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Pediatric acute myeloid leukemia (pAML) is characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains understudied in pediatric patients. We used single-cell RNA sequencing and single-cell ATAC sequencing to profile 28 patients representing different pAML subtypes at diagnosis, remission and relapse. At diagnosis, cellular composition differed between genetic subgroups. Upon relapse, cellular hierarchies transitioned toward a more primitive state regardless of subtype. Primitive cells in the relapsed tumor were distinct compared to cells at diagnosis, with under-representation of myeloid transcriptional programs and over-representation of other lineage programs. In some patients, this was accompanied by the appearance of a B-lymphoid-like hierarchy. Our data thus reveal the emergence of apparent subtype-specific plasticity upon treatment and inform on potentially targetable processes., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

CIC encodes a transcriptional repressor and MAPK signalling effector that is inactivated by loss-of-function mutations in several cancer types, consistent with a role as a tumour suppressor. Here, we used bioinformatic, genomic, and proteomic approaches to investigate CIC's interaction networks. We observed both previously identified and novel candidate interactions between CIC and SWI/SNF complex members, as well as novel interactions between CIC and cell cycle regulators and RNA processing factors. We found that CIC loss is associated with an increased frequency of mitotic defects in human cell lines and an in vivo mouse model and with dysregulated expression of mitotic regulators. We also observed aberrant splicing in CIC-deficient cell lines, predominantly at 3' and 5' untranslated regions of genes, including genes involved in MAPK signalling, DNA repair, and cell cycle regulation. Our study thus characterises the complexity of CIC's functional network and describes the effect of its loss on cell cycle regulation, mitotic integrity, and transcriptional splicing, thereby expanding our understanding of CIC's potential roles in cancer. In addition, our work exemplifies how multi-omic, network-based analyses can be used to uncover novel insights into the interconnected functions of pleiotropic genes/proteins across cellular contexts.

Glioblastomas (GBMs) are aggressive brain tumors characterized by extensive inter- and intratumor heterogeneity. Patient-derived models, such as organoids and explants, have recently emerged as useful models to study such heterogeneity, although the extent to which they can recapitulate GBM genomic features remains unclear. Here, we analyze bulk exome and single-cell genome and transcriptome profiles of 12 IDH wild-type GBMs, including two recurrent tumors, and of patient-derived explants (PDEs) and gliomasphere (GS) lines derived from these tumors. We find that PDEs are genetically similar to, and variably retain gene expression characteristics of, their parent tumors. Notably, PDEs appear to exhibit similar levels of transcriptional heterogeneity compared with their parent tumors, whereas GS lines tend to be enriched for cells in a more uniform transcriptional state. The approaches and datasets introduced here will provide a valuable resource to help guide experiments using GBM-derived models, especially in the context of studying cellular heterogeneity., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Capicua (CIC)'s transcriptional repressor function is implicated in neurodevelopment and in oligodendroglioma (ODG) aetiology. However, CIC's role in these contexts remains obscure, primarily from our currently limited knowledge regarding its biological functions. Moreover, CIC mutations in ODG invariably co-occur with a neomorphic IDH1/2 mutation, yet the functional relationship between these two genetic events is unknown. Here, we analysed models derived from an E6/E7/hTERT-immortalized (i.e. p53- and RB-deficient) normal human astrocyte cell line. To examine the consequences of CIC loss, we compared transcriptomic and epigenomic profiles between CIC wild-type and knockout cell lines, with and without mutant IDH1 expression. Our analyses revealed dysregulation of neurodevelopmental genes in association with CIC loss. CIC ChIP-seq was also performed to expand upon the currently limited ensemble of known CIC target genes. Among the newly identified direct CIC target genes were EPHA2 and ID1, whose functions are linked to neurodevelopment and the tumourigenicity of in vivo glioma tumour models. NFIA, a known mediator of gliogenesis, was discovered to be uniquely overexpressed in CIC-knockout cells expressing mutant IDH1-R132H protein. These results identify neurodevelopment and specific genes within this context as candidate targets through which CIC alterations may contribute to the progression of IDH-mutant gliomas. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd on behalf of The Pathological Society of Great Britain and Ireland., (© 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd on behalf of The Pathological Society of Great Britain and Ireland.)

