Biology subjects

Kim, M.

Publications and source records attributed to Kim, M..

At least 343 records · Page 19Linked to original sources

bioRxiv2019

Slit/Robo signals prevent spinal motor neuron emigration by organizing the spinal cord basement membrane

The developing spinal cord builds a boundary between the CNS and the periphery, in the form of a basement membrane. The spinal cord basement membrane is a barrier that retains CNS neuron cell bodies, while being selectively permeable to specific axon types. Spinal motor neuron cell bodies are located in the ventral neural tube next to the floor plate and project their axons out through the basement membrane to peripheral targets. However, little is known about how spinal motor neuron cell bodies are retained inside the ventral neural tube, while their axons can exit. In previous work, we found that disruption of Slit/Robo signals caused motor neuron emigration outside the spinal cord. In the current study, we investigate how Slit/Robo signals are necessary to keep spinal motor neurons within the neural tube. Our findings show that when Slit/Robo signals were removed from motor neurons, they migrated outside the spinal cord. Furthermore, this emigration was associated with abnormal basement membrane protein expression in the ventral spinal cord. Using Robo2 and Slit2 conditional mutants, we found that motor neuron-derived Slit/Robo signals were required to set up a normal basement membrane in the spinal cord. Together, our results suggest that motor neurons produce Slit signals that are required for the basement membrane assembly to retain motor neuron cell bodies within the spinal cord.

developmental biology↗

bioRxiv2019

PDXGEM: Patient-Derived Tumor Xenograft based Gene Expression Model for Predicting Clinical Response to Anticancer Therapy in Cancer Patients

BackgroundCancer is a highly heterogeneous disease and shows varying responses to anti-cancer drugs. Although several approaches have been attempted to predict the drug responses by analyzing molecular profiling data of tumors from preclinical cancer models or cancer patients, there is still a great need of developing highly accurate prediction models of response to the anti-cancer drugs for clinical applications toward personalized medicine. Here, we present PDXGEM pipeline to build a predictive gene expression model (GEM) for cancer patients drug responses on the basis of data on gene expression and drug activity in patient-derived xenograft (PDX) models.\n\nResultsDrug sensitivity biomarkers were identified by an association analysis between gene expression levels and post-treatment tumor volume changes in PDX models. Only biomarkers with concordant co-expression patterns between the PDX and cancer patient tumors were used in random-forest algorithm to build a drug response prediction model, so called PDXGEM. We applied PDXGEM to several cytotoxic chemotherapy as well as targeted therapy agents that are used to treat breast cancer, pancreatic cancer, colorectal cancer, or non-small cell lung cancer. Significantly accurate predictions of PDXGEM for pathological and survival outcomes were observed through extensive validation analyses of multiple independent cancer patient datasets obtained from retrospective observational study and prospective clinical trials.\n\nConclusionOur results demonstrated a strong potential of utilizing molecular profiles and drug activity data of PDX tumors for developing a clinically translatable predictive cancer biomarkers for cancer patients. PDXGEM web application is publicly available at http://pdxgem.moffitt.org.

bioinformatics↗

bioRxiv2019

Multiplex chromatin interaction analysis by signal processing and statistical algorithms

The single-molecule multiplex chromatin interaction data generated by emerging non-ligation-based 3D genome mapping technologies provide novel insights into high dimensional chromatin organization, yet introduce new computational challenges. We developed MIA-Sig (https://github.com/TheJacksonLaboratory/mia-sig.git), an algorithmic framework to de-noise the data, assess the statistical significance of chromatin complexes, and identify topological domains and inter-domain contacts. On chromatin immunoprecipitation (ChIP)-enriched data, MIA-Sig can clearly distinguish the protein-associated interactions from the non-specific topological domains.

genomics↗

bioRxiv2019

Fluorescent Sp3 Defect-Tailored Carbon Nanotubes Enable NIR-II Single Particle Imaging in Live Brain Slices at Ultra-Low Excitation Doses

