treatment-related changes (TRC) using simultaneously or sequentially acquired images as input data. We observed no significant differences between Dice overlap (p = 0.17; paired t-test), mutual information (p = 0.18; paired t-test) and Spearman correlation (p = 0.90; paired t-test) when comparing simultaneous PET−MRI and sequential PET/MRI acquisition. This also held true for the subgroup of patients with >14 days between exams. Importantly, for the diagnostic performance, ROC analysis showed similar AUCs for differentiation of PD and TRC (AUC simultaneous PET: 0.77; AUC sequential PET: 0.78; p = 0.83, DeLong’s test). We found no relevant differences between simultaneous and sequential acquisition of FET-PET and DSC perfusion, also regarding their diagnostic performance. Given the increasing attention to multi-parametric assessment of glioma treatment response, our results reassuringly suggest that sequential acquisition is clinically and scientifically acceptable.

TMET-20. TERT ACTS VIA FOXO1 TO ALTER REDOX METABOLISM IN BRAIN TUMORS

Abstract Telomere maintenance is a fundamental hallmark of cancer. Most tumors maintain telomere length via reactivation of telomerase reverse transcriptase (TERT) expression. Identifying imaging biomarkers of TERT can enable non-invasive assessment of tumor proliferation and response to therapy. Deuterium magnetic resonance spectroscopy (DMRS) following administration of 2H-labeled substrates recently emerged as a novel, clinically translatable method of monitoring metabolic activity in vivo. The goal of this study was to delineate metabolic reprogramming associated with TERT expression and to leverage this information for non-invasive imaging of tumor burden and treatment response in gliomas. Our results indicate that TERT expression is associated with elevated levels of the redox metabolite NADH in glioblastomas and oligodendrogliomas. Mechanistically, TERT expression is associated with inhibitory phosphorylation and cytosolic sequestration of FOXO1. FOXO1, in turn, negatively regulates nicotinamide phosphoribosyl transferase (NAMPT), which is the rate-limiting enzyme in NAD+ biosynthesis. As a result, TERT upregulates NAMPT, resulting in elevated steady-state pools of NAD+ and NADH. Concomitantly, FOXO1 negatively regulates the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase, which converts NAD+ to NADH. As a result, TERT upregulates the NADH/NAD+ ratio. Since elevated NADH and NADH/NAD+ ratio drive pyruvate conversion to lactate, we then examined whether DMRS-based imaging of [U-2H]-pyruvate metabolism reports on TERT expression in gliomas. Our results indicate that doxycycline-inducible TERT silencing significantly reduces lactate production from [U-2H]-pyruvate in tumor-bearing mice. Importantly, [U-2H]-pyruvate metabolism to lactate differentiates tumor from normal brain in vivo, including at clinical field strength (3T). Furthermore, [U-2H]-pyruvate reports on early response to treatment with TERT inhibitors or with radiochemotherapy in mice bearing orthotopic patient-derived gliomas at early timepoints before radiographic alterations can be visualized by magnetic resonance imaging. Collectively, our studies integrate a mechanistic understanding of TERT biology with innovative imaging that has the potential to improve assessment of tumor burden and treatment response for glioma patients.

TMIC-23. EXPLORING IBRUTINIB'S EFFECTS ON BLOOD-BRAIN BARRIER INTEGRITY AND GLIOMA PROGRESSION

Abstract BACKGROUND The blood-brain barrier (BBB), among malignant gliomas limits certain agents from impairing tumor growth. Thus, identifying agents that can transiently increase BBB permeability may prove useful in enhancing glioma treatment response. Previous ibrutinib studies showed it independently disrupted gut epithelial integrity and hampered glioma growth through BMX (bone marrow x-linked tyrosine kinase) inhibition. We propose BMX inhibition via ibrutinib disrupts BBB integrity while impairing glioma progression. METHODS To evaluate ibrutinib’s effect on brain endothelium, we evaluated electrical cell-cell impedance, junctional/cytoskeletal expression, downstream protein expression and functional ABC transporter activity; monitoring changes over time (0 to 8h) and at varied drug concentrations (1-10μM ibrutinib). Using rat glioma cells (S635) in vitro and in models, we examined cytotoxicity, apoptosis, model survival, and drug concentrations with ibrutinib alone or combined with poorly permeable Abcb1 substrate doxorubicin. RESULTS Ibrutinib dose-dependently decreased brain endothelial cell-cell impedance by 60% at 2h, without affecting cell viability. We observed decreased ZO-1 junctions, actin cytoskeletal rearrangement, and downstream pErk and pMek decreased expression optimally 2h (10μM ibrutinib). Dose-dependently ibrutinib inhibited Abcb1 efflux activity, further favoring a more permeable endothelium. Synergy with doxorubicin was seen in rat glioma cells treated with ibrutinib via increased apoptosis and cytotoxicity. However, while combined treatment resulted in decreased systemic doxorubicin concentrations, no differences in brain:plasma or tumor:plasma concentrations were evident. Combination therapy also did not increase rodent glioma model survival nor decrease tumor size. CONCLUSION Our results suggest that while ibrutinib induces brain endothelial permeability by junctional/cytoskeletal disruption and inhibition of Abcb1 efflux, no sustained effect can be seen in rodent glioma models in combination with a cytotoxic agent. Additional studies exploring similar agents that can enhance BBB permeability while slowing glioma growth are warranted, so as to improve upon current bleak malignant glioma treatment options.

