Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.

Adult diffuse gliomas are a diverse group of brain neoplasms that inflict a high emotional toll on patients and their families. The Cancer Genome Atlas and similar projects have provided a comprehensive understanding of the somatic alterations and molecular subtypes of glioma at diagnosis. However, gliomas undergo significant cellular and molecular evolution during disease progression. We review the current knowledge on the genomic and epigenetic abnormalities in primary tumors and after disease recurrence, highlight the gaps in the literature, and elaborate on the need for a new multi-institutional effort to bridge these knowledge gaps and how the Glioma Longitudinal Analysis Consortium (GLASS) aims to systemically catalog the longitudinal changes in gliomas. The GLASS initiative will provide essential insights into the evolution of glioma toward a lethal phenotype, with the potential to reveal targetable vulnerabilities and, ultimately, improved outcomes for a patient population in need.

Stroke-induced cerebral ischemia is a major cause of death and disability. The disruption of blood flow results in neuronal and glial cell death leading to brain injury. Reperfusion restores oxygen to the affected tissue, but can also cause damage through an enhanced oxidative stress and inflammatory response. This study examines mitochondrial transfer from MSC to neurons and the role it plays in neuronal preservation after oxidant injury. We observed the transfer of mitochondria from MSC to mouse neurons in vitro following hydrogen peroxide exposure. The observed transfer was dependent on cell-to-cell contact and led to increased neuronal survival and improved metabolism. A number of pro-inflammatory and mitochondrial motility genes were upregulated in neurons after hydrogen peroxide exposure. This included Miro1 and TNFAIP2, linking inflammation and mitochondrial transfer to oxidant injury. Increasing Miro1 expression in MSC improved the metabolic benefit of mitochondrial transfer after neuronal oxidant injury. Decreasing Miro1 expression had the opposite effect, decreasing the metabolic benefit of MSC co-culture. MSC transfer of mitochondria to oxidant-damaged neurons may help improve neuronal preservation and functional recovery after stroke.

Breast cancer brain metastases (BM) affect younger women disproportionally, including those lacking estrogen receptor (ER), progesterone receptor, and HER2 (known as triple-negative breast cancer; TNBC). Previous studies in preclinical models showed that pre-menopausal levels of estradiol (E2) promote TNBC-BM through incompletely understood mechanisms involving reactive astrocytes. Herein, a novel mechanism involving E2-dependent upregulation of brain-derived neurotrophic factor (BDNF) in astrocytes, and subsequent activation of tumor cell tropomyosin kinase receptor B (TrkB), is identified. E2 increased experimental BM of TNBC 4T1BR5 and E0771 cells by 21 and 3.6 fold, respectively, compared to E2-depleted mice. ERα⁺ reactive astrocytes were found at early and late stages of BM, and E2 upregulated BDNF in ER⁺ reactive astrocytes in vitro and in vivo. TrkB was expressed in TNBC brain-trophic cell lines, BM-patient-derived xenografts, and breast cancer BM. Conditioned media from E2-treated astrocytes (CM-E2) activated TrkB and downstream AKT, ERK, and PLC-γ signaling in TNBC cells, increasing their invasiveness and tumor-initiating capability in vitro. The promotion of BM by E2-activated astrocytes was found to be more complex, involving feedback loops and other receptor tyrosine kinases. In 4T1BR5 cells, there was a positive feedback loop whereby astrocytic BDNF induced cancer cell BDNF translation. Upregulation of cancer cell BDNF was required to promote full invasiveness of 4T1BR5 in response to CM-E2, and was observed in brain metastatic cells in E2-treated mice in vivo. Moreover, the non-competitive BDNF/TrkB inhibitor ANA-12 reduced E2-induced 4T1BR5 BM to levels similar to OVX mice. BDNF also activated EGFR in TrkB⁺EGFR⁺ TNBC cells, suggesting that E2 action through astrocytes activates redundant pathways promoting BM. These findings have important therapeutic implications, as they provide a rationale to use E2-depletion therapies or TrkB inhibitors to prevent or delay development of BM in younger women.

In the treatment of brain tumors, surgical intervention remains a common and effective therapeutic option. Recent advances in neuroimaging have provided neurosurgeons with new tools to overcome the challenge of differentiating healthy tissue from tumor-infiltrated tissue, with the aim of increasing the likelihood of maximizing the extent of resection volume while minimizing injury to functionally important regions. Novel applications of diffusion tensor imaging (DTI), and DTI-derived tractography (DDT) have demonstrated that preoperative, non-invasive mapping of eloquent cortical regions and functionally relevant white matter tracts (WMT) is critical during surgical planning to reduce postoperative deficits, which can decrease quality of life and overall survival. In this review, we summarize the latest developments of applying DTI and tractography in the context of resective surgery and highlight its utility within each stage of the neurosurgical workflow: preoperative planning and intraoperative management to improve postoperative outcomes.