The tumour microenvironment shapes innate lymphoid cells in patients with hepatocellular carcinoma.

OBJECTIVE: Hepatocellular carcinoma (HCC) represents a typical inflammation-associated cancer. Tissue resident innate lymphoid cells (ILCs) have been suggested to control tumour surveillance. Here, we studied how the local cytokine milieu controls ILCs in HCC. DESIGN: We performed bulk RNA sequencing of HCC tissue as well as flow cytometry and single-cell RNA sequencing of enriched ILCs from non-tumour liver, margin and tumour core derived from 48 patients with HCC. Simultaneous measurement of protein and RNA expression at the single-cell level (AbSeq) identified precise signatures of ILC subgroups. In vitro culturing of ILCs was used to validate findings from in silico analysis. Analysis of RNA-sequencing data from large HCC cohorts allowed stratification and survival analysis based on transcriptomic signatures. RESULTS: RNA sequencing of tumour, non-tumour and margin identified tumour-dependent gradients, which were associated with poor survival and control of ILC plasticity. Single-cell RNA sequencing and flow cytometry of ILCs from HCC livers identified natural killer (NK)-like cells in the non-tumour tissue, losing their cytotoxic profile as they transitioned into tumour ILC1 and NK-like-ILC3 cells. Tumour ILC composition was mediated by cytokine gradients that directed ILC plasticity towards activated tumour ILC2s. This was liver-specific and not seen in ILCs from peripheral blood mononuclear cells. Patients with high ILC2/ILC1 ratio expressed interleukin-33 in the tumour that promoted ILC2 generation, which was associated with better survival. CONCLUSION: Our results suggest that the tumour cytokine milieu controls ILC composition and HCC outcome. Specific changes of cytokines modify ILC composition in the tumour by inducing plasticity and alter ILC function.

The effects of telomere shortening on cancer cells: a network model of proteomic and microRNA analysis.

Previously, we have shown that shortening of telomeres by telomerase inhibition sensitized cancer cells to cisplatinum, slowed their migration, increased DNA damage and impaired DNA repair. The mechanism behind these effects is not fully characterized. Its clarification could facilitate novel therapeutics development and may obviate the time consuming process of telomere shortening achieved by telomerase inhibition. Here we aimed to decipher the microRNA and proteomic profiling of cancer cells with shortened telomeres and identify the key mediators in telomere shortening-induced damage to those cells. Of 870 identified proteins, 98 were differentially expressed in shortened-telomere cells. 47 microRNAs were differentially expressed in these cells; some are implicated in growth arrest or act as oncogene repressors. The obtained data was used for a network construction, which provided us with nodal candidates that may mediate the shortened-telomere dependent features. These proteins' expression was experimentally validated, supporting their potential central role in this system.

Common and specific signatures of gene expression and protein-protein interactions in autoimmune diseases.

The aim of this study is to understand intracellular regulatory mechanisms in peripheral blood mononuclear cells (PBMCs), which are either common to many autoimmune diseases or specific to some of them. We incorporated large-scale data such as protein-protein interactions, gene expression and demographical information of hundreds of patients and healthy subjects, related to six autoimmune diseases with available large-scale gene expression measurements: multiple sclerosis (MS), systemic lupus erythematosus (SLE), juvenile rheumatoid arthritis (JRA), Crohn's disease (CD), ulcerative colitis (UC) and type 1 diabetes (T1D). These data were analyzed concurrently by statistical and systems biology approaches tailored for this purpose. We found that chemokines such as CXCL1-3, 5, 6 and the interleukin (IL) IL8 tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In addition, the anti-apoptotic gene BCL3, interferon-γ (IFNG), and the vitamin D receptor (VDR) gene physically interact with significantly many genes that tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In general, similar cellular processes tend to be differentially expressed in PBMC in the analyzed autoimmune diseases. Specifically, the cellular processes related to cell proliferation (for example, epidermal growth factor, platelet-derived growth factor, nuclear factor-κB, Wnt/ß-catenin signaling, stress-activated protein kinase c-Jun NH2-terminal kinase), inflammatory response (for example, interleukins IL2 and IL6, the cytokine granulocyte-macrophage colony-stimulating factor and the B-cell receptor), general signaling cascades (for example, mitogen-activated protein kinase, extracellular signal-regulated kinase, p38 and TRK) and apoptosis are activated in most of the analyzed autoimmune diseases. However, our results suggest that in each of the analyzed diseases, apoptosis and chemotaxis are activated via different subsignaling pathways. Analyses of the expression levels of dozens of genes and the protein-protein interactions among them demonstrated that CD and UC have relatively similar gene expression signatures, whereas the gene expression signatures of T1D and JRA relatively differ from the signatures of the other autoimmune diseases. These diseases are the only ones activated via the Fcɛ pathway. The relevant genes and pathways reported in this study are discussed at length, and may be helpful in the diagnoses and understanding of autoimmunity and/or specific autoimmune diseases.