Cellular and tissue imaging in the second near-infrared window (NIR-II, [~]1000 - 1350 nm) is advantageous for in vivo studies because of low light extinction by biological constituents at these wavelengths. However, deep tissue imaging at the single molecule sensitivity has not been achieved in the NIR-II window due to lack of suitable bio-probes. Single-walled carbon nanotubes have emerged as promising near-infrared luminescent molecular bio-probes; yet, their inefficient photoluminescence (quantum yield [~]1%) drives requirements for sizeable excitation doses ([~]1-10 kW/cm2) that are significantly blue-shifted from the NIR-II region (<850 nm) and may thus ultimately compromise live tissue. Here, we show that single nanotube imaging can be achieved in live brain tissue using ultralow excitation doses ([~]100 W/cm2), an order of magnitude lower than those currently used. To accomplish this, we synthesized fluorescent sp3-defect tailored (6,5) carbon nanotubes which, when excited at their first order excitonic transition fluoresce brightly at [~]1160 nm. The biocompatibility of these functionalized nanotubes, which are wrapped by state-of-the-art encapsulation agents (phospholipid-polyethylene glycol), is demonstrated using standard cytotoxicity assays. Single molecule photophysical studies of these biocompatible nanotubes allowed us to identify the optimal luminescence properties in the context of biological imaging.

biophysics↗

bioRxiv2019

Logic-based Analysis of Gene Expression Data Predicts Pathway Crosstalk between TNF, TGFB1 and EGF in Basal-like Breast Cancer

For breast cancer, clinically important subtypes are well characterised at the molecular level in terms of gene expression profiles. In addition, signaling pathways in breast cancer have been extensively studied as therapeutic targets due to their roles in tumor growth and metastasis. However, it is challenging to put signaling pathways and gene expression profiles together to characterise biological mechanisms of breast cancer subtypes since many signaling events result from post-translational modifications, rather than gene expression differences.\n\nWe present a logic-based approach to explain the differences in gene expression profiles among breast cancer subtypes using Pathway Logic and transcriptional network information. Pathway Logic is a rewriting-logic-based formal system for modeling biological pathways including post-translational modifications. Proposed method demonstrated its utility by constructing subtype-specific path from key receptors (TNFR, TGFBR1 and EGFR) to key transcription factor (TF) regulators (RELA, ATF2, SMAD3 and ELK1) and identifying potential pathway crosstalk via TFs in basal-specific paths, which could provide a novel insight on aggressive breast cancer subtypes.\n\nAvailabilityAnalysis result is available at http://epigenomics.snu.ac.kr/PL/

bioinformatics↗

bioRxiv2019

ChIA-DropBox: a novel analysis and visualization pipeline for multiplex chromatin interactions

ChIA-Drop is a new experimental method for mapping multiplex chromatin interactions with single-molecule precision by barcoding chromatin complexes inside microfluidics droplets, followed by pooled DNA sequencing. The chromatin DNA reads with the same droplet-specific barcodes are inferred to be derived from the same chromatin interaction complex. Here, we describe an integrated computational pipeline, named ChIA-DropBox, that is specifically designed for reconstructing chromatin reads in each droplet and refining multiplex chromatin complexes from raw ChIA-Drop sequencing reads, and then visualizing the results. First, ChIA-DropBox maps and filters sequencing reads, and then reconstructs the \"chromatin droplets\" by parsing the barcode sequences and grouping together chromatin reads with the same barcode. Based on the concept of chromosome territories that most chromatin interactions take place within the same chromosome, potential mixing up of chromatin complexes derived from different chromosomes could be readily identified and separated. Accordingly, ChIA-DropBox refines these \"chromatin droplets\" into purely intra-chromosomal chromatin complexes, ready for downstream analysis. For visualization, ChIA-DropBox converts the ChIA-Drop data to pairwise format and automatically generates input files for viewing 2D contact maps in Juicebox and viewing loops in BASIC Browser. Finally, ChIA-DropBox introduces a new browser, named ChIA-View, for interactive visualization of multiplex chromatin interactions.

bioinformatics↗

bioRxiv2019

Complex interaction networks of cytokines after transarterial chemotherapy in patients with hepatocellular carcinoma

