Multimodal imaging of the dynamic brain tumor microenvironment during glioblastoma progression and in response to treatment

Microenvironmental reorganization in brain tumors following radiotherapy and recurrence revealed by hyperplexed immunofluorescence imaging

The tumor microenvironment plays a crucial role in determining response to treatment. This involves a series of interconnected changes in the cellular landscape, spatial organization, and extracellular matrix composition. However, assessing these alterations simultaneously is challenging from a spatial perspective, due to the limitations of current high-dimensional imaging techniques and the extent of intratumoral heterogeneity over large lesion areas. In this study, we introduce a spatial proteomic workflow termed Hyperplexed Immunofluorescence Imaging (HIFI) that overcomes these limitations. HIFI allows for the simultaneous analysis of > 45 markers in fragile tissue sections at high magnification, using a cost-effective high-throughput workflow. We integrate HIFI with machine learning feature detection, graph-based network analysis, and cluster-based neighborhood analysis to analyze the microenvironment response to radiation therapy in a preclinical model of glioblastoma, and compare this response to a mouse model of breast-to-brain metastasis. Here we show that glioblastomas undergo extensive spatial reorganization of immune cell populations and structural architecture in response to treatment, while brain metastases show no comparable reorganization. Our integrated spatial analyses reveal highly divergent responses to radiation therapy between brain tumor models, despite equivalent radiotherapy benefit.

Volume imaging to interrogate cancer cell-tumor microenvironment interactions in space and time

Volume imaging visualizes the three-dimensional (3D) complexity of tumors to unravel the dynamic crosstalk between cancer cells and the heterogeneous landscape of the tumor microenvironment (TME). Tissue clearing and intravital microscopy (IVM) constitute rapidly progressing technologies to study the architectural context of such interactions. Tissue clearing enables high-resolution imaging of large samples, allowing for the characterization of entire tumors and even organs and organisms with tumors. With IVM, the dynamic engagement between cancer cells and the TME can be visualized in 3D over time, allowing for acquisition of 4D data. Together, tissue clearing and IVM have been critical in the examination of cancer-TME interactions and have drastically advanced our knowledge in fundamental cancer research and clinical oncology. This review provides an overview of the current technical repertoire of fluorescence volume imaging technologies to study cancer and the TME, and discusses how their recent applications have been utilized to advance our fundamental understanding of tumor architecture, stromal and immune infiltration, vascularization and innervation, and to explore avenues for immunotherapy and optimized chemotherapy delivery.

Multimodal data fusion for cancer biomarker discovery with deep learning

Technological advances now make it possible to study a patient from multiple angles with high-dimensional, high-throughput multi-scale biomedical data. In oncology, massive amounts of data are being generated ranging from molecular, histopathology, radiology to clinical records. The introduction of deep learning has significantly advanced the analysis of biomedical data. However, most approaches focus on single data modalities leading to slow progress in methods to integrate complementary data types. Development of effective multimodal fusion approaches is becoming increasingly important as a single modality might not be consistent and sufficient to capture the heterogeneity of complex diseases to tailor medical care and improve personalised medicine. Many initiatives now focus on integrating these disparate modalities to unravel the biological processes involved in multifactorial diseases such as cancer. However, many obstacles remain, including lack of usable data as well as methods for clinical validation and interpretation. Here, we cover these current challenges and reflect on opportunities through deep learning to tackle data sparsity and scarcity, multimodal interpretability, and standardisation of datasets.

Cranial imaging window implantation technique for longitudinal multimodal imaging of the brain environment in live mice

Intravital two-photon microscopy of the mouse brain requires visual access without affecting normal cognitive functions, which is crucial for longitudinal imaging studies that may last several months. In this protocol, we describe the surgical implantation of a metal-free cranial imaging window, which can be used to perform two-photon microscopy and magnetic resonance imaging in the same animal. This multimodal imaging platform enables the investigation of dynamic processes in the central nervous system at a cellular and macroscopic level. For complete details on the use and execution of this protocol in the context of brain cancer, please refer to Zomer et al.¹.

