Biological Relevance Research Articles

Targeting RAF1 gene fusions with MEK inhibition in metastatic melanoma

Abstract The biological and clinical relevance of gene fusions in melanoma is unknown. Reports and preclinical data have suggested that tumor cells with specific rearrangements such as RAF1 gene fusions could be therapeutically targeted. To investigate the relevance of targeted therapy in patients with melanoma harboring RAF1 gene fusions, we reviewed records of 1268 melanoma patients with targeted sequencing data at the Dana-Farber Cancer Institute. We identified 9 cases and report here on their clinicopathologic characteristics. We describe the favorable outcome of 2 patients who received MEK inhibitor therapy, including 1 patient with a durable response. We coalesced our data with published reports of patients with RAF1 gene fusions who were treated with targeted therapy. We find that single-agent MEK inhibition has anti-tumor activity in melanoma patients harboring an RAF1 gene fusion, and we propose that patients with RAF1 gene fusions should be considered for single-agent MEK inhibitor therapy.

Potential of ex vivo organotypic slice cultures in neuro-oncology.

Over recent decades, in vitro and in vivo models have significantly advanced brain cancer research; however, each presents distinct challenges for accurately mimicking in situ conditions. In response, organotypic slice cultures have emerged as a promising model recapitulating precisely specific in vivo phenotypes through an ex vivo approach. Ex vivo organotypic brain slice models can integrate biological relevance and patient-specific variability early in drug discovery, thereby aiming for more precise treatment stratification. However, the challenges of obtaining representative fresh brain tissue, ensuring reproducibility, and maintaining essential central nervous system (CNS)-specific conditions reflecting the in situ situation over time have limited the direct application of ex vivo organotypic slice cultures in robust clinical trials. In this review, we explore the benefits and possible limitations of ex vivo organotypic brain slice cultures in neuro-oncological research. Additionally, we share insights from clinical experts in neuro-oncology on how to overcome these current limitations and improve the practical application of organotypic brain slice cultures beyond academic research.

Multimodal AI/ML for discovering novel biomarkers and predicting disease using multi-omics profiles of patients with cardiovascular diseases

Cardiovascular diseases (CVDs) are complex, multifactorial conditions that require personalized assessment and treatment. Advancements in multi-omics technologies, namely RNA sequencing and whole-genome sequencing, have provided translational researchers with a comprehensive view of the human genome. The efficient synthesis and analysis of this data through integrated approach that characterizes genetic variants alongside expression patterns linked to emerging phenotypes, can reveal novel biomarkers and enable the segmentation of patient populations based on personalized risk factors. In this study, we present a cutting-edge methodology rooted in the integration of traditional bioinformatics, classical statistics, and multimodal machine learning techniques. Our approach has the potential to uncover the intricate mechanisms underlying CVD, enabling patient-specific risk and response profiling. We sourced transcriptomic expression data and single nucleotide polymorphisms (SNPs) from both CVD patients and healthy controls. By integrating these multi-omics datasets with clinical demographic information, we generated patient-specific profiles. Utilizing a robust feature selection approach, we identified a signature of 27 transcriptomic features and SNPs that are effective predictors of CVD. Differential expression analysis, combined with minimum redundancy maximum relevance feature selection, highlighted biomarkers that explain the disease phenotype. This approach prioritizes both biological relevance and efficiency in machine learning. We employed Combination Annotation Dependent Depletion scores and allele frequencies to identify variants with pathogenic characteristics in CVD patients. Classification models trained on this signature demonstrated high-accuracy predictions for CVD. The best performing of these models was an XGBoost classifier optimized via Bayesian hyperparameter tuning, which was able to correctly classify all patients in our test dataset. Using SHapley Additive exPlanations, we created risk assessments for patients, offering further contextualization of these predictions in a clinical setting. Across the cohort, RPL36AP37 and HBA1 were scored as the most important biomarkers for predicting CVDs. A comprehensive literature review revealed that a substantial portion of the diagnostic biomarkers identified have previously been associated with CVD. The framework we propose in this study is unbiased and generalizable to other diseases and disorders.

