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Simple Summary: In Europe, seven out of eight patients with lung cancer die within 5 years after diagnosis. DDR1, a tyrosine kinase receptor, has emerged as a potential new therapeutic target for non-small cell lung cancer given its association with poor prognosis among affected patients. This study investigates the impact of DDR1 on tumor burden and immune cell infiltration into the tumor microenvironment. We found that pharmacological inhibition and knockout of DDR1 increased the tumor burden in an immunocompetent mouse model of lung adenocarcinoma. The absence of DDR1 reduced CD8+ cytotoxic T-cell infiltration but increased CD4+ helper and regulatory T-cell infiltration. Regulatory T cells, which promote tumorigenesis by suppressing the immune system, were also more common among The Cancer Genome Atlas (TCGA) lung adenocarcinoma patients with low DDR1 expression. These findings suggest that therapeutic inhibition of DDR1, in certain circumstances, might even have negative effects, although further studies are needed to confirm these findings. Lung cancer is the leading cause of cancer-related death worldwide. Discoidin domain receptor 1 (DDR1), a tyrosine kinase receptor, has been associated with poor prognosis in patients with non-small cell lung cancer (NSCLC). However, its role in tumorigenesis remains poorly understood. This work aimed to explore the impact of DDR1 expression on immune cell infiltration in lung adenocarcinoma. Pharmacological inhibition and knockout of DDR1 were used in an immunocompetent mouse model of KRAS/p53-driven lung adenocarcinoma (LUAD). Tumor cells were engrafted subcutaneously, after which tumors were harvested for investigation of immune cell composition via flow cytometry. The Cancer Genome Atlas (TCGA) cohort was used to perform gene expression analysis of 509 patients with LUAD. Pharmacological inhibition and knockout of DDR1 increased the tumor burden, with DDR1 knockout tumors showing a decrease in CD8+ cytotoxic T cells and an increase in CD4+ helper T cells and regulatory T cells. TCGA analysis revealed that low-DDR1-expressing tumors showed higher FoxP3 (regulatory T-cell marker) expression than high-DDR1-expressing tumors. Our study showed that under certain conditions, the inhibition of DDR1, a potential therapeutic target in cancer treatment, might have negative effects, such as inducing a pro-tumorigenic tumor microenvironment. As such, further investigations are necessary. [ABSTRACT FROM AUTHOR]

We present the molecular landscape of pediatric acute myeloid leukemia (AML) and characterize nearly 1,000 participants in Children's Oncology Group (COG) AML trials. The COG-National Cancer Institute (NCI) TARGET AML initiative assessed cases by whole-genome, targeted DNA, mRNA and microRNA sequencing and CpG methylation profiling. Validated DNA variants corresponded to diverse, infrequent mutations, with fewer than 40 genes mutated in [greater than] 2% of cases. In contrast, somatic structural variants, including new gene fusions and focal deletions of MBNL1, ZEB2 and ELF1, were disproportionately prevalent in young individuals as compared to adults. Conversely, mutations in DNMT3A and TP53, which were common in adults, were conspicuously absent from virtually all pediatric cases. New mutations in GATA2, FLT3 and CBL and recurrent mutations in MYC-ITD, NRAS, KRAS and WT1 were frequent in pediatric AML. Deletions, mutations and promoter DNA hypermethylation convergently impacted Wnt signaling, Polycomb repression, innate immune cell interactions and a cluster of zinc finger-encoding genes associated with KMT2A rearrangements. These results highlight the need for and facilitate the development of age-tailored targeted therapies for the treatment of pediatric AML., Author(s): Hamid Bolouri (corresponding author) [1]; Jason E Farrar [2]; Timothy Triche, Jr [3]; Rhonda E Ries [4]; Emilia L Lim [5]; Todd A Alonzo [6, 7]; Yussanne Ma [5]; [...]

