Power-law scaling in intratumoral microbiota of colorectal cancer.

It has recently been proposed that the study of microbial dynamics in humans may gain insights from island biogeographical theory. Here, we test whether the diversity of the intratumoral microbiota of colorectal cancer tumors (CRC) follows a power law with tumor size akin to the island species-area relationship. We confirm a direct correlation between the quantity of Amplicon Sequence Variants (ASVs) within CRC tumors and tumor sizes, following a (log)power model, explaining 47% of the variation. Understanding the processes involved, potentially through the analogy of tumors and islands, may ultimately contribute to future clinical and therapeutic strategies.

Oncostatin M Induces a Pro-inflammatory Phenotype in Intestinal Subepithelial Myofibroblasts.

BACKGROUND: Oncostatin-M (OSM) is associated with antitumor necrosis factor (anti-TNF)-α resistance in inflammatory bowel disease (IBD) and fibrosis in inflammatory diseases. We studied the expression of OSM and its receptors (OSMR, gp130) on intestinal subepithelial myofibroblasts (SEMFs) and the effect of OSM stimulation on SEMFs. METHODS: The mRNA and protein expression of OSM, OSMR, gp130, and several fibrotic and chemotactic factors were studied in mucosal biopsies and isolated human intestinal SEMFs of patients with IBD and healthy controls (HCs) and in a model of human intestinal organoids (HIOs). Subepithelial myofibroblasts and HIOs were stimulated with OSM and interleukin (IL)-1α/TNF-α. RNAseq data of mucosal biopsies were also analyzed. RESULTS: Oncostatin-M receptors and gp130 were overexpressed in mucosal biopsies of patients with IBD (P < .05), especially in inflamed segments (P < .05). The expression of OSM, OSMR, and gp130 in SEMFs from HCs was increased after stimulation with IL-1α/TNF-α (P < .001; P < .01; P < .01). The expression of CCL2, CXCL9, CXCL10, and CXCL11 was increased in SEMFs from patients with IBD and HCs after stimulation with OSM in a dose-dependent manner (P < .001; P < .05; P < .001; P < .001) and was further increased after prestimulation with IL-1α/TNF-α (P < .01 vs OSM-alone). Similar results were yielded after stimulation of HIOs (P < .01). Oncostatin-M did not induce the expression of collagen I, III, and fibronectin. Oncostatin-M receptor expression was positively correlated with CCL2, CXCL9, CXCL10, and CXCL11 expression in mucosal biopsies (P < .001; P < .001; P = .045; P = .033). CONCLUSIONS: Human SEMFs overexpress OSMR in an inflammatory microenvironment. Oncostatin-M may promote inflammation in IBD via its stimulatory effects on SEMFs, which primarily involve chemoattraction of immune cells to the intestinal mucosa.

Oncostatin-M/OSMR show elevated expression on intestinal fibroblasts that is regulated by IBD-relevant pro-inflammatory stimuli. In turn, OSM induces a pro-inflammatory phenotype on primary intestinal fibroblasts, with prominent overexpression of chemotactic factors, without demonstrating a substantial profibrotic effect.

Dysbiosis Signature of Fecal Microbiota in Patients with Pancreatic Adenocarcinoma and Pancreatic Intraductal Papillary Mucinous Neoplasms.

