Correlation of LLT-1 and NLRC4 inflammasome and its effect on glioblastoma prognosis.

PURPOSE: LLT-1 is a well-known ligand for the natural killer (NK) cell inhibitory receptor NKRP1A. Here, we examined NLRC4 inflammasome components and LLT-1 expression in glioblastoma (GBM) tissues to elucidate potential associations and interactions between these factors. METHODS: GBM tissues were collected for RNA sequencing (RNA-seq) and Immunofluorescent experiments. Colocalization of LLT-1 and other proteins was assessed by immunofluorescence. Computational analyses utilized RNA-seq data from 296 to 52 patients from the Chinese Glioma Genome Atlas and CHA medical records, respectively. These data were subjected to survival, non-negative matrix factorization clustering, Gene Ontology enrichment, and protein-protein interaction analyses. Receptor-ligand interactions between tumor and immune cells were confirmed by single-cell RNA-seq analysis. RESULTS: In GBM tissues, LLT-1 was predominantly colocalized with glial fibrillary acidic protein (GFAP)-expressing astrocytes, but not with microglial markers like Iba-1. Additionally, LLT-1 and activated NLRC4 inflammasomes were mainly co-expressed in intratumoral astrocytes, suggesting an association between LLT-1, NLRC4, and glioma malignancy. High LLT-1 expression correlates with poor prognosis, particularly in the mesenchymal subtype, and is associated with TNF and NOD-like receptor signaling pathway enrichment, indicating a potential role in tumor inflammation and progression. At the single-cell level, mesenchymal-like malignant cells showed high NF, NLR, and IL-1 signaling pathway enrichment compared to other malignant cell types. CONCLUSION: We revealed an association between NLRC4 inflammasome activity and LLT-1 expression, suggesting a novel regulatory pathway involving TNF, inflammasomes, and IL-1, potentially offering new NK-cell-mediated anti-glioma approaches.

Dysregulation of inflammasome activation in glioma.

Gliomas are the most common brain tumors characterized by complicated heterogeneity. The genetic, molecular, and histological pathology of gliomas is characterized by high neuro-inflammation. The inflammatory microenvironment in the central nervous system (CNS) has been closely linked with inflammasomes that control the inflammatory response and coordinate innate host defenses. Dysregulation of the inflammasome causes an abnormal inflammatory response, leading to carcinogenesis in glioma. Because of the clinical importance of the various physiological properties of the inflammasome in glioma, the inflammasome has been suggested as a promising treatment target for glioma management. Here, we summarize the current knowledge on the contribution of the inflammasomes in glioma and therapeutic insights. Video Abstract.

Non-canonical NLRC4 inflammasomes in astrocytes contribute to glioma malignancy.

BACKGROUND: The present study was designed to explore the pathological role of non-canonical NLRC4 inflammasome in glioma. METHODS: This retrospective study included bioinformatical analysis, including survival, gene ontology, ssGSEA, cox regression, IPA and drug repositioning with TCGA and DepMap database. Experimental validations were conducted in glioma patient's sample and evaluated with histological or cellular functional analysis. RESULT: Clinical dataset analysis revealed that non-canonical NLRC4 inflammasomes significantly contribute to glioma progression and poor survival rates. Experimental validation was revealed that the expression of non-canonical NLRC4 inflammasomes were co-localized with astrocytes in malignant gliomas, with a sustained clinical correlation observed between astrocytes and inflammasome signatures. Indeed, the formation of an inflammatory microenvironment increased in malignant gliomas, leading to pyroptosis, known as inflammatory cell death. Molecular interaction analysis revealed that NF-κB pathways potentially serve as the connecting point between the canonical and noncanonical pathways of the NLRC4 inflammasome. Finally, drug repositioning analysis of non-canonical NLRC4 inflammasome-associated molecules revealed that MK-5108, PF4981517, and CTEP may represent effective options for glioma therapy. CONCLUSION: The findings of this study suggest that non-canonical NLRC4 inflammasomes contribute to poor prognosis in patients with glioma and induce an inflammatory microenvironment. We propose the pathological phenomenon of non-canonical NLRC4 inflammasomes and several therapeutic strategies based on the modulation of the inflammatory tumor microenvironment.

