Liquid Biopsies in Renal Cell Carcinoma-Recent Advances and Promising New Technologies for the Early Detection of Metastatic Disease

Non-coding transcriptome profiles in clear-cell renal cell carcinoma

Clear-cell renal cell carcinoma (ccRCC) is a common urological malignancy with an increasing incidence. The development of molecular biomarkers that can predict the response to treatment and guide personalized therapy selection would substantially improve patient outcomes. Dysregulation of non-coding RNA (ncRNA) has been shown to have a role in the pathogenesis of ccRCC. Thus, an increasing number of studies are being carried out with a focus on the identification of ncRNA biomarkers in ccRCC tissue samples and the connection of these markers with patients' prognosis, pathological stage and grade (including metastatic potential), and therapy outcome. RNA sequencing analysis led to the identification of several ncRNA biomarkers that are dysregulated in ccRCC and might have a role in ccRCC development. These ncRNAs have the potential to be prognostic and predictive biomarkers for ccRCC, with prospective applications in personalized treatment selection. Research on ncRNA biomarkers in ccRCC is advancing, but clinical implementation remains preliminary owing to challenges in validation, standardization and reproducibility. Comprehensive studies and integration of ncRNAs into clinical trials are essential to accelerate the clinical use of these biomarkers.

Metabolic signature biomarkers for predicting the recurrence of urological cancers

A significant number of patients diagnosed with localized urological cancers experience relapse and disease progression after surgery. Hence, molecular markers for patient risk stratification are needed to improve the current management guidelines. This article critically reviews for the first time, to our knowledge, the promise of metabolomics-based approaches to identify metabolic signatures as candidate prognostic biomarkers to predict recurrences at the time of surgery in prostate cancer (PCa), bladder cancer (BCa), and renal cell carcinoma (RCC). Dysregulations in the levels of several tumoral, circulating, and excreted metabolites have been reported in PCa patients experiencing recurrence within 1.5 to 8 years of follow-up. The combination of these metabolic biomarkers with clinical parameters (e.g., pathological T stage, Gleason score) has shown great potential to improve the predictive ability of PCa recurrence. In contrast, predictive biomarkers of recurrence in BCa and RCC have been poorly explored. Overall, this review highlights the great potential of metabolomics in discovering prognostic biomarkers for a more accurate patient risk stratification in urological cancers.

Exploring the Characteristics of Circulating Tumor DNA in Pt1a Clear Cell Renal Cell Carcinoma: A Pilot Study

Circulating tumor DNA (ctDNA) is a promising biomarker for clear cell renal cell carcinoma (ccRCC); however, its characteristics in small renal masses of ccRCC remain unclear. In this pilot study, we explored the characteristics of ctDNA in pT1a ccRCC. Plasma samples were collected preoperatively from 53 patients with pT1a ccRCC. The ctDNA of pT1a ccRCC was profiled using next-generation sequencing and compared with that of higher-stage ccRCC. The association of ctDNA in pT1a ccRCC with clinicopathological features was investigated. The positive relationship of mutations between ctDNA and matched tissues was evaluated. In pT1a ccRCC, the ctDNA detection rate, cell-free DNA concentration, and median variant allele frequency were 20.8%, 5.8 ng/mL, and 0.38%, respectively, which were significantly lower than those in metastatic ccRCC. The ctDNA gene proportions in pT1a samples differed from those in metastatic ccRCC samples. The relationships between ctDNA and tumor size, tumor grade, and patient age were not elucidated. The positive concordance between ctDNA and matched tissues was poor for pT1a ccRCC. Strategies are needed to increase sensitivity while eliminating noise caused by clonal hematopoiesis to increase the clinical utility of ctDNA analysis in small renal masses of ccRCC.