Inflammation in the tumor microenvironment influences all stages of HCC development and progression as well as the anti-cancer response by immune system. In this study, we studied cytokine networks before and after transarterial chemotherapy (TACE). Serum samples obtained from 203 HCC patients treated with TACE were analyzed for inflammatory cytokines including interleukin (IL)-1{beta}, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12, IL-13, IL-17, IL-22, TNF-, IFN-{gamma}, and C-reactive protein (CRP) levels. Cytokine concentrations were measured at day 0 (D0, baseline), day3 (D3), day7 (D7), and day 60 (D60) after TACE. Network analysis revealed that modules within cytokine network at D0 were lost by D60 and modularity value (Mc) was decreased from 0.177 at D0 to -0.091 at D60. D60 had the lowest network heterogeneity and lower diameter, clustering coefficient, network density and recruited nodes. Degree correlation revealed that assortative network turned to disassortative network by D60 indicating that the network gained scale free feature. CRP, IL-2 were components of modules related with adverse outcome and IL-13, favorable outcome. Median survival month of patient group with high and low values with P-values were as follows: D0 CRP, 9.5 month (M), 54.2M (P<0.0001); D0 IL-2, 39.9M, 56.1M (P=0.0084); D3 CRP, 31.3M, 55.1 M (P=0.0056); D7 CRP, 28.7M, 50.7M (P=0.0065); IL-13, 51.9M, 33.6M (P=0.06). Network modularity decreased with temporal changes. Components of modules that included CRP, IL-2 and IL-6 were associated with adverse outcome and short overall survival. These modules were dissolved by D60 after TACE. Degree correlation decreased by D60, indicating that the cytokine network gained the scale free network property as in other biological network. TACE treatment converted cytokine network from that with inflammatory module to that with scale free network feature and without modules. Further studies are required to verify temporal changes of cytokine network in HCC patients after TACE.

immunology↗

bioRxiv2019

Oscillations, criticality and responsiveness in complex brain networks

Brain networks during unconscious states resulting from sleep, anesthesia, or traumatic injuries are associated with a limited capacity for complex responses to stimulation. Even during the conscious resting state, responsiveness to stimulus is highly dependent on spontaneous brain activities. Many empirical findings have been suggested that the brain responsiveness is determined mainly by the ongoing brain activity when a stimulus is given. However, there has been no systematic study exploring how such various brain activities with high or low synchronization, amplitude, and phase response to stimuli. In this model study, we simulated large-scale brain network dynamics in three brain states (below, near, and above the critical state) and investigated a relationship between ongoing oscillation properties and a stimulus decomposing the brain activity into fundamental oscillation properties (instantaneous global synchronization, amplitude, and phase). We identified specific stimulation conditions that produce varying levels of brain responsiveness. When a single pulsatile stimulus was applied to globally desynchronized low amplitude of oscillation, the network generated a large response. By contrast, when a stimulus was applied to specific phases of oscillation that were globally synchronized with high amplitude activity, the response was inhibited. This study proposes the oscillatory conditions to induce specific stimulation outcomes in the brain that can be systematically derived from networked oscillator properties, and reveals the presence of state-dependent temporal windows for optimal brain stimulation. The identified relationship will help advance understanding of the small/large responsiveness of the brain in different states of consciousness and suggest state-dependent methods to modulate responsiveness. Author SummaryA responsiveness of the brain network to external stimulus is different across brain states such as wakefulness, sleep, anesthesia, and traumatic injuries. It has been shown that responsiveness of the brain during conscious state also varies due to the diverse transient states of the brain characterized by different global and local oscillation properties. In this computational model study using large-scale brain network, we hypothesized that the brain responsiveness is determined by the interactions of networked oscillators when a stimulus is applied to the brain. We examined relationships between responsiveness of the brain network, global synchronization levels, and instantaneous oscillation properties such as amplitude and phase in different brain states. We found specific stimulation conditions of the brain that produce large or small levels of responsiveness. The identified relationship suggests the existence of temporal windows that periodically inhibit sensory information processing during conscious state and develops state-dependent methods to modulate brain responsiveness considering dynamically changed functional brain network.

neuroscience↗

bioRxiv2019

Multi-Cell ECM compaction is predictable via superposition of nonlinear cell dynamics linearized in augmented state space