A Novel Prognostic Signature Based on Glioma Essential Ferroptosis-Related Genes Predicts Clinical Outcomes and Indicates Treatment in Glioma.

BackgroundFerroptosis is a form of programmed cell death (PCD) that has been implicated in cancer progression, although the specific mechanism is not known. Here, we used the latest DepMap release CRISPR data to identify the essential ferroptosis-related genes (FRGs) in glioma and their role in patient outcomes.MethodsRNA-seq and clinical information on glioma cases were obtained from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). FRGs were obtained from the FerrDb database. CRISPR-screened essential genes (CSEGs) in glioma cell lines were downloaded from the DepMap portal. A series of bioinformatic and machine learning approaches were combined to establish FRG signatures to predict overall survival (OS) in glioma patients. In addition, pathways analysis was used to identify the functional roles of FRGs. Somatic mutation, immune cell infiltration, and immune checkpoint gene expression were analyzed within the risk subgroups. Finally, compounds for reversing high-risk gene signatures were predicted using the GDSC and L1000 datasets.ResultsSeven FRGs (ISCU, NFS1, MTOR, EIF2S1, HSPA5, AURKA, RPL8) were included in the model and the model was found to have good prognostic value (p < 0.001) in both training and validation groups. The risk score was found to be an independent prognostic factor and the model had good efficacy. Subgroup analysis using clinical parameters demonstrated the general applicability of the model. The nomogram indicated that the model could effectively predict 12-, 36-, and 60-months OS and progression-free interval (PFI). The results showed the presence of more aggressive phenotypes (lower numbers of IDH mutations, higher numbers of EGFR and PTEN mutations, greater infiltration of immune suppressive cells, and higher expression of immune checkpoint inhibitors) in the high-risk group. The signaling pathways enriched closely related to the cell cycle and DNA damage repair. Drug predictions showed that patients with higher risk scores may benefit from treatment with RTK pathway inhibitors, including compounds that inhibit RTKs directly or indirectly by targeting downstream PI3K or MAPK pathways.ConclusionIn summary, the proposed cancer essential FRG signature predicts survival and treatment response in glioma.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques.

ObjectiveSummarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.MethodsExperts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).ResultsHigh-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.ConclusionConsiderable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics.

ObjectiveTo summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments.MethodsThe current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging).ResultsThe biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application.ConclusionAdvanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.

Seeing more with less: virtual gadolinium-enhanced glioma imaging

MRI is the main modality to diagnose and monitor the evolution and treatment of brain tumours. Radiological tumour grading relies on evidence of abnormal blood–brain barrier permeability, achieved by intravenous injection of gadolinium-based contrast agents (GBCA), leading to enhanced signal intensity on T1-weighted images. The current goal in glioma surgery is resection of the enhancing tumour parts and the response assessment in neuro-oncology (RANO) criteria for monitoring glioma treatment response heavily rely on the demonstration of recurring or enlarging enhancing tumour.

MRI-Based Deep-Learning Method for Determining Glioma MGMT Promoter Methylation Status.