Spreading depression in focal ischemia: a computational study.

When a cerebral infarction occurs, surrounding the core of dying tissue there usually is an ischemic penumbra of nonfunctional but still viable tissue. One current but controversial hypothesis is that this penumbra tissue often eventually dies because of the metabolic stress imposed by multiple cortical spreading depression (CSD) waves, that is, by ischemic depolarizations. We describe here a computational model of CSD developed to study the implications of this hypothesis. After simulated infarction, the model displays the linear relation between final infarct size and the number of CSD waves traversing the penumbra that has been reported experimentally, although damage with each individual wave progresses nonlinearly with time. It successfully reproduces the experimental dependency of final infarct size on midpenumbra cerebral blood flow and potassium reuptake rates, and predicts a critical penumbra blood flow rate beyond which damage does not occur. The model reproduces the dependency of CSD wave propagation on N-methyl-D-aspartate activation. It also makes testable predictions about the number, velocity, and duration of ischemic CSD waves and predicts a positive correlation between the duration of elevated potassium in the infarct core and the number of CSD waves. These findings support the hypothesis that CSD waves play an important causal role in the death of ischemic penumbra tissue.

Pathogenesis of schizophrenic delusions and hallucinations: a neural model.

We implement and study a computational model of Stevens' theory of the pathogenesis of schizophrenia. This theory hypothesizes that the onset of schizophrenia is associated with reactive synaptic regeneration in brain regions that receive degenerating temporal lobe projections. Concentrating on one such area, the frontal cortex, we model a frontal module as an associative memory neural network whose input synapses represent incoming temporal projections. Modeling Stevens' hypothesized pathological synaptic changes in this framework results in adverse side effects similar to hallucinations and delusions seen in schizophrenia: spontaneous, stimulus-independent retrieval of stored memories focused on just a few of the stored patterns. These could account for the delusions and hallucinations that occur in schizophrenia without any apparent external trigger and for their tendency to concentrate on a few central cognitive and perceptual themes. The model explains why the positive symptoms of schizophrenia tend to wane as the disease progresses, why delayed therapeutic intervention leads to a much slower response, and why delusions and hallucinations may persist for a long time when they do occur.

Cortical spreading depression and the pathogenesis of brain disorders: a computational and neural network-based investigation.

This paper reviews our recent studies of the role of cortical spreading depression (CSD) in the pathogenesis of brain disorders. Our investigation is a computational one, involving the development and utilization of a complex neuro-metabolic model of the interactions assumed to occur in the cortex during the passage of multiple CSD waves. Incorporating these neuro-metabolic changes of CSD within a neural network model of normoxic cortex produces cortical activation patterns during the passage of a CSD wave that, projected onto the visual fields, resemble the visual hallucinations observed during the migraine aura. When focal ischemia is simulated with the model, the evoked CSD waves are found to affect the expansion of the infarction into the ischemic penumbra. Our findings support the hypothesis that CSD does play an important pathogenic role in these and other neurological disorders, and suggest additional experimental studies that may further substantiate it.

Distributed synchrony in a cell assembly of spiking neurons.

