Unveiling Common Transcriptomic Features between Melanoma Brain Metastases and Neurodegenerative Diseases.

Melanoma represents a critical clinical challenge owing to its unfavorable outcomes. This type of skin cancer exhibits unique adaptability to the brain microenvironment, but its underlying molecular mechanisms are poorly understood. Recent findings have suggested that melanoma brain metastases may share biological processes similar to those found in various neurodegenerative diseases.

MetaFun: unveiling sex-based differences in multiple transcriptomic studies through comprehensive functional meta-analysis.

Background: While sex-based differences in various health scenarios have been thoroughly acknowledged in the literature, we lack sufficient tools and methods that allow for an in-depth analysis of sex as a variable in biomedical research. To fill this knowledge gap, we created MetaFun as an easy-to-use web-based tool to meta-analyze multiple transcriptomic datasets with a sex-based perspective to gain major statistical power and biological soundness.

Description: MetaFun is a complete suite that allows the analysis of transcriptomics data and the exploration of the results at all levels, performing single-dataset exploratory analysis, differential gene expression, gene set functional enrichment, and finally, combining results in a functional meta-analysis.

Comparative profiling of whole-cell and exosome samples reveals protein signatures that stratify breast cancer subtypes.

Identifying novel breast cancer biomarkers will improve patient stratification, enhance therapeutic outcomes, and help develop non-invasive diagnostics. We compared the proteomic profiles of whole-cell and exosomal samples of representative breast cancer cell subtypes to evaluate the potential of extracellular vesicles as non-invasive disease biomarkers in liquid biopsies. Overall, differentially-expressed proteins in whole-cell and exosome samples (which included markers for invasion, metastasis, angiogenesis, and drug resistance) effectively discriminated subtypes; furthermore, our results confirmed that the proteomic profile of exosomes reflects breast cancer cell-of-origin, which underscores their potential as disease biomarkers.

The impact of sex on gene expression in the brain of schizophrenic patients: a systematic review and meta-analysis of transcriptomic studies.

Background: Schizophrenia is a severe neuropsychiatric disorder characterized by altered perception, mood, and behavior that profoundly impacts patients and society despite its relatively low prevalence. Sex-based differences have been described in schizophrenia epidemiology, symptomatology and outcomes. Different studies explored the impact of schizophrenia in the brain transcriptome, however we lack a consensus transcriptomic profile that considers sex and differentiates specific cerebral regions.

An integrated approach to identifying sex-specific genes, transcription factors, and pathways relevant to Alzheimer's disease.

Background: Age represents a significant risk factor for the development of Alzheimer's disease (AD); however, recent research has documented an influencing role of sex in several features of AD. Understanding the impact of sex on specific molecular mechanisms associated with AD remains a critical challenge to creating tailored therapeutic interventions.

Methods: The exploration of the sex-based differential impact on disease (SDID) in AD used a systematic review to first select transcriptomic studies of AD with data regarding sex in the period covering 2002 to 2021 with a focus on the primary brain regions affected by AD - the cortex (CT) and the hippocampus (HP).

The role of microRNAs in understanding sex-based differences in Alzheimer's disease.

Background: The incidence of Alzheimer's disease (AD)-the most frequent cause of dementia-is expected to increase as life expectancies rise across the globe. While sex-based differences in AD have previously been described, there remain uncertainties regarding any association between sex and disease-associated molecular mechanisms. Studying sex-specific expression profiles of regulatory factors such as microRNAs (miRNAs) could contribute to more accurate disease diagnosis and treatment.

Integrated transcriptomic landscape of the effect of anti-steatotic treatments in high-fat diet mouse models of non-alcoholic fatty liver disease.

High-fat diet (HFD) mouse models are widely used in research to develop medications to treat non-alcoholic fatty liver disease (NAFLD), as they mimic the steatosis, inflammation, and hepatic fibrosis typically found in this complex human disease. The aims of this study were to identify a complete transcriptomic signature of these mouse models and to characterize the transcriptional impact exerted by different experimental anti-steatotic treatments. For this reason, we conducted a systematic review and meta-analysis of liver transcriptomic studies performed in HFD-fed C57BL/6J mice, comparing them with control mice and HFD-fed mice receiving potential anti-steatotic treatments.