O6-Methylguanine-DNA methyltransferase (MGMT) promoter methylation confers an improved prognosis and treatment response in gliomas. We developed a deep learning network for determining MGMT promoter methylation status using T2 weighted Images (T2WI) only. Brain MR imaging and corresponding genomic information were obtained for 247 subjects from The Cancer Imaging Archive and The Cancer Genome Atlas. One hundred sixty-three subjects had a methylated MGMT promoter. A T2WI-only network (MGMT-net) was developed to determine MGMT promoter methylation status and simultaneous single-label tumor segmentation. The network was trained using 3D-dense-UNets. Three-fold cross-validation was performed to generalize the performance of the networks. Dice scores were computed to determine tumor-segmentation accuracy. The MGMT-net demonstrated a mean cross-validation accuracy of 94.73% across the 3 folds (95.12%, 93.98%, and 95.12%, [SD, 0.66%]) in predicting MGMT methylation status with a sensitivity and specificity of 96.31% [SD, 0.04%] and 91.66% [SD, 2.06%], respectively, and a mean area under the curve of 0.93 [SD, 0.01]. The whole tumor-segmentation mean Dice score was 0.82 [SD, 0.008]. We demonstrate high classification accuracy in predicting MGMT promoter methylation status using only T2WI. Our network surpasses the sensitivity, specificity, and accuracy of histologic and molecular methods. This result represents an important milestone toward using MR imaging to predict prognosis and treatment response.

In vivo characterization of physiological and metabolic changes related to isocitrate dehydrogenase 1 mutation expcression by multiparametric MRI and MRS in a rat model with orthotopically grafted human-derived glioblastoma cell lines.

The physiological mechanism induced by the isocitrate dehydrogenase 1 (IDH1) mutation, associated with better treatment response in gliomas, remains unknown. The aim of this preclinical study was to characterize the IDH1 mutation through in vivo multiparametric MRI and MRS. Multiparametric MRI, including the measurement of blood flow, vascularity, oxygenation, permeability, and in vivo MRS, was performed on a 4.7 T animal MRI system in rat brains grafted with human-derived glioblastoma U87 cell lines expressing or not the IDH1 mutation by the CRISPR/Cas9 method, and secondarily characterized with additional ex vivo HR-MAS and histological analyses. In univariate analyses, compared with IDH1-, IDH1+ tumors exhibited higher vascular density (p < 0.01) and better perfusion (p = 0.02 for cerebral blood flow), but lower vessel permeability (p < 0.01 for time to peak (TTP), p = 0.04 for contrast enhancement) and decreased T1 map values (p = 0.02). Using linear discriminant analysis, vascular density and TTP values were found to be independent MRI parameters for characterizing the IDH1 mutation (p < 0.01). In vivo MRS and ex vivo HR-MAS analysis showed lower metabolites of tumor aggressiveness for IDH1+ tumors (p < 0.01). Overall, the IDH1 mutation exhibited a higher vascularity on MRI, a lower permeability, and a less aggressive metabolic profile. These MRI features may prove helpful to better pinpoint the physiological mechanisms induced by this mutation.

Early imaging marker of progressing glioblastoma: a window of opportunity.

Therapeutic intervention at glioblastoma (GBM) progression, as defined by current assessment criteria, is arguably too late as second-line therapies fail to extend survival. Still, most GBM trials target recurrent disease. We propose integration of a novel imaging biomarker to more confidently and promptly define progression and propose a critical timepoint for earlier intervention to extend therapeutic exposure. A retrospective review of 609 GBM patients between 2006 and 2019 yielded 135 meeting resection, clinical, and imaging inclusion criteria. We qualitatively and quantitatively analyzed 2000+ sequential brain MRIs (initial diagnosis to first progression) for development of T2 FLAIR signal intensity (SI) within the resection cavity (RC) compared to the ventricles (V) for quantitative inter-image normalization. PFS and OS were evaluated using Kaplan-Meier curves stratified by SI. Specificity and sensitivity were determined using a 2 × 2 table and pathology confirmation at progression. Multivariate analysis evaluated SI effect on the hazard rate for death after adjusting for established prognostic covariates. Recursive partitioning determined successive quantifiers and cutoffs associated with outcomes. Neurological deficits correlated with SI. Seventy-five percent of patients developed SI on average 3.4months before RANO-assessed progression with 84% sensitivity. SI-positivity portended neurological decline and significantly poorer outcomes for PFS (median, 10 vs. 15months) and OS (median, 20 vs. 29months) compared to SI-negative. RC/V ratio ≥ 4 was the most significant prognostic indicator of death. Implications of these data are far-reaching, potentially shifting paradigms for glioma treatment response assessment, altering timepoints for salvage therapeutic intervention, and reshaping glioma clinical trial design.

Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data.