We investigate the formation of a Hebbian cell assembly of spiking neurons, using a temporal synaptic learning curve that is based on recent experimental findings. It includes potentiation for short time delays between pre- and post-synaptic neuronal spiking, and depression for spiking events occurring in the reverse order. The coupling between the dynamics of synaptic learning and that of neuronal activation leads to interesting results. One possible mode of activity is distributed synchrony, implying spontaneous division of the Hebbian cell assembly into groups, or subassemblies, of cells that fire in a cyclic manner. The behavior of distributed synchrony is investigated both by simulations and by analytic calculations of the resulting synaptic distributions.

NMDA receptor delayed maturation and schizophrenia.

This paper presents the hypothesis that NMDA receptor delayed maturation (NRDM) may lead to the pathogenesis of schizophrenic psychotic symptoms. This hypothesis is further analyzed in the language of a neural modeling formulation. This formulation points to a possible chain of pathological events, leading from molecular-level NRDM to over-increased synaptic plasticity, and to the formation of pathological attractors, a putative macroscopic-level correlate of schizophrenic positive symptoms. The relations of the NRDM hypothesis to other alterations which are assumed to take place in schizophrenia are discussed, together with possible ways to test this hypothesis.

Extra-pyramidal symptoms in Alzheimer's disease: a hypothesis.

Recent studies have shown that compensatory processes have an important role in counteracting the neurodegenerative changes underlining Alzheimer's disease (AD), much like their well known role in Parkinson's disease (PD). In the light of these reports, we review the findings of the positive correlation existing between the appearance of extra-pyramidal symptoms and an increased rate of progression in AD patients. We propose that this correlated symptomatology arises from the wasting of globally shared compensatory resources, manifested both in an increasing inability to compensate for persisting sub-clinical nigral lesions, and in enhanced AD deterioration rate. Our hypothesis gains support from various clinical reports and by the neural modeling of synaptic changes in AD.

A single-iteration threshold Hamming network.

We analyze in detail the performance of a Hamming network classifying inputs that are distorted versions of one of its m stored memory patterns, each being a binary vector of length n. It is shown that the activation function of the memory neurons in the original Hamming network may be replaced by a simple threshold function. By judiciously determining the threshold value, the "winner-take-all" subnet of the Hamming network (known to be the essential factor determining the time complexity of the network's computation) may be altogether discarded. For m growing exponentially in n, the resulting threshold Hamming network correctly classifies the input pattern in a single iteration, with probability approaching 1.

Pathogenic mechanisms in ischemic damage: a computational study.

The pathogenesis of penumbral tissue infarction during acute ischemic stroke is controversial. This peri-infarct tissue may subsequently die, or survive and recuperate, and its preservation has been a prime goal of recent therapeutic trials in acute stroke. Two major hypotheses currently under consideration are that penumbral tissue is recruited into an infarct by cortical spreading depression (CSD) waves, or by a non-wave self-propagating process such as glutamate excitotoxicity (GE). Careful experimental attempts to discriminate between these two hypotheses have so far been quite ambiguous. Using a computational metabolic model of acute focal stroke we show here that the spatial patterns of tissue damage arising from artificially induced foci of infarction having specific geometric shapes are inherently different. This is due to the distinct propagation characteristics underlying self-regenerating waves and non-wave diffusional processes. The experimental testing of these predicted spatial patterns of damage may help determine the relative contributions of the two pathological mechanisms hypothesized for ischemic tissue damage.

Reinforcement-driven dimensionality reduction--a model for information processing in the basal ganglia.

Although anatomical studies of the basal ganglia show the existence of extensive convergence and lateral inhibitory connections, physiological studies failed to show correlated neural activity or lateral interaction in these nuclei. These seemingly contradictory results could be explained with a model in which the basal ganglia reduce the dimensionality of cortical information using optimal extraction methods. Simulations of this model predict a transient change in the efficacy of the feed-forward and lateral synapses following changes in reinforcement signal, causing an increase in correlated firing rates. This process ultimately restores the steady-state situation with diminished efficacy of lateral inhibition and no correlation of firing. Our experimental results confirm the model's predictions: rate correlations show a drastic decrease between the input stage (cortex) and output stage (pallidum). Moreover, preliminary analysis revealed that pallidal correlations show a transient increase following discrepancies between the animal's predictions and reality. We therefore propose that by using a reinforcement-driven dimensionality reduction process the basal ganglia achieve efficient extraction of cortical salient information that may then be used by the frontal cortex for execution and planning of forthcoming actions.

