Health-related quality-of-life results from the randomised phase II TAVAREC trial on temozolomide with or without bevacizumab in 1p/19q intact first-recurrence World Health Organization grade 2 and 3 glioma (European Organization for Research and Treatment of Cancer 26091)

BACKGROUND: In an international randomised controlled phase II study of temozolomide (TMZ) versus TMZ in combination with bevacizumab (BEV) in locally diagnosed non-1p/19q co-deleted World Health Organization grade 2 or 3 gliomas with a first and contrast-enhancing recurrence after initial radiotherapy, and overall survival at 12 months was not significantly different (61% in the TMZ arm and 55% in the TMZ + BEV arm). OBJECTIVES: Health-related quality of life (HRQoL) was a key secondary end-point in this trial, and the main objective of this study was to determine the impact of the addition of BEV to TMZ on HRQoL. METHODS: HRQoL was assessed using the European Organization for Research and Treatment of Cancer QLQ-C30 (version 3) and QLQ-BN20 at baseline, and then every 12 weeks until disease progression. The pre-selected primary HRQoL end-point was the QLQ-C30 global health scale, with self-perceived cognitive functioning and pain selected as secondary HRQoL issues. Analysis was undertaken using linear mixed modelling and complemented with sensitivity analyses using summary statistics. A difference was considered clinically relevant with ≥10 points difference on a 100-point scale. RESULTS: Baseline compliance was high at 94% and remained above 60% until 72 weeks, limiting the analysis to 60 weeks. Compliance was similar in both arms. We found no statistically significant or clinically significant differences between the primary HRQoL end-point in both treatment arms (p = 0.2642). The sensitivity analyses confirmed this finding. The overall test for post-baseline differences between the two treatment arms also showed no statistically or clinically significant differences regarding the selected secondary end-point scales. INTERPRETATION: The addition of BEV to TMZ in this patient group neither improves nor negatively impacts HRQoL

Mathematical modeling to elucidate brain tumor abrogation by immunotherapy with T11 target structure

T11 Target structure (T11TS), a membrane glycoprotein isolated from sheep erythrocytes, reverses the immune suppressed state of brain tumor induced animals by boosting the functional status of the immune cells. This study aims at aiding in the design of more efficacious brain tumor therapies with T11 target structure. We propose a mathematical model for brain tumor (glioma) and the immune system interactions, which aims in designing efficacious brain tumor therapy. The model encompasses considerations of the interactive dynamics of macrophages, cytotoxic T lymphocytes, glioma cells, TGF-$\beta$, IFN-$\gamma$ and the T11TS. The system undergoes sensitivity analysis, that determines which state variables are sensitive to the given parameters and the parameters are estimated from the published data. Computer simulations were used for model verification and validation, which highlight the importance of T11 target structure in brain tumor therapy

Extracellular Matrix Protein Tenascin C Increases Phagocytosis Mediated by CD47 Loss of Function in Glioblastoma.

Glioblastomas (GBM) are highly infiltrated by myeloid-derived innate immune cells that contribute to the immunosuppressive nature of the brain tumor microenvironment (TME). CD47 has been shown to mediate immune evasion, as the CD47-SIRPα axis prevents phagocytosis of tumor cells by macrophages and other myeloid cells. In this study, we established CD47 homozygous deletion (CD47-/-) in human and mouse GBM cells and investigated the impact of eliminating the "don't eat me" signal on tumor growth and tumor-TME interactions. CD47 knockout (KO) did not significantly alter tumor cell proliferation in vitro but significantly increased phagocytosis of tumor cells by macrophages in cocultures. Compared with CD47 wild-type xenografts, orthotopic xenografts derived from CD47-/- tumor cells grew significantly slower with enhanced tumor cell phagocytosis and increased recruitment of M2-like tumor-associated microglia/macrophages (TAM). CD47 KO increased tumor-associated extracellular matrix protein tenascin C (TNC) in xenografts, which was further examined in vitro. CD47 loss of function upregulated TNC expression in tumor cells via a Notch pathway-mediated mechanism. Depletion of TNC in tumor cells enhanced the growth of CD47-/- xenografts in vivo and decreased the number of TAM. TNC knockdown also inhibited phagocytosis of CD47-/- tumor cells in cocultures. Furthermore, TNC stimulated release of proinflammatory factors including TNFα via a Toll-like receptor 4 and STAT3-dependent mechanism in human macrophage cells. These results reveal a vital role for TNC in immunomodulation in brain tumor biology and demonstrate the prominence of the TME extracellular matrix in affecting the antitumor function of brain innate immune cells. SIGNIFICANCE: These findings link TNC to CD47-driven phagocytosis and demonstrate that TNC affects the antitumor function of brain TAM, facilitating the development of novel innate immune system-based therapies for brain tumors

Modeling brain dynamics in brain tumor patients using the virtual brain

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance

The role of the immune system in brain metastasis

Metastatic brain tumors are the most common brain tumors in adults. With numerous successful advancements in systemic treatment of most common cancer types, brain metastasis is becoming increasingly important in the overall prognosis of cancer patients. Brain metastasis of peripheral tumor is the result of complex interplay of primary tumor, immune system and central nervous system microenvironment. Once formed, brain metastases hide behind the blood brain barrier and become inaccessible to chemotherapies that are otherwise successful in targeting systemic cancer. The approval of immune checkpoint inhibitors for several common cancers such as advanced melanoma and lung cancers brings with it the opportunity and obligation to further understand the mechanisms of immunosuppression by tumors that spread to the brain as well as the interaction between the brain environment and tumor microenvironment. In this review paper we define the central role of the immune system in the development of brain metastases. We performed a comprehensive review of the literature to outline the molecular mechanisms of immunosuppression used by tumors and how the immune system interacts with the central nervous system to facilitate brain metastasis. In particular we discuss the tumor-type-specific mechanisms of metastasis of cancers that preferentially metastasize to the brain as well as the therapies that effectively modulate the immune response, such as immune checkpoint inhibitors and vaccines

Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans

The magnetic resonance (MR) analysis of brain tumors is widely used for diagnosis and examination of tumor subregions. The overlapping area among the intensity distribution of healthy, enhancing, non-enhancing, and edema regions makes the automatic segmentation a challenging task. Here, we show that a convolutional neural network trained on high-contrast images can transform the intensity distribution of brain lesions in its internal subregions. Specifically, a generative adversarial network (GAN) is extended to synthesize high-contrast images. A comparison of these synthetic images and real images of brain tumor tissue in MR scans showed significant segmentation improvement and decreased the number of real channels for segmentation. The synthetic images are used as a substitute for real channels and can bypass real modalities in the multimodal brain tumor segmentation framework. Segmentation results on BraTS 2019 dataset demonstrate that our proposed approach can efficiently segment the tumor areas. In the end, we predict patient survival time based on volumetric features of the tumor subregions as well as the age of each case through several regression models