Differential sensitivity of Glioma stem cells to Aurora kinase A inhibitors: implications for stem cell mitosis and centrosome dynamics

Glioma stem-cell-like cells are considered to be responsible for treatment resistance and tumour recurrence following chemo-radiation in glioblastoma patients, but specific targets by which to kill the cancer stem cell population remain elusive. A characteristic feature of stem cells is their ability to undergo both symmetric and asymmetric cell divisions. In this study we have analysed specific features of glioma stem cell mitosis. We found that glioma stem cells appear to be highly prone to undergo aberrant cell division and polyploidization. Moreover, we discovered a pronounced change in the dynamic of mitotic centrosome maturation in these cells. Accordingly, glioma stem cell survival appeared to be strongly dependent on Aurora A activity. Unlike differentiated cells, glioma stem cells responded to moderate Aurora A inhibition with spindle defects, polyploidization and a dramatic increase in cellular senescence, and were selectively sensitive to Aurora A and Plk1 inhibitor treatment. Our study proposes inhibition of centrosomal kinases as a novel strategy to selectively target glioma stem cells

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

INTEGRATIVE ANALYSIS OF OMICS DATA IN ADULT GLIOMA AND OTHER TCGA CANCERS TO GUIDE PRECISION MEDICINE

Transcriptomic profiling and gene expression signatures have been widely applied as effective approaches for enhancing the molecular classification, diagnosis, prognosis or prediction of therapeutic response towards personalized therapy for cancer patients. Thanks to modern genome-wide profiling technology, scientists are able to build engines leveraging massive genomic variations and integrating with clinical data to identify “at risk” individuals for the sake of prevention, diagnosis and therapeutic interventions. In my graduate work for my Ph.D. thesis, I have investigated genomic sequencing data mining to comprehensively characterise molecular classifications and aberrant genomic events associated with clinical prognosis and treatment response, through applying high-dimensional omics genomic data to promote the understanding of gene signatures and somatic molecular alterations contributing to cancer progression and clinical outcomes. Following this motivation, my dissertation has been focused on the following three topics in translational genomics. 1) Characterization of transcriptomic plasticity and its association with the tumor microenvironment in glioblastoma (GBM). I have integrated transcriptomic, genomic, protein and clinical data to increase the accuracy of GBM classification, and identify the association between the GBM mesenchymal subtype and reduced tumorpurity, accompanied with increased presence of tumor-associated microglia. Then I have tackled the sole source of microglial as intrinsic tumor bulk but not their corresponding neurosphere cells through both transcriptional and protein level analysis using a panel of sphere-forming glioma cultures and their parent GBM samples.FurthermoreI have demonstrated my hypothesis through longitudinal analysis of paired primary and recurrent GBM samples that the phenotypic alterations of GBM subtypes are not due to intrinsic proneural-to-mesenchymal transition in tumor cells, rather it is intertwined with increased level of microglia upon disease recurrence. Collectively I have elucidated the critical role of tumor microenvironment (Microglia and macrophages from central nervous system) contributing to the intra-tumor heterogeneity and accurate classification of GBM patients based on transcriptomic profiling, which will not only significantly impact on clinical perspective but also pave the way for preclinical cancer research. 2) Identification of prognostic gene signatures that stratify adult diffuse glioma patientsharboring1p/19q co-deletions. I have compared multiple statistical methods and derived a gene signature significantly associated with survival by applying a machine learning algorithm. Then I have identified inflammatory response and acetylation activity that associated with malignant progression of 1p/19q co-deleted glioma. In addition, I showed this signature translates to other types of adult diffuse glioma, suggesting its universality in the pathobiology of other subset gliomas. My efforts on integrative data analysis of this highly curated data set usingoptimizedstatistical models will reflect the pending update to WHO classification system oftumorsin the central nervous system (CNS). 3) Comprehensive characterization of somatic fusion transcripts in Pan-Cancers. I have identified a panel of novel fusion transcripts across all of TCGA cancer types through transcriptomic profiling. Then I have predicted fusion proteins with kinase activity and hub function of pathway network based on the annotation of genetically mobile domains and functional domain architectures. I have evaluated a panel of in -frame gene fusions as potential driver mutations based on network fusion centrality hypothesis. I have also characterised the emerging complexity of genetic architecture in fusion transcripts through integrating genomic structure and somatic variants and delineating the distinct genomic patterns of fusion events across different cancer types. Overall my exploration of the pathogenetic impact and clinical relevance of candidate gene fusions have provided fundamental insights into the management of a subset of cancer patients by predicting the oncogenic signalling and specific drug targets encoded by these fusion genes. Taken together, the translational genomic research I have conducted during my Ph.D. study will shed new light on precision medicine and contribute to the cancer research community. The novel classification concept, gene signature and fusion transcripts I have identified will address several hotly debated issues in translational genomics, such as complex interactions between tumor bulks and their adjacent microenvironments, prognostic markers for clinical diagnostics and personalized therapy, distinct patterns of genomic structure alterations and oncogenic events in different cancer types, therefore facilitating our understanding of genomic alterations and moving us towards the development of precision medicine