Chasing the Role of miRNAs in RCC: From Free-Circulating to Extracellular-Vesicle-Derived Biomarkers

Renal cell carcinoma (RCC) is the second most common cancer of the urinary system. The current therapeutic strategies are based on partial or total nephrectomy and/or targeted therapies based on immune checkpoint inhibitors to which patients are often refractory. Preventive and screening strategies do not exist and the few available biomarkers for RCC are characterized by a lack of sensitivity, outlining the need for novel noninvasive and sensitive biomarkers for early diagnosis and better disease monitoring. Blood liquid biopsy (LB) is a non- or minimally invasive procedure for a more representative view of tumor heterogeneity than a tissue biopsy, potentially allowing the real-time monitoring of cancer evolution. Growing interest is focused on the extracellular vesicles (EVs) secreted by either healthy or tumoral cells and recovered in a variety of biological matrices, blood included. EVs are involved in cell-to-cell crosstalk transferring their mRNAs, microRNAs (miRNAs), and protein content. In particular, transferred miRNAs may regulate tumorigenesis and proliferation also impacting resistance to apoptosis, thus representing potential useful biomarkers. Here, we present the latest efforts in the identification of circulating miRNAs in blood samples, focusing on the potential use of EV-derived miRNAs as RCC diagnostic and prognostic markers.

Adjuvant Therapy for High-Risk Localized Renal Cell Carcinoma: Current Landscape and Future Direction

Locally and regionally advanced renal cell carcinoma (RCC) can recur at high rates even after visually complete resection of primary disease. Both targeted therapies and immunotherapies represent potential agents that might help reduce recurrence of RCC in these patients. This paper reviews the current body of evidence defining their potential impact and examines the large Phase III randomized clinical trials that have been performed to assess the safety and efficacy of these systemic therapies in the adjuvant setting. Given that the findings from these trials have been predominantly negative, this paper also explores the role of other potential adjuvant agents, including single and combination agent targeted therapies and immunotherapies, whose use is currently limited to metastatic RCC. Finally, the use of radiation therapy and the use of advanced imaging modalities in RCC are also considered.

Precision Medicine: An Optimal Approach to Patient Care in Renal Cell Carcinoma

Renal cell cancer (RCC) is a heterogeneous tumor that shows both intra- and inter-heterogeneity. Heterogeneity is displayed not only in different patients but also among RCC cells in the same tumor, which makes treatment difficult because of varying degrees of responses generated in RCC heterogeneous tumor cells even with targeted treatment. In that context, precision medicine (PM), in terms of individualized treatment catered for a specific patient or groups of patients, can shift the paradigm of treatment in the clinical management of RCC. Recent progress in the biochemical, molecular, and histological characteristics of RCC has thrown light on many deregulated pathways involved in the pathogenesis of RCC. As PM-based therapies are rapidly evolving and few are already in current clinical practice in oncology, one can expect that PM will expand its way toward the robust treatment of patients with RCC. This article provides a comprehensive background on recent strategies and breakthroughs of PM in oncology and provides an overview of the potential applicability of PM in RCC. The article also highlights the drawbacks of PM and provides a holistic approach that goes beyond the involvement of clinicians and encompasses appropriate legislative and administrative care imparted by the healthcare system and insurance providers. It is anticipated that combined efforts from all sectors involved will make PM accessible to RCC and other patients with cancer, making a tremendous positive leap on individualized treatment strategies. This will subsequently enhance the quality of life of patients.

Tumor-Educated Platelets as a Promising Biomarker for Blood-Based Detection of Renal Cell Carcinoma

Purpose

Tumor-educated platelets (TEPs) are a promising liquid biopsy in many cancers. However, their role in renal cell carcinoma (RCC) is unknown. Thus, this study explored the diagnostic value of TEPs in RCC patients.

Methods

Platelets were prospectively collected from 24 RCC patients and 25 controls. RNA-seq was performed to identify the differentially expressed genes (DEGs) between RCC patients and controls. Besides, RNA-seq data of pan-cancer TEPs were downloaded and randomly divided into training and validation sets. A pan-cancer TEP model was developed in the training set using the support vector machine (SVM) and validated in the validation set and our RCC dataset. Finally, an RCC-based TEP model was developed and optimized through the SVM algorithms and recursive feature elimination (RFE) method.

