Cancer Stem Cell-Secreted Macrophage Migration Inhibitory Factor Stimulates Myeloid Derived Suppressor Cell Function and Facilitates Glioblastoma Immune Evasion.

Shifting the balance away from tumor-mediated immune suppression toward tumor immune rejection is the conceptual foundation for a variety of immunotherapy efforts currently being tested. These efforts largely focus on activating antitumor immune responses but are confounded by multiple immune cell populations, including myeloid-derived suppressor cells (MDSCs), which serve to suppress immune system function. We have identified immune-suppressive MDSCs in the brains of GBM patients and found that they were in close proximity to self-renewing cancer stem cells (CSCs). MDSCs were selectively depleted using 5-flurouracil (5-FU) in a low-dose administration paradigm, which resulted in prolonged survival in a syngeneic mouse model of glioma. In coculture studies, patient-derived CSCs but not nonstem tumor cells selectively drove MDSC-mediated immune suppression. A cytokine screen revealed that CSCs secreted multiple factors that promoted this activity, including macrophage migration inhibitory factor (MIF), which was produced at high levels by CSCs. Addition of MIF increased production of the immune-suppressive enzyme arginase-1 in MDSCs in a CXCR2-dependent manner, whereas blocking MIF reduced arginase-1 production. Similarly to 5-FU, targeting tumor-derived MIF conferred a survival advantage to tumor-bearing animals and increased the cytotoxic T cell response within the tumor. Importantly, tumor cell proliferation, survival, and self-renewal were not impacted by MIF reduction, demonstrating that MIF is primarily an indirect promoter of GBM progression, working to suppress immune rejection by activating and protecting immune suppressive MDSCs within the GBM tumor microenvironment. Stem Cells 2016;34:2026-2039.

Development of a Fluorescent Reporter System to Delineate Cancer Stem Cells in Triple-Negative Breast Cancer.

Advanced cancers display cellular heterogeneity driven by self-renewing, tumorigenic cancer stem cells (CSCs). The use of cell lines to model CSCs is challenging due to the difficulty of identifying and isolating cell populations that possess differences in self-renewal and tumor initiation. To overcome these barriers in triple-negative breast cancer (TNBC), we developed a CSC system using a green fluorescent protein (GFP) reporter for the promoter of the well-established pluripotency gene NANOG. NANOG-GFP+ cells gave rise to both GFP+ and GFP(-) cells, and GFP+ cells possessed increased levels of the embryonic stem cell transcription factors NANOG, SOX2, and OCT4 and elevated self-renewal and tumor initiation capacities. GFP+ cells also expressed mesenchymal markers and demonstrated increased invasion. Compared with the well-established CSC markers CD24(-) /CD44(+) , CD49f, and aldehyde dehydrogenase (ALDH) activity, our NANOG-GFP reporter system demonstrated increased enrichment for CSCs. To explore the utility of this system as a screening platform, we performed a flow cytometry screen that confirmed increased CSC marker expression in the GFP+ population and identified new cell surface markers elevated in TNBC CSCs, including junctional adhesion molecule-A (JAM-A). JAM-A was highly expressed in GFP+ cells and patient-derived xenograft ALDH+ CSCs compared with the GFP(-) and ALDH(-) cells, respectively. Depletion of JAM-A compromised self-renewal, whereas JAM-A overexpression induced self-renewal in GFP(-) cells. Our data indicate that we have defined and developed a robust system to monitor differences between CSCs and non-CSCs in TNBC that can be used to identify CSC-specific targets for the development of future therapeutic strategies.

Cancer stem cell-specific scavenger receptor CD36 drives glioblastoma progression.

Glioblastoma (GBM) contains a self-renewing, tumorigenic cancer stem cell (CSC) population which contributes to tumor propagation and therapeutic resistance. While the tumor microenvironment is essential to CSC self-renewal, the mechanisms by which CSCs sense and respond to microenvironmental conditions are poorly understood. Scavenger receptors are a broad class of membrane receptors well characterized on immune cells and instrumental in sensing apoptotic cellular debris and modified lipids. Here, we provide evidence that CSCs selectively use the scavenger receptor CD36 to promote their maintenance using patient-derived CSCs and in vivo xenograft models. CD36 expression was observed in GBM cells in addition to previously described cell types including endothelial cells, macrophages, and microglia. CD36 was enriched in CSCs and was able to functionally distinguish self-renewing cells. CD36 was coexpressed with integrin alpha 6 and CD133, previously described CSC markers, and CD36 reduction resulted in concomitant loss of integrin alpha 6 expression, self-renewal, and tumor initiation capacity. We confirmed oxidized phospholipids, ligands of CD36, were present in GBM and found that the proliferation of CSCs, but not non-CSCs, increased with exposure to oxidized low-density lipoprotein. CD36 was an informative biomarker of malignancy and negatively correlated to patient prognosis. These results provide a paradigm for CSCs to thrive by the selective enhanced expression of scavenger receptors, providing survival, and metabolic advantages.

Segmentation of cellular ultrastructures on sparsely labeled 3D electron microscopy images using deep learning.