Pancreatic cancer (PC) ranks as the seventh leading cause of cancer-related deaths, with approximately 500,000 new cases reported in 2020. Existing strategies for early PC detection primarily target individuals at high risk of developing the disease. Nevertheless, there is a pressing need to identify innovative clinical approaches and personalized treatments for effective PC management. This study aimed to explore the dysbiosis signature of the fecal microbiota in PC and potential distinctions between its Intraductal papillary mucinous neoplasm (IPMN) and pancreatic ductal adenocarcinoma (PDAC) phenotypes, which could carry diagnostic significance. The study enrolled 33 participants, including 22 diagnosed with PDAC, 11 with IPMN, and 24 healthy controls. Fecal samples were collected and subjected to microbial diversity analysis across various taxonomic levels. The findings revealed elevated abundances of Firmicutes and Proteobacteria in PC patients, whereas healthy controls exhibited higher proportions of Bacteroidota. Both LEfSe and Random Forest analyses indicated the microbiome's potential to effectively distinguish between PC and healthy control samples but fell short of differentiating between IPMN and PDAC samples. These results contribute to the current understanding of this challenging cancer type and highlight the applications of microbiome research. In essence, the study provides clear evidence of the gut microbiome's capability to serve as a biomarker for PC detection, emphasizing the steps required for further differentiation among its diverse phenotypes.

Insights into Therapeutic Response Prediction for Ustekinumab in Ulcerative Colitis Using an Ensemble Bioinformatics Approach.

INTRODUCTION: Optimizing treatment with biological agents is an ideal goal for patients with ulcerative colitis (UC). Recent data suggest that mucosal inflammation patterns and serum cytokine profiles differ between patients who respond and those who do not. Ustekinumab, a monoclonal antibody targeting the p40 subunit of interleukin (IL)-12 and IL-23, has shown promise, but predicting treatment response remains a challenge. We aimed to identify prognostic markers of response to ustekinumab in patients with active UC, utilizing information from their mucosal transcriptome. METHODS: We performed a prospective observational study of 36 UC patients initiating treatment with ustekinumab. Colonic mucosal biopsies were obtained before treatment initiation for a gene expression analysis using a microarray panel of 84 inflammatory genes. A differential gene expression analysis (DGEA), correlation analysis, and network centrality analysis on co-expression networks were performed to identify potential biomarkers. Additionally, machine learning (ML) models were employed to predict treatment response based on gene expression data. RESULTS: Seven genes, including BCL6, CXCL5, and FASLG, were significantly upregulated, while IL23A and IL23R were downregulated in non-responders compared to responders. The co-expression analysis revealed distinct patterns between responders and non-responders, with key genes like BCL6 and CRP highlighted in responders and CCL11 and CCL22 in non-responders. The ML algorithms demonstrated a high predictive power, emphasizing the significance of the IL23R, IL23A, and BCL6 genes. CONCLUSIONS: Our study identifies potential biomarkers associated with ustekinumab response in UC patients, shedding light on its underlying mechanisms and variability in treatment outcomes. Integrating transcriptomic approaches, including gene expression analyses and ML, offers valuable insights for personalized treatment strategies and highlights avenues for further research to enhance therapeutic outcomes for patients with UC.

West Nile Virus Subgenomic RNAs Modulate Gene Expression in a Neuronal Cell Line.

Subgenomic flaviviral RNAs (sfRNAs) are small non-coding products of the incomplete degradation of viral genomic RNA. They accumulate during flaviviral infection and have been associated with many functional roles inside the host cell. Studies so far have demonstrated that sfRNA plays a crucial role in determining West Nile virus (WNV) pathogenicity. However, its modulatory role on neuronal homeostasis has not been studied in depth. In this study, we investigated the mechanism of sfRNA biosynthesis and its importance for WNV replication in neuronal cells. We found that sfRNA1 is functionally redundant for both replication and translation of WNV. However, the concurrent absence of sfRNA1 and sfRNA2 species is detrimental for the survival of the virus. Differential expression analysis on RNA-seq data from WT and ΔsfRNA replicon cell lines revealed transcriptional changes induced by sfRNA and identified a number of putative targets. Overall, it was shown that sfRNA contributes to the viral evasion by suppressing the interferon-mediated antiviral response. An additional differential expression analysis among replicon and control Neuro2A cells also clarified the transcriptional changes that support WNV replication in neuronal cells. Increased levels of translation and oxidative phosphorylation, post-translational modification processes, and activated DNA repair pathways were observed in replicon cell lines, while developmental processes such as axonal growth were deficient.