Frequency-spatial transformation: a proposal for parsimonious intra-cortical communication.

This work examines a neural network model of a cortical module, where neurons are organized on a 2-dimensional sheet and are connected with higher probability to their spatial neighbors. Motivated by recent findings that cortical neurons have a resonant peak in their impedance magnitude function, we present a frequency-spatial transformation scheme that is schematically described as follows: An external input signal, applied to a small input subset of the neurons, spreads along the network. Due to a stochastic component in the dynamics of the neurons, the frequency of the spreading signal decreases as it propagates through the network. Depending on the input signal frequency, different neural assemblies will hence fire at their specific resonance frequency. We show analytically that the resulting frequency-spatial transformation is well-formed; an injective, fixed, mapping is obtained. Extensive numerical simulations demonstrate that a homogeneous, well-formed transformation may also be obtained in neural networks with cortical-like "Mexican-hat" connectivity. We hypothesize that a frequency-spatial transformation may serve as a basis for parsimonious cortical communication.

A systems level strategy for analyzing the cell death network: implication in exploring the apoptosis/autophagy connection.

The mammalian cell death network comprises three distinct functional modules: apoptosis, autophagy and programmed necrosis. Currently, the field lacks systems level approaches to assess the extent to which the intermodular connectivity affects cell death performance. Here, we developed a platform that is based on single and double sets of RNAi-mediated perturbations targeting combinations of apoptotic and autophagic genes. The outcome of perturbations is measured both at the level of the overall cell death responses, using an unbiased quantitative reporter, and by assessing the molecular responses within the different functional modules. Epistatic analyses determine whether seemingly unrelated pairs of proteins are genetically linked. The initial running of this platform in etoposide-treated cells, using a few single and double perturbations, identified several levels of connectivity between apoptosis and autophagy. The knock down of caspase3 turned on a switch toward autophagic cell death, which requires Atg5 or Beclin-1. In addition, a reciprocal connection between these two autophagic genes and apoptosis was identified. By applying computational tools that are based on mining the protein-protein interaction database, a novel biochemical pathway connecting between Atg5 and caspase3 is suggested. Scaling up this platform into hundreds of perturbations potentially has a wide, general scope of applicability, and will provide the basis for future modeling of the cell death network.

The effect of phenotypic plasticity on evolution in multipeaked fitness landscapes.

When facing the challenge of developing an individual that best fits its environment, nature demonstrates an interesting combination of two fundamentally different adaptive mechanisms: genetic evolution and phenotypic plasticity. Following numerous computational models, it has become the accepted wisdom that lifetime acclimation (e.g. via learning) smooths the fitness landscape and consequently accelerates evolution. However, analytical studies, focusing on the effect of phenotypic plasticity on evolution in simple unimodal landscapes, have often found that learning hinders the evolutionary process rather than accelerating it. Here, we provide a general framework for studying the effect of plasticity on evolution in multipeaked landscapes and introduce a rigorous mathematical analysis of these dynamics. We show that the convergence rate of the evolutionary process in a given arbitrary one-dimensional fitness landscape is dominated by the largest descent (drawdown) in the landscape and provide numerical evidence to support an analogous dominance also in multidimensional landscapes. We consider several schemes of phenotypic plasticity and examine their effect on the landscape drawdown, identifying the conditions under which phenotypic plasticity is advantageous. The lack of such a drawdown in unimodal landscapes vs. its dominance in multipeaked landscapes accounts for the seemingly contradictory findings of previous studies.

Compensatory mechanisms in an attractor neural network model of schizophrenia.

We investigate the effect of synaptic compensation on the dynamic behavior of an attractor neural network receiving its input stimuli as external fields projecting on the network. It is shown how, in the face of weakened inputs, memory performance may be preserved by strengthening internal synaptic connections and increasing the noise level. Yet, these compensatory changes necessarily have adverse side effects, leading to spontaneous, stimulus-independent retrieval of stored patterns. These results can support Stevens' recent hypothesis that the onset of schizophrenia is associated with frontal synaptic regeneration, occurring subsequent to the degeneration of temporal neurons projecting on these areas.