Focused ion beam-scanning electron microscopy (FIB-SEM) images can provide a detailed view of the cellular ultrastructure of tumor cells. A deeper understanding of their organization and interactions can shed light on cancer mechanisms and progression. However, the bottleneck in the analysis is the delineation of the cellular structures to enable quantitative measurements and analysis. We mitigated this limitation using deep learning to segment cells and subcellular ultrastructure in 3D FIB-SEM images of tumor biopsies obtained from patients with metastatic breast and pancreatic cancers. The ultrastructures, such as nuclei, nucleoli, mitochondria, endosomes, and lysosomes, are relatively better defined than their surroundings and can be segmented with high accuracy using a neural network trained with sparse manual labels. Cell segmentation, on the other hand, is much more challenging due to the lack of clear boundaries separating cells in the tissue. We adopted a multi-pronged approach combining detection, boundary propagation, and tracking for cell segmentation. Specifically, a neural network was employed to detect the intracellular space; optical flow was used to propagate cell boundaries across the z-stack from the nearest ground truth image in order to facilitate the separation of individual cells; finally, the filopodium-like protrusions were tracked to the main cells by calculating the intersection over union measure for all regions detected in consecutive images along z-stack and connecting regions with maximum overlap. The proposed cell segmentation methodology resulted in an average Dice score of 0.93. For nuclei, nucleoli, and mitochondria, the segmentation achieved Dice scores of 0.99, 0.98, and 0.86, respectively. The segmentation of FIB-SEM images will enable interpretative rendering and provide quantitative image features to be associated with relevant clinical variables.

A workflow for visualizing human cancer biopsies using large-format electron microscopy.

Recent developments in large format electron microscopy have enabled generation of images that provide detailed ultrastructural information on normal and diseased cells and tissues. Analyses of these images increase our understanding of cellular organization and interactions and disease-related changes therein. In this manuscript, we describe a workflow for two-dimensional (2D) and three-dimensional (3D) imaging, including both optical and scanning electron microscopy (SEM) methods, that allow pathologists and cancer biology researchers to identify areas of interest from human cancer biopsies. The protocols and mounting strategies described in this workflow are compatible with 2D large format EM mapping, 3D focused ion beam-SEM and serial block face-SEM. The flexibility to use diverse imaging technologies available at most academic institutions makes this workflow useful and applicable for most life science samples. Volumetric analysis of the biopsies studied here revealed morphological, organizational and ultrastructural aspects of the tumor cells and surrounding environment that cannot be revealed by conventional 2D EM imaging. Our results indicate that although 2D EM is still an important tool in many areas of diagnostic pathology, 3D images of ultrastructural relationships between both normal and cancerous cells, in combination with their extracellular matrix, enables cancer researchers and pathologists to better understand the progression of the disease and identify potential therapeutic targets.

Development of a Sox2 reporter system modeling cellular heterogeneity in glioma.

BACKGROUND: Malignant gliomas are complex systems containing a number of factors that drive tumor initiation and progression, including genetic aberrations that lead to extensive cellular heterogeneity within the neoplastic compartment. Mouse models recapitulate these genetic aberrations, but readily observable heterogeneity remains challenging. METHODS: To interrogate cellular heterogeneity in mouse glioma models, we utilized a replication-competent avian sarcoma-leukosis virus long terminal repeat with splice acceptor/tumor virus A (RCAS-tva) system to generate spontaneous mouse gliomas that contained a Sox2-enhanced green fluorescent protein (EGFP) reporter. Glial fibrillary acidic protein-tva mice were crossed with Sox2-EGFP mice, and tumors were initiated that contained a subpopulation of Sox2-EGFP-high cells enriched for tumor-initiating cell properties such as self-renewal, multilineage differentiation potential, and perivascular localization. RESULTS: Following implantation into recipient mice, Sox2-EGFP-high cells generated tumors containing Sox2-EGFP-high and Sox2-EGFP-low cells. Kinomic analysis of Sox2-EGFP-high cells revealed activation of known glioma signaling pathways that are strongly correlated with patient survival including platelet-derived growth factor receptor beta, phosphoinositide-3 kinase, and vascular endothelial growth factor. Our functional analysis identified active feline sarcoma (Fes) signaling in Sox2-EGFP-high cells. Fes negatively correlated with glioma patient survival and was coexpressed with Sox2-positive cells in glioma xenografts and primary patient-derived tissue. CONCLUSIONS: Our RCAS-tva/Sox2-EGFP model will empower closer examination of cellular heterogeneity and will be useful for identifying novel glioma pathways as well as testing preclinical treatment efficacy.

High-throughput flow cytometry screening reveals a role for junctional adhesion molecule a as a cancer stem cell maintenance factor.

Stem cells reside in niches that regulate the balance between self-renewal and differentiation. The identity of a stem cell is linked with the ability to interact with its niche through adhesion mechanisms. To identify targets that disrupt cancer stem cell (CSC) adhesion, we performed a flow cytometry screen on patient-derived glioblastoma (GBM) cells and identified junctional adhesion molecule A (JAM-A) as a CSC adhesion mechanism essential for self-renewal and tumor growth. JAM-A was dispensable for normal neural stem/progenitor cell (NPC) function, and JAM-A expression was reduced in normal brain versus GBM. Targeting JAM-A compromised the self-renewal of CSCs. JAM-A expression negatively correlated to GBM patient prognosis. Our results demonstrate that GBM-targeting strategies can be identified through screening adhesion receptors and JAM-A represents a mechanism for niche-driven CSC maintenance.