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. Meta-analysis results from data merged, normalized, and corrected for batch effect show an enrichment for Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways related to the immune response, nucleic acid metabolism, and purinergic signaling. We discovered the overrepresentation of terms associated with the immune response, particularly with the acute inflammatory response, and purinergic signaling in female lung adenocarcinoma patients, which could influence reported clinical differences. Further evaluations of the identified differential biological processes and pathways could lead to the discovery of new biomarkers and therapeutic targets. Our findings also emphasize the relevance of sex-specific analyses in biomedicine, which represents a crucial aspect influencing biological variability in diseaseThis work was supported by Fondo de Investigación Sanitaria (ISCIII PI15-00209), GV/2020/ 186, and ISCIII PT17/0009/0015 FEDE

SARS-CoV-2-encoded small RNAs are able to repress the host expression of SERINC5 to facilitate viral replication

19 páginas, 9 figuras, 1 tablaSerine incorporator protein 5 (SERINC5) is a key innate immunity factor that operates in the cell to restrict the infectivity of certain viruses. Different viruses have developed strategies to antagonize SERINC5 function but, how SERINC5 is controlled during viral infection is poorly understood. Here, we report that SERINC5 levels are reduced in COVID-19 patients during the infection by SARS-CoV-2 and, since no viral protein capable of repressing the expression of SERINC5 has been identified, we hypothesized that SARS-CoV-2 non-coding small viral RNAs (svRNAs) could be responsible for this repression. Two newly identified svRNAs with predicted binding sites in the 3'-untranslated region (3'-UTR) of the SERINC5 gene were characterized and we found that the expression of both svRNAs during the infection was not dependent on the miRNA pathway proteins Dicer and Argonaute-2. By using svRNAs mimic oligonucleotides, we demonstrated that both viral svRNAs can bind the 3'UTR of SERINC5 mRNA, reducing SERINC5 expression in vitro. Moreover, we found that an anti-svRNA treatment to Vero E6 cells before SARS-CoV-2 infection recovered the levels of SERINC5 and reduced the levels of N and S viral proteins. Finally, we showed that SERINC5 positively controls the levels of Mitochondrial Antiviral Signalling (MAVS) protein in Vero E6. These results highlight the therapeutic potential of targeting svRNAs based on their action on key proteins of the innate immune response during SARS-CoV-2 viral infection.This work has been supported by grant CSIC-COV19-106 (202020 E164) from the Spanish National Research Council (CSIC) to FA and FI, and grant from RTI2018-101291-B-I00 to EE from the Spanish Ministry of Science and InnovationPeer reviewe

PROCare4Life: An integrated care platform to improve the quality of life of Parkinson’s and Alzheimer’s patients

The incredible increase in smart sensing technologies has provided a very high range of new potential applications for healthcare systems. In this scope, several initiatives are taking the advantage of sensors technologies and the new capabilities to collect properly all the raw information. Thanks to the inclusion and combination of wearable and fixed sensors, image device sensors among others, the number of solutions for accurate health monitoring in different environments has grown exponentially. In this paper, we present a complete system called PROCare4Life divided into two main subsystems. The first, will use a combination of sensing technologies to collect the raw information and get prior knowledge with some detection algorithms to generate a final daily summary of the relevant data. The second, a cloud-based platform, that centralizes the entire ecosystem to perform a multimodal fusion using the collected data, medical information, and other relevant inputs from medical experts. Finally, the system tries to improve the quality of life by providing recommendations, alerts, events, and other relevant information to the users in different interfaces