Association of Tim-3/Gal-9 Axis with NLRC4 Inflammasome in Glioma Malignancy: Tim-3/Gal-9 Induce the NLRC4 Inflammasome.

Tim-3/Gal-9 and the NLRC4 inflammasome contribute to glioma progression. However, the underlying mechanisms involved are unclear. Here, we observed that Tim-3/Gal-9 expression increased with glioma malignancy and found that Tim-3/Gal-9 regulate NLRC4 inflammasome formation and activation. Tim-3/Gal-9 and NLRC4 inflammasome-related molecule expression levels increased with WHO glioma grade, and this association was correlated with low survival. We investigated NLRC4 inflammasome formation by genetically regulating Tim-3 and its ligand Gal-9. Tim-3/Gal-9 regulation was positively correlated with the NLRC4 inflammasome, NLRC4, and caspase-1 expression. Tim-3/Gal-9 did not trigger IL-1ß secretion but were strongly positively correlated with caspase-1 activity as they induced programmed cell death in glioma cells. A protein-protein interaction analysis revealed that the FYN-JAK1-ZNF384 pathways are bridges in NLRC4 inflammasome regulation by Tim-3/Gal-9. The present study showed that Tim-3/Gal-9 are associated with poor prognosis in glioma patients and induce NLRC4 inflammasome formation and activation. We proposed that a Tim-3/Gal-9 blockade could be beneficial in glioma therapy as it would reduce the inflammatory microenvironment by downregulating the NLRC4 inflammasome.

Free energy measurements by the generalized fluctuation theorems: Theory and numerical study of a model filament.

We measure the free energy of a model filament, which undergoes deformations and structural transitions, as a function of its extension, in silico. We perform Brownian Dynamics (BD) simulations of pulling experiments at various speeds, following a protocol close to experimental ones. The results from the fluctuation theorems are compared with the estimates from Monte Carlo (MC) simulation, where the rugged free energy landscape is produced by the density of states method. The fluctuation theorems (FT) give accurate estimates of the free energy up to moderate pulling speeds. At higher pulling speeds, the work distributions do not efficiently sample the domain of small work and FT slightly overestimates free energy. In order to comprehend the differences, we analyze the work distributions from the BD simulations in the framework of trajectory thermodynamics and propose the generalized fluctuation theorems that take into account the information (relative entropy) evaluated in the expanded phase space. The measured work - free energy relation is consistent with the results obtained from the generalized fluctuation theorems. We discuss operational methods to improve the estimates at high pulling speed.

Modularity enhances the rate of evolution in a rugged fitness landscape.

Biological systems are modular, and this modularity affects the evolution of biological systems over time and in different environments. We here develop a theory for the dynamics of evolution in a rugged, modular fitness landscape. We show analytically how horizontal gene transfer couples to the modularity in the system and leads to more rapid rates of evolution at short times. The model, in general, analytically demonstrates a selective pressure for the prevalence of modularity in biology. We use this model to show how the evolution of the influenza virus is affected by the modularity of the proteins that are recognized by the human immune system. Approximately 25% of the observed rate of fitness increase of the virus could be ascribed to a modular viral landscape.

General protocol for predicting outbreaks of infectious diseases in social networks.

