Epitranscriptomics has gained ground in recent years, especially after the advent of techniques for accurately studying these mechanisms. Among all modifications occurring in RNA molecules, N6-methyladenosine (m6A) is the most frequent, especially among mRNAs. m6A has been demonstrated to play important roles in many physiological processes and several disease states, including various cancer models (from solid to liquid tumors). Tumor cells’ epitranscriptome is indeed disrupted in a way to promote cancer-prone features, by means of up/downregulating m6A-related players: the so-called writers, readers and erasers. These proteins modulate m6A establishment, removal and determine mRNAs fate, acting in a context-dependent manner, so that a single player may act as an oncogenic signal in one tumor model (methyltransferase like 3 (METTL3) in lung cancer) and as a tumor suppressor in another context (METTL3 in glioblastoma). Despite recent advances, however, little attention has been directed towards urological cancer. By means of a thorough analysis of the publicly available TCGA (The Cancer Genome Atlas) database, we disclosed the most relevant players in four major urogenital neoplasms—kidney, bladder, prostate and testicular cancer—for prognostic, subtype discrimination and survival purposes. In all tumor models assessed, the most promising player was shown to be Vir like m6A methyltransferase associated (VIRMA), which could constitute a potential target for personalized therapies.
Background The lack of sensitive and specific biomarkers for the early detection of prostate cancer (PCa) is a major hurdle to improve patient management. Methods A metabolomics approach based on GC-MS was used to investigate the performance of volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine as potential markers for PCa detection. Results Results showed that PCa patients (n = 40) can be differentiated from cancer-free subjects (n = 42) based on their urinary volatile profile in both VOCs and VCCs models, unveiling significant differences in the levels of several metabolites. The models constructed were further validated using an external validation set (n = 18 PCa and n = 18 controls) to evaluate sensitivity, specificity and accuracy of the urinary volatile profile to discriminate PCa from controls. The VOCs model disclosed 78% sensitivity, 94% specificity and 86% accuracy, whereas the VCCs model achieved the same sensitivity, a specificity of 100% and an accuracy of 89%. Our findings unveil a panel of 6 volatile compounds significantly altered in PCa patients’ urine samples that was able to identify PCa, with a sensitivity of 89%, specificity of 83%, and accuracy of 86%. Conclusions It is disclosed a biomarker panel with potential to be used as a non-invasive diagnostic tool for PCa.
DNA methylation is an epigenetic modification that plays a pivotal role in regulating gene expression and, consequently, influences a wide variety of biological processes and diseases. The advances in next-generation sequencing technologies allow for genome-wide profiling of methyl marks both at a single-nucleotide and at a single-cell resolution. These profiling approaches vary in many aspects, such as DNA input, resolution, coverage, and bioinformatics analysis. Thus, the selection of the most feasible method according with the project’s purpose requires in-depth knowledge of those techniques. Currently, high-throughput sequencing techniques are intensively used in epigenomics profiling, which ultimately aims to find novel biomarkers for detection, diagnosis prognosis, and prediction of response to therapy, as well as to discover new targets for personalized treatments. Here, we present, in brief, a portrayal of next-generation sequencing methodologies’ evolution for profiling DNA methylation, highlighting its potential for translational medicine and presenting significant findings in several diseases.
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