Neuro-Immune Communication at the Core of Craving-Associated Brain Structural Network Reconfiguration in Methamphetamine Users

Methamphetamine (MA) use disorder is a chronic neurotoxic brain disease characterized by a high risk of relapse driven by intense cravings. However, the neurobiological signatures of cravings remain unclear, limiting the effectiveness of various treatment methods. Diffusion MRI (dMRI) scans from 62 MA users and 57 healthy controls (HC) were used in this study. The MA users were longitudinally followed up during their period of long-term abstinence (duration of long-term abstinence: 347.52±99.25 days). We systematically quantified the control ability of each brain region for craving-associated state transitions using network control theory from a causal perspective. Craving-associated structural alterations (CSA) were investigated through multivariate group comparisons and biological relevance analysis. The neural mechanisms underlying CSA were elucidated using transcriptomic and neurochemical analyses. We observed that long-term abstinence-induced structural alterations significantly influenced the state transition energy involved in the cognitive control response to external information, which correlated with changes in craving scores (r ∼ 0.35, P <0.01). Our causal network analysis further supported the crucial role of the prefrontal cortex (PFC) in craving mechanisms. Notably, while the PFC is central to the craving, the CSAs were distributed widely across multiple brain regions (PFDR<0.05), with strong alterations in somatomotor regions (PFDR<0.05) and moderate alterations in high-level association networks (PFDR<0.05). Additionally, transcriptomic, chemical compounds, cell-type analyses, and molecular imaging collectively highlight the influence of neuro-immune communication on human craving modulation. Our results offer an integrative, multi-scale perspective on unraveling the neural underpinnings of craving and suggest that neuro-immune signaling may be a promising target for future human addiction therapeutics.

MicroRNAs in Congenital Diaphragmatic Hernia: Insights into Prenatal and Perinatal Biomarkers and Altered Molecular Pathways: microRNAs in Congenital Diaphragmatic Hernia for Pathway Analysis and Prognostic Biomarkers

Congenital diaphragmatic hernia (CDH) is characterized by a diaphragmatic defect, leading to herniation of abdominal organs into the chest, lung compression, and impaired lung development, often resulting in pulmonary hypertension and lung hypoplasia. Prenatal imaging techniques like ultrasound and MRI provide anatomical predictors of outcomes, but their limitations necessitate novel biomarkers for better prognostic accuracy. This study aims to identify unique circulating maternal, fetal, and neonatal microRNAs (miRNAs) that can distinguish CDH pregnancies from healthy controls and assess their potential as markers of disease severity. We conducted a prospective study involving third-trimester maternal blood, amniotic fluid, cord blood, and neonatal blood samples from pregnancies complicated by CDH and healthy controls. miRNA expression was analyzed using RNA-sequencing, and random forest analysis identified miRNAs distinguishing CDH survivors from non-survivors. Pathway enrichment analyses were performed to explore the biological relevance of differentially expressed miRNAs. Significant miRNA expression differences were observed between CDH and control samples across all sample types. In infant blood, 148 miRNAs were up-regulated, and 36 were down-regulated in CDH cases. Pathway analysis revealed that dysregulated miRNAs in CDH targeted pathways related to protein binding, transcription regulation, and signaling pathways implicated in pulmonary hypertension and lung hypoplasia. Random forest analysis identified miRNAs in maternal blood (miR-7850-5p_L-1R+2, miR-942-3p, and miR-197-3p) that distinguished CDH survivors from non-survivors, with an ROC area under the curve of 1.0. Circulating miRNAs in maternal blood offer promising biomarkers for predicting CDH outcomes. miRNAs from infant blood provide mechanistic insights and potential targets for therapeutic intervention in critical pathways of pulmonary hypertension and lung hypoplasia. Further studies with larger cohorts are needed to validate these findings and explore the clinical application of miRNA biomarkers in CDH management.

Orchestrating ROS regulation: coordinated post-translational modification switches in NADPH oxidases.

Reactive oxygen species (ROS) are among the most important signaling molecules, playing a significant role in plant growth, development, and responses to various environmental stresses. Respiratory burst oxidase homologs (RBOHs) are key enzymes in ROS production. Plants tightly regulate the activation and deactivation of RBOHs through various post-translational modifications (PTMs), including phosphorylation, ubiquitination, S-nitrosylation, and persulfidation. These PTMs fine-tune ROS production, ensuring normal plant growth and development while facilitating rapid responses to abiotic and biotic stresses. This review discusses the effects of different PTMs on RBOH function and their biological relevance. Additionally, we examine the evolutionary conservation of PTM sites and emphasize the complex interplay between multiple PTMs regulating RBOHs.

