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Background: Obesity and aging are associated with the progressive loss of brown adipose tissue (BAT), an increase in visceral white adipose tissue (vWAT), and a reduction in subcutaneous white adipose tissue (sWAT). The progressive expansion of visceral obesity promotes a low grade of systemic chronic inflammation (meta-inflammation), contributing to the onset of comorbidities such as type 2 diabetes mellitus (T2DM), metabolic syndrome, and even cancer. Thus, preserving the thermogenic activity of adipose tissue and improving the metabolic flexibility of sWAT could be an effective strategy to prevent the development of metabolic chronic diseases and promote healthy aging. Precision nutrition has emerged as a complementary approach to control the metabolic alterations associated with unhealthy obesity and aging. In a previous work, we described that a silymarin-enriched extract from milk thistle (Mthistle) increased markers of browning and thermogenesis in vitro in human differentiated adipocytes (SGBS). Objectives/Methods: Therefore, this study aims to evaluate the potential of Mthistle to activate thermogenesis in a preclinical model of high-fat diet (HFD)-induced obesity (DIO). Results: Our results demonstrate that Mthistle increases systemic energy expenditure (EE), preserves body temperature after cold exposure, improves insulin resistance, and reduces inflammatory markers in WAT. Conclusions: Based on these results, silymarin-enriched extract from Mthistle may be proposed as a nutraceutical for the management of metabolic chronic diseases and/or accelerated aging. [ABSTRACT FROM AUTHOR]

Simple Summary: The survival of advanced melanoma patients has been improved in recent years due to immunotherapy. However, not all patients respond to this treatment. For this reason, it is necessary to know the mechanisms of the response and resistance to immunotherapy. In this work, clinical samples from advanced melanoma patients treated with immunotherapy were analyzed. The obtained results suggested that the proteins involved in protein processing in the endoplasmic reticulum and antigen presentation, as well as the immune and inflammatory responses, play a role in the response to immunotherapy. Additionally, we built a prognostic signature capable of identifying those patients that will respond to immunotherapy. The study of the mechanisms of the resistance and response to immunotherapy could help in the definition of new therapies for these patients that do not respond to immunotherapy. Immunotherapy improves the survival of patients with advanced melanoma, 40% of whom become long-term responders. However, not all patients respond to immunotherapy. Further knowledge of the processes involved in the response and resistance to immunotherapy is still needed. In this study, clinical paraffin samples from fifty-two advanced melanoma patients treated with anti-PD-1 inhibitors were assessed via high-throughput proteomics and RNA-seq. The obtained proteomics and transcriptomics data were analyzed using multi-omics network analyses based on probabilistic graphical models to identify those biological processes involved in the response to immunotherapy. Additionally, proteins related to overall survival were studied. The activity of the node formed by the proteins involved in protein processing in the endoplasmic reticulum and antigen presentation machinery was higher in responders compared to non-responders; the activity of the immune and inflammatory response node was also higher in those with complete or partial responses. A predictor for overall survival based on two proteins (AMBP and PDSM5) was defined. In summary, the response to anti-PD-1 therapy in advanced melanoma is related to protein processing in the endoplasmic reticulum, and also to genes involved in the immune and inflammatory responses. Finally, a two-protein predictor can define survival in advanced disease. The molecular characterization of the mechanisms involved in the response and resistance to immunotherapy in melanoma leads the way to establishing therapeutic alternatives for patients who will not respond to this treatment. [ABSTRACT FROM AUTHOR]

The GPRO suite is an in-progress bioinformatic project for -omics data analysis. As part of the continued growth of this project, we introduce a client- and server-side solution for comparative transcriptomics and analysis of variants. The client-side consists of two Java applications called "RNASeq" and "VariantSeq" to manage pipelines and workflows based on the most common command line interface tools for RNA-seq and Variant-seq analysis, respectively. As such, "RNASeq" and "VariantSeq" are coupled with a Linux server infrastructure (named GPRO Server-Side) that hosts all dependencies of each application (scripts, databases, and command line interface software). Implementation of the Server-Side requires a Linux operating system, PHP, SQL, Python, bash scripting, and third-party software. The GPRO Server-Side can be installed, via a Docker container, in the user's PC under any operating system or on remote servers, as a cloud solution. "RNASeq" and "VariantSeq" are both available as desktop (RCP compilation) and web (RAP compilation) applications. Each application has two execution modes: a step-by-step mode enables each step of the workflow to be executed independently, and a pipeline mode allows all steps to be run sequentially. "RNASeq" and "VariantSeq" also feature an experimental, online support system called GENIE that consists of a virtual (chatbot) assistant and a pipeline jobs panel coupled with an expert system. The chatbot can troubleshoot issues with the usage of each tool, the pipeline jobs panel provides information about the status of each computational job executed in the GPRO Server-Side, while the expert system provides the user with a potential recommendation to identify or fix failed analyses. Our solution is a ready-to-use topic specific platform that combines the user-friendliness, robustness, and security of desktop software, with the efficiency of cloud/web applications to manage pipelines and workflows based on command line interface software. [ABSTRACT FROM AUTHOR]

Integrating transcriptional profiles results in identifying gene expression signatures that are more robust than those obtained for individual datasets. However, a direct comparison of datasets derived from heterogeneous experimental conditions is problematic, hence their integration requires applying of specific meta-analysis techniques. The transcriptional response to hypoxia has been the focus of intense research due to its central role in tissue homeostasis and prevalent diseases. Accordingly, many studies have determined the gene expression profile of hypoxic cells. Yet, despite this wealth of information, little effort has been made to integrate these datasets to produce a robust hypoxic signature. We applied a formal meta-analysis procedure to datasets comprising 430 RNA-seq samples from 43 individual studies including 34 different cell types, to derive a pooled estimate of the effect of hypoxia on gene expression in human cell lines grown ingin vitro. This approach revealed that a large proportion of the transcriptome is significantly regulated by hypoxia (8556 out of 20,888 genes identified across studies). However, only a small fraction of the differentially expressed genes (1265 genes, 15%) show an effect size that, according to comparisons to gene pathways known to be regulated by hypoxia, is likely to be biologically relevant. By focusing on genes ubiquitously expressed, we identified a signature of 291 genes robustly and consistently regulated by hypoxia. Overall, we have developed a robust gene signature that characterizes the transcriptomic response of human cell lines exposed to hypoxia in vitro by applying a formal meta-analysis to gene expression profiles. [ABSTRACT FROM AUTHOR]

Congenital lactic acidosis (CLA) is a rare condition in most instances due to a range of inborn errors of metabolism that result in defective mitochondrial function. Even though the implementation of next generation sequencing has been rapid, the diagnosis rate for this highly heterogeneous allelic condition remains low. The present work reports our group's experience of using a clinical/biochemical analysis system in conjunction with genetic findings that facilitates the taking of timely clinical decisions with minimum need for invasive procedures. The system's workflow combines different metabolomics datasets and phenotypic information with the results of clinical exome sequencing and/or RNA analysis. The system's use detected genetic variants in 64% of a cohort of 39 CLA-patients; these variants, 14 of which were novel, were found in 19 different nuclear and two mitochondrial genes. For patients with variants of unknown significance, the genetic analysis was combined with functional genetic and/or bioenergetics analyses in an attempt to detect pathogenicity. Our results warranted subsequent testing of antisense therapy to rescue the abnormal splicing in cultures of fibroblasts from a patient with a defective GFM1 gene. The discussed system facilitates the diagnosis of CLA by avoiding the need to use invasive techniques and increase our knowledge of the causes of this condition. [ABSTRACT FROM AUTHOR]