Epidemic spreading on social networks with quenched connections is strongly influenced by dynamic correlations between connected nodes, posing theoretical challenges in predicting outbreaks of infectious diseases. The quenched connections introduce dynamic correlations, indicating that the infection of one node increases the likelihood of infection among its neighboring nodes. These dynamic correlations pose significant difficulties in developing comprehensive theories for threshold determination. Determining the precise epidemic threshold is pivotal for diseases control. In this study, we propose a general protocol for accurately determining epidemic thresholds by introducing a new set of fundamental conditions, where the number of connections between individuals of each type remains constant in the stationary state, and by devising a rescaling method for infection rates. Our general protocol is applicable to diverse epidemic models, regardless of the number of stages and transmission modes. To validate our protocol's effectiveness, we apply it to two widely recognized standard models, the susceptible-infected-recovered-susceptible model and the contact process model, both of which have eluded precise threshold determination using existing sophisticated theories. Our results offer essential tools to enhance disease control strategies and preparedness in an ever-evolving landscape of infectious diseases.

Translocation of Hydrophobic Polyelectrolytes under Electrical Field: Molecular Dynamics Study.

We studied the translocation of polyelectrolyte (PE) chains driven by an electric field through a pore by means of molecular dynamics simulations of a coarse-grained HP model mimicking high salt conditions. Charged monomers were considered as polar (P) and neutral monomers as hydrophobic (H). We considered PE sequences that had equally spaced charges along the hydrophobic backbone. Hydrophobic PEs were in the globular form in which H-type and P-type monomers were partially segregated and they unfolded in order to translocate through the narrow channel under the electric field. We provided a quantitative comprehensive study of the interplay between translocation through a realistic pore and globule unraveling. By means of molecular dynamics simulations, incorporating realistic force fields inside the channel, we investigated the translocation dynamics of PEs at various solvent conditions. Starting from the captured conformations, we obtained distributions of waiting times and drift times at various solvent conditions. The shortest translocation time was observed for the slightly poor solvent. The minimum was rather shallow, and the translocation time was almost constant for medium hydrophobicity. The dynamics were controlled not only by the friction of the channel, but also by the internal friction related to the uncoiling of the heterogeneous globule. The latter can be rationalized by slow monomer relaxation in the dense phase. The results were compared with those from a simplified Fokker-Planck equation for the position of the head monomer.

Comparing the Expression of Canonical and Non-Canonical Inflammasomes Across Glioma Grades: Evaluating Their Potential as an Aggressiveness Marker.

BACKGROUND: Inflammasomes are key in the initiation of inflammatory responses and serve to defend the organism. However, when the immune system is imbalanced, these complexes contribute to tumor progression. The purpose of this study was to investigate the effect of non-canonical inflammasomes on glioma malignancy. METHODS: We performed bioinformatics analysis to confirm the expression of canonical and non-canonical inflammasome-related molecules according to the degree of malignancy through immunohistochemical examination of glioma tissues obtained with patient consent from our institution. RESULTS: Bioinformatics analysis confirmed that the expression levels of non-canonical inflammasome-related molecules were significantly higher in tumor tissues than in normal tissues, and they also increased according to malignancy, which adversely affected the survival rate. Furthermore, in gliomas, positive correlations were found between N-form gasdermin-D, a key molecule associated with the non-canonical inflammasome, and other related molecules, including NLRP3, caspase-1, caspase-4, and caspase-5. These results were verified by immunohistochemical examination of glioma tissues, and the expression levels of these molecules also increased significantly with increasing grade. In addition, the features of pyroptosis were confirmed. CONCLUSION: This study identified the potential of non-canonical inflammasomes as aggressiveness markers for gliomas and presented a perspective for improving glioma treatment.

Molecular characteristics of incidental lower-grade glioma for treatment decision-making.

