Unveiling the World of Circulating and Exosomal microRNAs in Renal Cell Carcinoma

Biomarkers for Pre-Treatment Risk Stratification of Prostate Cancer Patients: A Systematic Review

BACKGROUND

Prostate cancer (PCa) is one of the most frequently occurring malignancies. Although most cases are not life-threatening, approximately 20% endure an unfavorable outcome. PSA-based screening reduced mortality but at the cost of an increased overdiagnosis/overtreatment of low-risk (lrPCa) and favorable intermediate-risk (firPCa) PCa. PCa risk-groups are usually identified based on serum Prostate-Specific Antigen (PSA), the Gleason score, and clinical T stage, which have consistent although variable specificity or subjectivity. Thus, more effective and specific tools for risk assessment are needed, ideally making use of minimally invasive methods such as liquid biopsies. In this systematic review we assessed the clinical potential and analytical performance of liquid biopsy-based biomarkers for pre-treatment risk stratification of PCa patients.

METHODS

Studies that assessed PCa pre-treatment risk were retrieved from PubMed, Scopus, and MedLine. PCa risk biomarkers were analyzed, and the studies' quality was assessed using the QUADAS-2 tool.

RESULTS

The final analysis comprised 24 full-text articles, in which case-control studies predominated, mostly reporting urine-based biomarkers (54.2%) and biomarker quantification by qPCR (41.7%). Categorization into risk groups was heterogeneous, predominantly making use of the Gleason score.

CONCLUSION

This systematic review unveils the substantial clinical promise of using circulating biomarkers in assessing the risk for prostate cancer patients. However, the standardization of groups, categories, and biomarker validation are mandatory before this technique can be implemented. Circulating biomarkers might represent a viable alternative to currently available tools, obviating the need for tissue biopsies, and allowing for faster and more cost-effective testing, with superior analytical performance, specificity, and reproducibility.

OncoUroMiR: Circulating miRNAs for Detection and Discrimination of the Main Urological Cancers Using a ddPCR-Based Approach

The three most common genitourinary malignancies (prostate/kidney/bladder cancers) constitute a substantial proportion of all cancer cases, mainly in the elderly population. Early detection is key to maximizing the patients' survival, but the lack of highly accurate biomarkers that might be used through non-/minimally invasive methods has impaired progress in this domain. Herein, we sought to develop a minimally invasive test to detect and discriminate among those urological cancers based on miRNAs assessment through ddPCR. Plasma samples from 268 patients with renal cell (RCC; n = 119), bladder (BlCa; n = 73), and prostate (PCa; n = 76) carcinomas (UroCancer group), and 74 healthy donors were selected. Hsa-miR-126-3p, hsa-miR-141-3p, hsa-miR-153-5p, hsa-miR-155-5p, hsa-miR-182-5p, hsa-miR-205-5p, and hsa-miR-375-3p levels were assessed. UroCancer cases displayed significantly different circulating hsa-miR-182-5p/hsa-miR-375-3p levels compared to healthy donors. Importantly, the hsa-miR-155-5p/hsa-miR-375-3p panel detected RCC with a high specificity (80.54%) and accuracy (66.04%). Furthermore, the hsa-miR-126-3p/hsa-miR-375-3p panel identified BlCa with a 94.87% specificity and 76.45% NPV whereas higher hsa-miR-126-3p levels were found in PCa patients. We concluded that plasma-derived miRNAs can identify and discriminate among the main genitourinary cancers, with high analytical performance. Although validation in a larger cohort is mandatory, these findings demonstrate that circulating miRNA assessment by ddPCR might provide a new approach for early detection and risk stratification of the most common urological cancers.

Extracellular Vesicles as Potential Bladder Cancer Biomarkers: Take It or Leave It?

Bladder cancer (BC) is the 10th most frequently diagnosed cancer worldwide. Although urine cytology and cystoscopy are current standards for BC diagnosis, both have limited sensitivity to detect low-grade and small tumors. Moreover, effective prognostic biomarkers are lacking. Extracellular vesicles (EVs) are lipidic particles that contain nucleic acids, proteins, and metabolites, which are released by cells into the extracellular space, being crucial effectors in intercellular communication. These particles have emerged as potential tools carrying biomarkers for either diagnosis or prognosis in liquid biopsies namely urine, plasma, and serum. Herein, we review the potential of liquid biopsies EVs’ cargo as BC diagnosis and prognosis biomarkers. Additionally, we address the emerging advantages and downsides of using EVs within this framework.

Importance and implications of exosomes in nephrology and urology

Exosomes are extracellular vesicles that are formed by two invaginations of the plasma membrane and can be released by all eukaryotic cells. Because of their bioactive contents, including nucleic acids and proteins, exosomes can activate a variety of functions in their recipient cells. Due to the plethora of physiological and pathophysiological functions, exosomes have received a lot of attention from researchers over the past few years. However, there is still no consensus regarding isolation and characterization protocols of exosomes and their subtypes. This heterogeneity poses a lot of methodical challenges but also offers new clinical opportunities simultaneously. So far, exosome-based research is still mostly limited to preclinical experiments and early-stage clinical trials since the translation of experimental findings remains difficult. Exosomes could potentially play an important role as future diagnostic and prognostic agents and might also be part of the development of new treatment strategies. Therefore, they have previously been investigated in a variety of nephrological and urological conditions such as acute kidney injury or prostate cancer.