A Comprehensive Transcriptional Signature in Pancreatic Ductal Adenocarcinoma Reveals New Insights into the Immune and Desmoplastic Microenvironments.

Pancreatic ductal adenocarcinoma (PDAC) prognoses and treatment responses remain devastatingly poor due partly to the highly heterogeneous, aggressive, and immunosuppressive nature of this tumor type. The intricate relationship between the stroma, inflammation, and immunity remains vaguely understood in the PDAC microenvironment. Here, we performed a meta-analysis of stroma-, and immune-related gene expression in the PDAC microenvironment to improve disease prognosis and therapeutic development.

Deciphering the sex bias in housekeeping gene expression in adipose tissue: a comprehensive meta-analysis of transcriptomic studies.

Background: As the housekeeping genes (HKG) generally involved in maintaining essential cell functions are typically assumed to exhibit constant expression levels across cell types, they are commonly employed as internal controls in gene expression studies. Nevertheless, HKG may vary gene expression profile according to different variables introducing systematic errors into experimental results. Sex bias can indeed affect expression display, however, up to date, sex has not been typically considered as a biological variable.

Unveiling sex-based differences in Parkinson's disease: a comprehensive meta-analysis of transcriptomic studies.

Background: In recent decades, increasing longevity (among other factors) has fostered a rise in Parkinson's disease incidence. Although not exhaustively studied in this devastating disease, the impact of sex represents a critical variable in Parkinson's disease as epidemiological and clinical features differ between males and females.

Methods: To study sex bias in Parkinson's disease, we conducted a systematic review to select sex-labeled transcriptomic data from three relevant brain tissues: the frontal cortex, the striatum, and the substantia nigra.

Minimal hepatic encephalopathy is associated to alterations in eye movements.

Minimal hepatic encephalopathy (MHE) is diagnosed using PHES battery, but other tests are more sensitive, and a simple tool for early MHE detection is required. Assessment of saccadic eye movements is useful for early detection of cognitive alterations in different pathologies. We characterized the alterations in saccadic eye movements in MHE patients, its relationship with cognitive alterations and its utility for MHE diagnosis.

NPC transplantation rescues sci-driven cAMP/EPAC2 alterations, leading to neuroprotection and microglial modulation.

Neural progenitor cell (NPC) transplantation represents a promising treatment strategy for spinal cord injury (SCI); however, the underlying therapeutic mechanisms remain incompletely understood. We demonstrate that severe spinal contusion in adult rats causes transcriptional dysregulation, which persists from early subacute to chronic stages of SCI and affects nearly 20,000 genes in total tissue extracts. Functional analysis of this dysregulated transcriptome reveals the significant downregulation of cAMP signalling components immediately after SCI, involving genes such as EPAC2 (exchange protein directly activated by cAMP), PKA, BDNF, and CAMKK2.

Mechanistic models of signaling pathways deconvolute the glioblastoma single-cell functional landscape.

Single-cell RNA sequencing is revealing an unexpectedly large degree of heterogeneity in gene expression levels across cell populations. However, little is known on the functional consequences of this heterogeneity and the contribution of individual cell fate decisions to the collective behavior of the tissues these cells are part of. Here, we use mechanistic modeling of signaling circuits, which reveals a complex functional landscape at single-cell level.

Genome-scale mechanistic modeling of signaling pathways made easy: A bioconductor/cytoscape/web server framework for the analysis of omic data.

Genome-scale mechanistic models of pathways are gaining importance for genomic data interpretation because they provide a natural link between genotype measurements (transcriptomics or genomics data) and the phenotype of the cell (its functional behavior). Moreover, mechanistic models can be used to predict the potential effect of interventions, including drug inhibitions. Here, we present the implementation of a mechanistic model of cell signaling for the interpretation of transcriptomic data as an R/Bioconductor package, a Cytoscape plugin and a web tool with enhanced functionality which includes building interpretable predictors, estimation of the effect of perturbations and assessment of the effect of mutations in complex scenarios.