Glioma through the looking GLASS: molecular evolution of diffuse gliomas and the Glioma Longitudinal Analysis Consortium.

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

An Open-Source Tool for Anisotropic Radiation Therapy Planning in Neuro-oncology Using DW-MRI Tractography.

There is evidence from histopathological studies that glioma tumor cells migrate preferentially along large white matter bundles. If the peritumoral white matter structures can be used to predict the likely trajectory of migrating tumor cells outside of the surgical margin, then this information could be used to inform the delineation of radiation therapy (RT) targets. In theory, an anisotropic expansion that takes large white matter bundle anatomy into account may maximize the chances of treating migrating cancer cells and minimize the amount of brain tissue exposed to high doses of ionizing radiation. Diffusion-weighted MRI (DW-MRI) can be used in combination with fiber tracking algorithms to model the trajectory of large white matter pathways using the direction and magnitude of water movement in tissue. The method presented here is a tool for translating a DW-MRI fiber tracking (tractography) dataset into a white matter path length (WMPL) map that assigns each voxel the shortest distance along a streamline back to a specified region of interest (ROI). We present an open-source WMPL tool, implemented in the package Diffusion Imaging in Python (DIPY), and code to convert the resulting WMPL map to anisotropic contours for RT in a commercial treatment planning system. This proof-of-concept lays the groundwork for future studies to evaluate the clinical value of incorporating tractography modeling into treatment planning

The role of EGFR double minutes in modulating the response of malignant gliomas to radiotherapy.

EGFR amplification in cells having double minute chromosomes (DM) is commonly found in glioblastoma multiforme (GBM); however, how much it contributes to the current failure to treat GBM successfully is unknown. We studied two syngeneic primary cultures derived from a GBM with and without cells carrying DM, for their differential molecular and metabolic profiles, in vivo growth patterns, and responses to irradiation (IR). Each cell line has a distinct molecular profile consistent with an invasive "go" (with DM) or angiogenic "grow" phenotype (without DM) demonstrated in vitro and in intracranial xenograft models. Cells with DM were relatively radio-resistant and used higher glycolytic respiration and lower oxidative phosphorylation in comparison to cells without them. The DM-containing cell was able to restore tumor heterogeneity by mis-segregation of the DM-chromosomes, giving rise to cell subpopulations without them. As a response to IR, DM-containing cells switched their respiration from glycolic metabolism to oxidative phosphorylation and shifted molecular profiles towards that of cells without DM. Irradiated cells with DM showed the capacity to alter their extracellular microenvironment to not only promote invasiveness of the surrounding cells, regardless of DM status, but also to create a pro-angiogenic tumor microenvironment. IR of cells without DM was found primarily to increase extracellular MMP2 activity. Overall, our data suggest that the DM-containing cells of GBM are responsible for tumor recurrence due to their high invasiveness and radio-resistance and the mis-segregation of their DM chromosomes, to give rise to fast-growing cells lacking DM chromosomes

Multiparametric MRI and [18F]fluorodeoxyglucose positron emission tomography imaging is a potential prognostic imaging biomarker in recurrent glioblastoma