Cells interacting through an extracellular matrix (ECM) exhibit emergent behaviors resulting from collective intercellular interaction. In wound healing and tissue development, characteristic compaction of ECM gel is induced by multiple cells that generate tensions in the ECM fibers and coordinate their actions with other cells. Computational prediction of collective cell-ECM interaction based on first principles is highly complex especially as the number of cells increase. Here, we introduce a computationally-efficient method for predicting nonlinear behaviors of multiple cells interacting mechanically through a 3-D ECM fiber network. The key enabling technique is superposition of single cell computational models to predict multicellular behaviors. While cell-ECM interactions are highly nonlinear, they can be linearized accurately with a unique method, termed Dual-Faceted Linearization. This method recasts the original nonlinear dynamics in an augmented space where the system behaves more linearly. The independent state variables are augmented by combining auxiliary variables that inform nonlinear elements involved in the system. This computational method involves a) expressing the original nonlinear state equations with two sets of linear dynamic equations b) reducing the order of the augmented linear system via principal component analysis and c) superposing individual single cell-ECM dynamics to predict collective behaviors of multiple cells. The method is computationally efficient compared to original nonlinear dynamic simulation and accurate compared to traditional Taylor expansion linearization. Furthermore, we reproduce reported experimental results of multi-cell induced ECM compaction.\n\nAuthor summaryCollective behaviors of multiple cells interacting through an ECM are prohibitively complex to predict with a mechanistic computational model due to its highly nonlinear dynamics and high dimensional space. We introduce a methodology where nonlinear dynamics of single cells are superposed to predict collective multi-cellular behaviors through a developed linearization method. We represent nonlinear single cell dynamics with linear state equations by augmenting the independent state variables with a set of auxiliary variables. We then transform the linear augmented state equations to a low-dimensional latent model and superpose the linear latent models of individual cells to predict collective behaviors that emerge from multi-cellular interactions. The method successfully reproduced experimental results of cell-induced ECM compaction.

systems biology↗

bioRxiv2018

Retinoid X receptor alpha is a spatiotemporally-specific therapeutic target for doxorubicin-induced cardiomyopathy in adult zebrafish

While the genetic suppressor screen is efficient in suggesting therapeutic genes, this strategy has yet to be successful for cardiomyopathies in vertebrates. To develop such a strategy, we recently established a mutagenesis screen platform in zebrafish for systematic discovery of genetic modifiers of doxorubicin-induced cardiomyopathy (DIC). Here, we further revealed both molecular and cellular insights of the first salutary modifier emerged from the screen, i.e. gene-breaking transposon (GBT) 0419 that affects the retinoid X receptor alpha a (rxraa) gene. First, by rescuing the mutation in tissue-specific manner with multiple Cre-loxP systems, we demonstrated that the endothelial, but not myocardial or epicardial, function of rxraa is primary to this cardioprotective effects. Next, we showed that the rxraa-associated salutary effects on DIC were conferred partially by the activation of retinoid acid (RA) signaling. Finally, we identified isotretinoin and bexarotene, 2 US Food and Drug Administration-approved RXRA agonists that are effective in treating adult zebrafish DIC when administered during the early, but not the late, phase of DIC progression. Collectively, we provided the first in vivo genetic evidence in supporting RXRA as the therapeutic target for DIC, and uncovered a previously unrecognized spatiotemporally-restricted mechanism for this gene-based therapeutic strategy. Our study also justified that searching salutary modifiers via zebrafish mutagenesis screen can be effective in discovering new therapeutic targets for cardiomyopathies.

genetics↗

bioRxiv2018

In silico Drug Repositioning of bortezomib to reverse metastatic effect of GALNT14 in lung cancer

