Liquid biopsy: possibilities and limitations in uro-oncology

In the recent years, research in oncologyhas focused on liquid biopsies, which rely on thedetection of cancer-derived components, includingcirculating tumor cells (CTCs), circulating tumor DNA(ctDNA), circulating free RNA (cfRNA), and extracellularvesicles (EVs), in the biofluids of patients, providinggenomic, epigenetic and transcriptomic, informationabout tumors and metastatic sites. In this reviewwe collect current evidence regarding the potentialof liquid biopsies for the diagnosis and follow-up ofuro-oncology patients, as well as the advantages andlimitations of these approaches. Although promising,the way in which this methodology must be incorporatedinto the clinical routine needs to be still definedboth at the pre-analytical and analytical level beforetheir clinical utility is demonstrated.

Optimization of PSA and its variants and other biomarkers for the follow-up of low-risk prostate cancer in active surveillance

INTRODUCTION AND OBJECTIVES

Active surveillance (AS) is currently a therapeuticstrategy recommended by all Clinical Guidelines forthe initial management of very low-risk, low-risk, andsome intermediate-risk prostate cancer (PCa). However,a high percentage of cases will present the need for active treatment and a quarter of them will presentunfavorable anatomopathological characteristics.

METHODS

review of the biomarkers' literature oncircumscribed to the inclusion and follow-up of patientsin AS.

RESULTS

PSA and its variants remain the most widelyused and most cost-effective biomarker in AS. Inparticular, the use of PSA density based on the prostatevolume detected by mpMRI has gained much weight.Different multipanel biomarkers in blood and urineare commercially available to predict progressionto PCa ≥3 + 4 (GG2), but they have not clearly beenprospectively tested in AS cohorts. Tissue biomarkersanalyze gene panels that offer predictive informationindependent of classical clinicopathological variablesand may play a role in controversial indications for AS.Lastly, risk calculators are cost-effective and validatedfor their care use in AS and are probably underused.

CONCLUSIONS

Although there is no specific biomarkerfor the optimization of AS, its rational use togetherwith mpMRI may in the future optimize the inclusionof patients in AS and follow-up differentiatedby risk groups.

Active Surveillance in Prostate Cancer: Role of Available Biomarkers in Daily Practice

Prostate cancer (PCa) is the most commonly diagnosed cancer in men. The diagnosis is currently based on PSA levels, which are associated with overdiagnosis and overtreatment. Moreover, most PCas are localized tumours; hence, many patients with low-/very low-risk PCa could benefit from active surveillance (AS) programs instead of more aggressive, active treatments. Heterogeneity within inclusion criteria and follow-up strategies are the main controversial issues that AS presently faces. Many biomarkers are currently under investigation in this setting; however, none has yet demonstrated enough diagnostic ability as an independent predictor of pathological or clinical progression. This work aims to review the currently available literature on tissue, blood and urine biomarkers validated in clinical practice for the management of AS patients.

A Tetra-Panel of Serum Circulating miRNAs for the Diagnosis of the Four Most Prevalent Tumor Types

The purpose of this study is to clinically validate a series of circulating miRNAs that distinguish between the 4 most prevalent tumor types (lung cancer (LC); breast cancer (BC); colorectal cancer (CRC); and prostate cancer (PCa)) and healthy donors (HDs). A total of 18 miRNAs and 3 housekeeping miRNA genes were evaluated by qRT-PCR on RNA extracted from serum of cancer patients, 44 LC, 45 BC, 27 CRC, and 40 PCa, and on 45 HDs. The cancer detection performance of the miRNA expression levels was evaluated by studying the area under the curve (AUC) of receiver operating characteristic (ROC) curves at univariate and multivariate levels. miR-21 was significantly overexpressed in all cancer types compared with HDs, with accuracy of 67.5% (p = 0.001) for all 4 tumor types and of 80.8% (p < 0.0001) when PCa cases were removed from the analysis. For each tumor type, a panel of miRNAs was defined that provided cancer-detection accuracies of 91%, 94%, 89%, and 77%, respectively. In conclusion, we have described a series of circulating miRNAs that define different tumor types with a very high diagnostic performance. These panels of miRNAs would constitute the basis of different approaches of cancer-detection systems for which clinical utility should be validated in prospective cohorts.