Utility of PD-1, PD-L1, and IDO-1 Stains in Ocular Extranodal Marginal Zone Lymphoma (MZL) and Diffuse Large B-cell Lymphoma (DLBCL).

Extranodal marginal zone lymphoma (EMZL) is the most common subtype of ocular lymphomas. Diffuse large B-cell lymphoma (DLBCL) and EMZL with large-cell transformation present diagnostic challenges. Radiotherapy is the standard treatment for ocular lymphomas, but complications and relapse are common. Diagnostic utility in challenging cases, as well as treatment options using immune checkpoint inhibitors, are unclear in ocular lymphomas. We herein investigated the PD-1, PD-L1, and IDO1 staining patterns in 20 cases of ocular lymphomas, including EMZL (n=14), EMZL with increased large cells (n=2), and DLBCL (n=4). PD-1, PD-L1, and IDO1 staining was not detected in lymphoma cells in any cases but was observed within the tumor microenvironment in all cases. Positivity for PD-1, PD-L1, and IDO1 in inflammatory cells was seen either intratumorally or peritumorally. In all 6 cases with significantly more large B cells, the density of PD-1, PD-L1, and IDO1 expression in the tumor microenvironment was higher than that of the remaining 14 cases without large B cells (P-value<0.0001), whereas other clinicopathologic features showed no statistical correlation. Increased expression of PD-1, PD-L1, and IDO1 in the inflammatory milieu in cases with large cells may provide diagnostic utility in small biopsies as well as therapeutic potential.

Advancing presurgical non-invasive molecular subgroup prediction in medulloblastoma using artificial intelligence and MRI signatures.

Global investigation of medulloblastoma has been hindered by the widespread inaccessibility of molecular subgroup testing and paucity of data. To bridge this gap, we established an international molecularly characterized database encompassing 934 medulloblastoma patients from thirteen centers across China and the United States. We demonstrate how image-based machine learning strategies have the potential to create an alternative pathway for non-invasive, presurgical, and low-cost molecular subgroup prediction in the clinical management of medulloblastoma. Our robust validation strategies-including cross-validation, external validation, and consecutive validation-demonstrate the model's efficacy as a generalizable molecular diagnosis classifier. The detailed analysis of MRI characteristics replenishes the understanding of medulloblastoma through a nuanced radiographic lens. Additionally, comparisons between East Asia and North America subsets highlight critical management implications. We made this comprehensive dataset, which includes MRI signatures, clinicopathological features, treatment variables, and survival data, publicly available to advance global medulloblastoma research.

A rare non-gadolinium enhancing sarcoma brain metastasis with microenvironment dominated by tumor-associated macrophages.

Brain metastases occur in 1% of sarcoma cases and are associated with a median overall survival of 6 months. We report a rare case of a brain metastasis with unique radiologic and histopathologic features in a patient with low grade fibromyxoid sarcoma (LGFMS) previously treated with immune checkpoint inhibitor (ICI) therapy. The lone metastasis progressed in the midbrain tegmentum over 15 months as a non-enhancing, T2-hyperintense lesion with peripheral diffusion restriction, mimicking a demyelinating lesion. Histopathology of the lesion at autopsy revealed a rich infiltrate of tumor-associated macrophages (TAMs) with highest density at the leading edge of the metastasis, whereas there was a paucity of lymphocytes, suggestive of an immunologically cold environment. Given the important immunosuppressive and tumor-promoting functions of TAMs in gliomas and carcinoma/melanoma brain metastases, this unusual case provides an interesting example of a dense TAM infiltrate in a much rarer sarcoma brain metastasis.

A novel mouse model of cerebral adrenoleukodystrophy highlights NLRP3 activity in lesion pathogenesis.