RNA sequencing (RNAseq) has been widely used to generate bulk gene expression measurements collected from pools of cells. Only relatively recently have single-cell RNAseq (scRNAseq) methods provided opportunities for gene expression analyses at the single-cell level, allowing researchers to study heterogeneous mixtures of cells at unprecedented resolution. Tumors tend to be composed of heterogeneous cellular mixtures and are frequently the subjects of such analyses. Extensive method developments have led to several protocols for scRNAseq but, owing to the small amounts of RNA in single cells, technical constraints have required compromises. For example, the majority of scRNAseq methods are limited to sequencing only the 3' or 5' termini of transcripts. Other protocols that facilitate full-length transcript profiling tend to capture only polyadenylated mRNAs and are generally limited to processing only 96 cells at a time. Here, we address these limitations and present a novel protocol that allows for the high-throughput sequencing of full-length, total RNA at single-cell resolution. We demonstrate that our method produced strand-specific sequencing data for both polyadenylated and non-polyadenylated transcripts, enabled the profiling of transcript regions beyond only transcript termini, and yielded data rich enough to allow identification of cell types from heterogeneous biological samples., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Haile, Corbett, LeBlanc, Wei, Pleasance, Bilobram, Nip, Brown, Trinh, Smith, Trinh, Bala, Chuah, Coope, Moore, Mungall, Mungall, Zhao, Hirst, Aparicio, Birol, Jones and Marra.)

CIC encodes a transcriptional repressor, capicua (CIC), whose disrupted activity appears to be involved in several cancer types, including type I low-grade gliomas (LGGs) and stomach adenocarcinomas (STADs). To explore human CIC's transcriptional network in an isogenic background, we developed novel isogenic CIC knockout cell lines as model systems, and used these in transcriptome analyses to study the consequences of CIC loss. We also compared our results with analyses of transcriptome data from TCGA for type I LGGs and STADs. We identified 39 candidate targets of CIC transcriptional regulation, and confirmed seven of these as direct targets. We showed that, although many CIC targets appear to be context-specific, the effects of CIC loss converge on the dysregulation of similar biological processes in different cancer types. For example, we found that CIC deficiency was associated with disruptions in the expression of genes involved in cell-cell adhesion, and in the development of several cell and tissue types. We also showed that loss of CIC leads to overexpression of downstream members of the mitogen-activated protein kinase (MAPK) signalling cascade, indicating that CIC deficiency may present a novel mechanism for activation of this oncogenic pathway. © 2017 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland., (© 2017 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.)

Adult diffuse gliomas account for the majority of primary malignant brain tumours, and are in most cases lethal. Current therapies are often only marginally effective, and improved options will almost certainly benefit from further insight into the various processes contributing to gliomagenesis and pathology. While molecular characterization of these tumours classifies them on the basis of genetic alterations and chromosomal abnormalities, DNA methylation patterns are increasingly understood to play a role in glioma pathogenesis. Indeed, a subset of gliomas associated with improved survival is characterized by the glioma CpG island methylator phenotype (G-CIMP), which can be induced by the expression of mutant isocitrate dehydrogenase (IDH1/2). Aberrant methylation of particular genes or regulatory elements, within the context of G-CIMP-positive and/or negative tumours, has also been shown to be associated with differential survival. In this review, we provide an overview of the current knowledge regarding the role of DNA methylation in adult diffuse gliomas. In particular, we discuss IDH mutations and G-CIMP, MGMT promoter methylation, DNA methylation-mediated microRNA regulation and aberrant methylation of specific genes or groups of genes., (© The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Malignant rhabdoid tumors (MRTs) are rare lethal tumors of childhood that most commonly occur in the kidney and brain. MRTs are driven by SMARCB1 loss, but the molecular consequences of SMARCB1 loss in extra-cranial tumors have not been comprehensively described and genomic resources for analyses of extra-cranial MRT are limited. To provide such data, we used whole-genome sequencing, whole-genome bisulfite sequencing, whole transcriptome (RNA-seq) and microRNA sequencing (miRNA-seq), and histone modification profiling to characterize extra-cranial MRTs. Our analyses revealed gene expression and methylation subgroups and focused on dysregulated pathways, including those involved in neural crest development., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Next-generation sequencing (NGS) technologies and data have revolutionized cancer research and are increasingly being deployed to guide clinicians in treatment decision-making. NGS technologies have allowed us to take an "omics" approach to cancer in order to reveal genomic, transcriptomic, and epigenomic landscapes of individual malignancies. Integrative multi-platform analyses are increasingly used in large-scale projects that aim to fully characterize individual tumours as well as general cancer types and subtypes. In this review, we examine how NGS technologies in particular have contributed to "omics" approaches in cancer research, allowing for large-scale integrative analyses that consider hundreds of tumour samples. These types of studies have provided us with an unprecedented wealth of information, providing the background knowledge needed to make small-scale (including "N of 1") studies informative and relevant. We also take a look at emerging opportunities provided by NGS and state-of-the-art third-generation sequencing technologies, particularly in the context of translational research. Cancer research and care are currently poised to experience significant progress catalyzed by accessible sequencing technologies that will benefit both clinical- and research-based efforts.