Common pathways and functional profiles reveal underlying patterns in Breast, Kidney and Lung cancers.

Background: Cancer is a major health problem which presents a high heterogeneity. In this work we explore omics data from Breast, Kidney and Lung cancers at different levels as signalling pathways, functions and miRNAs, as part of the CAMDA 2019 Hi-Res Cancer Data Integration Challenge. Our goal is to find common functional patterns which give rise to the generic microenvironment in these cancers and contribute to a better understanding of cancer pathogenesis and a possible clinical translation down further studies.

Hepatic steatosis and steatohepatitis: a functional meta-analysis of sex-based differences in transcriptomic studies.

Background: Previous studies have described sex-based differences in the epidemiological and clinical patterns of non-alcoholic fatty liver disease (NAFLD); however, we understand relatively little regarding the underlying molecular mechanisms. Herein, we present the first systematic review and meta-analysis of NAFLD transcriptomic studies to identify sex-based differences in the molecular mechanisms involved during the steatosis (NAFL) and steatohepatitis (NASH) stages of the disease.

Methods: Transcriptomic studies in the Gene Expression Omnibus database were systematically reviewed following the PRISMA statement guidelines.

Functional Signatures in Non-Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis of Sex-Based Differences in Transcriptomic Studies.

While studies have established the existence of differences in the epidemiological and clinical patterns of lung adenocarcinoma between male and female patients, we know relatively little regarding the molecular mechanisms underlying such sex-based differences. In this study, we explore said differences through a meta-analysis of transcriptomic data. We performed a meta-analysis of the functional profiling of nine public datasets that included 1366 samples from Gene Expression Omnibus and The Cancer Genome Atlas databases.

Mechanistic modeling of the SARS-CoV-2 disease map.

Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied.

Unveiling Sex-Based Differences in the Effects of Alcohol Abuse: A Comprehensive Functional Meta-Analysis of Transcriptomic Studies.

The abuse of alcohol, one of the most popular psychoactive substances, can cause several pathological and psychological consequences, including alcohol use disorder (AUD). An impaired ability to stop or control alcohol intake despite adverse health or social consequences characterize AUD. While AUDs predominantly occur in men, growing evidence suggests the existence of distinct cognitive and biological consequences of alcohol dependence in women.

Effectiveness of Laparoscopic Sleeve Gastrectomy in Super-obese and Non-Super-obese Patients.

Objectives: The primary aim of this study was to assess the effectiveness of sleeve gastrectomy (SG) in super-obese patients. The secondary aim was to identify patient characteristics associated with worse SG outcomes in this group.

Methods: A retrospective analysis was carried out of our electronic prospective bariatric surgery patient database, including all patients who underwent SG between January 2007 and January 2017.

Operative and Postoperative Complications of Laparoscopic Sleeve Gastrectomy in Super and Nonsuper Obese Patients: A Center of Excellence Experience Comparative Study.

Laparoscopic sleeve gastrectomy (LSG) is now one of the most common surgical procedures worldwide. It was initially defined for staged procedures in super or super-super obese, or in very complex patients. The primary objective of the study was to assess the safety of LSG for morbid-obese (MO, body mass index [BMI] >40 kg/m) and super-morbid-obese (SMO, BMI >50 kg/m) patients in terms of operative and postoperative complication rate.

Using mechanistic models for the clinical interpretation of complex genomic variation.

The sustained generation of genomic data in the last decade has increased the knowledge on the causal mutations of a large number of diseases, especially for highly penetrant Mendelian diseases, typically caused by a unique or a few genes. However, the discovery of causal genes in complex diseases has been far less successful. Many complex diseases are actually a consequence of the failure of complex biological modules, composed by interrelated proteins, which can happen in many different ways, which conferring a multigenic nature to the condition that can hardly be attributed to one or a few genes.