Although many molecular targets for cancer therapy have been discovered, they often show poor druggability, which is a major obstacle to develop targeted drugs. As an alternative route to drug discovery, we adopted an in silico drug repositioning (in silico DR) approach based on large-scale gene expression signatures, with the goal of identifying inhibitors of lung cancer metastasis. Our analysis of clinicogenomic data identified GALNT14, an enzyme involved in O-linked N-acetyl galactosamine glycosylation, as a putative driver of lung cancer metastasis leading to poor survival. To overcome the poor druggability of GALNT14, we leveraged Connectivity Map approach, an in silico screening for drugs that are likely to revert the metastatic expression patterns. It leads to identification of bortezomib (BTZ) as a potent metastatic inhibitor, bypassing direct inhibition of poorly druggable target, GALNT14. The anti-metastatic effect of BTZ was verified in vitro and in vivo. Notably, both BTZ treatment and GALNT14 knockdown attenuated TGF{beta}-mediated gene expression and suppressed TGF{beta}-dependent metastatic genes, suggesting that BTZ acts by modulating TGF{beta} signalingTaken together, these results demonstrate that our in silico DR approach is a viable strategy to identify a candidate drug for undruggable targets, and to uncover its underlying mechanisms.

cancer biology↗

bioRxiv2018

Microglia-triggered hyperexcitability in the cerebellum depresses animal behaviors

Clinical studies have suggested that cerebellar dysfunction is involved in various psychiatric disorders, including autism spectrum disorders, dyslexia, and depressive disorders. However, the physiological aspect is less-advanced. Here, we comprehensively investigated the immune-triggered excitability plasticity in the cerebellum. Activated microglia (MG) via exposure to bacterial endotoxin lipopolysaccharide or heat-killed Gram-negative bacteria induced a potentiation of the excitability of Purkinje neurons, which was suppressed by MG-activity inhibitor and MG-depletion. An inflammatory cytokine, tumor necrosis factor- (TNF-) released from MG triggered this plasticity. While our new two-photon FRET ATP-imaging showed an increase in ATP concentration following endotoxin exposure, both TNF- and ATP secretion facilitated synaptic transmission. Inflammation in the cerebellar anterior vermis in vivo immobilized animals, and reduced sociability. Such abulia-like behavioral impairments were reverted by TNF--inhibition and MG-depletion. Resting-state functional MRI revealed overconnectivity between the inflamed cerebellum and prefrontal neocortical regions, which may underlie the psychomotor depressiveness in animals.

neuroscience↗

bioRxiv2018

A network-based model for drug repurposing in Rheumatoid Arthritis

BackgroundThe identification of drug repositioning targets through computational methods has the potential to provide a fast, inexpensive alternative to traditional drug discovery process. Diseases where complicated pathophysiology evolves over time are excellent targets for such methods. One such disease is Rheumatoid Arthritis (RA), a chronic inflammatory autoimmune disease, where the drug survival at 5-years is less than 50% for patients treated with disease-modifying anti-rheumatic drugs (DMARDs).\n\nMethods and FindingsWe have developed a network-based approach for drug repositioning that takes into account the human interactome network, proximity measures between drug targets and disease-associated genes, potential side-effects, genome-wide gene expression and disease modules that emerge through pertinent analysis. We found that all DMARDs, except for hydroxychloroquine (HCQ), were found to be significantly proximal to RA-related genes. Application of the method on anti-diabetic agents, statins and H2 receptor blockers identified anti-diabetic agents - gliclazide, sitagliptin and metformin - that have similar network signatures with the DMARDs. Subsequent in-vitro experiments on mouse fibroblast NIH-3T3 cells validated the findings and the down regulation of six key RA-related inflammatory genes. Our analysis further argues that the combination of HCQ and/or sulfasalazine with methotrexate (MTX) is predicted to have an additive synergistic effect in treatment based on network complementarity. Similarly, leflunomide and tofacitinib were found to be suitable alternatives upon chemoresistance to MTX-based double/triple therapy, given the complementary network signatures and overlapping critical target hubs.\n\nConclusionsOur results corroborate that computational methods that are based on network proximity, among other contextual information can help narrow down the drug candidates for drug repositioning, as well as support decisions for combinatorial drug treatment that is tailored to patients needs.\n\nAuthor summaryThe network-based proximity between drug targets and disease genes can provide novel insights on the repercussion, interplay, and reposition of drugs in the context of disease. Disease-modifying anti-rheumatic drugs (DMARDs) located significantly close to rheumatoid arthritis (RA)-associated genes and RA-relevant pathways. Three anti-diabetic agents were identified to have an anti-inflammatory effect like DMARDs. We built RA disease module encompassing the emerging small-molecule targets and functional neighbors, which better explained the RA pathophysiology. By proximity and network robustness, tofacitinib and tocilizumab were the most potent for RA disease module as a single agent, and this is consistent with clinical observation. Side effects of clinical importance are predictable by measuring network-based proximity between drug targets and side effect protein. Network-based drug-disease proximity offers a novel and clinically actionable information about drugs and opens the new possibility to drug combination and reposition.