OBJECTIVE: Several limitations are associated with the early diagnosis and treatment of incidental lower-grade glioma (iLGG), and due to its unknown molecular features, its management is categorized as either the "wait-and-see" strategy or immediate treatment. Therefore, in this study the authors explored iLGG's clinical and molecular landscape to improve its management. METHODS: The authors retrospectively assessed the differences between the molecular and clinical characteristics of iLGG and symptomatic lower-grade glioma (sLGG) samples filtered based on symptom data corresponding to The Cancer Genome Atlas cohort with mutations. Thereafter, genomic and transcriptomic analysis was performed. RESULTS: There was no significant difference between iLGG and sLGG with respect to mutation status; however, there was an increase in the interaction between major mutations in sLGG, depending on the histological subtype and the IDH1 mutation status. Furthermore, the IDH1 mutation characteristics corresponding to wild-type glioma were much more obvious in sLGG than in iLGG. Additionally, in sLGG, genes associated with malignancy, including cell proliferation-related, cell migration-related, epithelial-to-mesenchymal transition-related, and negative regulation of cell death-related genes, were significantly upregulated, and groups showing higher expression levels of these genes were associated with worse prognosis. Also, 8 of the 75 identified upregulated genes showed positive correlation with resistance to the drugs that are normally used for glioma treatment, including procarbazine, carmustine, vincristine, and temozolomide. CONCLUSIONS: The new insights regarding the different molecular features of iLGG and sLGG indicated that the immediate management of iLGG could result in better prognosis than the wait-and-see strategy.

Downregulation of LOC441461 Promotes Cell Growth and Motility in Human Gastric Cancer.

Gastric cancer is a common tumor, with a high mortality rate. The severity of gastric cancer is assessed by TNM staging. Long noncoding RNAs (lncRNAs) play a role in cancer treatment; investigating the clinical significance of novel biomarkers associated with TNM staging, such as lncRNAs, is important. In this study, we investigated the association between the expression of the lncRNA LOC441461 and gastric cancer stage. LOC441461 expression was lower in stage IV than in stages I, II, and III. The depletion of LOC441461 promoted cell proliferation, cell cycle progression, apoptosis, cell motility, and invasiveness. LOC441461 downregulation increased the epithelial-to-mesenchymal transition, as indicated by increased TRAIL signaling and decreased RUNX1 interactions. The interaction of the transcription factors RELA, IRF1, ESR1, AR, POU5F1, TRIM28, and GATA1 with LOC441461 affected the degree of the malignancy of gastric cancer by modulating gene transcription. The present study identified LOC441461 and seven transcription factors as potential biomarkers and therapeutic targets for the treatment of gastric cancer.

Translocation, Rejection and Trapping of Polyampholytes.

Polyampholytes (PA) are a special class of polymers comprising both positive and negative monomers along their sequence. Most proteins have positive and negative residues and are PAs. Proteins have a well-defined sequence while synthetic PAs have a random charge sequence. We investigated the translocation behavior of random polyampholyte chains through a pore under the action of an electric field by means of Monte Carlo simulations. The simulations incorporated a realistic translocation potential profile along an extended asymmetric pore and translocation was studied for both directions of engagement. The study was conducted from the perspective of statistics for disordered systems. The translocation behavior (translocation vs. rejection) was recorded for all 220 sequences comprised of N = 20 charged monomers. The results were compared with those for 107 random sequences of N = 40 to better demonstrate asymptotic laws. At early times, rejection was mainly controlled by the charge sequence of the head part, but late translocation/rejection was governed by the escape from a trapped state over an antagonistic barrier built up along the sequence. The probability distribution of translocation times from all successful attempts revealed a power-law tail. At finite times, there was a population of trapped sequences that relaxed very slowly (logarithmically) with time. If a subensemble of sequences with prescribed net charge was considered the power-law decay was steeper for a more favorable net charge. Our findings were rationalized by theoretical arguments developed for long chains. We also provided operational criteria for the translocation behavior of a sequence, explaining the selection by the translocation process. From the perspective of protein translocation, our findings can help rationalize the behavior of intrinsically disordered proteins (IDPs), which can be modeled as polyampholytes. Most IDP sequences have a strong net charge favoring translocation. Even for sequences with those large net charges, the translocation times remained very dispersed and the translocation was highly sequence-selective.

Potential of Hematologic Parameters in Predicting Mortality of Patients with Traumatic Brain Injury.