BACKGROUND. Despite a rapidly growing body of literature on coronavirus disease 2019 (COVID-19), our understanding of the immune correlates of disease severity, course, and outcome remains poor. METHODS. Using mass cytometry, we assessed the immune landscape in longitudinal whole-blood specimens from 59 patients presenting with acute COVID-19 and classified based on maximal disease severity. Hospitalized patients negative for SARS-CoV-2 were used as controls. RESULTS. We found that the immune landscape in COVID-19 formed 3 dominant clusters, which correlated with disease severity. Longitudinal analysis identified a pattern of productive innate and adaptive immune responses in individuals who had a moderate disease course, whereas those with severe disease had features suggestive of a protracted and dysregulated immune response. Further, we identified coordinate immune alterations accompanying clinical improvement and decline that were also seen in patients who received IL-6 pathway blockade. CONCLUSION. The hospitalized COVID-19 negative cohort allowed us to identify immune alterations that were shared between severe COVID-19 and other critically ill patients. Collectively, our findings indicate that selection of immune interventions should be based in part on disease presentation and early disease trajectory due to the profound differences in the immune response in those with mild to moderate disease and those with the most severe disease. FUNDING. Benaroya Family Foundation, the Leonard and Norma Klorfine Foundation, Glenn and Mary Lynn Mounger, and the National Institutes of Health., Introduction The coronavirus disease 2019 (COVID-19) pandemic has brought a worldwide focus not only on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but also on how immunity to the [...]

Tumor heterogeneity may reduce the efficacy of molecularly guided systemic therapy for cancers that have metastasized. To determine whether the genomic alterations in a single metastasis provide a reasonable assessment of the major oncogenic drivers of other dispersed metastases in an individual, we analyzed multiple tumors from men with disseminated prostate cancer through whole-exome sequencing, array comparative genomic hybridization (CGH) and RNA transcript profiling, and we compared the genomic diversity within and between individuals. In contrast to the substantial heterogeneity between men, there was limited diversity among metastases within an individual. The number of somatic mutations, the burden of genomic copy number alterations and aberrations in known oncogenic drivers were all highly concordant, as were metrics of androgen receptor (AR) activity and cell cycle activity. AR activity was inversely associated with cell proliferation, whereas the expression of Fanconi anemia (FA)-complex genes was correlated with elevated cell cycle progression, expression of the E2F transcription factor 1 (E2F1) and loss of retinoblastoma 1 (RB1). Men with somatic aberrations in FA-complex genes or in ATM serine/threonine kinase (ATM) exhibited significantly longer treatment-response durations to carboplatin than did men without defects in genes encoding DNA-repair proteins. Collectively, these data indicate that although exceptions exist, evaluating a single metastasis provides a reasonable assessment of the major oncogenic driver alterations that are present in disseminated tumors within an individual, and thus may be useful for selecting treatments on the basis of predicted molecular vulnerabilities., Personalized approaches for cancer treatment rely on the premise that defined molecular alterations in tumors will confer susceptibility to specific therapeutics, and that malignancies without the alteration will not respond [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ydbio.2009.06.007 Byline: Hamid Bolouri, Eric H. Davidson Keywords: Community effect; Intradomain signaling; Sea urchin embryo; nodal gene regulation Abstract: The 'Community Effect' denotes intra-territorial signaling amongst cells which constitute a particular tissue or embryonic progenitor field. The cells of the territory express the same transcriptional regulatory state, and the intra-territorial signaling is essential to maintenance of this specific regulatory state. The structure of the underlying gene regulatory network (GRN) subcircuitry explains the genomically wired mechanism by which community effect signaling is linked to the continuing transcriptional generation of the territorial regulatory state. A clear example is afforded by the oral ectoderm GRN of the sea urchin embryo where cis-regulatory evidence, experimental embryology, and network analysis combine to provide a complete picture. We review this example and consider less well known but similar cases in other developing systems where the same subcircuit GRN topology is present. To resolve mechanistic issues that arise in considering how community effect signaling could operate to produce its observed effects, we construct and analyze the behavior of a quantitative model of community effect signaling in the sea urchin embryo oral ectoderm. Community effect network topology could constitute part of the genomic regulatory code that defines transcriptional function in multicellular tissues composed of cells in contact, and hence may have arisen as a metazoan developmental strategy. Author Affiliation: Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA Article History: Received 18 March 2009; Revised 20 May 2009; Accepted 5 June 2009 Article Note: (footnote) [star] This article was accepted in 2009 to celebrate the 50th anniversary of Developmental Biology.