Objective: We sought to create and characterize a mouse model of the inflammatory, cerebral demyelinating phenotype of X-linked adrenoleukodystrophy (ALD) that would facilitate the study of disease pathogenesis and therapy development. We also sought to cross-validate potential therapeutic targets such as fibrin, oxidative stress, and the NLRP3 inflammasome, in post-mortem human and murine brain tissues. Background: ALD is caused by mutations in the gene ABCD1 encoding a peroxisomal transporter. More than half of males with an ABCD1 mutation develop the cerebral phenotype (cALD). Incomplete penetrance and absence of a genotype-phenotype correlation imply a role for environmental triggers. Mechanistic studies have been limited by the absence of a cALD phenotype in the Abcd1-null mouse. Methods: We generated a cALD phenotype in 8-week-old, male Abcd1-null mice by deploying a two-hit method that combines cuprizone (CPZ) and experimental autoimmune encephalomyelitis (EAE) models. We employed in vivo MRI and post-mortem immunohistochemistry to evaluate myelin loss, astrogliosis, blood-brain barrier (BBB) disruption, immune cell infiltration, fibrin deposition, oxidative stress, and Nlrp3 inflammasome activation in mice. We used bead-based immunoassay and immunohistochemistry to evaluate IL-18 in CSF and post-mortem human cALD brain tissue. Results: MRI studies revealed T2 hyperintensities and post-gadolinium enhancement in the medial corpus callosum of cALD mice, similar to human cALD lesions. Both human and mouse cALD lesions shared common histologic features of myelin phagocytosis, myelin loss, abundant microglial activation, T and B-cell infiltration, and astrogliosis. Compared to wild-type controls, Abcd1-null mice had more severe cerebral inflammation, demyelination, fibrin deposition, oxidative stress, and IL-18 activation. IL-18 immunoreactivity co-localized with macrophages/microglia in the perivascular region of both human and mouse brain tissue. Interpretation: This novel mouse model of cALD suggests loss of Abcd1 function predisposes to more severe cerebral inflammation, oxidative stress, fibrin deposition, and Nlrp3 pathway activation, which parallels the findings seen in humans with cALD. We expect this model to enable long-sought investigations into cALD mechanisms and accelerate development of candidate therapies for lesion prevention, cessation, and remyelination.

Treatment Course and Outcomes of Intracranial Teratomas in Pediatric Patients: A Retrospective 15-Year Case Series Study.

INTRODUCTION: There is no standard treatment paradigm for intracranial teratomas, a rare subset of primary intracranial non-germinomatous germ cell tumors (NGGCT), which comprise less than 1% of pediatric brain tumors. This case series retrospectively analyzes treatment and outcomes of pediatric intracranial teratomas from a single institution. METHODS: Authors reviewed a comprehensive pathology database at Stanford's Lucile Packard Children's Hospital for intracranial teratomas in pediatric patients treated from 2006 to 2021; their demographics, treatment, and clinical course were analyzed. RESULTS: Among 14 patients, median follow-up time was 4.6 years and mean age at diagnosis was 10.5 years. Ten had elevated tumor markers and underwent chemotherapy as initial treatment for NGGCT. Ultimately, these patients all required surgery for progressive or residual disease. Two patients did not undergo radiation. After biopsy or resection, 8 patients had pure mature teratoma, five had mixed germ cell tumor with teratoma component, and one had immature teratoma. The patient with immature teratoma died during chemotherapy from septic shock. No patients experienced recurrence. Common sequelae were endocrine (42.8%) and eye movement (50.0%) abnormalities. DISCUSSION/CONCLUSION: We highlight the variable treatment course and outcome for pediatric patients with intracranial teratomas. Elevated tumor markers at presentation, along with imaging findings, favor chemotherapy initiation for presumed NGGCT. Resection of residual tumor is recommended even if tumor markers return to normal. Prognosis remains excellent; no patients had recurrence with a median follow-up of 4.6 years.

Regeneration of neuromuscular synapses after acute and chronic denervation by inhibiting the gerozyme 15-prostaglandin dehydrogenase.

