Bladder cancer (BC) is characterized by high incidence and recurrence rates together with genomic instability and elevated mutation degree. Currently, cystoscopy combined with cytology is routinely used for diagnosis, prognosis and disease surveillance. Such an approach is often associated with several side effects, discomfort for the patient and high economic burden. Thus, there is an essential demand of non-invasive, sensitive, fast and inexpensive biomarkers for clinical management of BC patients. In this context, liquid biopsy represents a very promising tool that has been widely investigated over the last decade. Liquid biopsy will likely be at the basis of patient selection for precision medicine, both in terms of treatment choice and real-time monitoring of therapeutic effects. Several different urinary biomarkers have been proposed for liquid biopsy in BC, including DNA methylation and mutations, protein-based assays, non-coding RNAs and mRNA signatures. In this review, we summarized the state of the art on different available tests concerning their potential clinical applications for BC detection, prognosis, surveillance and response to therapy.

Widespread use of PSA as the standard tool for prostate cancer (PCa) diagnosis led to a high rate of overdiagnosis and overtreatment. In this study, we evaluated the performance of the prostate health index (PHI) and multiparametric magnetic resonance imaging (mpMRI) for the prediction of positive biopsy and of high-grade PCa at radical prostatectomy (RP). To this end, we prospectively enrolled 196 biopsy-naïve patients who underwent mpMRI. A subgroup of 116 subjects with biopsy-proven PCa underwent surgery. We found that PHI significantly outperformed both PI-RADS score (difference in AUC: 0.14; p < 0.001) and PHI density (difference in AUC: 0.08; p = 0.002) in the ability to predict positive biopsy with a cut-off value of 42.7 as the best threshold. Conversely, comparing the performance in the identification of clinically significant prostate cancer (csPCa) at RP, we found that PHI ≥ 61.68 and PI-RADS score ≥ 4 were able to identify csPCa (Gleason score ≥ 7 (3 + 4)) both alone and added to a base model including age, PSA, fPSA-to-tPSA ratio and prostate volume. In conclusion, PHI had a better ability than PI-RADS score to predict positive biopsy, whereas it had a comparable performance in the identification of pathological csPCa.

Objective: The objective of this research is to demonstrate the release of SARS-CoV-2 Spike (S) antibodies in human milk samples obtained by patients who have been vaccinated with mRNABNT162b2 vaccine. Methods: Milk and serum samples were collected in 10 volunteers 20 days after the first dose and 7 seven days after the second dose of the mRNABNT162b2 vaccine. Anti-SARS-CoV-2 S antibodies were measured by the Elecsys^® Anti-SARS-CoV-2 S ECLIA assay (Roche Diagnostics AG, Rotkreuz, Switzerland), a quantitative electrochemiluminescence immunometric method. Results: At first sample, anti-SARS-CoV-2 S antibodies were detected in all serum samples (103.9 ± 54.9 U/mL) and only in two (40%) milk samples with a low concentration (1.2 ± 0.3 U/mL). At the second sample, collected 7 days after the second dose, anti-SARS-CoV-2 S antibodies were detected in all serum samples (3875.7 ± 3504.6 UI/mL) and in all milk samples (41.5 ± 47.5 UI/mL). No correlation was found between the level of serum and milk antibodies; the milk antibodies/serum antibodies ratio was on average 2% (range: 0.2–8.4%). Conclusion: We demonstrated a release of anti-SARS-CoV-2 S antibodies in the breast milk of women vaccinated with mRNABNT162b2. Vaccinating breastfeeding women could be a strategy to protect their infants from COVID-19 infection.

Periprostatic adipose tissue (PPAT) has emerged as a key player in the prostate cancer (PCa) microenvironment. In this study, we evaluated the ability of PPAT to promote PCa cell migration, as well as the molecular mechanisms involved. Methods: We collected conditioned mediums from in vitro differentiated adipocytes isolated from PPAT taken from PCa patients during radical prostatectomy. Migration was studied by scratch assay. Results: Culture with CM of human PPAT (AdipoCM) promotes migration in two different human androgen-independent (AI) PCa cell lines (DU145 and PC3) and upregulated the expression of CTGF. SB431542, a well-known TGFβ receptor inhibitor, counteracts the increased migration observed in presence of AdipoCM and decreased CTGF expression, suggesting that a paracrine secretion of TGFβ by PPAT affects motility of PCa cells. Conclusions: Collectively, our study showed that factors secreted by PPAT enhanced migration through CTGF upregulation in AI PCa cell lines. These findings reveal the potential of novel therapeutic strategies targeting adipocyte-released factors and TGFβ/CTGF axis to fight advanced PCa dissemination.

After skin cancer, prostate cancer (PC) is the most common cancer among men. The gold standard for PC diagnosis is based on the PSA (prostate-specific antigen) test. Based on this preliminary screening, the physician decides whether to proceed with further tests, typically prostate biopsy, to confirm cancer and evaluate its aggressiveness. Nevertheless, the specificity of the PSA test is suboptimal and, as a result, about 75% of men who undergo a prostate biopsy do not have cancer even if they have elevated PSA levels. Overdiagnosis leads to unnecessary overtreatment of prostate cancer with undesirable side effects, such as incontinence, erectile dysfunction, infections, and pain. Here, we used artificial neuronal networks to develop models that can diagnose PC efficiently. The model receives as an input a panel of 4 clinical variables (total PSA, free PSA, p2PSA, and PSA density) plus age. The output of the model is an estimate of the Gleason score of the patient. After training on a dataset of 190 samples and optimization of the variables, the model achieved values of sensitivity as high as 86% and 89% specificity. The efficiency of the method can be improved even further by training the model on larger datasets.

Background: The erythrocyte sedimentation rate (ESR) is a routine and aspecific test that is still widely used. The reference-manual method for ESR determination is the Westergren method. The VES-MATIC 5 is a novel, fully automated, and closed system based on a modified Westergren method. This study conceived the aim of comparing two ESR analytical analysers, Test 1 and the VES-MATIC 5, with the reference method in routine practice. Methods: This study included 264 randomly analysed samples. A comparison between the two methods and Westergren was performed, and they were evaluated for inter-run and intra-run precision. In addition, we investigated possible interferences and different sensitivities to conventional analytes. Results: The comparison of methods by Passing–Bablok analysis provided a good agreement for both systems, with a better correlation for VES-MATIC 5 (p = 0.96) than Test 1 (p = 0.93), and sensitivity studies did not show any significant influence. Conclusions: The VES-MATIC 5 analyser demonstrated excellent comparability with the reference method, and it had better performance than Test 1. It can be employed in routine practice, bringing advantages such as a reduction in the probability of human error compared to the manual method, as well as an increase in operator safety and environmental protection.