Slug-based epithelial-mesenchymal transition gene signature is associated with prolonged time to recurrence in glioblastoma

Background
We previously identified a precise stage-associated gene expression signature of coordinately expressed genes, including the transcription factor Slug (SNAI2) and other epithelial mesenchymal transition (EMT) markers, present in samples from publicly available gene expression datasets in multiple cancer types. The expression levels of the co-expressed genes vary in a continuous and coordinate manner across the samples, ranging from absence of expression to strong co-expression of all genes. These data suggest that tumor cells may pass through an EMT like process of mesenchymal transition to varying degrees. 

Findings
Here we show that this signature in glioblastoma multiforme (GBM) is associated with time to recurrence following initial treatment. By analyzing data from The Cancer Genome Atlas (TCGA), we found that GBM patients who responded to therapy and had long time to recurrence had low levels of the signature in their tumor samples (P = 3x10^-7^). We also found that the signature is strongly correlated in gliomas with the putative stem cell marker CD44, and is highly enriched among the differentially expressed genes in glioblastomas vs. lower grade gliomas. 

Conclusions 
Our results suggest that long delay before tumor recurrence is associated with absence of the mesenchymal transition signature, raising the possibility that inhibiting this transition might improve the durability of therapy in glioma patients

Convection-Enhanced Delivery for Targeted Delivery of Antiglioma Agents: The Translational Experience

Recent improvements in the understanding of glioblastoma (GBM) have allowed for increased ability to develop specific, targeted therapies. In parallel, however, there is a need for effective methods of delivery to circumvent the therapeutic obstacles presented by the blood-brain barrier and systemic side effects. The ideal delivery system should allow for adequate targeting of the tumor while minimizing systemic exposure, applicability across a wide range of potential therapies, and have existing safe and efficacious systems that allow for widespread application. Though many alternatives to systemic delivery have been developed, this paper will focus on our experience with convection-enhanced delivery (CED) and our focus on translating this technology from pre-clinical studies to the treatment of human GBM

Human stem cell transplantation models of Alzheimer’s disease

Alzheimer’s disease (AD) is the most frequent form of dementia. It is characterized by pronounced neuronal degeneration with formation of neurofibrillary tangles and deposition of amyloid β throughout the central nervous system. Animal models have provided important insights into the pathogenesis of AD and they have shown that different brain cell types including neurons, astrocytes and microglia have important functions in the pathogenesis of AD. However, there are difficulties in translating promising therapeutic observations in mice into clinical application in patients. Alternative models using human cells such as human induced pluripotent stem cells (iPSCs) may provide significant advantages, since they have successfully been used to model disease mechanisms in neurons and in glial cells in neurodegenerative diseases in vitro and in vivo. In this review, we summarize recent studies that describe the transplantation of human iPSC-derived neurons, astrocytes and microglial cells into the forebrain of mice to generate chimeric transplantation models of AD. We also discuss opportunities, challenges and limitations in using differentiated human iPSCs for in vivo disease modeling and their application for biomedical research

Glioblastoma Models Reveal the Connection between Adult Glial Progenitors and the Proneural Phenotype

Tumor heterogeneity is a major obstacle for finding effective treatment of Glioblastoma (GBM). Based on global expression analysis, GBM can be classified into distinct subtypes: Proneural, Neural, Classical and Mesenchymal. The signatures of these different tumor subtypes may reflect the phenotypes of cells giving rise to them. However, the experimental evidence connecting any specific subtype of GBM to particular cells of origin is lacking. In addition, it is unclear how different genetic alterations interact with cells of origin in determining tumor heterogeneity. This issue cannot be addressed by studying end-stage human tumors.To address this issue, we used retroviruses to deliver transforming genetic lesions to glial progenitors in adult mouse brain. We compared the resulting tumors to human GBM. We found that different initiating genetic lesions gave rise to tumors with different growth rates. However all mouse tumors closely resembled the human Proneural GBM. Comparative analysis of these mouse tumors allowed us to identify a set of genes whose expression in humans with Proneural GBM correlates with survival.This study offers insights into the relationship between adult glial progenitors and Proneural GBM, and allows us to identify molecular alterations that lead to more aggressive tumor growth. In addition, we present a new preclinical model that can be used to test treatments directed at a specific type of GBM in future studies

Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A review

Cancer remains one of the most challenging diseases to treat in the medical field. Machine learning has enabled in-depth analysis of rich multi-omics profiles and medical imaging for cancer diagnosis and prognosis. Despite these advancements, machine learning models face challenges stemming from limited labeled sample sizes, the intricate interplay of high-dimensionality data types, the inherent heterogeneity observed among patients and within tumors, and concerns about interpretability and consistency with existing biomedical knowledge. One approach to surmount these challenges is to integrate biomedical knowledge into data-driven models, which has proven potential to improve the accuracy, robustness, and interpretability of model results. Here, we review the state-of-the-art machine learning studies that adopted the fusion of biomedical knowledge and data, termed knowledge-informed machine learning, for cancer diagnosis and prognosis. Emphasizing the properties inherent in four primary data types including clinical, imaging, molecular, and treatment data, we highlight modeling considerations relevant to these contexts. We provide an overview of diverse forms of knowledge representation and current strategies of knowledge integration into machine learning pipelines with concrete examples. We conclude the review article by discussing future directions to advance cancer research through knowledge-informed machine learning.Comment: 41 pages, 4 figures, 2 table

Tumor-associated T cell receptor repertoires in low- and high-grade gliomas

Glioblastoma (GBM) remains prognostically dismal, with care centered on resection, motivating research into novel therapies. Although inducing anti-tumor immunity remains an attractive target for therapeutic and preventative intervention, the interplay between evolving dysregulation of the glioma microenvironment and T cell inefficacy remains poorly understood. In our murine model of proneural glioma, retroviral delivery of PDGF and cre-mediated knockout of PTEN in glial progenitors of adult C57BL/6 gives rise to slow-growing tumors, which were harvested at early- mid- and late-stage progression timepoints following induction, along with peripheral blood. From human patients, tissue from low- and high-grade glioma resections and corresponding peripheral lymphocytes were cryofrozen during surgery at New York Presbyterian-CUMC. For both species, we employed a commercially available primer set (iRepertoire) for nested PCR of the complementarity-determining region 3 (CDR3) of the TCR-alpha and TCR-beta chains from the T cell RNA, followed by next-generation sequencing on an Illumina MiSeq. We developed a computational pipeline for mapping TCR cassettes, in silico translation, pairwise analysis of tissue/periphery per subject, and error analysis. In the murine model, we observe that at late-stage, the intratumoral TCR repertoire diverges significantly from the peripheral, including dramatic expansion of single tumor-associated CDR3s, while the peripheral repertoire itself diverges from those of healthy mice. In both human patients and mice, we observed tumor-associated CDR3s, disproportionately abundant in tumor tissue compared to the corresponding peripheral blood, at both the amino acid and nucleotide level. In human samples we observed tumor-specific TCR expansions that were associated with particular functional subsets (CD8+, CD4+, Treg, NKT). Sequence-level study of the TCR repertoire promises new insight into the scope of glioma immunosuppression, especially systemic effects which remain elusive and the origins of intratumoral suppressive populations, and holds the potential for immunotherapeutic interventions, non-invasive diagnostics, and direct assessment of global responses to immunotherapy

Human cancer cells express Slug-based epithelial-mesenchymal transition gene expression signature obtained in vivo

Background: The biological mechanisms underlying cancer cell motility and invasiveness remain unclear, although it has been hypothesized that they involve some type of epithelial-mesenchymal transition (EMT). Methods: We used xenograft models of human cancer cells in immunocompromised mice, profiling the harvested tumors separately with species-specific probes and computationally analyzing the results. Results: Here we show that human cancer cells express in vivo a precise multi-cancer invasion-associated gene expression signature that prominently includes many EMT markers, among them the transcription factor Slug, fibronectin, and α-SMA. We found that human, but not mouse, cells express the signature and Slug is the only upregulated EMT-inducing transcription factor. The signature is also present in samples from many publicly available cancer gene expression datasets, suggesting that it is produced by the cancer cells themselves in multiple cancer types, including nonepithelial cancers such as neuroblastoma. Furthermore, we found that the presence of the signature in human xenografted cells was associated with a downregulation of adipocyte markers in the mouse tissue adjacent to the invasive tumor, suggesting that the signature is triggered by contextual microenvironmental interactions when the cancer cells encounter adipocytes, as previously reported. Conclusions: The known, precise and consistent gene composition of this cancer mesenchymal transition signature, particularly when combined with simultaneous analysis of the adjacent microenvironment, provides unique opportunities for shedding light on the underlying mechanisms of cancer invasiveness as well as identifying potential diagnostic markers and targets for metastasis-inhibiting therapeutics

Combined inhibition of Bcl-2/Bcl-xL and Usp9X/Bag3 overcomes apoptotic resistance in glioblastoma in vitro and in vivo