Traumatic brain injury (TBI) occurs frequently, and acute TBI requiring surgical treatment is closely related to patient survival. Models for predicting the prognosis of patients with TBI do not consider various factors of patient status; therefore, it is difficult to predict the prognosis more accurately. In this study, we created a model that can predict the survival of patients with TBI by adding hematologic parameters along with existing non-hematologic parameters. The best-fitting model was created using the Akaike information criterion (AIC), and hematologic factors including preoperative hematocrit, preoperative C-reactive protein (CRP), postoperative white blood cell (WBC) count, and postoperative hemoglobin were selected to predict the prognosis. Among several prediction models, the model that included age, Glasgow Coma Scale, Injury Severity Score, preoperative hematocrit, preoperative CRP, postoperative WBC count, postoperative hemoglobin, and postoperative CRP showed the highest area under the curve and the lowest corrected AIC for a finite sample size. Our study showed a new prediction model for mortality in patients with TBI using non-hematologic and hematologic parameters. This prediction model could be useful for the management of patients with TBI.

Derivation of evolutionary entropy in the steady-state thermodynamics of evolutionary dynamics.

We investigate the parallel mutation-selection model with varying population size, which is formulated in terms of individuals undergoing the evolution processes of reproduction and mutation, to derive evolutionary entropy. Under the framework of the steady-state thermodynamics for evolutionary dynamics, the excess growth (the difference between the maximum growth rate and the total growth rate) can be interpreted as the evolutionary entropy defined in terms of the probability distributions characteristic of evolutionary dynamics. The Clausius inequality states that the excess growth is always less than or equal to the entropy difference in evolutionary dynamics. Analytically, by using the genome sequence length L=3, we derive the growth after evolutionary dynamics with the finite number of environmental changes and calculate the entropy difference during this evolutionary dynamics, and we verify the Clausius inequality. Furthermore, by taking the infinite limit of the number of environmental changes, we verify that the equality holds for the quasistatic environmental change. By using the derived evolutionary entropy, we propose the thermodynamic relation between the free fitness and evolutionary entropy, where the free fitness is the maximum growth rate possible. Numerically, we use the Gillespie-type simulations, which provides direct realizations of the master equation governing evolutionary dynamics, to verify the Clausius inequality and we find that the simulation results are in good agreement with the analytic results.

The Measurement of Information and Free Energy in Mechanical-Force-Driven Coil-Globule Transitions.

We study the role of information (the relative entropy) for polymers undergoing coil-globule transitions driven by a time-dependent force. Pulling experiments at various speeds are performed by Brownian dynamics simulations. We obtain the work distributions for the forward and time-reversed backward processes and information stored at the end of the nonequilibrium pulling processes. We present the systematic method to measure the information from the pulling experiments and extract the information by analyzing slowly relaxing modes. When the information is incorporated, the work distributions modified by the information allow access to the proper free energy via the formulation of the generalized fluctuation theorems even if the initial states of the forward and time-reversed backward processes are out of equilibrium. This demonstrates that the work-information conversion works well for a single-molecule system with many degrees of freedom.

Transcriptomic Landscape of Lower Grade Glioma Based on Age-Related Non-Silent Somatic Mutations.

Glioma accounts for 80% of all malignant brain tumours and is the most common adult primary brain tumour. Age is an important factor affecting the development of cancer, as somatic mutations accumulate with age. Here, we aimed to analyse the significance of age-dependent non-silent somatic mutations in glioma prognosis. Histological tumour grade depends on age at diagnosis in patients with IDH1, TP53, ATRX, and EGFR mutations. Age of patients with wild-type IDH1 and EGFR increased with increase in tumour grade, while the age of patients with IDH1 or EGFR mutation remained constant. However, the age of patients with EGFR mutation was higher than that of patients with IDH1 mutation. The hierarchical clustering of patients was dominantly separated by IDH1 and EGFR mutations. Furthermore, patients with IDH1 mutation were dominantly separated by TP53 and ATRX double mutation and its double wild-type counterpart. The age of patients with ATRX and TP53 mutation was lower than that of patients with wild-type ATRX and TP53. Patients with the double mutation showed poorer prognosis than those with the double wild type genotype. Unlike IDH1 mutant, IDH1 wild-type showed upregulation of expression of epithelial mesenchymal transition associated genes.