Purpose/objectivesMultiparametric advanced MR and [18F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) imaging may be important biomarkers for prognosis as well for distinguishing recurrent glioblastoma multiforme (GBM) from treatment-related changes.Methods/materialsWe retrospectively evaluated 30 patients treated with chemoradiation for GBM and underwent advanced MR and FDG-PET for confirmation of tumor progression. Multiparametric MRI and FDG-PET imaging metrics were evaluated for their association with 6-month overall (OS) and progression-free survival (PFS) based on pathological, radiographic, and clinical criteria.Results17 males and 13 females were treated between 2001 and 2014, and later underwent FDG-PET at suspected recurrence. Baseline FDG-PET and MRI imaging was obtained at a median of 7.5 months [interquartile range (IQR) 3.7–12.4] following completion of chemoradiation. Median follow-up after FDG-PET imaging was 10 months (IQR 7.2–13.0). Receiver-operator characteristic curve analysis identified that lesions characterized by a ratio of the SUVmax to the normal contralateral brain (SUVmax/NB index) >1.5 and mean apparent diffusion coefficient (ADC) value of ≤1,400 × 10−6 mm2/s correlated with worse 6-month OS and PFS. We defined three patient groups that predicted the probability of tumor progression: SUVmax/NB index >1.5 and ADC ≤1,400 × 10−6 mm2/s defined high-risk patients (n = 7), SUVmax/NB index ≤1.5 and ADC >1,400 × 10−6 mm2/s defined low-risk patients (n = 11), and intermediate-risk (n = 12) defined the remainder of the patients. Median OS following the time of the FDG-PET scan for the low, intermediate, and high-risk groups were 23.5, 10.5, and 3.8 months (p < 0.01). Median PFS were 10.0, 4.4, and 1.9 months (p = 0.03). Rates of progression at 6-months in the low, intermediate, and high-risk groups were 36, 67, and 86% (p = 0.04).ConclusionRecurrent GBM in the molecular era is associated with highly variable outcomes. Multiparametric MR and FDG-PET biomarkers may provide a clinically relevant, non-invasive and cost-effective method of predicting prognosis and improving clinical decision making in the treatment of patients with suspected tumor recurrence

The first-in-class alkylating deacetylase inhibitor molecule tinostamustine shows antitumor effects and is synergistic with radiotherapy in preclinical models of glioblastoma

Background: The use of alkylating agents such as temozolomide in association with radiotherapy (RT) is the therapeutic standard of glioblastoma (GBM). This regimen modestly prolongs overall survival, also if, in light of the still dismal prognosis, further improvements are desperately needed, especially in the patients with O6- methylguanine-DNA-methyltransferase (MGMT) unmethylated tumors, in which the benefit of standard treatment is less. Tinostamustine (EDO-S101) is a first-in-class alkylating deacetylase inhibitor (AK-DACi) molecule that fuses the DNA damaging effect of bendamustine with the fully functional pan-histone deacetylase (HDAC) inhibitor, vorinostat, in a completely new chemical entity. Methods: Tinostamustine has been tested in models of GBM by using 13 GBM cell lines and seven patient-derived GBM proliferating/stem cell lines in vitro. U87MG and U251MG (MGMT negative), as well as T98G (MGMT positive), were subcutaneously injected in nude mice, whereas luciferase positive U251MG cells and patient-derived GBM stem cell line (CSCs-5) were evaluated the orthotopic intra-brain in vivo experiments. Results: We demonstrated that tinostamustine possesses stronger antiproliferative and pro-apoptotic effects than those observed for vorinostat and bendamustine alone and similar to their combination and irrespective of MGMT expression. In addition, we observed a stronger radio-sensitization of single treatment and temozolomide used as control due to reduced expression and increased time of disappearance of γH2AX indicative of reduced signal and DNA repair. This was associated with higher caspase-3 activation and reduction of RT-mediated autophagy. In vivo, tinostamustine increased time-to-progression (TTP) and this was additive/synergistic to RT. Tinostamustine had significant therapeutic activity with suppression of tumor growth and prolongation of DFS (disease-free survival) and OS (overall survival) in orthotopic intra-brain models that was superior to bendamustine, RT and temozolomide and showing stronger radio sensitivity. Conclusions: Our data suggest that tinostamustine deserves further investigation in patients with glioblastoma