Result

Two hundred three DEGs, 64 (31.5%) upregulated and 139 (68.5%) downregulated, were detected in the platelets of RCC patients compared with controls. The pan-cancer TEP model had a high accuracy in detecting cancer in the internal validation (training set, accuracy 98.8%, AUC: 0.999; validation set, accuracy 95.4%, AUC: 0.972; different tumor subtypes, accuracy 86.6%–96.1%, AUC: 0.952–1.000). However, the pan-cancer TEP model in the external validation had a scarce diagnostic value in RCC patients (accuracy 48.7%, AUC: 0.615). Therefore, to develop the RCC-based TEP model, the gene biomarkers mostly contributing to the model were selected using the RFE method. The RCC-based TEP model containing 68 gene biomarkers reached a diagnostic accuracy of 100% (AUC: 1.000) in the training set, 88.9% (AUC: 0.963) in the validation set, and 95.9% (AUC: 0.988) in the overall cohort.

Conclusion

TEPs could function as a minimally invasive blood biomarker in the detection of RCC.

Validation in an Independent Cohort of MiR-122, MiR-1271, and MiR-15b as Urinary Biomarkers for the Potential Early Diagnosis of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma, and the absence of symptoms in the early stages makes metastasis more likely and reduces survival. To aid in the early diagnosis of ccRCC, we recently developed a method based on urinary miR-122-5p, miR-1271-5p, and miR-15b-5p levels and three controls. The study here presented aimed to validate the previously published method through its application on an independent cohort. The expression of miRNAs in urine specimens from 28 ccRCC patients and 28 healthy subjects (HSs) of the same sex and age was evaluated by RT-qPCR. Statistical analyses were performed, including the preparation of receiver operating characteristic (ROC) curves. The mean ccRCC diameter in ccRCC patients was 4.2 ± 2.4 mm. Urinary miRNA levels were higher in patients than in HSs. The data were processed using the previously developed algorithm (7p-urinary score), and the area under the curve (AUC) of the algorithm's ROC curve was 0.81 (p-value = 0.0003), with a sensitivity of 96% and specificity of 65%. Therefore, the 7p-urinary score is a potential tool for the early diagnosis of ccRCC.

Advancements in the identification of EV derived mRNA biomarkers for liquid biopsy of clear cell renal cell carcinomas

OBJECTIVE

To propose EV-derived mRNA as a potential diagnostic biomarker detecting the presence of clear cell renal cell carcinoma (ccRCC). There is currently no kidney cancer specific screening or diagnostic technology. Therefore, one-third of kidney cancer diagnoses occur after the cancer has metastasized and is past curative measures MATERIALS AND METHODS: Urine, plasma, normal tumor adjacent tissue, and tumor tissue was collected from a limited population of ccRCC patients. Extracellular vesicle (EV) isolation was performed on each sample, followed by mRNA extraction from isolated EVs. NanoString nCounter technology was utilized to count the mRNA transcripts present in matched plasma, urine, tumor tissue, and normal tumor adjacent tissue samples.

RESULTS

770 mRNA transcripts related to gene's affecting cancer's progression and metastasis processes were evaluated. Four EV derived mRNA transcripts (ALOX5, RBL2, VEGFA, TLK2) were found specific to urine and tumor tissue samples.

CONCLUSION

Four candidate RCC-specific urine EV biomarkers were identified. However, due to the lack of a true negative control and urine collection techniques, further re-examination is necessary for validation. This study demonstrates the promise of defining disease-specific EV biomarkers in liquid biopsy patient samples.