systems biology↗

bioRxiv2018

Thalamus, subiculum and retrosplenial cortex encode 3D head direction information in volumetric space

Head direction cells are critical for navigation because they convey information about which direction an animal is facing within an environment. To date, most studies on head direction encoding have been conducted on a horizontal two-dimensional (2D) plane, and little is known about how three-dimensional (3D) direction information is encoded in the brain despite humans and other animals living in a 3D world. Here, we investigated head direction encoding in the human brain while participants moved within a virtual 3D \"spaceship\" environment. Movement was not constrained to planes and instead participants could move along all three axes in volumetric space as if in zero gravity. Using functional MRI multivoxel pattern similarity analysis, we found evidence that the thalamus, particularly the anterior portion, and the subiculum encoded the horizontal component of 3D head direction (azimuth). In contrast, the retrosplenial cortex was significantly more sensitive to the vertical direction (pitch) than to the azimuth. Our results also indicated that vertical direction information in the retrosplenial cortex was significantly correlated with behavioural performance during a direction judgment task. Our findings represent the first evidence showing that the classic head direction system that has been identified on a horizontal 2D plane also seems to encode vertical and horizontal heading in 3D space in the human brain.

neuroscience↗

bioRxiv2018

MEST induces epithelial-mesenchymal transition through IL-6/JAK/STAT3 signaling in breast cancers

The loss of imprinting of MEST has been linked to certain types of cancer by promoter switching. However, MEST-mediated regulation of tumorigenicity and metastasis are yet to be understood. Herein, we reported that MEST is a key regulator of IL-6/JAK/STAT3/Twist-1 signal pathway-mediated tumor metastasis. Enhanced MEST expression is significantly associated with pathogenesis of breast cancer patients. Also, MEST induces metastatic potential of breast cancer through induction of the EMT-TFs-mediated EMT program. Moreover, MEST leads to Twist-1 induction by STAT3 activation and subsequently enables the induction of activation of the EMT program via the induction of STAT3 nuclear translocation. Furthermore, the c-terminal region of MEST was essential for STAT3 activation via the induction of JAK2/STAT3 complex formation. Finally, MEST significantly increases the breast cancers ability to metastasize from the mammary gland to the lung. These observations suggest that MEST is a promising target for intervention to prevent tumor metastasis.

cancer biology↗

bioRxiv2018

Robo1 and 2 repellent receptors cooperate to guide facial neuron cell migration and axon projections in the embryonic mouse hindbrain

BackgroundThe facial nerve is necessary for our ability to eat, speak, and make facial expressions. Both the axons and cell bodies of the facial nerve undergo a complex embryonic migration pattern involving migration of the cell bodies caudally and tangentially through rhombomeres, and simultaneously the axons projecting to exit the hindbrain to form the facial nerve.\n\nResultsOur goal in this study was to test the functions of the chemorepulsive receptors Robo1 and Robo2 in facial neuron and axon migration by analyzing genetically marked motor neurons in double mutant mouse embryos through the migration time course, E10.0-E13.5. In Robo1/2 double mutants, axon and cell body migration errors were more severe than in single mutants. Most axons did not make it to their motor exit point, and instead projected into and longitudinally within the floor plate. Surprisingly, some facial neurons had bifurcated axons that either exited or projected into the floor plate. At the same time, a subset of mutant facial cell bodies failed to migrate caudally, and instead shifted into the floor plate.\n\nConclusionsRobo1 and Robo2 have redundant functions to guide multiple aspects of the complex cell migration of the facial nucleus, as well as regulating axon trajectories and suppressing formation of ectopic axons.\n\nBullet pointsO_LIRobo1 and 2 repellent receptors were tested for functions in facial neuron cell body and axon migration in the developing E10.0-E13.5 hindbrain of double mutant mouse embryos.\nC_LIO_LIIn Robo1;Robo2 double mutant embryos, facial motor neuron cell bodies and axons abnormally grew into the hindbrain floor plate, with stronger effects than in single Robo mutants.\nC_LIO_LIMany facial nerve axons abnormally bifurcated, failed to project to their proper exit point, and instead projected longitudinally within the floor plate.\nC_LIO_LIFacial neuron cell body tangential migration was disrupted.\nC_LIO_LIRobo receptor-mediated repulsion is required for proper migration of both facial axon projections and cell body migrations.\nC_LI\n\nFunding was provided to G.S.M. by NIH R01 NS054740, R21 NS077169, and R01 EY025205. Core facilities at the University of Nevada Reno campus are supported by NIH COBREs GM103650 and GM103554, and Nevada INBRE GM103440.