In vivo imaging of inflammatory response in cancer research

Inflammation can contribute to the development and progression of cancer. The inflammatory responses in the tumor microenvironment are shaped by complex sequences of dynamic intercellular cross-talks among diverse types of cells, and recapitulation of these dynamic events in vitro has yet to be achieved. Today, intravital microscopy with two-photon excitation microscopes (2P-IVM) is the mainstay technique for observing intercellular cross-talks in situ, unraveling cellular and molecular mechanisms in the context of their spatiotemporal dynamics. In this review, we summarize the current state of 2P-IVM with fluorescent indicators of signal transduction to reveal the cross-talks between cancer cells and surrounding cells including both immune and non-immune cells. We also discuss the potential application of red-shifted indicators along with optogenetic tools to 2P-IVM. In an era of single-cell transcriptomics and data-driven research, 2P-IVM will remain a key advantage in delivering the missing spatiotemporal context in the field of cancer research.

Dual Immunostimulatory Pathway Agonism through a Synthetic Nanocarrier Triggers Robust Anti-Tumor Immunity in Murine Glioblastoma

Myeloid cells are abundant, create a highly immunosuppressive environment in glioblastoma (GBM), and thus contribute to poor immunotherapy responses. Based on the hypothesis that small molecules can be used to stimulate myeloid cells to elicit anti-tumor effector functions, a synthetic nanoparticle approach is developed to deliver dual NF-kB pathway-inducing agents into these cells via systemic administration. Synthetic, cyclodextrin-adjuvant nanoconstructs (CANDI) with high affinity for tumor-associated myeloid cells are dually loaded with a TLR7 and 8 (Toll-like receptor, 7 and 8) agonist (R848) and a cIAP (cellular inhibitor of apoptosis protein) inhibitor (LCL-161) to dually activate these myeloid cells. Here CANDI is shown to: i) readily enter the GBM tumor microenvironment (TME) and accumulate at high concentrations, ii) is taken up by tumor-associated myeloid cells, iii) potently synergize payloads compared to monotherapy, iv) activate myeloid cells, v) fosters a "hot" TME with high levels of T effector cells, and vi) controls the growth of murine GBM as mono- and combination therapies with anti-PD1. Multi-pathway targeted myeloid stimulation via the CANDI platform can efficiently drive anti-tumor immunity in GBM.

Significant Systemic Insulin Resistance is Associated With Unique Glioblastoma Multiforme Phenotype

Background

Some glioblastoma multiforme (GBM) are characterized by the presence of gemistocytes (GCs), a unique phenotype of reactive astrocytes. Certain GCs can be identified as neoplastic cells but these cells were also found to be associated with diabetes in non-neoplastic lesions of the central nervous system. Our aim was to find a correlation between insulin - resistance metabolic features and the presence of GCs in patients with newly diagnosed GBM.

Methods

Medical records from histologically confirmed GBM patients were retrospectively extracted for different systemic metabolic variables. A statistic-based comparison was made between GBM, diabetic patients with and without GC. Patients with poorly controlled diabetes (ie, hemoglobin A1C ⩾ 8.0) were also compared between the 2 groups.

Results

A total of 220 newly diagnosed GBM patients were included in our study. 58 (26.3%) patients had a history of diabetes mellitus type 2 (DM2) at the time of admission. The rate of poorly-controlled DM2 was nearly as twice in the GC-GBM group than in the non-GC GBM group (18.75% vs 9.5%; P = .130). In the DM2 cohort, the subgroup of GC-GBM was significantly associated with demographic and metabolic features related to insulin resistance such as male gender predominance (89% vs 50%, P = .073) and morbid obesity (weight ⩾85 kg: OR 6.16; P = .0019 and mean BMI: 34.1 ± 11.42 vs 28.7 ± 5.44; P = .034 for group with and without GCs, respectively). In the poorly-controlled DM2 group, none of the GC-GBM patients were using insulin prior to diagnosis, compared to 61.1% in the non-GC GBM patients (OR = 0.04, P = .045).

