Abstract Background: Treatment effect (TE) poses a diagnostic challenge in patients treated with immune-checkpoint inhibitors (ICIs). Although TE has been described in patients with primary brain tumors (PBT) treated with chemoradiation as pseudo-progression, it has not been well characterized with ICI therapy. TE is thought to be less symptomatic than true tumor progression (TP), but this has not been well studied. We investigated MRI characteristics and symptoms in PBT patients with histologically confirmed TP or TE. Methods: A retrospective cohort study of 50 PBT patients treated with ICI therapy (single or doublet) with/without chemotherapy that had biopsy proven TP or TE, histologically confirmed with either mitotically active tumor cells or necrosis with macrophages without tumor cells, respectively. Blinded review of pre-operative MRI using T1-post contrast, T2-FLAIR, Perfusion, and Diffuse Weighted Index (DWI) sequences were evaluated for characteristics such as extent of T2-FLAIR, midline shift, and appearance of contrast enhancement. PRO symptom severity had been collected using the M.D. Anderson Symptom Inventory-Brain Tumor (MDASI-BT), and PROMIS Anxiety and Depression 8b short forms. Results: Forty had pathologically confirmed TP and 10 had TE; median age 44, predominantly male (58%), white (80%), non-Hispanic (82%) with GBM (40%). No differences in sex, age, ethnicity, diagnosis, prior treatment, or steroid use at the time of imaging between patients with TP vs TE. TE imaging was more likely to show midline shift (40%) on MRI than TP (9.7%), p-value=0.047. TE lesions had more T2-FLAIR relative to contrast enhancement; the ratio of contrast enhancement/T2-FLAIR hyperintensity was smaller in the TE group vs TP group (0.337 vs 0.569, respectively (p=0.010). Patients with TP had a significantly higher neurologic factor symptom score (1.88 vs 0.35, p-value=0.003). Of the neurologic symptoms, there were statistically significant group differences in numbness/tingling (1.8 vs 0.0, p<0.001) and weakness (2.8 vs 0.0, p<0.001) but not pain (2.1 vs 1.4, p<0.58) and seizures (0.8 vs 0.0, p<0.44). While not statistically significant but with effect sizes (ES) greater than 0.5, patients with TE had worse cognitive symptoms (factor score 2.3 vs 1.2, ES=0.62), difficulty remembering (4.0 vs 1.5, ES=1.03), and difficulty understanding (2.0 vs 0.7, ES=0.79), and worse scores on PROMIS Depression (51.9 vs 47.1, ES=0.51). Conclusions: TE was symptomatic and not uncommon (20%) in this cohort. The symptom profile between TE and TP differed; TE presented with more cognitive and affective symptoms, whereas TP presented with focal neurologic symptoms, including weakness and numbness/tingling. The imaging findings in TE of more midline shift and T2-FLAIR suggest a possible diffuse cytokine-release process causing parenchymal changes rather than tumor invasion. These findings highlight that TE with ICI treatment is common and may have symptoms and imaging changes that are related to the underlying inflammatory process. Confirmatory studies are required. Citation Format: Emma M. Byrne, Maeve Pascoe, Elizabeth Vera, Tito Mendoza, Hope Miller, Tricia Kunst, Kelly Mentges, Kathleen Wall, Matt Lindsley, Anna Choi, Ewa Grajkowska, John Kohrs, Jim Smirniotopoulos, Eric Burton, Byram Ozer, Marta Penas-Prado, Jing Wu, Solmaz Sahebjam, Terri S. Armstrong, Mark R. Gilbert. Testing neuro-oncology tenets: are MRI findings and symptoms different with true progression compared with immunotherapy-related treatment effect in patients with primary brain tumors? [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr A044.
Corticosteroids are routinely utilized to alleviate edema in patients with intracranial lesions and are first-line agents to combat immune-related adverse events (irAEs) that arise with immune checkpoint blockade treatment. However, it is not known if or when corticosteroids can be administered without abrogating the efforts of immunotherapy. The purpose of this study was to evaluate the impact of dexamethasone on lymphocyte activation and proliferation during checkpoint blockade to provide guidance for corticosteroid use while immunotherapy is being implemented as a cancer treatment.
Methods
Lymphocyte proliferation, differentiation, and cytokine production were evaluated during dexamethasone exposure. Human T cells were stimulated through CD3 ligation and co-stimulated either directly by CD28 ligation or by providing CD80, a shared ligand for CD28 and CTLA-4. CTLA-4 signaling was inhibited by antibody blockade using ipilimumab which has been approved for the treatment of several solid tumors. The in vivo effects of dexamethasone during checkpoint blockade were evaluated using the GL261 syngeneic mouse intracranial model, and immune populations were profiled by flow cytometry.