Endoderm and mesoderm specification are the most fundamental pattern formation events in embryonic development. This process starts with blimp1 and wnt8 gene expression at the vegetal pole when the embryonic transcription begins.

Author(s): Mark Gilchrist [1]; Vesteinn Thorsson [1]; Bin Li [1]; Alistair G. Rust [1]; Martin Korb [1]; Kathleen Kennedy [1]; Tsonwin Hai [2]; Hamid Bolouri [1]; Alan Aderem (corresponding author) [...]

Different experimental technologies measure different aspects of a system and to differing depth and breadth. High-throughput assays have inherently high false-positive and false-negative rates. Moreover, each technology includes systematic biases of a different nature. These differences make network reconstruction from multiple data sets difficult and error-prone. Additionally, because of the rapid rate of progress in biotechnology, there is usually no curated exemplar data set from which one might estimate data integration parameters. To address these concerns, we have developed data integration methods that can handle multiple data sets differing in statistical power, type, size, and network coverage without requiring a curated training data set. Our methodology is general in purpose and may be applied to integrate data from any existing and future technologies. Here we outline our methods and then demonstrate their performance by applying them to simulated data sets. The results show that these methods select truepositive data elements much more accurately than classical approaches. In an accompanying companion paper, we demonstrate the applicability of our approach to biological data. We have integrated our methodology into a free open source software package named POINTILLIST. Fisher's method | mixture distribution models

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ydbio.2005.04.023 Byline: William J.R. Longabaugh (a), Eric H. Davidson (b), Hamid Bolouri (a)(b) Abstract: Developmental genetic regulatory networks (GRNs) have unique architectural characteristics. They are typically large-scale, multi-layered, and organized in a nested, modular hierarchy of regulatory network kernels, function-specific building blocks, and structural gene batteries. They are also inherently multicellular and involve changing topological relationships among a growing number of cells. Reconstruction of developmental GRNs requires unique computational tools that support the above representational requirements. In addition, we argue that DNA-centered network modeling, separate descriptions of network organization and network behavior, and support for network documentation and annotation are essential requirements for computational modeling of developmental GRNs. Based on these observations, we have developed a freely available, platform-independent, open source software package (BioTapestry) which supports both the process of model construction and also model visualization, analysis, documentation, and dissemination. We provide an overview of the main features of BioTapestry. The BioTapestry software and additional documents are available from http://www.biotapestry.org. We recommend BioTapestry as the substrate for further co-development for and by the developmental biology community. Author Affiliation: (a) Institute for Systems Biology, Seattle, WA 98103-8904, USA (b) Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA

Gene network analysis requires computationally based models which represent the functional architecture of regulatory interactions, and which provide directly testable predictions. The type of model that is useful is constrained by the particular features of developmentally active cis-regulatory systems. These systems function by processing diverse regulatory inputs, generating novel regulatory outputs. A computational model which explicitly accommodates this basic concept was developed earlier for the cis-regulatory system of the endo16 gene of the sea urchin. This model represents the genetically mandated logic functions that the system executes, but also shows how time-varying kinetic inputs are processed in different circumstances into particular kinetic outputs. The same basic design features can be utilized to construct models that connect the large number of cis-regulatory elements constituting developmental gene networks. The ultimate aim of the network models discussed here is to represent the regulatory relationships among the genomic control systems of the genes in the network, and to state their functional meaning. The target site sequences of the cis-regulatory elements of these genes constitute the physical basis of the network architecture. Useful models for developmental regulatory networks must represent the genetic logic by which the system operates, but must also be capable of explaining the real time dynamics of cis-regulatory response as kinetic input and output data become available. Most importantly, however, such models must display in a direct and transparent manner fundamental network design features such as intra-and intercellular feedback circuitry; the sources of parallel inputs into each cis-regulatory element; gene battery organization; and use of repressive spatial inputs in specification and boundary formation. Successful network models lead to direct tests of key architectural features by targeted cis-regulatory analysis. Key Words: gene regulatory network; model; endo16 gene; regulatory genomics.