Exploring Microbial Metabolite Receptors in Inflammatory Bowel Disease: An In Silico Analysis of Their Potential Role in Inflammation and Fibrosis.

Metabolites produced by dysbiotic intestinal microbiota can influence disease pathophysiology by participating in ligand-receptor interactions. Our aim was to investigate the differential expression of metabolite receptor (MR) genes between inflammatory bowel disease (IBD), healthy individuals (HIs), and disease controls in order to identify possible interactions with inflammatory and fibrotic pathways in the intestine. RNA-sequencing datasets containing 643 Crohn's disease (CD) patients, 467 ulcerative colitis (UC) patients and 295 HIs, and 4 Campylobacter jejuni-infected individuals were retrieved from the Sequence Read Archive, and differential expression was performed using the RaNA-seq online platform. The identified differentially expressed MR genes were used for correlation analysis with up- and downregulated genes in IBD, as well as functional enrichment analysis using a R based pipeline. Overall, 15 MR genes exhibited dysregulated expression in IBD. In inflamed CD, the hydroxycarboxylic acid receptors 2 and 3 (HCAR2, HCAR3) were upregulated and were associated with the recruitment of innate immune cells, while, in the non-inflamed CD ileum, the cannabinoid receptor 1 (CNR1) and the sphingosine-1-phospate receptor 4 (S1PR4) were downregulated and were involved in the regulation of B-cell activation. In inflamed UC, the upregulated receptors HCAR2 and HCAR3 were more closely associated with the process of TH-17 cell differentiation, while the pregnane X receptor (NR1I2) and the transient receptor potential vanilloid 1 (TRPV1) were downregulated and were involved in epithelial barrier maintenance. Our results elucidate the landscape of metabolite receptor expression in IBD, highlighting associations with disease-related functions that could guide the development of new targeted therapies.

Next-Generation Sequencing of microRNAs in Small Abdominal Aortic Aneurysms: MiR-24 as a Biomarker.

BACKGROUND: Small abdominal aortic aneurysms (AAAs) are asymptomatic but can potentially lead to rupture if left undetected. To date, there is a lack of simple nonradiologic routine tests available for diagnosing AAAs. MicroRNAs (miRNAs) have been proven to be good-quality biomarkers in several diseases, including AAA. METHODS: An attempt to identify a panel of circulating miRNAs with differential expression in AAAs via next-generation sequencing (NGS) was performed in serum samples: small AAAs (n = 3), large AAAs (n = 3), and controls (n = 3). For miR-24, validation with real-time polymerase chain reaction (PCR) was undertaken in a larger group (n = 80). RESULTS: In the NGS study, 23 miRNAs were identified as differentially expressed (with statistical significance) in small AAAs in comparison with controls. Among them, miR-24 showed the largest upregulation with 23-fold change (log2FC 4.5, P = 0.024). For large AAAs compared with controls, and small AAAs compared with large AAAs, a panel of 33 and 131 miRNAs showed statistically significant differential expression, respectively. Based on the results of the NGS stage, a literature search was performed, and information regarding AAA pathogenesis, coronary artery disease, and peripheral arterial disease was documented where applicable: miR-24, miR-103, miR-193a, miR-486, miR-582, and miR-3663. Of these 6 miRNAs, miR-24 was chosen for further validation with real-time PCR. Additionally, in the NGS study analysis, 17 miRNAs were common between the small-large AAAs, small AAAs-controls, and large AAAs-controls comparisons: miR-7846, miR-3195, miR-486-2, miR-3194, miR-5589, miR-1538, miR-3178, miR-4771-1, miR-5695, miR-6504, miR-1908, miR-6823, miR-3159, miR-23a, miR-7853, miR-496, and miR-193a. Interestingly, in the validation stage with real-time PCR, miR-24 was found downregulated in small and large AAAs compared with controls (fold-changes: 0.27, P = 0.015 and 0.15, P = 0.005, respectively). No correlation was found between average Ct values, aneurysm diameter, and patients' age. CONCLUSIONS: Our findings further highlight the importance of miR-24 as a potential biomarker as well as a therapeutic target for abdominal aneurysmal disease. Future research and validation of a panel of miRNAs for AAA would aid in diagnosis and discrimination between diseases with overlapping pathogeneses.