Microvascular blood flow disturbances predict poor outcome of revascularization in CLTI patients

Abstract Background We have recently established hypoxic microvascular remodelling as a critical pathomechanistic factor that limits oxygen diffusion to muscle in chronic limb threatening ischaemia (CLTI). Using animal models of experimental hind limb ischaemia we have also displayed the biological relevance of post-ischaemic microvascular remodelling in skeletal muscle. Our results indicate that differential microvascular changes associate to muscle damage and repair. The natural microvascular dynamics that inherently promote muscle recovery are defected in CLTI patients. Particularly, a progressive arterialization of capillaries in CLTI muscle differentiates the dynamics of the microvasculature from initially assisting muscle regeneration to aggravating ischaemic damage. Methods To establish the clinical relevance of the post-ischaemic microvascular changes in CLTI, we now have studied the effect of microvascular remodelling on the outcome of CLTI patients undergoing surgical or endovascular revascularization. Contrast enhanced ultrasound was used preoperatively to determine the microvascular status of CLTI patients (n=36) scheduled for immediate revascularization. Outcome events such as: hospitalization; reoperation; leg amputation; or death, were postoperatively followed from medical records up to 6 months after revascularization. Patients were grouped according to muscle capillary transit time (Tct) being either similar (n=18) or shorter (n=18) to that in the contralateral legs of the patients, and treatment outcomes were compared between groups. Results The results display consistent increases in postoperative event rates in all measured outcomes in the ShortTct group as compared to controls (at 1 month 8 vs. 2 events (rate ratio 4.00 (95%CI: 0.85-18.84, p=0.080)); at 3 months 13 vs. 4 events (rate ratio 3.25 (95%CI: 1.06-9.97, p=0.039)); at 6 months 17 vs. 9 events (rate ratio 1.89 (95%CI: 0.84-4.24, p=0.123))). For example, 5 vs. 0; 7 vs. 1; and 7 vs. 4 reoperations were detected in the ShortTct group as compared to controls at 1, 3 and 6 months, respectively. By 6 months after initial revascularization also 2 deaths were recorded in the ShortTct group as compared to no deaths in the controls. Conclusions Despite still small samples size in this study, these results suggest that microvascular blood flow disturbances, such as short preoperative muscle capillary transit time, can predict poor outcome of CLTI patients after revascularization. Importantly, the results also identify patients with microvascular blood flow disturbances a subgroup of CLTI patients that should likely receive more specialized care to improve outcomes. The results also call for immediate actions from the scientific community to improve clinical detection of microvascular alterations and to develop strategies to normalize microvascular function in CLTI patients.

Targeting an altered sphingolipid profile with consecutive lipotoxicity as therapeutic approach to calcific aortic valve disease

