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Acute promyelocytic leukemia (APL) is initiated by the PML-RARA ( PR ) fusion oncogene and has a characteristic expression profile that includes high levels of the Notch ligand Jagged-1 ( JAG1 ). In this study, we used a series of bioinformatic, in vitro , and in vivo assays to assess the role of Notch signaling in human APL samples, and in a PML-RARA knock-in mouse model of APL (Ctsg-PML-RARA) . We identified a Notch expression signature in both human primary APL cells and in Kit+Lin−Sca1+ cells from pre-leukemic Ctsg-PML-RARA mice. Both genetic and pharmacologic inhibition of Notch signaling abrogated the enhanced self-renewal seen in hematopoietic stem/progenitor cells from pre-leukemic Ctsg-PML-RARA mice, but had no influence on cells from age-matched wild-type mice. In addition, six of nine murine APL tumors tested displayed diminished growth in vitro when Notch signaling was inhibited pharmacologically. Finally, we found that genetic inhibition of Notch signaling with a dominant-negative Mastermind-like protein reduced APL growth in vivo in a subset of tumors. These findings expand the role of Notch signaling in hematopoietic diseases, and further define the mechanistic events important for PML-RARA -mediated leukemogenesis.

Glioblastoma (GBM) is the most common primary brain tumor in adults and has a dismal prognosis despite multimodality treatment. Given the resistance of glioma stem cells (GSC) to chemotherapy and radiation therapy, their eradication could prevent tumor recurrence. We sought to evaluate the antitumor activity of measles virus (MV) derivatives against GSC. We generated neurosphere cultures from patient-derived primary tumor GBM xenografts, and we characterized them for the GSC markers CD133, SOX2, Nestin, ATF5 and OLIG2. Using the MV-strains MV-GFP, MV-CEA and MV-NIS we demonstrated infection, viral replication and significant cytopathic effect in vitro against GSC lines. In tumorigenicity experiments, GBM44 GSC were infected with MV in vitro and subsequently implanted into the right caudate nucleus of nude mice: significant prolongation of survival in mice implanted with infected GSC was observed, compared with mock-infected controls ( P =0.0483). In therapy experiments in GBM6 and GBM12 GSC xenograft models, there was significant prolongation of survival in MV-GFP-treated animals compared with inactivated virus-treated controls (GBM6 P =0.0021, GBM12 P =0.0416). Abundant syncytia and viral replication was demonstrated in tumors of MV-treated mice. Measles virus derivatives have significant antitumor activity against glioma-derived stem cells in vitro and in vivo.

Mass spectrometry imaging (MSI) is an emerging technology that holds potential for improving, biomarker discovery, metabolomics research, pharmaceutical applications and clinical diagnosis. Despite many solutions being developed, the large data size and high dimensional nature of MSI, especially 3D datasets, still pose computational and memory complexities that hinder accurate identification of biologically relevant molecular patterns. Moreover, the subjectivity in the selection of parameters for conventional pre-processing approaches can lead to bias. Therefore, we assess if a probabilistic generative model based on a fully connected variational autoencoder can be used for unsupervised analysis and peak learning of MSI data to uncover hidden structures. The resulting msiPL method learns and visualizes the underlying non-linear spectral manifold, revealing biologically relevant clusters of tissue anatomy in a mouse kidney and tumor heterogeneity in human prostatectomy tissue, colorectal carcinoma, and glioblastoma mouse model, with identification of underlying m/z peaks. The method is applied for the analysis of MSI datasets ranging from 3.3 to 78.9 GB, without prior pre-processing and peak picking, and acquired using different mass spectrometers at different centers. The high dimensional and complex nature of mass spectrometry imaging (MSI) data poses challenges to downstream analyses. Here the authors show an application of artificial intelligence in mining MSI data revealing biologically relevant metabolomic and proteomic information from data acquired on different mass spectrometry platforms.

Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with extremely poor prognostic outcome despite intensive treatment. All chemotherapeutic agents currently used have no greater than 30-40% response rate, many fall into the range of 10-20%, with delivery across the blood brain barrier (BBB) or chemoresistance contributing to the extremely poor outcomes despite treatment. Increased expression of the multidrug resistance protein 1(MRP1) in high grade glioma, and it's role in BBB active transport, highlights this member of the ABC transporter family as a target for improving drug responses in GBM. In this study we show that small molecule inhibitors and gene silencing of MRP1 had a significant effect on GBM cell response to temozolomide (150 μM), vincristine (100 nM), and etoposide (2 μM). Pre-treatment with Reversan (inhibitor of MRP1 and P-glycoprotein) led to a significantly improved response to cell death in the presence of all three chemotherapeutics, in both primary and recurrent GBM cells. The presence of MK571 (inhibitor of MRP1 and multidrug resistance protein 4 (MRP4) led to an enhanced effect of vincristine and etoposide in reducing cell viability over a 72 h period. Specific MRP1 inhibition led to a significant increase in vincristine and etoposide-induced cell death in all three cell lines assessed. Treatment with MK571, or specific MRP1 knockdown, did not have any effect on temozolomide drug response in these cells. These findings have significant implications in providing researchers an opportunity to improve currently used chemotherapeutics for the initial treatment of primary GBM, and improved treatment for recurrent GBM patients.

Cadherins are essential components of the adherens junction complexes that mediate cell-cell adhesion and regulate cell motility. During tissue morphogenesis, changes in cadherin expression (known as cadherin switching) are a common mechanism for altering cell fate. Cadherin switching is also common during epithelial tumor progression, where it is thought to promote tumor invasion and metastasis. E-cadherin is the predominant cadherin expressed in epithelial tissues, but its expression is very limited in normal brain. We identified E-cadherin expression in a retrospective series of glioblastomas exhibiting epithelial or pseudoepithelial differentiation. Unlike in epithelial tissues, E-cadherin expression in gliomas correlated with an unfavorable clinical outcome. Western blotting of two panels of human GBM cell lines propagated either as xenografts in nude mice or grown under conventional cell culture conditions confirmed that E-cadherin expression is rare. However, a small number of xenograft lines did express E-cadherin, its expression correlating with increased invasiveness when the cells were implanted orthotopically in mouse brain. In the conventionally cultured SF767 glioma cell line, E-cadherin expression was localized throughout the plasma membrane rather than being restricted to areas of cell-cell contact. ShRNA knockdown of E-cadherin in these cells resulted in decreased proliferation and migration in vitro. Our data shows an unexpected correlation between the abnormal expression of E-cadherin in a subset of GBM tumor cells and the growth and migration of this aggressive brain tumor subtype.

Understanding the molecular events controlling melanoma progression is of paramount importance for the development of alternative treatment options for this devastating disease. Here we report a mechanism regulated by the oncogenic SOX2-GLI1 transcriptional complex driving melanoma invasion through the induction of the sialyltransferase ST3GAL1. Using in vitro and in vivo studies, we demonstrate that ST3GAL1 drives melanoma metastasis. Silencing of this enzyme suppresses melanoma invasion and significantly reduces the ability of aggressive melanoma cells to enter the blood stream, colonize distal organs, seed and survive in the metastatic environment. Analysis of glycosylated proteins reveals that the receptor tyrosine kinase AXL is a major effector of ST3GAL1 pro-invasive function. ST3GAL1 induces AXL dimerization and activation that, in turn, promotes melanoma invasion. Our data support a key role of the ST3GAL1-AXL axis as driver of melanoma metastasis, and highlight the therapeutic potential of targeting this axis to treat metastatic melanoma. Understanding the molecular events controlling melanoma progression are necessary to find improved therapeutics. Here, the authors report oncogenic SOX2-GLI1 transcriptional complex to drive melanoma invasion through the induction of the sialyltransferase ST3GAL1, and report ST3GAL1-AXL axis as driver of melanoma metastasis.

