Sonali Arora

Mutant IDH1 regulates the tumor-associated immune system in gliomas

Gliomas harboring mutations in isocitrate dehydrogenase 1/2 (IDH1/2) have the CpG island methylator phenotype (CIMP) and significantly longer patient survival time than wild-type IDH1/2 (wtIDH1/2) tumors. Although there are many factors underlying the differences in survival between these two tumor types, immune-related differences in cell content are potentially important contributors. In order to investigate the role of IDH mutations in immune response, we created a syngeneic pair mouse model for mutant IDH1 (muIDH1) and wtIDH1 gliomas and demonstrated that muIDH1 mice showed many molecular and clinical similarities to muIDH1 human gliomas, including a 100-fold higher concentration of 2-hydroxygluratate (2-HG), longer survival time, and higher CpG methylation compared with wtIDH1. Also, we showed that IDH1 mutations caused down-regulation of leukocyte chemotaxis, resulting in repression of the tumor-associated immune system. Given that significant infiltration of immune cells such as macrophages, microglia, monocytes, and neutrophils is linked to poor prognosis in many cancer types, these reduced immune infiltrates in muIDH1 glioma tumors may contribute in part to the differences in aggressiveness of the two glioma types.

Human glioblastoma-associated microglia/monocytes express a distinct RNA profile compared to human control and murine samples

Glioblastoma (GBM) is the most aggressive brain tumor in adults. It is strongly infiltrated by microglia and peripheral monocytes that support tumor growth. In the present study we used RNA sequencing to compare the expression profile of CD11b+ human glioblastoma‐associated microglia/monocytes (hGAMs) to CD11b+ microglia isolated from non‐tumor samples. Hierarchical clustering and principal component analysis showed a clear separation of the two sample groups and we identified 334 significantly regulated genes in hGAMs. In comparison to human control microglia hGAMs upregulated genes associated with mitotic cell cycle, cell migration, cell adhesion, and extracellular matrix organization. We validated the expression of several genes associated with extracellular matrix organization in samples of human control microglia, hGAMs, and the hGAMs‐depleted fraction via qPCR. The comparison to murine GAMs (mGAMs) showed that both cell populations share a significant fraction of upregulated transcripts compared with their respective controls. These genes were mostly related to mitotic cell cycle. However, in contrast to murine cells, human GAMs did not upregulate genes associated to immune activation. Comparison of human and murine GAMs expression data to several data sets of in vitro‐activated human macrophages and murine microglia showed that, in contrast to mGAMs, hGAMs share a smaller overlap to these data sets in general and in particular to cells activated by proinflammatory stimulation with LPS + INFγ or TNFα. Our findings provide new insights into the biology of human glioblastoma‐associated microglia/monocytes and give detailed information about the validity of murine experimental models. GLIA 2016 GLIA 2016;64:1416–1436

Genomic Annotation Resources in R/Bioconductor.

Annotation resources make up a significant proportion of the Bioconductor project (Huber et al., Nat Methods 12:115-121, 2015). And there are also a diverse set of online resources available which are accessed using specific packages. Here we describe the most popular of these resources and give some high level examples on how to use them.

Enhancing the functional content of eukaryotic protein interaction networks.

Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS) to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks.

Ion channel expression patterns in glioblastoma stem cells with functional and therapeutic implications for malignancy

Ion channels and transporters have increasingly recognized roles in cancer progression through the regulation of cell proliferation, migration, and death. Glioblastoma stem-like cells (GSCs) are a source of tumor formation and recurrence in glioblastoma multiforme, a highly aggressive brain cancer, suggesting that ion channel expression may be perturbed in this population. However, little is known about the expression and functional relevance of ion channels that may contribute to GSC malignancy. Using RNA sequencing, we assessed the enrichment of ion channels in GSC isolates and non-tumor neural cell types. We identified a unique set of GSC-enriched ion channels using differential expression analysis that is also associated with distinct gene mutation signatures. In support of potential clinical relevance, expression of selected GSC-enriched ion channels evaluated in human glioblastoma databases of The Cancer Genome Atlas and Ivy Glioblastoma Atlas Project correlated with patient survival times. Finally, genetic knockdown as well as pharmacological inhibition of individual or classes of GSC-enriched ion channels constrained growth of GSCs compared to normal neural stem cells. This first-in-kind global examination characterizes ion channels enriched in GSCs and explores their potential clinical relevance to glioblastoma molecular subtypes, gene mutations, survival outcomes, regional tumor expression, and experimental responses to loss-of-function. Together, the data support the potential biological and therapeutic impact of ion channels on GSC malignancy and provide strong rationale for further examination of their mechanistic and therapeutic importance.

Copy number profiling across glioblastoma populations has implications for clinical trial design

Background Copy number alterations form prognostic molecular subtypes of glioblastoma with clear differences in median overall survival. In this study, we leverage molecular data from several glioblastoma cohorts to define the distribution of copy number subtypes across random cohorts as well as cohorts with selection biases for patients with inherently better outcome. Methods Copy number subtype frequency was established for 4 glioblastoma patient cohorts. Two randomly selected cohorts include The Cancer Genome Atlas (TCGA) and the German Glioma Network (GGN). Two more selective cohorts include the phase II trial ARTE in elderly patients with newly diagnosed glioblastoma and a multi-institutional cohort focused on paired resected initial/recurrent glioblastoma. The paired initial/recurrent cohort also had exome data available, which allowed for evaluation of multidimensional scaling analysis. Results Smaller selective glioblastoma cohorts are enriched for copy number subtypes that are associated with better survival, reflecting the selection of patients who do well enough to enter a clinical trial or who are deemed well enough to undergo resection at recurrence. Adding exome data to copy number data provides additional data reflective of outcome. Conclusions The overall outcome for diffuse glioma patients is predicted by DNA structure at initial tumor resection. Molecular signature shifts across glioblastoma populations reflect the inherent bias of patient selection toward longer survival in clinical trials. Therefore it may be important to include molecular profiling, including copy number, when enrolling patients for clinical trials in order to balance arms and extrapolate relevance to the general glioblastoma population.