Chimeric antigen receptor (CAR) T-cell therapy has shown promise in the treatment of haematological cancers and is currently being investigated for solid tumours, including high-grade glioma brain tumours. There is a desperate need to quantitatively study the factors that contribute to the efficacy of CAR T-cell therapy in solid tumours. In this work, we use a mathematical model of predator–prey dynamics to explore the kinetics of CAR T-cell killing in glioma: the Chimeric Antigen Receptor T-cell treatment Response in GliOma (CARRGO) model. The model includes rates of cancer cell proliferation, CAR T-cell killing, proliferation, exhaustion, and persistence. We use patient-derived and engineered cancer cell lines with an in vitro real-time cell analyser to parametrize the CARRGO model. We observe that CAR T-cell dose correlates inversely with the killing rate and correlates directly with the net rate of proliferation and exhaustion. This suggests that at a lower dose of CAR T-cells, individual T-cells kill more cancer cells but become more exhausted when compared with higher doses. Furthermore, the exhaustion rate was observed to increase significantly with tumour growth rate and was dependent on level of antigen expression. The CARRGO model highlights nonlinear dynamics involved in CAR T-cell therapy and provides novel insights into the kinetics of CAR T-cell killing. The model suggests that CAR T-cell treatment may be tailored to individual tumour characteristics including tumour growth rate and antigen level to maximize therapeutic benefit.

Diagnostic performance of multiparametric MRI in the evaluation of treatment response in glioma patients at 3T.

MRI is one of the most important techniques to assess the treatment response of gliomas. However, differentiating tumor recurrence (TuR) from treatment effects (TrE) remains challenging. To compare the diagnostic performance of MR diffusion-weighted imaging (DWI), arterial spin labeling (ASL), proton MR spectroscopy (MRS), and amide proton transfer (APT) imaging in differentiating between TuR and TrE in posttreatment glioma patients. Prospective. Thirty patients with suspected tumor progression. DWI, ASL, proton MRS, and APT imaging were performed at 3T MR. MR indices, including ADC, relative cerebral blood flow (rCBF), ratios of Cho/Cr, Cho/NAA, and NAA/Cr and APT-weighted (APTw) effect were obtained from DWI, ASL, proton MRS, and APT imaging, respectively. Indices were measured in the contralateral normal-appearing white matter and lesions defined on the Gd-enhanced T1 w image. TuR or TrE was either determined histologically or clinically from longitudinal MRI follow-up for at least 6 months. The diagnostic performance of the indices was evaluated using Student's t-test, receiver operating characteristic (ROC) curve, and multivariate logistic regression analyses. Among the 30 patients, 16 were diagnosed as having TuR and the rest having TrE. The recurrent tumors showed a significantly higher APTw effect (1.56 ± 1.14%) and rCBF (1.44 ± 0.61) compared with lesions representing treatment effects (-0.44 ± 1.34% and 0.72 ± 0.25, respectively, with P < 0.001). The areas under the curve (AUCs) were 0.87 and 0.90 for APTw and rCBF, respectively, in differentiating between TuR and TrE. Combining APTw and rCBF achieved a higher AUC of 0.93. MRS index ratios of Cho/Cr (P = 0.25), Cho/NAA (P = 0.16), and NAA/Cr (P = 0.86) and ADC (P = 0.37) showed no significant differences between TuR and TrE lesions, with AUCs lower than 0.70. Compared with DWI and MRS, ASL and APT imaging techniques showed better diagnostic capability in distinguishing TuR from TrE. 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2020;51:1154-1161.

Hyperpolarized Pyruvate MR Spectroscopy Depicts Glycolytic Inhibition in a Mouse Model of Glioma.

BackgroundA generation of therapies targeting tumor metabolism is becoming available for treating glioma. Hyperpolarized MRI is uniquely suited to directly measure the metabolic effects of these emerging treatments.PurposeTo explore the feasibility of the use of hyperpolarized [1-carbon 13 {13C}]-pyruvate for real-time measurement of metabolism and response to treatment with a glycolytic inhibitor in an orthotopic mouse model of glioma.Materials and MethodsIn this animal study, anatomic MRI and dynamic 13C MR spectroscopy were performed at 7 T during intravenous injection of hyperpolarized [1-13C]-pyruvate on mice with orthotopic U87MG glioma and healthy control mice. Anatomic MRI and dynamic 13C MR spectroscopy were repeated after administration of the glycolytic inhibitor WP1122, a prodrug of 2-deoxy-d-glucose. All experiments were conducted in athymic nude mice between October 2016 and March 2017. Hyperpolarized lactate production was quantified as an apparent reaction rate, or kPL, and normalized lactate ratio (nLac). The Wilcoxon signed-rank test was used to assess changes in paired measures of lactate production before and after treatment.ResultsThirteen 12-16-week-old female mice and five healthy female mice underwent anatomic MRI and hyperpolarized [1-13C]-pyruvate spectroscopy. Large contrast agent-enhanced tumors were shown in mice with glioma at T2-weighted and T1-weighted postcontrast MRI by postimplantation day 40. After treatment with WP1122, a decrease in lactate was observed in mice with glioma (baseline and treatment mean kPL, 0.027 and 0.018 sec-1, respectively, P = .01; baseline and posttreatment mean nLac, 0.28 and 0.22, respectively, P = .01) whereas no significant decrease was observed in healthy control mice (baseline and posttreatment mean kPL, 0.011 and 0.017 sec-1, respectively, P = .91; baseline and posttreatment mean nLac, 0.16 and 0.21, respectively, P = .84).ConclusionHyperpolarized carbon 13 measurements of pyruvate metabolism can provide rapid feedback for monitoring treatment response in glioma.© RSNA, 2019.

Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas.

Isocitrate dehydrogenase (IDH) and 1p19q codeletion status are importantin providing prognostic information as well as prediction of treatment response in gliomas. Accurate determination of the IDH mutation status and 1p19q co-deletion prior to surgery may complement invasive tissue sampling and guide treatment decisions. Preoperative MRIs of 538 glioma patients from three institutions were used as a training cohort. Histogram, shape, and texture features were extracted from preoperative MRIs of T1 contrast enhanced and T2-FLAIR sequences. The extracted features were then integrated with age using a random forest algorithm to generate a model predictive of IDH mutation status and 1p19q codeletion. The model was then validated using MRIs from glioma patients in the Cancer Imaging Archive. Our model predictive of IDH achieved an area under the receiver operating characteristic curve (AUC) of 0.921 in the training cohort and 0.919 in the validation cohort. Age offered the highest predictive value, followed by shape features. Based on the top 15 features, the AUC was 0.917 and 0.916 for the training and validation cohort, respectively. The overall accuracy for 3 group prediction (IDH-wild type, IDH-mutant and 1p19q co-deletion, IDH-mutant and 1p19q non-codeletion) was 78.2% (155 correctly predicted out of 198). Using machine-learning algorithms, high accuracy was achieved in the prediction of IDH genotype in gliomas and moderate accuracy in a three-group prediction including IDH genotype and 1p19q codeletion.

Abstract 1913: Investigation of targeting SKP2 to improve the treatment response in glioma

Abstract Glioma is the most frequent tumor in central nervous system (CNS), constituting about 30% of CNS tumors and 80% of malignant brain tumors. The current standard strategy for glioma treatment is surgery plus adjuvant chemotherapy and concurrent radiotherapy. However, the prognosis of glioma is still poor. It has been proved that the existence of glioma stem cells and the timely repair of DNA damages are the main causes of treatment failure. Skp2 (S-phase kinase associated protein-2), a member of F-box proteins, forms the Skp2 SCF complex with Skp1, Cullin-1, and Rbx1, serves as one of the important E3-ligases in the process of ubiquitination, and is responsible for substrate recognition. Skp2 is overexpressed in a variety of human cancers and promotes cancer progression by inducing p27 degradation. Importantly, Skp2 deficiency profoundly restricts cancer progression in multiple genetic mouse tumor models. Our group has demonstrated that Skp2 is involved in the regulation of pool size and self-renewal ability of hematopoietic stem cells, as well as breast cancer stem cells and nasopharyngeal carcinoma stem cell-like cells. However, the exact role of Skp2 in the regulation of glioma stem cells and DNA damage repair in glioma has not been elucidated yet. We proposed that targeting Skp2 could promote radio- and chemotherapy sensitivity through suppressing function of glioma stem cells. We first detected the expression of SKP2 in glioma tumor tissues and found that SKP2 was highly expressed in glioma and related to the prognosis of glioma patients. We also adopted gene knockdown methods and inhibitor pretreatment with small molecules in order to suppress the level of Skp2, and then checked the sphere formation and self-renewal ability of glioma stem cell upon radio/chemo treatments. In this way we evaluated the role of Skp2 in repressing the glioma cell proliferation and subsequently triggering apoptosis. Our project will clarify the novel mechanisms about how Skp2 is involved in the glioma radio- and chemotherapy resistance, which will provide a potential target to improve the radio/chemo therapeutic effect through targeting one single target. Citation Format: Jing Wang, Hong-Kai Su, Zhong-Ping Chen, Yue Qu, Hai-Ping Cai. Investigation of targeting SKP2 to improve the treatment response in glioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1913.

Towards a molecular algorithm predicting glioma treatment response and resistance: A biomarker analysis and path to real time profiling in N2M2.

12090Background: Gliomas regularly evade current therapies through primary and acquired resistance and the effect of temozolomide is mainly restricted to the subgroup of methylguanin-O6-methyltrans...