The management and screening of prostate cancer (PC) is still the main problem in clinical practice. In this study, we investigated the role of aggressiveness genetic markers for PC stratification. We analyzed 201 plasma samples from PC patients and controls by digital PCR. For selection and validation, 26 formalin-fixed paraffin-embedded tissues, 12 fresh tissues, and 24 plasma samples were characterized by RNA-Seq, immunochemistry, immunofluorescence, Western blot, and extracellular-vesicles analyses. We identified three novel non-invasive biomarkers; all with an increased expression pattern in patients (PCA3: p = 0.002, S100A4: p ≤ 0.0001 and MRC2: p = 0.005). S100A4 presents the most informative AUC (area under the curve) (0.735). Combination of S100A4, MRC2, and PCA3 increases the discriminatory power between patients and controls and between different more and less aggressive stages (AUC = 0.761, p ≤ 0.0001). However, although a sensitivity of 97.47% in PCA3 and a specificity of 90.32% in S100A4 was reached, the detection signal level could be variable in some analyses owing to tumor heterogeneity. This is the first time that the role of S100A4 and MRC2 has been described in PC aggressiveness. Moreover, the combination of S100A4, MRC2, and PCA3 has never been described as a non-invasive biomarker for PC screening and aggressiveness.

The COVID-19 pandemic presents a spectrum of clinical outcomes ranging from respiratory conditions to cardiovascular complications that challenge management and resource allocation. Identification of early predictive biomarkers that are easy to detect is a priority to optimize medical care and resources. ACE2 and TMPRSS2 have received special attention due to their role in viral infectivity but also due to their physiological anti-inflammatory activities. CD15 and CD45 are key proteins in the immune response also associated with SARS-CoV-2 response. This study focused on analyzing the expression of ACE2, TMPRSS2, CD15, and CD45 in a cohort of 216 patients (111 mild and 105 severe disease) to ascertain their potential as biomarkers for predicting disease severity. We aimed to assess the correlation between these markers and the severity of symptoms, utilizing qPCR and flow cytometry. We used mixed-effects linear regression models and Receiver Operating Characteristic (ROC) curves to test the performance of the biomarkers in the prediction of the severity of the disease. Significant lower surface expression of CD15 and ACE2 was observed in severe cases in addition to a strong association between aging and the severity of the disease. By integrating these findings, we developed a predictive model achieving 92.9% specificity and 79.3% sensitivity (AUC = 0.91; 95% CI: 0.87–0.96). The study concludes that our combined biomarker model could significantly enhance the management of COVID-19 by enabling early identification of patients at risk for severe outcomes, thus improving treatment strategies and resource distribution.

The androgenic signalling pathway is essential for carcinogenesis and tumour development in prostate cancer (PC). The importance of that pathway makes it the main target of treatments against PC, among which androgen deprivation therapy (ADT) stands out. The heterogeneity of the response against the same treatment shows the importance of the search for molecular biomarkers, which enable the prediction of the response to the therapy in each case. This work focuses on the characterization of the response to treatment in several patients of PC through the analysis of different genetic variants (rs10877012 (CYP27B1); rs3768490 (GSTM5); rs1004446 (IGF2)). The statistical analysis revealed a certain tendency to resistance in A/G genotype carriers in rs1004446 (IGF2). Furthermore, a significant statistical relation between aggressive phenotypes was confirmed in single nucleotide polymorphism (SNP) rs10877012 (CYP27B1, p = 0.013).

Information about the paper titled "APPLICATION OF DIGITAL BOARDS AS AN INNOVATION FOR TEACHING IN BIOCHEMISTRY AND MOLECULAR BIOLOGY" at IATED Digital Library

Information about the paper titled "USE OF VIRTUAL TOOLS IN THE DISSEMINATION OF DNA AND ITS APPLICATIONS" at IATED Digital Library

Prostate cancer (PC) is one of the most prevalent tumours in the world, however, the hereditary (Hereditary PC; HPC) form is a rare pathology, that does not exceed 6%. Despite its very low incidence, a family history of PC in a first-degree relative multiplies the risk of suffering from PC by approximately two-fold. Therefore, the search for genetic variables associated with the detection, monitoring and treatment of the condition is paramount. In this study, we conduct deep screening of exomes by next-generation sequencing (NGS) analysis in search of new biomarkers. We performed this analysis in a family with a high incidence of PC. Our data reveal that variants in some genes, such as HIBCH and DPP4, are present in all HPC patients. Moreover, high-risk patients have unique additional variants, such as FANK1, TUBA3FP and ALDH3B2. These results provide a new set of promising biomarkers in HCP.