Glioblastoma (GBM) is the most common primary adult brain tumor. Despite extensive efforts, the median survival for GBM patients is approximately 14 months. GBM therapy could benefit greatly from patient-specific targeted therapies that maximize treatment efficacy. Here we report a platform termed SynergySeq to identify drug combinations for the treatment of GBM by integrating information from The Cancer Genome Atlas (TCGA) and the Library of Integrated Network-Based Cellular Signatures (LINCS). We identify differentially expressed genes in GBM samples and devise a consensus gene expression signature for each compound using LINCS L1000 transcriptional profiling data. The SynergySeq platform computes disease discordance and drug concordance to identify combinations of FDA-approved drugs that induce a synergistic response in GBM. Collectively, our studies demonstrate that combining disease-specific gene expression signatures with LINCS small molecule perturbagen-response signatures can identify preclinical combinations for GBM, which can potentially be tested in humans. Inherent or acquired resistance to treatment of glioblastoma (GBM) is nearly universal. Here, the authors introduce a platform to identify synergistic drug combinations for patient-specific treatment of GBM based on gene expression signatures and small molecule perturbation-response profiles.

Background Glioma stem cells (GSCs) are a subpopulation of stem-like cells that contribute to glioblastoma (GBM) aggressiveness, recurrence, and resistance to radiation and chemotherapy. Therapeutically targeting the GSC population may improve patient survival, but unique vulnerabilities need to be identified. Results We isolate GSCs from well-characterized GBM patient-derived xenografts (PDX), characterize their stemness properties using immunofluorescence staining, profile their epigenome including 5mC, 5hmC, 5fC/5caC, and two enhancer marks, and define their transcriptome. Fetal brain-derived neural stem/progenitor cells are used as a comparison to define potential unique and common molecular features between these different brain-derived cells with stem properties. Our integrative study reveals that abnormal expression of ten-eleven-translocation (TET) family members correlates with global levels of 5mC and 5fC/5caC and may be responsible for the distinct levels of these marks between glioma and neural stem cells. Heterogenous transcriptome and epigenome signatures among GSCs converge on several genes and pathways, including DNA damage response and cell proliferation, which are highly correlated with TET expression. Distinct enhancer landscapes are also strongly associated with differential gene regulation between glioma and neural stem cells; they exhibit unique co-localization patterns with DNA epigenetic mark switching events. Upon differentiation, glioma and neural stem cells exhibit distinct responses with regard to TET expression and DNA mark changes in the genome and GSCs fail to properly remodel their epigenome. Conclusions Our integrative epigenomic and transcriptomic characterization reveals fundamentally distinct yet potentially targetable biologic features of GSCs that result from their distinct epigenomic landscapes.

The tumor suppressor p53 has been found to be the most commonly mutated gene in human cancers; however, the frequency of p53 mutations varies from 10 to 70% across different cancer types. This variability can partly be explained by inactivating mechanisms aside from direct genomic polymorphisms. The p53 gene encodes 12 isoforms, some of which can modulate full-length p53 activity in cancer. In this study, we characterized p53 isoform expression patterns in glioblastoma, gliosis, non-tumor brain and neural progenitor cells by SDS–PAGE, immunoblot, mass spectrometry and reverse transcription–PCR. We found that the most consistently expressed isoform in glioblastoma, Δ40p53, was uniquely expressed in regenerative processes, such as those involving neural progenitor cells and gliosis compared with tumor samples. Isoform profiling of glioblastoma tissues revealed the presence of both Δ40p53 and full-length p53, neither of which were detected in non-tumor cerebral cortex. Upon xenograft propagation of tumors, p53 levels increased. The variability of overall p53 expression and relative levels of isoforms suggest fluctuations in subpopulations of cells with greater or lesser capacity for proliferation, which can change as the tumor evolves under different growth conditions.