Abstract Background Aortic stenosis due to calcific aortic valve disease (CAVD) is the most common valvular heart disease. In symptomatic patients, without repair the prognosis is poor. Treatment to date is based on surgery or catheter-based interventions. Pharmacological therapy options to prevent the progression of valve calcification are not available. In vascular smooth muscle cells, cellular accumulation of sphingolipids is associated with a proinflammatory response in the sense of lipotoxicity. Chronic inflammatory processes are indeed also essential for aortic valve calcification. Purpose With the subsequent goal of developing innovative treatment approaches for CAVD, we therefore aim to elucidate the unclear role of sphingolipids in the development of CAVD. Methods Human aortic valve and plasma samples of CAVD patients and controls (n=26) were analysed by liquid chromatography–mass spectrometry for lipidomics and proteomics. Human aortic valve interstitial cells (hVICs) were stimulated with ceramides. Calcification was detected by alizarin red staining. mRNA expression of bone-related proteins was determined by qPCR. NF-kB pathway was assessed by proteome profiler. Myriocin and GW4869 were applied to inhibit ceramide biosynthesis. PDTC and MCC950 were used to inhibit NF-kB Pathway and NLRP3 activation. ApoE-/- mice received a gain-of-function PCSK9 adeno-associated virus vector and fed high cholesterol diet for 14 weeks. Myriocin was applied orally over the treatment period to inhibit ceramide de novo synthesis in vivo. Murine echocardiography was used to measure transvalvular velocity and left ventricular function. Calcification degree of murine aortic valve was determined by histological staining. Results A significantly altered sphingolipid profile was observed in aortic valve tissue of CAVD patients (Fig. 1). Ceramide species e.g. Cer (17:1;2O/16:0) were increased. Verifying the biological relevance of these findings in vitro, C2-Cer (d18:1/2:0) enhanced hVIC calcification (Fig. 2). Accordingly, ALP activity and mRNA expression of osteogenic genes RUNX2, ALPL and MSX2 were increased. Furthermore, C2-Cer (d18:1/2:0) enhanced NF-kB p65 phosphorylation and NLRP3 activation, while treatment with both PDTC and MCC950 protected against C2-Cer (d18:1/2:0) induced calcification. Supporting the role of sphingolipid biosynthesis in hVIC calcification, Myriocin and GW4869 both reduced ox-LDL-induced VIC calcification which was reversed by C2-Cer(d18:1/2:0). Finally, Myriocin reduced the degree of calcification and transvalvular jet velocity of aortic valve in the PCSK9-AAV ApoE-/- mice model. Conclusion CAVD is accompanied by an accumulation of ceramides causing lipotoxicity in human aortic valve tissue. Pharmacological modulation of sphingolipid metabolism is an effective approach to prevent the development and progression of aortic valve calcification in vivo and should be considered as a future therapeutic strategy in CAVD patients.Volcano Plot of CAVD tissue lipidomicsC2 Ceramide enhances hVIC calcification

Time-Dependent Comparison of the Structural Variations of Natural Products and Synthetic Compounds

The identification of natural products (NPs) has played a pivotal role in drug discovery and shaped the evolution of synthetic compounds (SCs). However, the extent to which NPs have historically influenced the structural characteristics of SCs remains unclear. In this study, we conducted a comprehensive, time-dependent chemoinformatic analysis to investigate the impact of NPs on the structural evolution of SCs. The physicochemical properties, molecular fragments, biological relevance, and chemical space of the molecules from the Dictionary of Natural Products were compared in a time series fashion with a synthetic compound collection sourced from 12 databases. Our findings reveal that NPs have become larger, more complex, and more hydrophobic over time, exhibiting increased structural diversity and uniqueness. Conversely, SCs exhibit a continuous shift in physicochemical properties, yet these changes are constrained within a defined range governed by drug-like constraints. SCs possess a broader range of synthetic pathways and structural diversity, albeit with a decline in biological relevance. The chemical space of NPs has become less concentrated compared to that of SCs. In conclusion, our study suggests that the structural evolution of SCs is influenced by NPs to some extent; however, SCs have not fully evolved in the direction of NPs.

Optical control of sphingolipid biosynthesis using photoswitchable sphingosines.

Sphingolipid metabolism comprises a complex interconnected web of enzymes, metabolites and modes of regulation that influence a wide range of cellular and physiological processes. Deciphering the biological relevance of this network is challenging as numerous intermediates of sphingolipid metabolism are short-lived molecules with often opposing biological activities. Here, we introduce clickable, azobenzene-containing sphingosines, termed caSph s, as light-sensitive substrates for sphingolipid biosynthesis. Photo-isomerization of the azobenzene moiety enables reversible switching between a straight trans - and curved cis -form of the lipid's hydrocarbon tail. Combining in vitro enzyme assays with metabolic labeling studies, we demonstrate that trans -to- cis isomerization of caSph s profoundly stimulates their metabolic conversion by ceramide synthases and downstream sphingomyelin synthases. These light-induced changes in sphingolipid production rates are acute, reversible, and can be implemented with great efficiency in living cells. Our findings establish caSph s as versatile tools with unprecedented opportunities to manipulate sphingolipid biosynthesis and function with the spatiotemporal precision of light.

Deciphering the role of lipid metabolism-related genes in Alzheimer's disease: a machine learning approach integrating Traditional Chinese Medicine.