Investigating Urinary Circular RNA Biomarkers for Improved Detection of Renal Cell Carcinoma

Renal cell carcinomas (RCC) are usually asymptomatic until late stages, posing several challenges for early detection of malignant disease. Non-invasive liquid biopsy biomarkers are emerging as an important diagnostic tool which could aid with routine screening of RCCs. Circular RNAs (circRNAs) are novel non-coding RNAs that play diverse roles in carcinogenesis. They are promising biomarkers due to their stability and ease of detection in small quantities from non-invasive sources such as urine. In this study, we analyzed the expression of various circRNAs that were previously identified in RCC tumors (circEGLN3, circABCB10, circSOD2 and circACAD11) in urinary sediment samples from non-neoplastic controls, patients with benign renal tumors, and clear cell RCC (ccRCC) patients. We observed significantly reduced levels of circEGLN3 and circSOD2 in urine from ccRCC patients compared to healthy controls. We also assessed the linear variant of EGLN3 and found differential expression between patients with benign tumors compared to ccRCC patients. These findings highlight the potential of circRNA markers as non-invasive diagnostic tools to detect malignant RCC.

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

Simple Summary

Liquid biopsies have emerged as a new tool for early diagnosis. In renal cell carcinoma, this need is also evident and may represent an improvement in disease management. Hence, in this review we discuss the most updated advances in the assessment of miRNAs in liquid biopsies. Moreover, we explore the potential of circulating or exosome miRNAs in renal cell carcinoma to overcome the tissue biopsies limitations.

Abstract

Renal cell carcinoma is the third most common urological cancer. Despite recent advances, late diagnosis and poor prognosis of advanced-stage disease remain a major problem, entailing the need for novel early diagnosis tools. Liquid biopsies represent a promising minimally invasive clinical tool, providing real-time feedback of tumor behavior and biological potential, addressing its clonal evolution and representing its heterogeneity. In particular, the study of circulating microRNAs and exosomal microRNAs in liquid biopsies experienced an exponential increase in recent years, considering the potential clinical utility and available technology that facilitates implementation. Herein, we provide a systematic review on the applicability of these biomarkers in the context of renal cell carcinoma. Issues such as additional benefit from extracting microRNAs transported in extracellular vesicles, use for subtyping and representation of different histological types, correlation with tumor burden, and prediction of patient outcome are also addressed. Despite the need for more conclusive research, available data indicate that exosomal microRNAs represent a robust minimally invasive biomarker for renal cell carcinoma. Thus, innovative research on microRNAs and novel detection techniques are likely to provide clinically relevant biomarkers, overcome current clinical challenges, and improve patient management.

Biomarkers for Renal Cell Carcinoma Recurrence: State of the Art

PURPOSE OF REVIEW

We aim to summarize the current state of art about the possible use of biomarkers for predicting renal cell carcinoma (RCC) recurrence after curative treatment. In addition, we aim to provide a snapshot about the clinical implication of biomarkers use for follow-up planification.

RECENT FINDINGS

A wide variety of biomarkers have been proposed. RCC biomarkers have been individuated in tumoral tissue, blood, and urine. A variety of molecules, including proteins, DNA, and RNA, warrant a good accuracy for RCC recurrence and progression prediction. Their use in prediction models might warrant a better patients' risk stratification. Future prognostic models will probably include a combination of classical features (tumor grade, stage, etc.) and novel biomarkers. Such models might allow a more accurate treatment and follow-up planification.

Urinary Extracellular Vesicles as Potential Biomarkers for Urologic Cancers: An Overview of Current Methods and Advances

Urologic cancers are a heterogeneous group of tumors, some of which have poor prognosis. This is partly due to the unavailability of specific and sensitive diagnostic techniques and monitoring tests, ideally non- or minimally invasive. Hence, liquid biopsies are promising tools that have been gaining significant attention over the last decade. Among the different classes of biomarkers that can be isolated from biofluids, urinary extracellular vesicles (uEVs) are a promising low-invasive source of biomarkers, with the potential to improve cancer diagnosis and disease management. Different techniques have been developed to isolate and characterize the cargo of these vesicles; however, no consensus has been reached, challenging the comparison among studies. This results in a vast number of studies portraying an extensive list of uEV-derived candidate biomarkers for urologic cancers, with the potential to improve clinical outcome; however, without significant validation. Herein, we review the current published research on miRNA and protein-derived uEV for prostate, bladder and kidney cancers, focusing on different uEV isolation methods, and its implications for biomarker studies.