Niemann-Pick Type C (NPC) disease is an autosomal recessive neurodegenerative disorder caused in most cases by mutations in the NPC1 gene. NPC1-deficiency is characterized by late endosomal accumulation of cholesterol, impaired cholesterol homeostasis, and a broad range of other cellular abnormalities. Although neuronal abnormalities and glial activation are observed in nearly all areas of the brain, the most severe consequence of NPC1-deficiency is a near complete loss of Purkinje neurons in the cerebellum. The link between cholesterol trafficking and NPC pathogenesis is not yet clear; however, increased oxidative stress in symptomatic NPC disease, increases in mitochondrial cholesterol, and alterations in autophagy/mitophagy suggest that mitochondria play a role in NPC disease pathology. Alterations in mitochondrial function affect energy and neurotransmitter metabolism, and are particularly harmful to the central nervous system. To investigate early metabolic alterations that could affect NPC disease progression, we performed metabolomics analyses of different brain regions from age-matched wildtype and Npc1 (-/-) mice at pre-symptomatic, early symptomatic and late stage disease by (1)H-NMR spectroscopy. Metabolic profiling revealed markedly increased lactate and decreased acetate/acetyl-CoA levels in Npc1 (-/-) cerebellum and cerebral cortex at all ages. Protein and gene expression analyses indicated a pre-symptomatic deficiency in the oxidative decarboxylation of pyruvate to acetyl-CoA, and an upregulation of glycolytic gene expression at the early symptomatic stage. We also observed a pre-symptomatic increase in several indicators of oxidative stress and antioxidant response systems in Npc1 (-/-) cerebellum. Our findings suggest that energy metabolism and oxidative stress may present additional therapeutic targets in NPC disease, especially if intervention can be started at an early stage of the disease.

The analysis of nonlinear delay-differential equations (DDEs) subjected to external forcing is difficult due to the infinite dimensionality of the space in which they evolve. To simplify the analysis of such systems, the present work develops a non-homogeneous center manifold (CM) reduction scheme, which allows the derivation of a time-dependent order parameter equation in finite dimension. This differential equation captures the major dynamical features of the delayed system. The forcing is assumed to be small compared to the amplitude of the autonomous system, in order to cause only small variations of the fixed points and of the autonomous CM. The time-dependent CM is shown to satisfy a non-homogeneous partial differential equation. We first briefly review CM theory for DDEs. Then we show, for the general scalar case, how an ansatz that separates the CM into one for the autonomous problem plus an additional time-dependent order-two correction leads to satisfying results. The paper then details the application to a transcritical bifurcation subjected to single or multiple periodic forcings. The validity limits of the reduction scheme are also highlighted. Finally, we characterize the specific case of additive stochastic driving of the transcritical bifurcation, where additive white noise shifts the mode of the probability density function of the state variable to larger amplitudes.