Conclusion

Systemic metabolic factors related to marked insulin resistance (DM2, morbid obesity, male gender) are associated with a unique histologic phenotype of GBM, characterized by the presence of GCs. This feature is prominent in poorly-controlled DM2 GBM patients who are not using synthetic insulin. This novel finding may add to the growing data on the relevance of glucose metabolism in astrocytes and in astrocytes associated with high-grade gliomas. In GBM patients, a correlation between patients' metabolic status, tumor's histologic phenotype, tumor's molecular changes, use of anti-diabetic drugs and the respective impact of these factor on survival warrants further investigation.

Cell signaling activation and extracellular matrix remodeling underpin glioma tumor microenvironment heterogeneity and organization

PURPOSE

Tumor cells thrive by adapting to the signals in their microenvironment. To adapt, cancer cells activate signaling and transcriptional programs and migrate to establish micro-niches, in response to signals from neighboring cells and non-cellular stromal factors. Understanding how the tumor microenvironment evolves during disease progression is crucial to deciphering the mechanisms underlying the functional behavior of cancer cells.

METHODS

Multiplex immunohistochemistry, spatial analysis and histological dyes were used to identify and measure immune cell infiltration, cell signal activation and extracellular matrix deposition in low-grade, high-grade astrocytoma and glioblastoma.

RESULTS

We show that lower grade astrocytoma tissue is largely devoid of infiltrating immune cells and extracellular matrix proteins, while high-grade astrocytoma exhibits abundant immune cell infiltration, activation, and extensive tissue remodeling. Spatial analysis shows that most T-cells are restricted to perivascular regions, but bone marrow-derived macrophages penetrate deep into neoplastic cell-rich regions. The tumor microenvironment is characterized by heterogeneous PI3K, MAPK and CREB signaling, with specific signaling profiles correlating with distinct pathological hallmarks, including angiogenesis, tumor cell density and regions where neoplastic cells border the extracellular matrix. Our results also show that tissue remodeling is important in regulating the architecture of the tumor microenvironment during tumor progression.

CONCLUSION

The tumor microenvironment in malignant astrocytoma, exhibits changes in cell composition, cell signaling activation and extracellular matrix deposition during disease development and that targeting the extracellular matrix, as well as cell signaling activation will be critical to designing personalized therapy.

Multiparametric Longitudinal Profiling of RCAS-tva-Induced PDGFB-Driven Experimental Glioma

Glioblastomas are incurable primary brain tumors harboring a heterogeneous landscape of genetic and metabolic alterations. Longitudinal imaging by MRI and [18F]FET-PET measurements enable us to visualize the features of evolving tumors in a dynamic manner. Yet, close-meshed longitudinal imaging time points for characterizing temporal and spatial metabolic alterations during tumor evolution in patients is not feasible because patients usually present with already established tumors. The replication-competent avian sarcoma-leukosis virus (RCAS)/tumor virus receptor-A (tva) system is a powerful preclinical glioma model offering a high grade of spatial and temporal control of somatic gene delivery in vivo. Consequently, here, we aimed at using MRI and [18F]FET-PET to identify typical neuroimaging characteristics of the platelet-derived growth factor B (PDGFB)-driven glioma model using the RCAS-tva system. Our study showed that this preclinical glioma model displays MRI and [18F]FET-PET features that highly resemble the corresponding established human disease, emphasizing the high translational relevance of this experimental model. Furthermore, our investigations unravel exponential growth dynamics and a model-specific tumor microenvironment, as assessed by histology and immunochemistry. Taken together, our study provides further insights into this preclinical model and advocates for the imaging-stratified design of preclinical therapeutic interventions.