Alzheimer's disease (AD) represents a progressive neurodegenerative disorder characterized by the accumulation of misfolded amyloid beta protein, leading to the formation of amyloid plaques and the aggregation of tau protein into neurofibrillary tangles within the cerebral cortex. The role of carbohydrates, particularly apolipoprotein E (ApoE), is pivotal in AD pathogenesis due to its involvement in lipid and cholesterol metabolism, and its status as a genetic predisposition factor for the disease. Despite its significance, the mechanistic contributions of Lipid Metabolism-related Genes (LMGs) to AD remain inadequately elucidated. This research endeavor seeks to bridge this gap by pinpointing biomarkers indicative of early-stage AD, with an emphasis on those linked to immune cell infiltration. To this end, advanced machine-learning algorithms and data derived from the Gene Expression Omnibus (GEO) database have been employed to facilitate the identification of these biomarkers. Differentially expressed genes (DEGs) were identified by comparing gene expression profiles between healthy individuals and Alzheimer's disease (AD) patients, using data from two Gene Expression Omnibus (GEO) datasets: GSE5281 and GSE138260. Functional enrichment analysis was conducted to elucidate the biological relevance of the DEGs. To ensure the reliability of the results, samples were randomly divided into training and validation sets. The analysis focused on lipid metabolism-related DEGs (LMDEGs) to explore potential biomarkers for AD. Machine learning algorithms, including Support Vector Machine-Recursive Feature Elimination (SVM-RFE) and the Least Absolute Shrinkage and Selection Operator (LASSO) regression model, were applied to identify a key gene biomarker. Additionally, immune cell infiltration and its relationship with the gene biomarker were assessed using the CIBERSORT algorithm. The Integrated Traditional Chinese Medicine (ITCM) database was also referenced to identify Chinese medicines related to lipid metabolism and their possible connection to AD. This comprehensive strategy aims to integrate modern computational methods with traditional medicine to deepen our understanding of AD and its underlying mechanisms. The study identified 137 genes from a pool of 751 lipid metabolism-related genes (LMGs) significantly associated with autophagy and immune response mechanisms. Through the application of LASSO and SVM-RFE machine-learning techniques, four genes-choline acetyl transferase (CHAT), member RAS oncogene family (RAB4A), acyl-CoA binding domain-containing protein 6 (ACBD6), and alpha-galactosidase A (GLA)-emerged as potential biomarkers for Alzheimer's disease (AD). These genes demonstrated strong therapeutic potential due to their involvement in critical biological pathways. Notably, nine Chinese medicine compounds were identified to target these marker genes, offering a novel treatment approach for AD. Further, ceRNA network analysis revealed complex regulatory interactions involving these genes, underscoring their importance in AD pathology. CIBERSORT analysis highlighted a potential link between changes in the immune microenvironment and CHAT expression levels in AD patients, providing new insights into the immunological dimensions of the disease. The discovery of these gene markers offers substantial promise for the diagnosis and understanding of Alzheimer's disease (AD). However, further investigation is necessary to validate their clinical utility. This study illuminates the role of Lipid Metabolism-related Genes (LMGs) in AD pathogenesis, offering potential targets for therapeutic intervention. It enhances our grasp of AD's complex mechanisms and paves the way for future research aimed at refining diagnostic and treatment strategies.

Rapid method for screening of both calcium and magnesium chelation with comparison of 21 known metal chelators.

Chelation is the rational treatment modality in metal overload conditions, but chelators are often non-selective and can, hence, cause an imbalance in the homeostasis of physiological metals including calcium and magnesium. The aim of this study was to develop an affordable, rapid but sensitive and precise method for determining the degree of chelation of calcium and magnesium ions and to employ this method for comparison on a panel of known metal chelators. Spectrophotometric method using o-cresolphthalein complexone (o-CC) was developed and its biological relevance was confirmed in human platelets by impedance aggregometry. The lowest detectable concentration of calcium and magnesium ions by o-CC was 2.5μM and 2μM, respectively. The indicator was stable for at least 110days. Four and seven out of twenty-one chelators strongly chelated calcium and magnesium ions, respectively. Importantly, the chelation effect of clinically used chelators was not negligible. Structure-activity relationships for eight quinolin-8-ols showed improvements in chelation particularly in the cases of dihalogen substitution, and a negative linear relationship between pKa and magnesium chelation was observed. Calcium chelation led to inhibition of platelet aggregation in concentrations corresponding to the complex formation. A novel method for screening of efficacy and safety of calcium and magnesium ion chelation was developed and validated.