We investigate the role of adaptation in a neural field model, composed of ON and OFF cells, with delayed all-to-all recurrent connections. As external spatially profiled inputs drive the network, ON cells receive inputs directly, while OFF cells receive an inverted image of the original signals. Via global and delayed inhibitory connections, these signals can cause the system to enter states of sustained oscillatory activity. We perform a bifurcation analysis of our model to elucidate how neural adaptation influences the ability of the network to exhibit oscillatory activity. We show that slow adaptation encourages input-induced rhythmic states by decreasing the Andronov-Hopf bifurcation threshold. We further determine how the feedback and adaptation together shape the resonant properties of the ON and OFF cell network and how this affects the response to time-periodic input. By introducing an additional frequency in the system, adaptation alters the resonance frequency by shifting the peaks where the response is maximal. We support these results with numerical experiments of the neural field model. Although developed in the context of the circuitry of the electric sense, these results are applicable to any network of spontaneously firing cells with global inhibitory feedback to themselves, in which a fraction of these cells receive external input directly, while the remaining ones receive an inverted version of this input via feedforward di-synaptic inhibition. Thus the results are relevant beyond the many sensory systems where ON and OFF cells are usually identified, and provide the backbone for understanding dynamical network effects of lateral connections and various forms of ON/OFF responses.

A neural field model of ON and OFF cells with all-to-all inhibitory feedback is investigated. External spatiotemporal stimuli drive the ON and OFF cells with, respectively, direct and inverted polarity. The dynamic differences between networks built of ON and OFF cells ("ON/OFF") and those having only ON cells ("ON/ON") are described for the general case where ON and OFF cells can have different spontaneous firing rates; this asymmetric case is generic. Neural responses to nonhomogeneous static and time-periodic inputs are analyzed in regimes close to and away from self-oscillation. Static stimuli can cause oscillatory behavior for certain asymmetry levels. Time-periodic stimuli expose dynamical differences between ON/OFF and ON/ON nets. Outside the stimulated region, we show that ON/OFF nets exhibit frequency doubling, while ON/ON nets cannot. On the other hand, ON/ON networks show antiphase responses between stimulated and unstimulated regions, an effect that does not rely on specific receptive field circuitry. An analysis of the resonance properties of both net types reveals that ON/OFF nets exhibit larger response amplitude. Numerical simulations of the neural field models agree with theoretical predictions for localized static and time-periodic forcing. This is also the case for simulations of a network of noisy integrate-and-fire neurons. We finally discuss the application of the model to the electrosensory system and to frequency-doubling effects in retina.

A neural field model with multiple cell-to-cell feedback connections is investigated. Our model incorporates populations of ON and OFF cells, receiving sensory inputs with direct and inverted polarity, respectively. Oscillatory responses to spatially localized stimuli are found to occur via Andronov-Hopf bifurcations of stationary activity. We explore the impact of multiple delayed feedback components as well as additional excitatory and/or inhibitory non-delayed recurrent signals on the instability threshold. Paradoxically, instantaneous excitatory recurrent terms are found to enhance network responsiveness by reducing the oscillatory response threshold, allowing smaller inputs to trigger oscillatory activity. Instantaneous inhibitory components do the opposite. The frequency of these response oscillations is further shaped by the polarity of the non-delayed terms., (This journal is © 2010 The Royal Society)

A globally coupled network of ON and OFF cells is studied using neural field theory. ON cells increase their activity when the amplitude of an external stimulus increases, while OFF cells do the opposite given the same stimulus. Theory predicts that, without input, multiple transitions to oscillations can occur depending on feedback delay and the difference between ON and OFF resting states. Static spatial stimuli can induce or suppress global oscillations via a Andronov-Hopf bifurcation. This is the case for either polarity of such stimuli. In contrast, only excitatory inputs can induce or suppress oscillations in an equivalent network built of ON cells only even though oscillations are more prevalent in such systems. Nonmonotonic responses to local stimuli occur where responses lateral to the stimulus switch from excitatory to inhibitory as the input amplitude increases. With local time-periodic forcing, the unforced cells oscillate at twice the driving frequency via full-wave rectification mediated by the feedback. Our results agree with simulations of the neural field model, and further, qualitative agreement is found with the behavior of a network of spiking stochastic integrate-and-fire model neurons.