A De Novo Mouse Model of C11orf95-RELA Fusion-Driven Ependymoma Identifies Driver Functions in Addition to NF-κB

SUMMARY The majority of supratentorial ependymomas (ST-ependymomas) have few mutations but frequently display chromothripsis of chromosome 11q that generates a fusion between C11orf95 and RELA (RELAFUS). Neural stem cells transduced with RELAFUS ex vivo form ependymomas when implanted in the brain. These tumors display enhanced NF-κB signaling, suggesting that this aberrant signal is the principal mechanism of oncogenesis. However, it is not known whether RELAFUS is sufficient to drive de novo ependymoma tumorigenesis in the brain and, if so, whether these tumors also arise from neural stem cells. We show that RELAFUS drives ST-ependymoma formation from periventricular neural stem cells in mice and that RELAFUS-induced tumorigenesis is likely dependent on a series of cell signaling pathways in addition to NF-κB.

Errors in RNA-seq transcript abundance estimates

RNA-sequencing data is widely used to identify disease biomarkers and therapeutic targets. Here, using data from five RNA-seq processing pipelines applied to 6,690 human tumor and normal tissues, we show that for >12% of protein-coding genes, in at least 1% of samples, current RNA-seq processing pipelines differ in their abundance estimates by more than four-fold using the same samples and the same set of RNA-seq reads, raising clinical concern.RNA-sequencing data is widely used to identify disease biomarkers and therapeutic targets. Here, using data from five RNA-seq processing pipelines applied to 6,690 human tumor and normal tissues, we show that for >12% of protein-coding genes, in at least 1% of samples, current best-in-class RNA-seq processing pipelines differ in their abundance estimates by more than four-fold using the same samples and the same set of RNA-seq reads, raising clinical concern.

CRISPR-Cas9 Screens Reveal Genes Regulating a G0-like State in Human Neural Progenitors

In depth knowledge of the cellular states associated with normal and disease tissue homeostasis is critical for understanding disease etiology and uncovering therapeutic opportunities. Here, we used single cell RNA-seq to survey the cellular states of neuroepithelial-derived cells in cortical and neurogenic regions of developing and adult mammalian brain to compare with 38,474 cells obtained from 59 human gliomas, as well as pluripotent ESCs, endothelial cells, CD45+ immune cells, and non-CNS cancers. This analysis suggests that a significant portion of neuroepithelial-derived stem and progenitor cells and glioma cells that are not in G2/M or S phase exist in two states: G1 or Neural G0, defined by expression of certain neuro-developmental genes. In gliomas, higher overall Neural G0 gene expression is significantly associated with less aggressive gliomas, IDH1 mutation, and extended patient survival, while also anti-correlated with cell cycle gene expression. Knockout of genes associated with the Hippo/Yap and p53 pathways diminished Neural G0 in vitro, resulting in faster G1 transit, down regulation of quiescence-associated markers, and loss of Neural G0 gene expression. Thus, Neural G0 is a dynamic cellular state required for indolent cell cycles in neural-specified stem and progenitors poised for cell division. As a result, Neural G0 occupancy may be an important determinant of glioma tumor progression.

Increased HOXA5 expression provides a selective advantage for gain of whole chromosome 7 in IDH wild-type glioblastoma

Glioblastoma is the most frequently occurring and invariably fatal primary brain tumor in adults. The vast majority of glioblastomas is characterized by chromosomal copy number alterations, including gain of whole chromosome 7 and loss of whole chromosome 10. Gain of whole chromosome 7 is an early event in gliomagenesis that occurs in proneural-like precursor cells, which give rise to all isocitrate dehydrogenase (IDH) wild-type glioblastoma transcriptional subtypes. Platelet-derived growth factor A (PDGFA) is one gene on chromosome 7 known to drive gliomagenesis, but, given its location near the end of 7p, there are likely several other genes located along chromosome 7 that select for its increased whole-chromosome copy number within glioblastoma cells. To identify other potential genes that could select for gain of whole chromosome 7, we developed an unbiased bioinformatics approach that identified homeobox A5 (HOXA5) as a gene whose expression correlated with gain of chromosome 7 and a more aggressive phenotype of the resulting glioma. High expression of HOXA5 in glioblastoma was associated with a proneural gene expression pattern and decreased overall survival in both human proneural and PDGF-driven mouse glioblastoma. Furthermore, HOXA5 overexpression promoted cellular proliferation and potentiated radioresistance. We also found enrichment of HOXA5 expression in recurrent human and mouse glioblastoma at first recurrence after radiotherapy. Overall, this study implicates HOXA5 as a chromosome 7-associated gene-level locus that promotes selection for gain of whole chromosome 7 and an aggressive phenotype in glioblastoma.