Results
Dexamethasone upregulated CTLA-4 mRNA and protein in CD4 and CD8 T cells and blocked CD28-mediated cell cycle entry and differentiation. Naïve T cells were most sensitive, leading to a decrease of the development of more differentiated subsets. Resistance to dexamethasone was conferred by blocking CTLA-4 or providing strong CD28 co-stimulation prior to dexamethasone exposure. CTLA-4 blockade increased IFNγ expression, but not IL-2, in stimulated human peripheral blood T cells exposed to dexamethasone. Finally, we found that CTLA-4 blockade partially rescued T cell numbers in mice bearing intracranial gliomas. CTLA-4 blockade was associated with increased IFNγ-producing tumor-infiltrating T cells and extended survival of dexamethasone-treated mice.
Conclusions
Dexamethasone-mediated T cell suppression diminishes naïve T cell proliferation and differentiation by attenuating the CD28 co-stimulatory pathway. However, CTLA-4, but not PD-1 blockade can partially prevent some of the inhibitory effects of dexamethasone on the immune response.
Abstract Resistance to therapeutic use of retinoids in glioma has been observed for over 20 years; however, the exact mechanism of resistance remains unknown. To understand retinoic acid resistance in glioma, we studied the turnover mechanism of retinoid receptor proteins in neural stem cells and glioma stem-like cells. Here, we show that in normal neural stem cells, proteasomal degradation of retinoid receptors involves sumoylation, ubiquitination and recognition by the valosin-containing protein (VCP/p97/Cdc48). We find that Sumo1 modification has a dual role to stabilize the retinoid receptor from unwanted degradation and signal additional modification via ubiquitination. Subsequently, the modified receptor binds to the VCP chaperone and both proteins are degraded by the proteasome. Additionally, we reveal that all trans retinoic acid (ATRA) induces VCP expression, creating a positive feedback loop that enhances degradation. In contrast, the pathway is impaired in the glioma stem-like cells resulting in the accumulation of sumoylated and high molecular weight forms of retinoid receptors that lack transcriptional activity and fail to be recognized by the proteasome. Moreover, modified receptor accumulation occurs before ATRA treatment; therefore, the transcritptional defect in glioma is due to a block in the proteasomal degradation pathway that occurs after the sumo modification step.
NRG Oncology/RTOG 9802 (ClinicalTrials.gov Identifier: NCT00003375) is a practice-changing study for patients with WHO low-grade glioma (LGG, grade II), as it was the first to demonstrate a survival benefit of adjuvant chemoradiotherapy over radiotherapy. This post hoc study sought to determine the prognostic and predictive impact of the WHO-defined molecular subgroups and corresponding molecular alterations within NRG Oncology/RTOG 9802.IDH1/2 mutations were determined by immunohistochemistry and/or deep sequencing. A custom Ion AmpliSeq panel was used for mutation analysis. 1p/19q codeletion and MGMT promoter methylation were determined by copy-number arrays and/or Illumina 450K array, respectively. Progression-free survival (PFS) and overall survival (OS) were estimated using the Kaplan-Meier method. Hazard ratios (HRs) were calculated using the Cox proportional hazard model and tested using the log-rank test. Multivariable analyses (MVAs) were performed incorporating treatment and common prognostic factors as covariates.Of the eligible patients successfully profiled for the WHO-defined molecular groups (n = 106/251), 26 (24%) were IDH-wild type, 43 (41%) were IDH-mutant/non-codeleted, and 37(35%) were IDH-mutant/codeleted. MVAs demonstrated that WHO subgroup was a significant predictor of PFS after adjustment for clinical variables and treatment. Notably, treatment with postradiation chemotherapy (PCV; procarbazine, lomustine (CCNU), and vincristine) was associated with longer PFS (HR, 0.32; P = .003; HR, 0.13; P < .001) and OS (HR, 0.38; P = .013; HR, 0.21; P = .029) in the IDH-mutant/non-codeleted and IDH-mutant/codeleted subgroups, respectively. In contrast, no significant difference in either PFS or OS was observed with the addition of PCV in the IDH-wild-type subgroup.This study is the first to report the predictive value of the WHO-defined diagnostic classification in a set of uniformly treated patients with LGG in a clinical trial. Importantly, this post hoc analysis supports the notion that patients with IDH-mutant high-risk LGG regardless of codeletion status receive benefit from the addition of PCV.
PURPOSE The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time, some limitations of these criteria were identified, and challenges emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria. METHODS Informed by data from studies evaluating the different criteria, updates to the RANO criteria are proposed (RANO 2.0). RESULTS We recommend a standard set of criteria for both high- and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the postradiotherapy magnetic resonance imaging (MRI), rather than the postsurgical MRI, will be used as the baseline for comparison with subsequent scans. Since the incidence of pseudoprogression is high in the 12 weeks after radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, are required to define tumor progression. However, confirmation scans are not mandatory after this period nor for the evaluation of treatment for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (two-dimensional) but volumetric measurements are an option. For IDH wild-type glioblastoma, the nonenhancing disease will no longer be evaluated except when assessing response to antiangiogenic agents. In IDH-mutated tumors with a significant nonenhancing component, clinical trials may require evaluating both the enhancing and nonenhancing tumor components for response assessment. CONCLUSION The revised RANO 2.0 criteria refine response assessment in gliomas.