We present the current form of a provisional DNA sequence-based regulatory gene network that explains in outline how endomesodermal specification in the sea urchin embryo is controlled. The model of the network is in a continuous process of revision and growth as new genes are added and new experimental results become available; see http://www.its.cahech.edu/~mirsky/endomeso.htm (End-mes Gene Network Update) for the latest version. The network contains over 40 genes at present, many newly uncovered in the course of this work, and most encoding DNA-binding transcriptional regulatory factors. The architecture of the network was approached initially by construction of a logic model that integrated the extensive experimental evidence now available on endomesoderm specification. The internal linkages between genes in the network have been determined functionally, by measurement of the effects of regulatory perturbations on the expression of all relevant genes in the network. Five kinds of perturbation have been applied: (1) use of morpholino antisense oligonucleotides targeted to many of the key regulatory genes in the network; (2) transformation of other regulatory factors into dominant repressors by construction of Engrailed repressor domain fusions; (3) ectopic expression of given regulatory factors, from genetic expression constructs and from injected mRNAs; (4) blockade of the [beta]-catenin/Tcf pathway by introduction of mRNA encoding the intracellular domain of cadherin; and (5) blockade of the Notch signaling pathway by introduction of mRNA encoding the extracellular domain of the Notch receptor. The network model predicts the cis-regulatory inputs that link each gene into the network. Therefore, its architecture is testable by cis-regulatory analysis. Strongylocentroms purpuratus and Lytechinus variegatus genomic BAC recombinants that include a large number of the genes in the network have been sequenced and annotated. Tests of the cis-regulatory predictions of the model are greatly facilitated by interspecific computational sequence comparison, which affords a rapid identification of likely cis-regulatory elements in advance of experimental analysis. The network specifies genomically encoded regulatory processes between early cleavage and gastrula stages. These control the specification of the micromere lineage and of the initial [veg.sub.2] endomesodermal domain; the blastula-stage separation of the central [veg.sub.2] mesodermal domain (i.e., the secondary mesenchyme progenitor field) from the peripheral [veg.sub.2] endodermal domain; the stabilization of specification state within these domains; and activation of some downstream differentiation genes. Each of the temporal--spatial phases of specification is represented in a subelement of the network model, that treats regulatory events within the relevant embryonic nuclei at particular stages. Key Words: gene network; sea urchin embryo; gene regulation.

The investigation and modeling of gene regulatory networks requires computational tools specific to the task. We present several locally developed software tools that have been used in support of our ongoing research into the embryogenesis of the sea urchin. These tools are especially well suited to iterative refinement of models through experimental and computational investigation. They include: BioArray, a macroarray spot processing program; SUGAR, a system to display and correlate large-BAC sequence analyses; SeqComp and FamilyRelations, programs for comparative sequence analysis; and NetBuilder, an environment for creating and analyzing models of gene networks. We also present an overview of the process used to build our model of the Strongylocentrotus purpuratus endomesoderm gene network. Several of the tools discussed in this paper are still in active development and some are available as open source. Key Words: sequence annotation; comparative analysis; macroarrays; gene network modeling; computational tools.

Passive substrate fault tolerance (PSFT) techniques were evaluated to determine their yield-enhancing capabilities. These techniques include the fault tolerant IO buses, spare RAM dies and paged memory space. It is found that spare memory dies and paged address space are effective solutions for the known good die (KGD) problem. Furthermore, these techniques can be used for reliability enhancement as well as to configure multichip modules (MCMs) by using substrates with defective interconnection tracks.

