The future of cancer immunotherapy for brain tumors: a collaborative workshop

Targeting SCD triggers lipotoxicity of cancer cells and enhances anti-tumor immunity in breast cancer brain metastasis mouse models

Breast cancer brain metastases (BCBM) are a significant cause of mortality and are incurable. Thus, identifying BCBM targets that reduce morbidity and mortality is critical. BCBM upregulate Stearoyl-CoA Desaturase (SCD), an enzyme that catalyzes the synthesis of monounsaturated fatty acids, suggesting a potential metabolic vulnerability of BCBM. In this study, we tested the effect of a brain-penetrant clinical-stage inhibitor of SCD (SCDi), on breast cancer cells and mouse models of BCBM. Lipidomics, qPCR, and western blot were used to study the in vitro effects of SCDi. Single-cell RNA sequencing was used to explore the effects of SCDi on cancer and immune cells in a BCBM mouse model. Pharmacological inhibition of SCD markedly reshaped the lipidome of breast cancer cells and resulted in endoplasmic reticulum stress, DNA damage, loss of DNA damage repair, and cytotoxicity. Importantly, SCDi alone or combined with a PARP inhibitor prolonged the survival of BCBM-bearing mice. When tested in a syngeneic mouse model of BCBM, scRNAseq revealed that pharmacological inhibition of SCD enhanced antigen presentation by dendritic cells, was associated with a higher interferon signaling, increased the infiltration of cytotoxic T cells, and decreased the proportion of exhausted T cells and regulatory T cells in the tumor microenvironment (TME). Additionally, pharmacological inhibition of SCD decreased engagement of immunosuppressive pathways, including the PD-1:PD-L1/PD-L2 and PVR/TIGIT axes. These findings suggest that SCD inhibition could be an effective strategy to intrinsically reduce tumor growth and reprogram anti-tumor immunity in the brain microenvironment to treat BCBM.

Navigating the Immune Maze: Pioneering Strategies for Unshackling Cancer Immunotherapy Resistance

Cancer immunotherapy has ushered in a transformative era in oncology, offering unprecedented promise and opportunities. Despite its remarkable breakthroughs, the field continues to grapple with the persistent challenge of treatment resistance. This resistance not only undermines the widespread efficacy of these pioneering treatments, but also underscores the pressing need for further research. Our exploration into the intricate realm of cancer immunotherapy resistance reveals various mechanisms at play, from primary and secondary resistance to the significant impact of genetic and epigenetic factors, as well as the crucial role of the tumor microenvironment (TME). Furthermore, we stress the importance of devising innovative strategies to counteract this resistance, such as employing combination therapies, tailoring immune checkpoints, and implementing real-time monitoring. By championing these state-of-the-art methods, we anticipate a paradigm that blends personalized healthcare with improved treatment options and is firmly committed to patient welfare. Through a comprehensive and multifaceted approach, we strive to tackle the challenges of resistance, aspiring to elevate cancer immunotherapy as a beacon of hope for patients around the world.

Smart brain tumor diagnosis system utilizing deep convolutional neural networks

The early diagnosis of cancer is crucial to provide prompt and adequate management of the diseases. Imaging tests, in particular magnetic resonance imaging (MRI), are the first preferred method for diagnosis. However, these tests have some limitations which can cause a delay in detection and diagnosis. The use of computer-aided intelligent systems can assist physicians in diagnosis. In this study, we established a Convolutional Neural Network (CNN)-based brain tumor diagnosis system using EfficientNetv2s architecture, which was improved with the Ranger optimization and extensive pre-processing. We also compared the proposed model with state-of-the-art deep learning architectures such as ResNet18, ResNet200d, and InceptionV4 in discriminating brain tumors based on their spatial features. We achieved the best micro-average results with 99.85% test accuracy, 99.89% Area under the Curve (AUC), 98.16% precision, 98.17% recall, and 98.21% f1-score. Furthermore, the experimental results of the improved model were compared to various CNN-based architectures using key performance metrics and were shown to have a strong impact on tumor categorization. The proposed system has been experimentally evaluated with different optimizers and compared with recent CNN architectures, on both augmented and original data. The results demonstrated a convincing performance in tumor detection and diagnosis.

A vision of 14 T MR for fundamental and clinical science

OBJECTIVE

We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set.

RESEARCH FIELDS

The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes.