Maternal Malnutrition in Mice Impairs Nephrogenesis by Disrupting DNA Methylation of Regulatory Regions.

Maternal caloric restriction during pregnancy significantly impacts kidney development, influencing susceptibility to chronic kidney disease in adulthood. This study explores DNA methylation changes in nephron progenitor cells resulting from caloric restriction and their implications for kidney health. Global DNA hypomethylation is observed in nephron progenitors from caloric-restricted embryos, with specific genomic regions displaying distinct methylation patterns, including hypomethylation and hypermethylation. Differentially methylated regions exhibit enhanced chromatin accessibility, indicating biological relevance. Hypomethylated regions are enriched for genes associated with developmental processes, reflecting changes in gene expression and highlighting their functional relevance in kidney development. The study also reveals that supplementing methionine, an essential amino acid, restores disrupted DNA methylation patterns, particularly in enhancer regions, emphasizing methionine's critical role in regulating nephron progenitor cell epigenetics and ensuring proper kidney development. The intricate relationship between maternal nutrition, dynamic DNA methylation, and kidney development is highlighted, emphasizing the enduring impact of early-life nutritional challenges on kidney function. This research elucidates epigenetic mechanisms as mediators for the lasting effects of maternal caloric restriction on kidney health. The study contributes valuable insights into the origins of chronic kidney diseases during early developmental stages, offering potential interventions to mitigate adverse outcomes.

Machine Learning Analysis of RNA-Seq Data Identifies Key Gene Signatures and Pathways in Mpox Virus-Induced Gastrointestinal Complications Using Colon Organoid Models.

Mpox, caused by the Mpox virus (MPXV), emerged globally in 2022 with the Clade IIb strain, presenting a critical public health challenge. While MPXV is primarily characterized by fever and rash, gastrointestinal (GI) complications, such as diarrhea and proctitis, have also been observed. This study is a reanalysis of GSE219036 without own data and focuses on the impact of MPXV infection on the colon, using human-induced pluripotent stem cell-derived colon organoids as a model. We applied a tailored statistical framework for RNA-seq data, Generalized Linear Models with Quasi-Likelihood F-tests and Relaxed Magnitude-Altitude Scoring (GLMQL-RMAS), to identify differentially expressed genes (DEGs) across MPXV clades: MPXV I (Zr-599 Congo Basin), MPXV IIa (Liberia), and MPXV IIb (2022 MPXV). Through a novel methodology called Cross-RMAS, we ranked genes by integrating statistical significance and biological relevance across all clades. Machine learning analysis using the genes identified by Cross-RMAS, demonstrated 100% accuracy in differentiating between the different MPXV strains and mock samples. Furthermore, our findings reveal that MPXV Clade I induces the most extensive alterations in gene expression, with significant upregulation of stress response genes, such as HSPA6 and FOS, and downregulation of genes involved in cytoskeletal organization and vesicular trafficking, such as PSAP and CFL1. In contrast, Clade IIb shows the least impact on gene expression. Through Gene Ontology (GO) analysis, we identified pathways involved in protein folding, immune response, and epithelial integrity that are disrupted in infected cells, suggesting mechanisms by which MPXV may contribute to GI symptoms.

Placental microphysiological systems: new advances on promising platforms that mimic the microenvironment of the human placenta.

One of the most complex human physiological processes to study is pregnancy. Standard animal models, as well as two-dimensional models, lack the complexity and biological relevance required to accurately study such a physiological process. Recent studies have focused on the development of three-dimensional models based on microfluidic systems, designated as placental microphysiological systems (PMPSs). PMPS devices provide a model of the placental barrier through culturing relevant cell types in specific arrangements and media to mimic the in vivo environment of the maternal-fetal circulation. Here, recent developments of PMPS models for embryo uterine implantation, preeclampsia evaluation, and toxicological screening are presented. Studies that use bioprinting techniques are also discussed. Lastly, recent developments in endometrium microphysiological systems are reviewed. All these presented models showed their superiority compared to standard models in recapitulating the biological environment seen in vivo. However, several limitations regarding the types of cells and materials used for these systems were also widely reported. Despite the need for further improvements, PMPS models contribute to a better understanding of the biological mechanisms surrounding pregnancy and the respective pathologies.