Infant Acute Myeloid Leukemia (AML) is a poorly-addressed, heterogeneous malignancy distinguished by surprisingly few mutations per patient but accompanied by myriad age-specific translocations. These characteristics make treatment of infant AML challenging. While infant AML is a relatively rare disease, it has enormous impact on families, and in terms of life-years-lost and life limiting morbidities. To better understand the mechanisms that drive infant AML, we performed integrative analyses of genome-wide mRNA, miRNA, and DNA-methylation data in diagnosis-stage patient samples. Here, we report the activation of an onco-fetal B-cell developmental gene regulatory network in infant AML. AML in infants is genomically distinct from AML in older children/adults in that it has more structural genomic aberrations and fewer mutations. Differential expression analysis of ~1500 pediatric AML samples revealed a large number of infant-specific genes, many of which are associated with B cell development and function. 18 of these genes form a well-studied B-cell gene regulatory network that includes the epigenetic regulators BRD4 and POU2AF1, and their onco-fetal targets LIN28B and IGF2BP3. All four genes are hypo-methylated in infant AML. Moreover, micro-RNA Let7a-2 is expressed in a mutually exclusive manner with its target and regulator LIN28B. These findings suggest infant AML may respond to bromodomain inhibitors and immune therapies targeting CD19, CD20, CD22, and CD79A. [ABSTRACT FROM AUTHOR]

Analysis of the fault and defect resistant interconnect technologies for a wafer-scale integration (WSI) associative string processor (WASP) device determines the practical constraints which limit their successful application by presupposing a realistic number of interconnect failures at the bump sites. The modeling of WASP devices with various topology variants, especially the cost-effective single-stage multicast network SMN-T2a, is discussed.

A model of the wafer-scale integration (WSI) associative string processor (WASP) uses discrete event simulation methods to simulate the acceptance, production, and operational life of a theoretical WASP device. A WASP device developed in favorable conditions and exposed to moderate operational conditions supports 12,500 associative processing elements (APEs) while a device developed under adverse conditions and exposed to harsh operational conditions supported 8000 APE's after 11.4 yr of uninterrupted operation. An architectural parameter sensitivity study for the WASP device is given.

In the version of this article originally published, the color key in Fig. 1a was wrong. In the Cytogenetics key, the box over t(8;21) originally was green. It should have been red, matching the color of the sections of the pie graphs below the key that were labeled with 15% and 19%., Author(s): Hamid Bolouri [sup.1] , Jason E Farrar [sup.2] , Timothy Triche [sup.3] [sup.17] , Rhonda E Ries [sup.4] , Emilia L Lim [sup.5] , Todd A Alonzo [sup.6] [sup.7] [...]

Single‐cell RNA sequencing has emerged as a powerful tool for resolving cellular states associated with normal and maligned developmental processes. Here, we used scRNA‐seq to examine the cell cycle states of expanding human neural stem cells (hNSCs). From these data, we constructed a cell cycle classifier that identifies traditional cell cycle phases and a putative quiescent‐like state in neuroepithelial‐derived cell types during mammalian neurogenesis and in gliomas. The Neural G0 markers are enriched with quiescent NSC genes and other neurodevelopmental markers found in non‐dividing neural progenitors. Putative glioblastoma stem‐like cells were significantly enriched in the Neural G0 cell population. Neural G0 cell populations and gene expression are significantly associated with less aggressive tumors and extended patient survival for gliomas. Genetic screens to identify modulators of Neural G0 revealed that 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 represents a dynamic quiescent‐like state found in neuroepithelial‐derived cells and gliomas. SYNOPSIS: scRNA‐seq and functional genomics are applied to human neural stem cells to characterize cell cycle phases and factors increasing proliferative rate. A new cell cycle state "Neural G0" is discovered, offering insights into glioma patient tumors and patient survival. Unsupervised cell clustering reveals eight distinct cell cycle phases in human neural stem cells.A novel Neural G0 cell cycle phase is characterized by up‐regulation of genes with key roles in neural development.Increased expression of a GBM‐specific Neural G0 gene signature is associated with better prognosis for glioma patients, independent of tumor grade and IDH1/2 mutation.A functional‐genomics screen identifies genes that alter the time spent in G0/G1‐like states thereby increasing the proliferative rate of neural stem cells. [ABSTRACT FROM AUTHOR]