Multispectral fluorine-19 MRI enables longitudinal and noninvasive monitoring of tumor-associated macrophages

High-grade gliomas, the most common and aggressive primary brain tumors, are characterized by a complex tumor microenvironment (TME). Among the immune cells infiltrating the glioma TME, tumor-associated microglia and macrophages (TAMs) constitute the major compartment. In patients with gliomas, increased TAM abundance is associated with more aggressive disease. Alterations in TAM phenotypes and functions have been reported in preclinical models of multiple cancers during tumor development and after therapeutic interventions, including radiotherapy and molecular targeted therapies. These findings indicate that it is crucial to evaluate TAM abundance and dynamics over time. Current techniques to quantify TAMs in patients rely mainly on histological staining of tumor biopsies. Although informative, these techniques require an invasive procedure to harvest the tissue sample and typically only result in a snapshot of a small region at a single point in time. Fluorine isotope 19 MRI (¹⁹F MRI) represents a powerful means to noninvasively and longitudinally monitor myeloid cells in pathological conditions by intravenously injecting perfluorocarbon-containing nanoparticles (PFC-NP). In this study, we demonstrated the feasibility and power of ¹⁹F MRI in preclinical models of gliomagenesis, breast-to-brain metastasis, and breast cancer and showed that the major cellular source of ¹⁹F signal consists of TAMs. Moreover, multispectral ¹⁹F MRI with two different PFC-NP allowed us to identify spatially and temporally distinct TAM niches in radiotherapy-recurrent murine gliomas. Together, we have imaged TAMs noninvasively and longitudinally with integrated cellular, spatial, and temporal resolution, thus revealing important biological insights into the critical functions of TAMs, including in disease recurrence.

The complex interactions between the cellular and non-cellular components of the brain tumor microenvironmental landscape and their therapeutic implications

Glioblastoma (GBM), an aggressive high-grade glial tumor, is resistant to therapy and has a poor prognosis due to its universal recurrence rate. GBM cells interact with the non-cellular components in the tumor microenvironment (TME), facilitating their rapid growth, evolution, and invasion into the normal brain. Herein we discuss the complexity of the interactions between the cellular and non-cellular components of the TME and advances in the field as a whole. While the stroma of non-central nervous system (CNS) tissues is abundant in fibrillary collagens, laminins, and fibronectin, the normal brain extracellular matrix (ECM) predominantly includes proteoglycans, glycoproteins, and glycosaminoglycans, with fibrillary components typically found only in association with the vasculature. However, recent studies have found that in GBMs, the microenvironment evolves into a more complex array of components, with upregulated collagen gene expression and aligned fibrillary ECM networks. The interactions of glioma cells with the ECM and the degradation of matrix barriers are crucial for both single-cell and collective invasion into neighboring brain tissue. ECM-regulated mechanisms also contribute to immune exclusion, resulting in a major challenge to immunotherapy delivery and efficacy. Glioma cells chemically and physically control the function of their environment, co-opting complex signaling networks for their own benefit, resulting in radio- and chemo-resistance, tumor recurrence, and cancer progression. Targeting these interactions is an attractive strategy for overcoming therapy resistance, and we will discuss recent advances in preclinical studies, current clinical trials, and potential future clinical applications. In this review, we also provide a comprehensive discussion of the complexities of the interconnected cellular and non-cellular components of the microenvironmental landscape of brain tumors to guide the development of safe and effective therapeutic strategies against brain cancer.

Managing the TME to improve the efficacy of cancer therapy

The tumor microenvironment (TME) influences tumor growth, metastatic spread and response to treatment. Often immunosuppression, mediated by the TME, impairs a beneficial response. The complexity of the tumor composition challenges our abilities to design new and more effective therapies. Going forward we will need to 'manage' the content and or functionality of the TME to improve treatment outcomes. Currently, several different kinds of treatments are available to patients with cancer: there are the traditional approaches of chemotherapy, radiation and surgery; there are targeted agents that inhibit kinases associated with oncogenic pathways; there are monoclonal antibodies that target surface antigens often delivering toxic payloads or cells and finally there are antibodies and biologics that seek to overcome the immunosuppression caused by elements within the TME. How each of these therapies interact with the TME is currently under intense and widespread investigation. In this review we describe how the TME and its immunosuppressive components can influence both tumor progression and response to treatment focusing on three particular tumor types, classic Hodgkin Lymphoma (cHL), Pancreatic Ductal Adenocarcinoma (PDAC) and Glioblastoma Multiforme (GBM). And, finally, we offer five approaches to manipulate or manage the TME to improve outcomes for cancer patients.