P01.08.A HYOXIA-INDUCED EXPRESSION OF ARHGAP FAMILY MEMBERS PROMOTES GLIOBLASTOMA DISSEMINATION

Abstract BACKGROUND The Rho GTPase activating proteins (ARHGAPs) perform vital roles in the regulation of the Rho GTPases with direct effect on cellular plasticity and cell migration/invasion. We recently reported on the role of five ARHGAPs, identified by a microarray screen, in morphological plasticity in established and patient-derived Glioblastoma (GBM) cell lines and associated clinical relevance in terms of tumour recurrence after treatment. We established that the ARHGAPs either promoted or targeted cell migration/invasion by allowing cells to undergo morphological changes in preparation for dissemination. We also showed that co-expression of two ARHGAPs, 12 and 29, is associated with reduced time to recurrence after initial treatment in patients. ARHGAP activity has been also reported in metastatic cancers including breast and colorectal cancer highlighting the biological relevance of these, as yet understudied, proteins. MATERIAL AND METHODS Here, we explored the GBM microenvironment and the effect of hypoxia on ARHGAP expression and localisation in glioma cell lines. RESULTS Using immunocytological and in vitro migration and invasion assays we were able to ascertain that ARHGAP4, 12, 22, 25 and 29 acquired subcellular distributions different to those recorded under normoxia and expression also decreased or increased under hypoxia. We also found that the effect of the migrastatic inhibitor 6-bromo-indirubin-3′-oxime (BIO) targeting GSK-3 signalling was potentiated when cells were challenged with the drug under hypoxic conditions. CONCLUSION Our results confirm our initial findings of biological relevance of the ARHGAPs in cellular activities and highlight important roles for the ARHGAPs for promoting migratory/invasive activity and behaviour in GBM cells. We also conclude that migrastatic inhibitors will exert enhanced activity on GBM cells under hypoxic conditions making them excellent candidates for complement treatment with cytotoxic drugs or radiotherapy for an improved management of GBM.

Visualizing Plant Responses: Novel Insights Possible Through Affordable Imaging Techniques in the Greenhouse.

Efficient and affordable plant phenotyping methods are an essential response to global climatic pressures. This study demonstrates the continued potential of consumer-grade photography to capture plant phenotypic traits in turfgrass and derive new calculations. Yet the effects of image corrections on individual calculations are often unreported. Turfgrass lysimeters were photographed over 8 weeks using a custom lightbox and consumer-grade camera. Subsequent imagery was analyzed for area of cover, color metrics, and sensitivity to image corrections. Findings were compared to active spectral reflectance data and previously reported measurements of visual quality, productivity, and water use. Results confirm that Red-Green-Blue imagery effectively measures plant treatment effects. Notable correlations were observed for corrected imagery, including between yellow fractional area with human visual quality ratings (r = -0.89), dark green color index with clipping productivity (r = 0.61), and an index combination term with water use (r = -0.60). The calculation of green fractional area correlated with Normalized Difference Vegetation Index (r = 0.91), and its RED reflectance spectra (r = -0.87). A new chromatic ratio correlated with Normalized Difference Red-Edge index (r = 0.90) and its Red-Edge reflectance spectra (r = -0.74), while a new calculation correlated strongest to Near-Infrared (r = 0.90). Additionally, the combined index term significantly differentiated between the treatment effects of date, mowing height, deficit irrigation, and their interactions (p < 0.001). Sensitivity and statistical analyses of typical image file formats and corrections that included JPEG, TIFF, geometric lens distortion correction, and color correction were conducted. Findings highlight the need for more standardization in image corrections and to determine the biological relevance of the new image data calculations.

Uncovering the interleukin-12 pharmacokinetic desensitization mechanism and its consequences with mathematical modeling.