Abstract Background As part of a National Institute of Allergy and Infectious Diseases funded collaborative project, we have performed over 150 microarray experiments measuring the response of C57/BL6 mouse bone marrow macrophages to toll-like receptor stimuli. These microarray expression profiles are available freely from our project web site http://www.innateImmunity-systemsbiology.org. Here, we report the development of a database of computationally predicted transcription factor binding sites and related genomic features for a set of over 2000 murine immune genes of interest. Our database, which includes microarray co-expression clusters and a host of web-based query, analysis and visualization facilities, is available freely via the internet. It provides a broad resource to the research community, and a stepping stone towards the delineation of the network of transcriptional regulatory interactions underlying the integrated response of macrophages to pathogens. Description We constructed a database indexed on genes and annotations of the immediate surrounding genomic regions. To facilitate both gene-specific and systems biology oriented research, our database provides the means to analyze individual genes or an entire genomic locus. Although our focus to-date has been on mammalian toll-like receptor signaling pathways, our database structure is not limited to this subject, and is intended to be broadly applicable to immunology. By focusing on selected immune-active genes, we were able to perform computationally intensive expression and sequence analyses that would currently be prohibitive if applied to the entire genome. Using six complementary computational algorithms and methodologies, we identified transcription factor binding sites based on the Position Weight Matrices available in TRANSFAC. For one example transcription factor (ATF3) for which experimental data is available, over 50% of our predicted binding sites coincide with genome-wide chromatin immnuopreciptation (ChIP-chip) results. Our database can be interrogated via a web interface. Genomic annotations and binding site predictions can be automatically viewed with a customized version of the Argo genome browser. Conclusion We present the Innate Immune Database (IIDB) as a community resource for immunologists interested in gene regulatory systems underlying innate responses to pathogens. The database website can be freely accessed at http://db.systemsbiology.net/IIDB.

Author(s): Hamid Bolouri; Jason E Farrar; Timothy Triche, Jr; Rhonda E Ries; Emilia L Lim; Todd A Alonzo; Yussanne Ma; Richard Moore; Andrew J Mungall; Marco A Marra; Jinghui Zhang; [...]

We present a multilayer hierarchical neural system for automatic classification of complex contour patterns. The system consists of a neocognitron-like network structure combined with self-organizing maps to automatically determine feature classes. We present results showing that multilayer hierarchical networks are able to tolerate pattern distortion considerably better than standard neural network implementations. Index Terms--Hierarchical feature extraction, self-organizing neural networks, visual pattern recognition.

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 ( RELA FUS ). Neural stem cells transduced with RELA FUS 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 RELA FUS 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 RELA FUS drives ST-ependymoma formation from periventricular neural stem cells in mice and that RELA FUS -induced tumorigenesis is likely dependent on a series of cell signaling pathways in addition to NF-κB. [ABSTRACT FROM AUTHOR]

Aim: It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high-risk subjects into longitudinal studies of effective prevention strategies.Methods: Utilizing a case-control study in Sweden, we applied a recently developed next generation targeted sequencing technology to genotype class II genes and applied an object-oriented regression to build and validate a prediction model for T1D.Results: In the training set, estimated risk scores were significantly different between patients and controls (P = 8.12 × 10-92 ), and the area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was 0.917. Using the validation data set, we validated the result with AUC of 0.886. Combining both training and validation data resulted in a predictive model with AUC of 0.903. Further, we performed a "biological validation" by correlating risk scores with 6 islet autoantibodies, and found that the risk score was significantly correlated with IA-2A (Z-score = 3.628, P < 0.001). When applying this prediction model to the Swedish population, where the lifetime T1D risk ranges from 0.5% to 2%, we anticipate identifying approximately 20 000 high-risk subjects after testing all newborns, and this calculation would identify approximately 80% of all patients expected to develop T1D in their lifetime.Conclusion: Through both empirical and biological validation, we have established a prediction model for estimating lifetime T1D risk, using class II HLA. This prediction model should prove useful for future investigations to identify high-risk subjects for prevention research in high-risk populations. [ABSTRACT FROM AUTHOR]

