Noncoding RNAs in Cancer Medicine

Several signalling proteins involved in cell growth and differentiation represent attractive candidate targets for cancer diagnosis and/or therapy since they can act as oncogenes. Because of their high specificity and low immunogeneicity, using artificial small noncoding RNA (ncRNAs) as therapeutics has recently become a highly promising and rapidly expanding field of interest. Indeed, ncRNAs may either interfere with RNA transcription, stability, translation or directly hamper the function of the targets by binding to their surface. The recent finding that the expression of several genes is under the control of small single-stranded regulatory RNAs, including miRNAs, makes these genes as appropriate targets for ncRNA gene silencing. Furthermore, another class of small ncRNA, aptamers, act as high-affinity ligands and potential antagonists of disease-associated proteins. We will review here the recent and innovative methods that have been developed and the possible applications of ncRNAs as inhibitors or tracers in cancer medicine

Differential SELEX in Human Glioma Cell Lines

The hope of success of therapeutic interventions largely relies on the possibility to distinguish between even close tumor types with high accuracy. Indeed, in the last ten years a major challenge to predict the responsiveness to a given therapeutic plan has been the identification of tumor specific signatures, with the aim to reduce the frequency of unwanted side effects on oncologic patients not responding to therapy. Here, we developed an in vitro evolution-based approach, named differential whole cell SELEX, to generate a panel of high affinity nucleic acid ligands for cell surface epitopes. The ligands, named aptamers, were obtained through the iterative evolution of a random pool of sequences using as target human U87MG glioma cells. The selection was designed so as to distinguish U87MG from the less malignant cell line T98G. We isolated molecules that generate unique binding patterns sufficient to unequivocally identify any of the tested human glioma cell lines analyzed and to distinguish high from low or non-tumorigenic cell lines. Five of such aptamers act as inhibitors of specific intracellular pathways thus indicating that the putative target might be important surface signaling molecules. Differential whole cell SELEX reveals an exciting strategy widely applicable to cancer cells that permits generation of highly specific ligands for cancer biomarkers

Neutralizing Aptamers from Whole-Cell SELEX Inhibit the RET Receptor Tyrosine Kinase

Targeting large transmembrane molecules, including receptor tyrosine kinases, is a major pharmacological challenge. Specific oligonucleotide ligands (aptamers) can be generated for a variety of targets through the iterative evolution of a random pool of sequences (SELEX). Nuclease-resistant aptamers that recognize the human receptor tyrosine kinase RET were obtained using RET-expressing cells as targets in a modified SELEX procedure. Remarkably, one of these aptamers blocked RET-dependent intracellular signaling pathways by interfering with receptor dimerization when the latter was induced by the physiological ligand or by an activating mutation. This strategy is generally applicable to transmembrane receptors and opens the way to targeting other members of this class of proteins that are of major biomedical importance

Assessing quality, reliability and accuracy of polycystic ovary syndrome‐related content on TikTok: A video‐based cross‐sectional analysis

Objective: Social networks share medical content with no peer-review or fact-checking. In the present study we aimed to assess the quality, reliability, and level of misinformation in TikTok videos about polycystic ovary syndrome (PCOS). Methods: We performed a cross-sectional analysis of TikTok videos retrieved using “PCOS” as the search term and analyzed using patient education materials assessment tool for audio-visual content (PEMAT A/V), modified DISCERN (mDISCERN), global quality scale (GQS), video information and quality index (VIQI) and misinformation assessment were employed. Results: A total of 180 videos were included. Most videos were partially accurate (containing 25%–50% of false information) or uninformative (more than 50%) (56.7% and 6.6%, respectively) with a significantly higher proportion of inaccurate or uninformative videos from PCOS-patients than healthcare professionals (14.4% vs. 0%; P < 0.001) as well as for partially accurate videos (78.4% vs. 37.5%; P < 0.001). PEMAT A/V scores for understandability and actionability were 50% (interquartile range [IQR]: 33%–58%) and 25% (IQR: 25%–50%), respectively with significantly higher understandability for healthcare professionals (54% [IQR: 42%–71%] vs. 33% [IQR: 25%–50%], P < 0.001). Median mDISCERN was 2 (IQR: 1–3) (low degree of reliability), with videos by healthcare professionals scoring significantly higher than those by patients (2 [IQR: 2–3] vs. 1 [IQR: 0–2]; P = 0.001). Intermediate-low overall video quality was reported in VIQI with median score of 12 (IQR: 10–15) and significantly lower scores for patients (9 [IQR: 5–12] vs. 13 [IQR: 12–17]; P < 0.001). Similarly, median GQS score was overall intermediate for degree of usefulness (median 3 [IQR: 2–4]), but patient-created videos were of significantly lower quality (median 2 [IQR: 2–3] vs. 4 [IQR: 3–4]; P < 0.001). Conclusion: PCOS-related videos on TikTok were mostly misinformative and of low quality and reliability. Healthcare professionals' videos were more informative with had higher quality compared to patient-created content. Identifying and addressing low-quality content is crucial for guiding future public health initiatives and improving the dissemination of trustworthy medical information on social networks