Inflammation and Immunity Gene Expression Patterns and Machine Learning Approaches in Association with Response to Immune-Checkpoint Inhibitors-Based Treatments in Clear-Cell Renal Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Despite the rapid evolution of targeted therapies, immunotherapy with checkpoint inhibition (ICI) as well as combination therapies, the cure of metastatic ccRCC (mccRCC) is infrequent, while the optimal use of the various novel agents has not been fully clarified. With the different treatment options, there is an essential need to identify biomarkers to predict therapeutic efficacy and thus optimize therapeutic approaches. This study seeks to explore the diversity in mRNA expression profiles of inflammation and immunity-related circulating genes for the development of biomarkers that could predict the effectiveness of immunotherapy-based treatments using ICIs for individuals with mccRCC. Gene mRNA expression was tested by the RT2 profiler PCR Array on a human cancer inflammation and immunity crosstalk kit and analyzed for differential gene expression along with a machine learning approach for sample classification. A number of mRNAs were found to be differentially expressed in mccRCC with a clinical benefit from treatment compared to those who progressed. Our results indicate that gene expression can classify these samples with high accuracy and specificity.

The Effect of Probiotic Supplements on Metabolic Parameters of People with Type 2 Diabetes in Greece-A Randomized, Double-Blind, Placebo-Controlled Study.

The role of probiotic supplementation in type 2 diabetes (T2D) treatment is controversial. The present study aimed to assess the effects of a multi-strain probiotic supplement (LactoLevureR (containing Lactobacillus acidophilus, Lactobacillus plantarum, Bifidobacterium lactis, and Saccharomyces boulardii)) over 6 months, primarily on glycemic control as well as on lipid levels and alterations in the gut microbiome, among individuals with T2D residing in Greece. A total of 91 adults with T2D (mean age [±SD] 65.12 ± 10.92 years, 62.6% males) were randomized to receive the probiotic supplement or a matching placebo capsule, once daily, for 6 months. Blood chemistries and anthropometric parameters were conducted every 3 months, and stool samples were collected at baseline and at 6 months. Significant reductions in HbA1c, fasting blood glucose, and total cholesterol were observed in participants treated with the probiotic supplement (n = 46) compared to the controls (n = 45), even after adjustment for a greater decrease in adiposity (waist circumference). Although there were no statistically significant differences in the diversity of the gut microbiome (α and ß diversity), the administration of probiotics did influence several genera, metabolites, and key enzymes associated with diabetes. Overall, the administration of the multi-strain probiotic LactoLevureR over a 6-month period in individuals with T2D was well-tolerated and had a positive impact on metabolic parameters, alongside improvements in indices of adiposity.

Beyond the Rhythm: In Silico Identification of Key Genes and Therapeutic Targets in Atrial Fibrillation.

Atrial fibrillation (AF) is a prevalent cardiac arrhythmia worldwide and is characterized by a high risk of thromboembolism, ischemic stroke, and fatality. The precise molecular mechanisms of AF pathogenesis remain unclear. The purpose of this study was to use bioinformatics tools to identify novel key genes in AF, provide deeper insights into the molecular pathogenesis of AF, and uncover potential therapeutic targets. Four publicly available raw RNA-Seq datasets obtained through the ENA Browser, as well as proteomic analysis results, both derived from atrial tissues, were used in this analysis. Differential gene expression analysis was performed and cross-validated with proteomics results to identify common genes/proteins between them. A functional enrichment pathway analysis was performed. Cross-validation analysis revealed five differentially expressed genes, namely FGL2, IGFBP5, NNMT, PLA2G2A, and TNC, in patients with AF compared with those with sinus rhythm (SR). These genes play crucial roles in various cardiovascular functions and may be part of the molecular signature of AF. Furthermore, functional enrichment analysis revealed several pathways related to the extracellular matrix, inflammation, and structural remodeling. This study highlighted five key genes that constitute promising candidates for further experimental exploration as biomarkers as well as therapeutic targets for AF.