A Novel, Simple, and Low-Cost Approach for Machine Learning Screening of Kidney Cancer: An Eight-Indicator Blood Test Panel with Predictive Value for Early Diagnosis

Clear cell renal cell carcinoma (ccRCC) accounts for more than 90% of all renal cancers. The five-year survival rate of early-stage (TNM 1) ccRCC reaches 96%, while the advanced-stage (TNM 4) is only 23%. Therefore, early screening of patients with renal cancer is essential for the treatment of renal cancer and the long-term survival of patients. In this study, blood samples of patients were collected and a pre-defined set of blood indicators were measured. A random forest (RF) model was established to predict based on each indicator in the blood, and was trained with all relevant indicators for comprehensive predictions. In our study, we found that there was a high statistical significance (p < 0.001) for all indicators of healthy individuals and early cancer patients, except for uric acid (UA). At the same time, ccRCC also presented great differences in most blood indicators between males and females. In addition, patients with ccRCC had a higher probability of developing a low ratio of albumin (ALB) to globulin (GLB) (AGR < 1.2). Eight key indicators were used to classify and predict renal cell carcinoma. The area under the receiver operating characteristic (ROC) curve (AUC) of the eight-indicator model was as high as 0.932, the sensitivity was 88.2%, and the specificity was 86.3%, which are acceptable in many applications, thus realising early screening for renal cancer by blood indicators in a simple blood-draw physical examination. Furthermore, the composite indicator prediction method described in our study can be applied to other clinical conditions or diseases, where multiple blood indicators may be key to enhancing the diagnostic potential of screening strategies.

Biomarkers of disease recurrence in stage I testicular germ cell tumours

Stage I testicular cancer is a disease restricted to the testicle. After orchiectomy, patients are considered to be without disease; however, the tumour is prone to relapse in ~4-50% of patients. Current predictive markers of relapse, which are tumour size and invasion to rete testis (in seminoma) or lymphovascular invasion (in non-seminoma), have limited clinical utility and are unable to correctly predict relapse in a substantial proportion of patients. Adjuvant therapeutic strategies based on available biomarkers can lead to overtreatment of 50-85% of patients. Discovery and implementation of novel biomarkers into treatment decision making will help to reduce the burden of adjuvant treatments and improve patient selection for adjuvant therapy.

LiKidMiRs: A ddPCR-Based Panel of 4 Circulating miRNAs for Detection of Renal Cell Carcinoma

Simple Summary

Early detection of renal cell carcinoma (RCC) significantly increases the likelihood of curative treatment, avoiding the need of adjuvant therapies, associated side effects and comorbidities. Thus, we aimed to discover circulating microRNAs that might aid in early, minimally invasive, RCC detection/diagnosis.

Abstract

Background: Decreased renal cell cancer-related mortality is an important societal goal, embodied by efforts to develop effective biomarkers enabling early detection and increasing the likelihood of curative treatment. Herein, we sought to develop a new biomarker for early and minimally invasive detection of renal cell carcinoma (RCC) based on a microRNA panel assessed by ddPCR. Methods: Plasma samples from patients with RCC (n = 124) or oncocytomas (n = 15), and 64 healthy donors, were selected. Hsa-miR-21-5p, hsa-miR-126-3p, hsa-miR-155-5p and hsa-miR-200b-3p levels were evaluated using a ddPCR protocol. Results: RCC patients disclosed significantly higher circulating levels of hsa-miR-155-5p compared to healthy donors, whereas the opposite was observed for hsa-miR-21-5p levels. Furthermore, hsa-miR-21-5p and hsa-miR-155-5p panels detected RCC with high sensitivity (82.66%) and accuracy (71.89%). The hsa-miR-126-3p/hsa-miR-200b-3p panel identified the most common RCC subtype (clear cell, ccRCC) with 74.78% sensitivity. Conclusion: Variable combinations of plasma miR levels assessed by ddPCR enable accurate detection of RCC in general, and of ccRCC. These findings, if confirmed in larger studies, provide evidence for a novel ancillary tool which might aid in early detection of RCC.

SERS Liquid Biopsy Profiling of Serum for the Diagnosis of Kidney Cancer

Renal cancer (RC) represents 3% of all cancers, with a 2% annual increase in incidence worldwide, opening the discussion about the need for screening. However, no established screening tool currently exists for RC. To tackle this issue, we assessed surface-enhanced Raman scattering (SERS) profiling of serum as a liquid biopsy strategy to detect renal cell carcinoma (RCC), the most prevalent histologic subtype of RC. Thus, serum samples were collected from 23 patients with RCC and 27 controls (CTRL) presenting with a benign urological pathology such as lithiasis or benign prostatic hypertrophy. SERS profiling of deproteinized serum yielded SERS band spectra attributed mainly to purine metabolites, which exhibited higher intensities in the RCC group, and Raman bands of carotenoids, which exhibited lower intensities in the RCC group. Principal component analysis (PCA) of the SERS spectra showed a tendency for the unsupervised clustering of the two groups. Next, three machine learning algorithms (random forest, kNN, naïve Bayes) were implemented as supervised classification algorithms for achieving discrimination between the RCC and CTRL groups, yielding an AUC of 0.78 for random forest, 0.78 for kNN, and 0.76 for naïve Bayes (average AUC 0.77 ± 0.01). The present study highlights the potential of SERS liquid biopsy as a diagnostic and screening strategy for RCC. Further studies involving large cohorts and other urologic malignancies as controls are needed to validate the proposed SERS approach.