The cytokine interleukin-12 (IL-12) is a potential immunotherapy because of its ability to induce a Th1 immune response. However, success in the clinic has been limited due to a phenomenon called IL-12 desensitization - the trend where repeated exposure to IL-12 leads to reduced IL-12 concentrations (pharmacokinetics) and biological effects (pharmacodynamics). Here, we investigated IL-12 pharmacokinetic desensitization via a modeling approach to (i) validate proposed mechanisms in literature and (ii) develop a mathematical model capable of predicting IL-12 pharmacokinetic desensitization. Two potential causes of IL-12 pharmacokinetic desensitization were identified: increased clearance or reduced bioavailability of IL-12 following repeated doses. Increased IL-12 clearance was previously proposed to occur due to the upregulation of IL-12 receptor on T cells that causes increased receptor-mediated clearance in the serum. However, our model with this mechanism, the accelerated-clearance model, failed to capture trends in clinical trial data. Alternatively, our novel reduced-bioavailability model assumed that upregulation of IL-12 receptor on T cells in the lymphatic system leads to IL-12 sequestration, inhibiting the transport to the blood. This model accurately fits IL-12 pharmacokinetic data from three clinical trials, supporting its biological relevance. Using this model, we analyzed the model parameter space to illustrate that IL-12 desensitization occurs over a robust range of parameter values and to identify the conditions required for desensitization. We next simulated local, continuous IL-12 delivery and identified several methods to mitigate systemic IL-12 exposure. Ultimately, our results provide quantitative validation of our proposed mechanism and allow for accurate prediction of IL-12 pharmacokinetics over repeated doses.

Key genes and immune pathways in T-cell mediated rejection post-liver transplantation identified via integrated RNA-seq and machine learning

Liver transplantation is the definitive treatment for end-stage liver disease, yet T-cell mediated rejection (TCMR) remains a major challenge. This study aims to identify key genes associated with TCMR and their potential biological processes and mechanisms. The GSE145780 dataset was subjected to differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms to pinpoint key genes associated with TCMR. Gene Set Enrichment Analysis (GSEA), immune infiltration analysis, and regulatory networks were constructed to ascertain the biological relevance of these genes. Expression validation was performed using single-cell RNA-seq (scRNA-seq) data and liver biopsy tissues from patients. We identified 5 key genes (ITGB2, FCER1G, IL-18, GBP1, and CD53) that are associated with immunological functions, such as chemotactic activity, antigen processing, and T cell differentiation. GSEA highlighted enrichment in chemokine signaling and antigen presentation pathways. A lncRNA-miRNA-mRNA network was delineated, and drug target prediction yielded 26 potential drugs. Evaluation of expression levels in non-rejection (NR) and TCMR groups exhibited significant disparities in T cells and myeloid cells. Tissue analyses from patients corroborated the upregulation of GBP1, IL-18, CD53, and FCER1G in TCMR cases. Through comprehensive analysis, this research has identified 4 genes intimately connected with TCMR following liver transplantation, shedding light on the underlying immune activation pathways and suggesting putative targets for therapeutic intervention.

Cation-Dependent Mixed Ionic-Electronic Transport in a Perylenediimide Small-Molecule Semiconductor.

A rapidly growing interest in organic bioelectronic applications has spurred the development of a wide variety of organic mixed ionic-electronic conductors. While these new mixed conductors have enabled the community to interface organic electronics with biological systems and efficiently transduce biological signals (ions) into electronic signals, the current materials selection does not offer sufficient selectivity towards specific ions of biological relevance without the use of auxiliary components such as ion-selective membranes. Here, we present the molecular design of an n-type (electron-transporting) perylene diimide semiconductor material decorated with pendant oligoether groups to facilitate interactions with cations such as Na+ and K+. Using the cyclic 15-crown-5 oligoether motif, we find that the resulting mixed conductor PDI-crown displays a strong dependence on the size of the electrolyte cation when tested in an organic electrochemical transistor configuration. In stark contrast to the low current response on the order of 1 μA observed with aqueous sodium chloride, a nearly 200-fold increase in current is observed with aqueous potassium chloride. We ascribe the high selectivity to extended molecular aggregation and therefore efficient charge transport in the presence of K+ due to a favourable sandwich-like structure between two adjacent 15-crown-5 motifs and the potassium ion.