Identifying Microbiome Dynamics in Pediatric IBD: More than a Family Matter.

BACKGROUND: Pediatric inflammatory bowel disease (IBD) is a chronic inflammatory intestinal disease that affects both children and adolescents. Symptoms can significantly affect a child's growth, development, and quality of life, making early diagnosis and effective management crucial. This study focuses on treatment-naïve pediatric IBD patients and their immediate families to identify the role of the microbiome in disease onset. METHODS: Nine families with pediatric IBD were recruited, comprising seven drug-naïve Crohn's disease (CD) patients and two drug-naïve ulcerative colitis (UC) patients, as well as twenty-four healthy siblings/parents. Fecal samples were collected for 16S ribosomal RNA gene sequencing and bioinformatics analysis. RESULTS: We identified patterns of dysbiosis and hallmark microbial taxa among patients who shared ethnic, habitual, and dietary traits with themselves and their families. In addition, we examined the impact of the disease on specific microbial taxa and how these could serve as potential biomarkers for early detection. CONCLUSIONS: Our results suggest a potential role of maternal factors in the establishment and modulation of the early life microbiome, consistent with the current literature, which may have implications for understanding the etiology and progression of IBD.

Multi-omics integration to identify the genetic expression and protein signature of dilated and ischemic cardiomyopathy.

Introduction: Heart failure (HF) is a complex clinical syndrome leading to high morbidity. In this study, we aimed to identify the gene expression and protein signature of HF main causes, namely dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM). Methods: Omics data were accessed through GEO repository for transcriptomic and PRIDE repository for proteomic datasets. Sets of differentially expressed genes and proteins comprising DCM (DiSig) and ICM (IsSig) signatures were analyzed by a multilayered bioinformatics approach. Enrichment analysis via the Gene Ontology was performed through the Metascape platform to explore biological pathways. Protein-protein interaction networks were analyzed via STRING db and Network Analyst. Results: Intersection of transcriptomic and proteomic analysis showed 10 differentially expressed genes/proteins in DiSig (AEBP1, CA3, HBA2, HBB, HSPA2, MYH6, SERPINA3, SOD3, THBS4, UCHL1) and 15 differentially expressed genes/proteins in IsSig (AEBP1, APOA1, BGN, CA3, CFH, COL14A1, HBA2, HBB, HSPA2, LTBP2, LUM, MFAP4, SOD3, THBS4, UCHL1). Common and distinct biological pathways between DiSig and IsSig were retrieved, allowing for their molecular characterization. Extracellular matrix organization, cellular response to stress and transforming growth factor-beta were common between two subphenotypes. Muscle tissue development was dysregulated solely in DiSig, while immune cells activation and migration in IsSig. Discussion: Our bioinformatics approach sheds light on the molecular background of HF etiopathology showing molecular similarities as well as distinct expression differences between DCM and ICM. DiSig and IsSig encompass an array of "cross-validated" genes at both transcriptomic and proteomic level, which can serve as novel pharmacological targets and possible diagnostic biomarkers.

Hepatitis C Core Protein Induces a Genotype-Specific Susceptibility of Hepatocytes to TNF-Induced Death In Vitro and In Vivo.