CONCLUSIONS

The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.

Tumor inflammation-associated neurotoxicity

Cancer immunotherapies have unique toxicities. Establishment of grading scales and standardized grade-based treatment algorithms for toxicity syndromes can improve the safety of these treatments, as observed for cytokine release syndrome (CRS) and immune effector cell associated neurotoxicity syndrome (ICANS) in patients with B cell malignancies treated with chimeric antigen receptor (CAR) T cell therapy. We have observed a toxicity syndrome, distinct from CRS and ICANS, in patients treated with cell therapies for tumors in the central nervous system (CNS), which we term tumor inflammation-associated neurotoxicity (TIAN). Encompassing the concept of 'pseudoprogression,' but broader than inflammation-induced edema alone, TIAN is relevant not only to cellular therapies, but also to other immunotherapies for CNS tumors. To facilitate the safe administration of cell therapies for patients with CNS tumors, we define TIAN, propose a toxicity grading scale for TIAN syndrome and discuss the potential management of this entity, with the goal of standardizing both reporting and management.

A Phase I Trial of VEGF-A Inhibition Combined with PD-L1 Blockade for Recurrent Glioblastoma

Purpose

The treatment of glioblastoma (GBM) poses challenges. The use of immune checkpoint inhibition (ICI) has been disappointing as GBM is characterized by low mutational burden and low T-cell infiltration. The combination of ICI with other treatment modalities may improve efficacy.

Patient and Methods

Patients with recurrent GBM were treated with avelumab, a human IgG1 antibody directed against PD-L1 (part A), or avelumab within a week after laser interstitial thermal therapy (LITT) and continuation of avelumab (part B). Bevacizumab was allowed to be combined with ICI to spare steroid use. The primary objective was to characterize the tolerability and safety of the regimens. The secondary objectives included overall survival, progression-free survival (PFS), signatures of plasma analytes, and immune cells.

Results

A total of 12 patients (median age 64; range, 37-73) enrolled, five in part A and seven in part B. Two serious adverse events occurred in the same patient, LITT treated, not leading to death. The median survival from enrollment was 13 months [95% confidence interval (CI), 4-16 months] with no differences for part A or B. The median PFS was 3 months (95% CI, 1.5-4.5 months). The decrease in MICA/MICB, γδT cells, and CD4+ T cell EMRA correlated with prolonged survival.

Conclusions

Avelumab was generally well tolerated. Adding bevacizumab to ICI may be beneficial by lowering cytokine and immune cell expression. The development of this combinatorial treatment warrants further investigation. Exploring the modulation of adaptive and innate immune cells and plasma analytes as biomarker signatures may instruct future studies in this dismal refractory disease.

Significance

Our phase I of PD-L1 inhibition combined with LITT and using bevacizumab to spare steroids had a good safety profile for recurrent GBM. Developing combinatory treatment may help outcomes. In addition, we found significant immune modulation of cytokines and immune cells by bevacizumab, which may enhance the effect of ICI.

Determining the Research Priorities for Adult Primary Brain Tumours in Australia and New Zealand: A Delphi Study with Consumers, Health Professionals, and Researchers

The aim of this project was to determine research priorities, barriers, and enablers for adult primary brain tumour research in Australia and New Zealand. Consumers, health professionals, and researchers were invited to participate in a two-phase modified Delphi study. Phase 1 comprised an initial online survey (n = 91) and then focus groups (n = 29) which identified 60 key research topics, 26 barriers, and 32 enablers. Phase 2 comprised two online surveys to (1) reduce the list to 37 research priorities which achieved consensus (>75% 2-point agreement) and had high mean importance ratings (n = 116 participants) and (2) determine the most important priorities, barriers, and enablers (n = 90 participants). The top ten ranked research priorities for the overall sample and sub-groups (consumers, health professionals, and researchers) were identified. Priorities focused on: tumour biology, pre-clinical research, clinical and translational research, and supportive care. Variations were seen between sub-groups. The top ten barriers to conducting brain tumour research related to funding and resources, accessibility and awareness of research, collaboration, and process. The top ten research enablers were funding and resources, collaboration, and workforce. The broad list of research priorities identified by this Delphi study, together with how consumers, health professionals, and researchers prioritised items differently, and provides an evidence-based research agenda for brain tumour research that is needed across a wide range of areas.