To date, there are no approved treatments for the diminished strength and paralysis that result from the loss of peripheral nerve function due to trauma, heritable neuromuscular diseases, or aging. Here, we showed that denervation resulting from transection of the sciatic nerve triggered a marked increase in the prostaglandin-degrading enzyme 15-hydroxyprostaglandin dehydrogenase (15-PGDH) in skeletal muscle in mice, providing evidence that injury drives early expression of this aging-associated enzyme or gerozyme. Treating mice with a small-molecule inhibitor of 15-PGDH promoted regeneration of motor axons and formation of neuromuscular synapses leading to an acceleration in recovery of force after an acute nerve crush injury. In aged mice with chronic denervation of muscles, treatment with the 15-PGDH inhibitor increased motor neuron viability and restored neuromuscular junctions and function. These presynaptic changes synergized with previously reported muscle tissue remodeling to result in a marked increase in the strength of aged muscles. We further found that 15-PGDH aggregates defined the target fibers that are histopathologic hallmarks of human neurogenic myopathies, suggesting that the gerozyme may be involved in their etiology. Our data suggest that inhibition of 15-PGDH may constitute a therapeutic strategy to physiologically boost prostaglandin E2, restore neuromuscular connectivity, and promote recovery of strength after acute or chronic denervation due to injury, disease, or aging.

Synthetic whole-slide image tile generation with gene expression profile-infused deep generative models.

In this work, we propose an approach to generate whole-slide image (WSI) tiles by using deep generative models infused with matched gene expression profiles. First, we train a variational autoencoder (VAE) that learns a latent, lower-dimensional representation of multi-tissue gene expression profiles. Then, we use this representation to infuse generative adversarial networks (GANs) that generate lung and brain cortex tissue tiles, resulting in a new model that we call RNA-GAN. Tiles generated by RNA-GAN were preferred by expert pathologists compared with tiles generated using traditional GANs, and in addition, RNA-GAN needs fewer training epochs to generate high-quality tiles. Finally, RNA-GAN was able to generalize to gene expression profiles outside of the training set, showing imputation capabilities. A web-based quiz is available for users to play a game distinguishing real and synthetic tiles: https://rna-gan.stanford.edu/, and the code for RNA-GAN is available here: https://github.com/gevaertlab/RNA-GAN.

Rewiring cancer drivers to activate apoptosis.

Genes that drive the proliferation, survival, invasion and metastasis of malignant cells have been identified for many human cancers1-4. Independent studies have identified cell death pathways that eliminate cells for the good of the organism5,6. The coexistence of cell death pathways with driver mutations suggests that the cancer driver could be rewired to activate cell death using chemical inducers of proximity (CIPs). Here we describe a new class of molecules called transcriptional/epigenetic CIPs (TCIPs) that recruit the endogenous cancer driver, or a downstream transcription factor, to the promoters of cell death genes, thereby activating their expression. We focused on diffuse large B cell lymphoma, in which the transcription factor B cell lymphoma 6 (BCL6) is deregulated7. BCL6 binds to the promoters of cell death genes and epigenetically suppresses their expression8. We produced TCIPs by covalently linking small molecules that bind BCL6 to those that bind to transcriptional activators that contribute to the oncogenic program, such as BRD4. The most potent molecule, TCIP1, increases binding of BRD4 by 50% over genomic BCL6-binding sites to produce transcriptional elongation at pro-apoptotic target genes within 15 min, while reducing binding of BRD4 over enhancers by only 10%, reflecting a gain-of-function mechanism. TCIP1 kills diffuse large B cell lymphoma cell lines, including chemotherapy-resistant, TP53-mutant lines, at EC50 of 1-10 nM in 72 h and exhibits cell-specific and tissue-specific effects, capturing the combinatorial specificity inherent to transcription. The TCIP concept also has therapeutic applications in regulating the expression of genes for regenerative medicine and developmental disorders.

PET imaging of TREM1 identifies CNS-infiltrating myeloid cells in a mouse model of multiple sclerosis.

Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system (CNS) that causes substantial morbidity and diminished quality of life. Evidence highlights the central role of myeloid lineage cells in the initiation and progression of MS. However, existing imaging strategies for detecting myeloid cells in the CNS cannot distinguish between beneficial and harmful immune responses. Thus, imaging strategies that specifically identify myeloid cells and their activation states are critical for MS disease staging and monitoring of therapeutic responses. We hypothesized that positron emission tomography (PET) imaging of triggering receptor expressed on myeloid cells 1 (TREM1) could be used to monitor deleterious innate immune responses and disease progression in the experimental autoimmune encephalomyelitis (EAE) mouse model of MS. We first validated TREM1 as a specific marker of proinflammatory, CNS-infiltrating, peripheral myeloid cells in mice with EAE. We show that the 64Cu-radiolabeled TREM1 antibody-based PET tracer monitored active disease with 14- to 17-fold higher sensitivity than translocator protein 18 kDa (TSPO)-PET imaging, the established approach for detecting neuroinflammation in vivo. We illustrate the therapeutic potential of attenuating TREM1 signaling both genetically and pharmacologically in the EAE mice and show that TREM1-PET imaging detected responses to an FDA-approved MS therapy with siponimod (BAF312) in these animals. Last, we observed TREM1+ cells in clinical brain biopsy samples from two treatment-naïve patients with MS but not in healthy control brain tissue. Thus, TREM1-PET imaging has potential for aiding in the diagnosis of MS and monitoring of therapeutic responses to drug treatment.

Pediatric Brain Tumours: Lessons from the Immune Microenvironment.

In spite of recent advances in tumour molecular subtyping, pediatric brain tumours (PBTs) remain the leading cause of cancer-related deaths in children. While some PBTs are treatable with favourable outcomes, recurrent and metastatic disease for certain types of PBTs remains challenging and is often fatal. Tumour immunotherapy has emerged as a hopeful avenue for the treatment of childhood tumours, and recent immunotherapy efforts have been directed towards PBTs. This strategy has the potential to combat otherwise incurable PBTs, while minimizing off-target effects and long-term sequelae. As the infiltration and activation states of immune cells, including tumour-infiltrating lymphocytes and tumour-associated macrophages, are key to shaping responses towards immunotherapy, this review explores the immune landscape of the developing brain and discusses the tumour immune microenvironments of common PBTs, with hopes of conferring insights that may inform future treatment design.

Cytodifferentiation of pituitary tumors influences pathogenesis and cavernous sinus invasion.

OBJECTIVE: Pituitary tumors (PTs) continue to present unique challenges given their proximity to the cavernous sinus, whereby invasive behavior can limit the extent of resection and surgical outcome, especially in functional tumors. The aim of this study was to elucidate patterns of cavernoinvasive behavior by PT subtype. METHODS: A total of 169 consecutive first-time surgeries for PTs were analyzed; 45% of the tumors were functional. There were 64 pituitary transcription factor-1 (PIT-1)-expressing, 62 steroidogenic factor-1 (SF-1)-expressing, 38 T-box transcription factor (TPIT)-expressing, and 5 nonstaining PTs. The gold standard for cavernous sinus invasion (CSI) was based on histopathological examination of the cavernous sinus medial wall and intraoperative exploration. RESULTS: Cavernous sinus disease was present in 33% of patients. Of the Knosp grade 3 and 4 tumors, 12 (19%) expressed PIT-1, 7 (11%) expressed SF-1, 8 (21%) expressed TPIT, and 2 (40%), were nonstaining (p = 0.36). PIT-1 tumors had a significantly higher predilection for CSI: 53% versus 24% and 18% for TPIT and SF-1 tumors, respectively (OR 6.08, 95% CI 2.86-13.55; p < 0.001). Microscopic CSI-defined as Knosp grade 0-2 tumors with confirmed invasion-was present in 44% of PIT-1 tumors compared with 7% and 13% of TPIT and SF-1 tumors, respectively (OR 11.72, 95% CI 4.35-35.50; p < 0.001). Using the transcavernous approach to excise cavernous sinus disease, surgical biochemical remission rates for patients with acromegaly, prolactinoma, and Cushing disease were 88%, 87%, and 100%, respectively. The granule density of PIT-1 tumors and corticotroph functional status did not influence CSI. CONCLUSIONS: The likelihood of CSI differed by transcription factor expression; PIT-1-expressing tumors had a higher predilection for invading the cavernous sinus, particularly microscopically, compared with the other tumor subtypes. This elucidates a unique cavernoinvasive behavior absent in cells from other lineages. Innovative surgical techniques, however, can mitigate tumor behavior and achieve robust, reproducible biochemical remission and gross-total resection rates. These findings can have considerable implications on the surgical management and study of PT biology and behavior.

Purification and characterization of human neural stem and progenitor cells.