Hepatitis C virus (HCV) core protein is a multifunctional protein that is involved in the proliferation, inflammation, and apoptosis mechanism of hepatocytes. HCV core protein genetic variability has been implicated in various outcomes of HCV pathology and treatment. In the present study, we aimed to analyze the role of the HCV core protein in tumor necrosis factor α (TNFα)-induced death under the viewpoint of HCV genetic variability. Immortalized hepatocytes (IHH), and not the Huh 7.5 hepatoma cell line, stably expressing HCV subtype 4a and HCV subtype 4f core proteins showed that only the HCV 4a core protein could increase sensitivity to TNFα-induced death. Development of two transgenic mice expressing the two different core proteins under the liver-specific promoter of transthyretin (TTR) allowed for the in vivo assessment of the role of the core in TNFα-induced death. Using the TNFα-dependent model of lipopolysaccharide/D-galactosamine (LPS/Dgal), we were able to recapitulate the in vitro results in IHH cells in vivo. Transgenic mice expressing the HCV 4a core protein were more susceptible to the LPS/Dgal model, while mice expressing the HCV 4f core protein had the same susceptibility as their littermate controls. Transcriptome analysis in liver biopsies from these transgenic mice gave insights into HCV core molecular pathogenesis while linking HCV core protein genetic variability to differential pathology in vivo.

Unpacking COVID-19 Systems Biology in Lung and Whole Blood with Transcriptomics and miRNA Regulators.

COVID-19 is a systemic disease affecting tissues and organs, including and beyond the lung. Apart from the current pandemic context, we also have vastly inadequate knowledge of consequences of repeated exposures to SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), the virus causing COVID-19, in multiple organ systems and the whole organism scales when the disease evolves from a pandemic to an endemic state. This calls for a systems biology and systems medicine approach and unpacking the effects of COVID-19 in lung as well as other tissues. We report here original findings from transcriptomics analyses and differentially expressed genes (DEGs) in lung samples from 60 patients and 27 healthy controls, and in whole blood samples from 255 patients and 103 healthy individuals. A total of 11 datasets with RNA-seq transcriptomic data were obtained from the Gene Expression Omnibus and the European Nucleotide Archive. The identified DEGs were used to construct protein interaction and functional networks and to identify related pathways and miRNAs. We found 35 DEGs common between lung and the whole blood, and importantly, 2 novel genes, namely CYP1B1 and TNFAIP6, which have not been previously implicated with COVID-19. We also identified four novel miRNA potential regulators, hsa-mir-192-5p, hsa-mir-221-3p, hsa-mir-4756-3p, and hsa-mir-10a-5p, implicated in lung or other diseases induced by coronaviruses. In summary, these findings offer new molecular leads and insights to unpack COVID-19 systems biology in a whole organism context and might inform future antiviral drug, diagnostics, and vaccine discovery efforts.

Novel clinical, molecular and bioinformatics insights into the genetic background of autism.

BACKGROUND: Clinical classification of autistic patients based on current WHO criteria provides a valuable but simplified depiction of the true nature of the disorder. Our goal is to determine the biology of the disorder and the ASD-associated genes that lead to differences in the severity and variability of clinical features, which can enhance the ability to predict clinical outcomes. METHOD: Novel Whole Exome Sequencing data from children (n = 33) with ASD were collected along with extended cognitive and linguistic assessments. A machine learning methodology and a literature-based approach took into consideration known effects of genetic variation on the translated proteins, linking them with specific ASD clinical manifestations, namely non-verbal IQ, memory, attention and oral language deficits. RESULTS: Linear regression polygenic risk score results included the classification of severe and mild ASD samples with a 81.81% prediction accuracy. The literature-based approach revealed 14 genes present in all sub-phenotypes (independent of severity) and others which seem to impair individual ones, highlighting genetic profiles specific to mild and severe ASD, which concern non-verbal IQ, memory, attention and oral language skills. CONCLUSIONS: These genes can potentially contribute toward a diagnostic gene-set for determining ASD severity. However, due to the limited number of patients in this study, our classification approach is mostly centered on the prediction and verification of these genes and does not hold a diagnostic nature per se. Substantial further experimentation is required to validate their role as diagnostic markers. The use of these genes as input for functional analysis highlights important biological processes and bridges the gap between genotype and phenotype in ASD.

