Machine Learning Gene Signature to Metastatic ccRCC Based on ceRNA Network.

Clear-cell renal-cell carcinoma (ccRCC) is a silent-development pathology with a high rate of metastasis in patients. The activity of coding genes in metastatic progression is well known. New studies evaluate the association with non-coding genes, such as competitive endogenous RNA (ceRNA).

A Novel Machine Learning 13-Gene Signature: Improving Risk Analysis and Survival Prediction for Clear Cell Renal Cell Carcinoma Patients.

Patients with clear cell renal cell carcinoma (ccRCC) have poor survival outcomes, especially if it has metastasized. It is of paramount importance to identify biomarkers in genomic data that could help predict the aggressiveness of ccRCC and its resistance to drugs. Thus, we conducted a study with the aims of evaluating gene signatures and proposing a novel one with higher predictive power and generalization in comparison to the former signatures.

An integrated approach to identify bimodal genes associated with prognosis in câncer.

Bimodal gene expression (where a gene expression distribution has two maxima) is associated with phenotypic diversity in different biological systems. A critical issue, thus, is the integration of expression and phenotype data to identify genuine associations. Here, we developed tools that allow both: i) the identification of genes with bimodal gene expression and ii) their association with prognosis in cancer patients from The Cancer Genome Atlas (TCGA).

A small interfering RNA (siRNA) database for SARS-CoV-2.

Coronavirus disease 2019 (COVID-19) rapidly transformed into a global pandemic, for which a demand for developing antivirals capable of targeting the SARS-CoV-2 RNA genome and blocking the activity of its genes has emerged. In this work, we presented a database of SARS-CoV-2 targets for small interference RNA (siRNA) based approaches, aiming to speed the design process by providing a broad set of possible targets and siRNA sequences. The siRNAs sequences are characterized and evaluated by more than 170 features, including thermodynamic information, base context, target genes and alignment information of sequences against the human genome, and diverse SARS-CoV-2 strains, to assess possible bindings to off-target sequences.

Mobile applications for sexual encounters accessed by men who have sex with men: Information on sexually transmitted infection.

We evaluated existing mobile applications (apps) on both Android and iOS (Apple) platforms that are used by men who have sex with men (MSM) to obtain sexual encounters. The word "gay" was used to search for apps in the Apple and Google Play virtual stores. The 10 most downloaded apps were analysed concerning safe sexual practices (SSP) messages.

Use of dating sites and applications by women and their risk of sexually transmitted infections: a systematic review and meta-analysis protocol.

Introduction: The use of social networks has been increasing worldwide. Mobile websites and applications (apps) allow people to network more quickly and have more partners for sex. This can facilitate risky sexual behaviours, such as having multiple partners and unprotected sex, which can lead to a higher incidence of sexually transmitted infections.

A decision tree to improve identification of pathogenic mutations in clinical practice.

Background: A variant of unknown significance (VUS) is a variant form of a gene that has been identified through genetic testing, but whose significance to the organism function is not known. An actual challenge in precision medicine is to precisely identify which detected mutations from a sequencing process have a suitable role in the treatment or diagnosis of a disease. The average accuracy of pathogenicity predictors is 85%.

Impact of mobile applications on adherence to cancer treatment: a systematic review and meta-analysis protocol.

Introduction: The number of patients taking oral chemotherapy is increasing around the world. It is essential to maximise the adherence to oral chemotherapy to improve the overall survival and life expectancy of the patients. In this systematic review and meta-analysis, we aim to evaluate the effectiveness of mobile applications in improving the adherence to oral chemotherapy and adjuvant hormonal therapy in cancer survivors.

Assessment of mobile phone applications for care management in gynecology and obstetrics.

We identified mobile applications (apps) found on digital platforms (iTunes Store and Google Play) that addressed topics about gynecology and obstetrics.

Genome-wide identification of cancer/testis genes and their association with prognosis in a pan-cancer analysis.

Cancer/testis (CT) genes are excellent candidates for cancer immunotherapies because of their restrict expression in normal tissues and the capacity to elicit an immune response when expressed in tumor cells. In this study, we provide a genome-wide screen for CT genes with the identification of 745 putative CT genes. Comparison with a set of known CT genes shows that 201 new CT genes were identified.

Bioinformatics Analysis of the Human Surfaceome Reveals New Targets for a Variety of Tumor Types.

It is estimated that 10 to 20% of all genes in the human genome encode cell surface proteins and due to their subcellular localization these proteins represent excellent targets for cancer diagnosis and therapeutics. Therefore, a precise characterization of the surfaceome set in different types of tumor is needed. Using TCGA data from 15 different tumor types and a new method to identify cancer genes, the -score, we identified several potential therapeutic targets within the surfaceome set.

Modeling tumor evolutionary dynamics.

Tumorigenesis can be seen as an evolutionary process, in which the transformation of a normal cell into a tumor cell involves a number of limiting genetic and epigenetic events, occurring in a series of discrete stages. However, not all mutations in a cell are directly involved in cancer development and it is likely that most of them (passenger mutations) do not contribute in any way to tumorigenesis. Moreover, the process of tumor evolution is punctuated by selection of advantageous (driver) mutations and clonal expansions.

Insights into gliomagenesis: systems biology unravels key pathways.

Technological advances have enabled a better characterization of all the genetic alterations in tumors. A picture that emerges is that tumor cells are much more genetically heterogeneous than originally expected. Thus, a critical issue in cancer genomics is the identification of the genetic alterations that drive the genesis of a tumor.

Modeling cancer: integration of "omics" information in dynamic systems.

The last 10 years have seen the rise of many technologies that produce an unprecedented amount of genome-scale data from many organisms. Although the research community has been successful in exploring these data, many challenges still persist. One of them is the effective integration of such data sets directly into approaches based on mathematical modeling of biological systems.

Regeneration of natural antibody repertoire after massive ablation of lymphoid system: robust selection mechanisms preserve antigen binding specificities.

Natural Abs (NAbs) are Igs present in the serum and body fluids of healthy vertebrate animals, without any previous intentional immunization. NAbs often exhibit autoreactivity but also play an essential role in immunity, being a first line of defense against infectious microorganisms. We have previously analyzed the natural serum IgM Ab repertoire of normal mice, characterizing their reactivity with hundreds/thousands of self Ags; a significant similarity among different individuals was observed, and it was found that many reactivities of NAbs stably kept during adulthood were established early in life, implicating that period as a critical time window in the physiology of NAb repertoire selection.