neuroscience↗

bioRxiv2018

Co-expression of MDM2 and CDK4 in transformed human mesenchymal stem cells induces dedifferentiated liposarcoma potency

Amplification and overexpression of MDM2 and CDK4 are well-known diagnostic criteria of well-differentiated liposarcoma (WDLPS)/dedifferentiated liposarcoma (DDLPS). Although it was reported that depletion of MDM2 or CDK4 decreased proliferation in DDLPS cell lines, it remains unclear whether MDM2 and CDK4 induce WDLPS/DDLPS tumorigenesis. We examined whether MDM2 and/or CDK4 produce WDLPS/DDLPS using transformed human bone marrow stem cells (BMSCs), 2H and 5H, with five oncogenic hits (overexpression of hTERT, TP53 degradation, RB inactivation, c-MYC stabilization, and overexpression of HRASv12). In vitro functional experiments revealed that co-overexpression of MDM2 and CDK4 plays key roles in tumorigenesis by increasing cell growth and migration and inhibiting adipogenic differentiation potency compared to sole expression of MDM2 or CDK4. Using mouse xenograft models, we found that co-overexpression of MDM2 and CDK4 in 5H cells with five additional oncogenic mutations can develop proliferative DDLPS in vivo. Our results suggest that co-overexpression of MDM2 and CDK4 induces DDLPS tumour potency in transformed human BMSCs by accelerating cell growth and migration and blocking adipogenetic potential incooperation with multiple genetic factors.

cancer biology↗

bioRxiv2018

3D grid cells in human entorhinal cortex: Theoretical and methodological considerations and fMRI findings

Recent human functional magnetic resonance imaging (fMRI) and animal electrophysiology studies suggest that grid cells in entorhinal cortex are an efficient neural mechanism for encoding knowledge about the world, not only for spatial location but also for more abstract cognitive information. The world, be it physical or abstract, is often high-dimensional, but grid cells have been mainly studied on a simple two-dimensional (2D) plane. Recent theoretical studies have proposed how grid cells encode three-dimensional (3D) physical space, but it is unknown whether grid codes can be examined non-invasively in humans. Here, we investigated whether it was feasible to test different 3D grid models using fMRI based on the direction-modulated property of grid signals. In doing so, we developed interactive software to help researchers visualize 3D grid fields and predict grid activity in 3D as a function of movement directions. We found that a direction-modulated grid analysis was sensitive to one type of 3D grid model - a face-centred cubic (FCC) lattice model. As a proof of concept, we searched for 3D grid-like signals in human entorhinal cortex using a novel 3D virtual reality paradigm and a new fMRI analysis method. We found that signals in the left entorhinal cortex were explained by the FCC model. This is preliminary evidence for 3D grid codes in the human brain, notwithstanding the inherent methodological limitations of fMRI. We believe that our findings and software serve as a useful initial stepping-stone for studying grid cells in realistic 3D worlds and also, potentially, for interrogating abstract high-dimensional cognitive processes.\n\nHighlightsWe present software and an analysis method to probe 3D grid codes using human fMRI Based on an alignment score between 3D movement direction and grid orientation We then tested this using a 3D virtual environment and fMRI\n\nSignals in entorhinal cortex were explained by a face-centred cubic lattice model

neuroscience↗