Defining virus-carrier networks that shape the composition of the mosquito core virome of a local ecosystem.

Mosquitoes are the most important vectors of emerging infectious diseases. During the past decade, our understanding of the diversity of viruses they carry has greatly expanded. Most of these viruses are considered mosquito-specific, but there is increasing evidence that these viruses may affect the vector competence of mosquitoes. Metagenomics approaches have focused on specific mosquito species for the identification of what is called the core virome. Despite the fact that, in most ecosystems, multiple species may participate in virus emergence and circulation, there is a lack of understanding of the virus-carrier/host network for both vector-borne and mosquito-specific viruses. Here, we studied the core virome of mosquitoes in a diverse local ecosystem that had 24 different mosquito species. The analysis of the viromes of these 24 mosquito species resulted in the identification of 34 viruses, which included 15 novel viruses, as determined according to the species demarcation criteria of the respective virus families. Most of the mosquito species had never been analysed previously, and a comparison of the individual viromes of the 24 mosquito species revealed novel relationships among mosquito species and virus families. Groups of related viruses and mosquito species from multiple genera formed a complex web in the local ecosystem. Furthermore, analyses of the virome of mixed-species pools of mosquitoes from representative traps of the local ecosystem showed almost complete overlap with the individual-species viromes identified in the study. Quantitative analysis of viruses' relative abundance revealed a linear relationship to the abundance of the respective carrier/host mosquito species, supporting the theory of a stable core virome in the most abundant species of the local ecosystem. Finally, our study highlights the importance of using a holistic approach to investigating mosquito viromes relationships in rich and diverse ecosystems.

Dissecting the Species-Specific Virome in Culicoides of Thrace.

Biting midges (Culicoides) are vectors of arboviruses of both veterinary and medical importance. The surge of emerging and reemerging vector-borne diseases and their expansion in geographical areas affected by climate change has increased the importance of understanding their capacity to contribute to novel and emerging infectious diseases. The study of Culicoides virome is the first step in the assessment of this potential. In this study, we analyzed the RNA virome of 10 Culicoides species within the geographical area of Thrace in the southeastern part of Europe, a crossing point between Asia and Europe and important path of various arboviruses, utilizing the Ion Torrent next-generation sequencing (NGS) platform and a custom bioinformatics pipeline based on TRINITY assembler and alignment algorithms. The analysis of the RNA virome of 10 Culicoides species resulted in the identification of the genomic signatures of 14 novel RNA viruses, including three fully assembled viruses and four segmented viruses with at least one segment fully assembled, most of which were significantly divergent from previously identified related viruses from the Solemoviridae, Phasmaviridae, Phenuiviridae, Reoviridae, Chuviridae, Partitiviridae, Orthomyxoviridae, Rhabdoviridae, and Flaviviridae families. Each Culicoides species carried a species-specific set of viruses, some of which are related to viruses from other insect vectors in the same area, contributing to the idea of a virus-carrier web within the ecosystem. The identified viruses not only expand our current knowledge on the virome of Culicoides but also set the basis of the genetic diversity of such viruses in the area of southeastern Europe. Furthermore, our study highlights that such metagenomic approaches should include as many species as possible of the local virus-carrier web that interact and share the virome of a geographical area.

miRNAs expression pattern and machine learning models elucidate risk for gastric GIST.