Association of an APBA3 Missense Variant with Risk of Premature Ovarian Failure in the Korean Female Population.

Premature ovarian failure (POF) is a complex disease of which the etiology is influenced by numerous genetic variations. Several POF candidate genes have been reported. However, no causal genes with high odds ratio (OR) have yet been discovered. This study included 564 females of Korean ethnicity, comprising 60 patients with POF and 182 controls in the discovery set and 105 patients with POF and 217 controls in the replication set. We conducted genome-wide association analysis to search for novel candidate genes predicted to influence POF development using Axiom Precision Medicine Research Arrays and additive model logistic regression analysis. One statistically significant single nucleotide polymorphism (SNP), rs55941146, which encodes a missense alteration (Val > Gly) in the APBA3 gene, was identified with OR values for association with POF of 13.33 and 4.628 in the discovery and replication sets, respectively. No rs55941146 minor allele homozygotes were present in either cases or controls. The APBA3 protein binds FIH-1 that inhibits hypoxia inducible factor-1α (HIF-1α). HIF-1α contributes to granulosa cell proliferation, which is crucial for ovarian follicle growth, by regulating cell proliferation factors and follicle stimulating hormone-mediated autophagy. Our data demonstrate that APBA3 is a candidate novel causal gene for POF.

Quasispecies theory for horizontal gene transfer and recombination.

We introduce a generalization of the parallel, or Crow-Kimura, and Eigen models of molecular evolution to represent the exchange of genetic information between individuals in a population. We study the effect of different schemes of genetic recombination on the steady-state mean fitness and distribution of individuals in the population, through an analytic field theoretic mapping. We investigate both horizontal gene transfer from a population and recombination between pairs of individuals. Somewhat surprisingly, these nonlinear generalizations of quasispecies theory to modern biology are analytically solvable. For two-parent recombination, we find two selected phases, one of which is spectrally rigid. We present exact analytical formulas for the equilibrium mean fitness of the population, in terms of a maximum principle, which are generally applicable to any permutation invariant replication rate function. For smooth fitness landscapes, we show that when positive epistatic interactions are present, recombination or horizontal gene transfer introduces a mild load against selection. Conversely, if the fitness landscape exhibits negative epistasis, horizontal gene transfer or recombination introduces an advantage by enhancing selection towards the fittest genotypes. These results prove that the mutational deterministic hypothesis holds for quasispecies models. For the discontinuous single sharp peak fitness landscape, we show that horizontal gene transfer has no effect on the fitness, while recombination decreases the fitness, for both the parallel and the Eigen models. We present numerical and analytical results as well as phase diagrams for the different cases.

Generating function, path integral representation, and equivalence for stochastic exclusive particle systems.

We present the path integral representation of the generating function for classical exclusive particle systems. By introducing hard-core bosonic creation and annihilation operators and appropriate commutation relations, we construct the Fock space structure. Using the state vector, the generating function is defined and the master equation of the system is transformed into the equation for the generating function. Finally, the solution of the linear equation for the generating function is derived in the form of the path integral. Applying the formalism, the equivalence of reaction-diffusion processes of single species and two species is described.

Quasispecies theory for evolution of modularity.

Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a quasispecies theory for the dynamics of modularity in populations of these systems. We show how the steady-state fitness in a randomly changing environment can be computed. We derive a fluctuation dissipation relation for the rate of change of modularity and use it to derive a relationship between rate of environmental changes and rate of growth of modularity. We also find a principle of least action for the evolved modularity at steady state. Finally, we compare our predictions to simulations of protein evolution and find them to be consistent.