Recent updating of the World Health Organization (WHO) classification of central nervous system (CNS) tumors in 2016 demonstrates the first organized effort to restructure brain tumor classification by incorporating histomorphologic features with recurrent molecular alterations. Revised CNS tumor diagnostic criteria also attempt to reduce interobserver variability of histological interpretation and provide more accurate stratification related to clinical outcome. As an example, diffuse gliomas (WHO grades II-IV) are now molecularly stratified based upon isocitrate dehydrogenase 1 or 2 (IDH) mutational status, with gliomas of WHO grades II and III being substratified according to 1p/19q codeletion status. For now, grading of diffuse gliomas is still dependent upon histological parameters. Independent of WHO classification criteria, multidimensional scaling analysis of molecular signatures for diffuse gliomas from The Cancer Genome Atlas (TCGA) has identified distinct molecular subgroups, and allows for their visualization in 2-dimensional (2D) space. Using the web-based platform Oncoscape as a tool, we applied multidimensional scaling-derived molecular groups to the 2D visualization of the 2016 WHO classification of diffuse gliomas. Here we show that molecular multidimensional scaling of TCGA data provides 2D clustering that represents the 2016 WHO classification of diffuse gliomas. Additionally, we used this platform to successfully identify and define novel copy-number alteration-based molecular subtypes, which are independent of WHO grading, as well as predictive of clinical outcome. The prognostic utility of these molecular subtypes was further validated using an independent data set of the German Glioma Network prospective glioblastoma patient cohort. [ABSTRACT FROM AUTHOR]

Summary To identify therapeutic targets for glioblastoma (GBM), we performed genome-wide CRISPR-Cas9 knockout (KO) screens in patient-derived GBM stem-like cells (GSCs) and human neural stem/progenitors (NSCs), non-neoplastic stem cell controls, for genes required for their in vitro growth. Surprisingly, the vast majority GSC-lethal hits were found outside of molecular networks commonly altered in GBM and GSCs (e.g., oncogenic drivers). In vitro and in vivo validation of GSC-specific targets revealed several strong hits, including the wee1-like kinase, PKMYT1/Myt1 . Mechanistic studies demonstrated that PKMYT1 acts redundantly with WEE1 to inhibit cyclin B-CDK1 activity via CDK1-Y15 phosphorylation and to promote timely completion of mitosis in NSCs. However, in GSCs, this redundancy is lost, most likely as a result of oncogenic signaling, causing GBM-specific lethality. [ABSTRACT FROM AUTHOR]

The evolutionary path from tumor initiation to metastasis can only be fully understood by considering cancer cells as part of a multi-species ecosystem within the tumor microenvironment. This paper reviews and suggests two important recent trends. Firstly, I review arguments that interactions among diverse cells in the tumor microenvironment create a distinct cellular environment that can confer growth advantages, resist interventions, and allow tumors to remain dormant for long periods. Second, I review and highlight a trend toward data-rich, molecularly detailed, computational models of the tumor microenvironment. I argue that data-driven molecularly detailed tumor microenvironment models can now be built using data from multiple emerging high-throughput technologies, and that such models can pinpoint mechanisms of dysregulation and suggest specific drug targets and follow up experiments. [ABSTRACT FROM AUTHOR]

Stem cells, believed to be the cellular origin of glioma, are able to generate gliomas, according to experimental studies. Here we investigated the potential and circumstances of more differentiated cells to generate glioma development. We and others have shown that oligodendrocyte precursor cells (OPCs) can also be the cell of origin for experimental oligodendroglial tumors. However, the question of whether OPCs have the capacity to initiate astrocytic gliomas remains unanswered. Astrocytic and oligodendroglial tumors represent the two most common groups of glioma and have been considered as distinct disease groups with putatively different origins. Here we show that mouse OPCs can give rise to both types of glioma given the right circumstances. Weanalyzed tumors induced by K-RAS andAKTand compared them to oligodendroglial platelet-derived growth factor B-induced tumors in Ctv-a mice with targeted deletions of Cdkn2a (p16Ink4a-/-, p19Arf-/-, Cdkn2a-/-). Our results showed that glioma can originate from OPCs through overexpression of K-RAS and AKT when combined with p19Arf loss, and these tumors displayed an astrocytic histology and high expression of astrocytic markers. We argue that OPCshave the potential to develop both astrocyticandoligodendroglial tumors given loss of p19Arf,and that oncogenic signaling is dominant to cell of origin in determining glioma phenotype. Our mouse data are supported by the fact that human astrocytoma and oligodendroglioma display a high degree of overlap in global gene expression with no clear distinctions between the two diagnoses. [ABSTRACT FROM AUTHOR]