BACKGROUND: Gatrointestinal stromal tumors (GISTs) are the main mesenchymal tumors found in the gastrointestinal system. GISTs clinical phenotypes differ significantly and their molecular basis is not yet completely known. microRNAs (miRNAs) have been involved in carcinogenesis pathways by regulating gene expression at post-transcriptional level. OBJECTIVE: The aim of the present study was to elucidate the expression profiles of miRNAs relevant to gastric GIST carcinogenesis, and to identify miRNA signatures that can discriminate the GIST from normal cases. METHODS: miRNA expression was tested by miScript™miRNA PCR Array Human Cancer PathwayFinder kit and then we used machine learning in order to find a miRNA profile that can predict the risk for GIST development. RESULTS: A number of miRNAs were found to be differentially expressed in GIST cases compared to healthy controls. Among them the hsa-miR-218-5p was found to be the best predictor for GIST development in our cohort. Additionally, hsa-miR-146a-5p, hsa-miR-222-3p, and hsa-miR-126-3p exhibit significantly lower expression in GIST cases compared to controls and were among the top predictors in all our predictive models. CONCLUSIONS: A machine learning classification approach may be accurate in determining the risk for GIST development in patients. Our findings indicate that a small number of miRNAs, with hsa-miR218-5p as a focus, may strongly affect the prognosis of GISTs.

Unlocking the Memory Component of Alzheimer's Disease: Biological Processes and Pathways across Brain Regions.

Alzheimer's Disease (AD) is a neurodegenerative disorder characterized by a progressive loss of memory and a general cognitive decline leading to dementia. AD is characterized by changes in the behavior of the genome and can be traced across multiple brain regions and cell types. It is mainly associated with ß-amyloid deposits and tau protein misfolding, leading to neurofibrillary tangles. In recent years, however, research has shown that there is a high complexity of mechanisms involved in AD neurophysiology and functional decline enabling its diverse presentation and allowing more questions to arise. In this study, we present a computational approach to facilitate brain region-specific analysis of genes and biological processes involved in the memory process in AD. Utilizing current genetic knowledge we provide a gene set of 265 memory-associated genes in AD, combinations of which can be found co-expressed in 11 different brain regions along with their functional role. The identified genes participate in a spectrum of biological processes ranging from structural and neuronal communication to epigenetic alterations and immune system responses. These findings provide new insights into the molecular background of AD and can be used to bridge the genotype-phenotype gap and allow for new therapeutic hypotheses.

Response to Anti-α4ß7 Blockade in Patients With Ulcerative Colitis Is Associated With Distinct Mucosal Gene Expression Profiles at Baseline.

BACKGROUND: Improving treatment outcomes with biological therapy is a demanding current need for patients with inflammatory bowel disease. Discovery of pretreatment prognostic indicators of response may facilitate patient selection and increase long-term remission rates. We aimed to identify baseline mucosal gene expression profiles with predictive value for subsequent response to or failure of treatment with the monoclonal antibody against integrin α4ß7, vedolizumab, in patients with active ulcerative colitis (UC). METHODS: Mucosal expression of 84 immunological and inflammatory genes was quantified in RNA extracted from colonic biopsies before vedolizumab commencement and compared between patients with or without response to treatment. Significantly differentiated genes were further validated in a larger patient cohort and within available public data sets, and their functional profiles were studied accordingly. RESULTS: In the discovery cohort, we identified 21 genes with a statistically significant differential expression between 54-week responders and nonresponders to vedolizumab. Our validation study allowed us to recognize a "core" mucosal profile that was preserved in both discovery and validation cohorts and in the public database. The applied functional annotation and analysis revealed candidate dysregulated pathways in nonresponders to vedolizumab, including immune cell trafficking, TNF receptor superfamily members mediating noncanonical NF-kB pathway, in addition to interleukin signaling, MyD88 signaling, and toll-like receptors (TLRs) cascade. CONCLUSIONS: Nonresponse to vedolizumab in UC is associated with specific pretreatment gene-expression mucosal signatures and dysregulation of particular immunological and inflammatory pathways. Baseline mucosal and/or systemic molecular profiling may help in the optimal stratification of patients to receive vedolizumab for active UC.