Despite great efforts taken to advance therapeutic measures for patients with glioblastoma, the clinical prognosis remains grim. The antiapoptotic Bcl-2 family protein Mcl-1 is overexpressed in glioblastoma and represents an important resistance factor to the BH-3 mimetic ABT263. In this study, we show that combined treatment with ABT263 and GX15-070 overcomes apoptotic resistance in established glioblastoma cell lines, glioma stem-like cells and primary cultures. Moreover, this treatment regimen also proves to be advantageous in vivo. On the molecular level, GX15-070 enhanced apoptosis by posttranslational down-regulation of the deubiquitinase, Usp9X, and the chaperone Bag3, leading to a sustained depletion of Mcl-1 protein levels. Moreover, knock-down of Usp9X or Bag3 depleted endogenous Mcl-1 protein levels and in turn enhanced apoptosis induced through Bcl-2/Bcl-xL inhibition. In conclusion, combined treatment with ABT263 and GX15-070 results in a significantly enhanced anti-cancer activity in vitro as well as in vivo in the setting of glioblastoma. Both drugs, ABT263 and GX15-070 have been evaluated in clinical studies which facilitates the translational aspect of taking this combinatorial approach to the clinical setting. Furthermore we present a novel mechanism by which GX15-070 counteracts Mcl-1 expression which may lay a foundation for a novel target in cancer therapy

PRMT5-mediated regulation of developmental myelination

Oligodendrocytes (OLs) are the myelin-forming cells of the central nervous system. They are derived from differentiation of oligodendrocyte progenitors through a process requiring cell cycle exit and histone modifications. Here we identify the histone arginine methyl-transferase PRMT5, a molecule catalyzing symmetric methylation of histone H4R3, as critical for developmental myelination. PRMT5 pharmacological inhibition, CRISPR/cas9 targeting, or genetic ablation decrease p53-dependent survival and impair differentiation without affecting proliferation. Conditional ablation of Prmt5 in progenitors results in hypomyelination, reduced survival and differentiation. Decreased histone H4R3 symmetric methylation is followed by increased nuclear acetylation of H4K5, and is rescued by pharmacological inhibition of histone acetyltransferases. Data obtained using purified histones further validate the results obtained in mice and in cultured oligodendrocyte progenitors. Together, these results identify PRMT5 as critical for oligodendrocyte differentiation and developmental myelination by modulating the cross-talk between histone arginine methylation and lysine acetylation

TCR repertoire divergence reflects micro-environmental immune phenotypes in glioma

Background & significance: Glioblastoma (GBM) remains prognostically dismal, with only modest gains in mean survival time with chemo- and radiotherapy motivating research into reversing its characteristic local and systemic immunosuppression with precision in this high-risk tissue. While whole-repertoire amplification of the TCR repertoire allows unprecedented depth regarding the potentiation of anti-tumor responses, most studies utilize TCRseq for monitoring reactivity to specific tumor antigens, or the identities of particular TCRs as biomarkers. In this study, we have utilized whole-repertoire analysis to describe the relationship between intra-tumoral T cells and peripheral circulation, and leverage mutual information between gene expression and the behavior of the T cell population to characterize glioma-reactive states, driven by the gene expression of the principal resident monocyte population, and perturbable by immunological interventions. Methods & results: From resected tumor tissue and peripheral lymphocytes of low- and high-grade human glioma patients, TCRseq libraries were generated using reverse transcription and nested PCR (iRepertoire 1) of the complementarity-determining region 3 (CDR3) of the TCR-alpha and TCR-beta chains, then sequenced on an Illumina MiSeq. We developed a computational pipeline for mapping TCR cassettes, in silico translation, and sequence error correction from these libraries, enabling sensitive calculation of tumor-infiltrating lymphocyte (TIL) and peripheral TCR diversity (Shannon entropy) 2, as well as the divergence (Jensen-Shannon divergence metric) between the two T cell populations. By integrating amino acid identity and V-J cassette combination, we observed varying levels of divergence between the TIL and peripheral lymphocytes of glioma patients, and changes in this divergence over tumor progression in a PDGF-driven murine model. Correlation of these properties with tumor tissue RNA profiling, by differential gene expression and mutual-information gene ontology, revealed an association between tumor growth and high blood-brain TCR divergence - particularly in amino-acid sequence, suggesting antigen-driven selection - while high expression of inflammatory and certain immune pathway markers computationally attributed to microglia 3 were anti-correlated with divergence. Preliminary murine experiments suggest that TCR divergence can be altered by induction and blockade of cytokine-mediated activation of these pathways. Conclusion: The expression of a subset of microglia-associated genes appears to describe micro-environmental states which are strongly tied to the tumor-specificity of the intra-tumoral TCR repertoire, complementary to the tumor-centric classifications of TCGA. TCRseq-based profiling not only promises to inform tailoring of local and systemic immunotherapy to target the most relevant immunosuppressive mechanisms, but may also provide non-invasive assessment of the intra-tumoral environment for refined diagnosis and monitoring during clinical trials