The human brain undergoes rapid development at mid-gestation from a pool of neural stem and progenitor cells (NSPCs) that give rise to the neurons, oligodendrocytes, and astrocytes of the mature brain. Functional study of these cell types has been hampered by a lack of precise purification methods. We describe a method for prospectively isolating ten distinct NSPC types from the developing human brain using cell-surface markers. CD24-THY1-/lo cells were enriched for radial glia, which robustly engrafted and differentiated into all three neural lineages in the mouse brain. THY1hi cells marked unipotent oligodendrocyte precursors committed to an oligodendroglial fate, and CD24+THY1-/lo cells marked committed excitatory and inhibitory neuronal lineages. Notably, we identify and functionally characterize a transcriptomically distinct THY1hiEGFRhiPDGFRA- bipotent glial progenitor cell (GPC), which is lineage-restricted to astrocytes and oligodendrocytes, but not to neurons. Our study provides a framework for the functional study of distinct cell types in human neurodevelopment.

Multimodal deep learning to predict prognosis in adult and pediatric brain tumors.

BACKGROUND: The introduction of deep learning in both imaging and genomics has significantly advanced the analysis of biomedical data. For complex diseases such as cancer, different data modalities may reveal different disease characteristics, and the integration of imaging with genomic data has the potential to unravel additional information than when using these data sources in isolation. Here, we propose a DL framework that combines these two modalities with the aim to predict brain tumor prognosis. METHODS: Using two separate glioma cohorts of 783 adults and 305 pediatric patients we developed a DL framework that can fuse histopathology images with gene expression profiles. Three strategies for data fusion were implemented and compared: early, late, and joint fusion. Additional validation of the adult glioma models was done on an independent cohort of 97 adult patients. RESULTS: Here we show that the developed multimodal data models achieve better prediction results compared to the single data models, but also lead to the identification of more relevant biological pathways. When testing our adult models on a third brain tumor dataset, we show our multimodal framework is able to generalize and performs better on new data from different cohorts. Leveraging the concept of transfer learning, we demonstrate how our pediatric multimodal models can be used to predict prognosis for two more rare (less available samples) pediatric brain tumors. CONCLUSIONS: Our study illustrates that a multimodal data fusion approach can be successfully implemented and customized to model clinical outcome of adult and pediatric brain tumors.

An increasing amount of complex patient data is generated when treating patients with cancer, including histopathology data (where the appearance of a tumor is examined under a microscope) and molecular data (such as analysis of a tumor's genetic material). Computational methods to integrate these data types might help us to predict outcomes in patients with cancer. Here, we propose a deep learning method which involves computer software learning from patterns in the data, to combine histopathology and molecular data to predict outcomes in patients with brain cancers. Using three cohorts of patients, we show that our method combining the different datasets performs better than models using one data type. Methods like ours might help clinicians to better inform patients about their prognosis and make decisions about their care.

Multifocal demyelinating leukoencephalopathy and oligodendroglial lineage cell loss with immune effector cell-associated neurotoxicity syndrome (ICANS) following CD19 CAR T-cell therapy for mantle cell lymphoma.

Immune effector cell-associated neurotoxicity syndrome (ICANS) is a prevalent condition seen after treatment with chimeric antigen receptor T-cell (CAR T) therapy and other cancer cell therapies. The underlying pathophysiology and neuropathology of the clinical syndrome are incompletely understood due to the limited availability of brain tissue evaluation from patient cases, and a lack of high-fidelity preclinical animal models for translational research. Here, we present the cellular and tissue neuropathologic analysis of a patient who experienced grade 4 ICANS after treatment with anti-CD19 CAR T therapy for mantle cell lymphoma. Our pathologic evaluation reveals a pattern of multifocal demyelinating leukoencephalopathy associated with a clinical course of severe ICANS. A focused analysis of glial subtypes further suggests region-specific oligodendrocyte lineage cell loss as a potential cellular and pathophysiologic correlate in severe ICANS. We propose a framework for the continuum of neuropathologic changes thus far reported across ICANS cases. Future elucidation of the mechanistic processes underlying ICANS will be critical in minimizing neurotoxicity following CAR T-cell and related immunotherapy treatments across oncologic and autoimmune diseases.