Checkpoint inhibition has demonstrated clinical efficacy in a variety of solid tumors. Reports of programmed death ligand 1 (PD-L1) expression in glioblastoma are highly variable (ranging from 6% to 88%) and its role as a prognostic marker has yielded conflicting results.To validate the prevalence and prognostic role of PD-L1 expression in a large cohort of diffuse gliomas according to the 2016 revised WHO classification.Using tissue microarrays, we compared 5 PD-L1 monoclonal antibodies (n = 56) and validated expression (n = 183) using quantitative immunohistochemistry (IHC) and RNA in situ hybridization (RISH). Expression data from The Cancer Genome Atlas (TCGA) and published studies were compared with clinical outcome. Multiplexed immunophenotyping was used to identify PD-L1+ cell populations in post-treatment glioblastoma.Using a 5% cut-off, PD-L1 expression was significantly associated with a poor prognosis in both histologically defined (n = 125, log-rank P < .001) and recurrent isocitrate dehydrogenase (IDH)-wildtype glioblastoma (n = 60, log-rank P = .015). PD-L1 remained a significant negative prognosticator in Cox regression analysis (hazard ratio: 1.96, P = .021). Analysis of TCGA data confirmed decreased overall survival in recurrent non-glioma CpG island methylator phenotype (G-CIMP) glioblastoma (n = 12, log-rank P = .023), but not in glioblastoma as a group (n = 444, log-rank P = .135). PD-L1 RISH showed a significant correlation with IHC (P < .0001). PD-L1 was observed in the proliferating perivascular stem cell and immune niche of post-treatment glioblastoma.A 5% PD-L1 expression cut-off identified a subset of glioblastoma that is associated with a worse clinical outcome. This association remained significant within the newly defined IDH-wildtype classification. These findings could have implications for patient stratification in future clinical trials of PD-1/PD-L1 blockade.
Precision health approaches to managing symptom burden in primary brain tumor (PBT) patients are imperative to improving patient outcomes and quality of life, but require tackling the complexity and heterogeneity of the symptom experience. Network Analysis (NA) can identify complex symptom co-severity patterns, and unsupervised clustering can unbiasedly stratify patients into clinically relevant subgroups based on symptom patterns. We combined these approaches in a novel study seeking to understand PBT patients' clinical and demographic determinants of symptom burden.MDASI-BT symptom severity data from a two-institutional cohort of 1128 PBT patients were analyzed. Gaussian Graphical Model networks were constructed for the all-patient cohort and subgroups identified by unsupervised clustering based on co-severity patterns. Network characteristics were analyzed and compared using permutation-based statistical tests.NA of the all-patient cohort revealed 4 core dimensions that drive the overall symptom burden of PBT patients: Cognitive, physical, focal neurologic, and affective. Fatigue/drowsiness was identified as pivotal to the symptom experience based on the network characteristics. Unsupervised clustering discovered 4 patient subgroups: PC1 (n = 683), PC2 (n = 244), PC3 (n = 92), and PC4 (n = 109). Moderately accurate networks could be constructed for PC1 and PC2. The PC1 patients had the highest interference scores among the subgroups and their network resembled the all-patient network. The PC2 patients were older and their symptom burden was driven by cognitive symptoms.In the future, the proposed framework might be able to prioritize symptoms for targeting individual patients, informing more personalized symptom management.
Cognitive reserve (CR) has been proposed to account for functional outcome differences in brain pathology and its clinical manifestations. The purpose of our paper is to systematically review the effects of CR on cognitive outcomes in individuals with neurodegenerative and structural CNS diseases. We performed a systematic search of PubMed, CINAHL (Cumulative Index to Nursing and Allied Health Literature), and PsychInfo using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Seventeen studies met the predetermined inclusion criteria and were selected for review. Education level was the most commonly used measure for CR, and various neuropsychological tests were used to measure cognitive outcomes. Regardless of the CNS disease of the individuals, almost all of the studies reported a positive association between CR and cognitive outcomes when they were evaluated cross-sectionally. However, when evaluated longitudinally, CR had either no effect on, or a negative association with, cognitive outcomes. Based on studies across a broad spectrum of CNS diseases, our findings suggest that CR may serve as a predictor of cognitive outcomes in individuals with CNS diseases. However, studies to date are limited by a lack of imaging analyses and standardized assessment strategies. The ability to use a standardized measure to assess the longitudinal effects of CR may allow for the development of more targeted treatment methods, resulting in improved disease outcomes for individuals.
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