Clinical significance of circulating tumor cells detection in renal cell carcinoma with thrombus: A STROBE-compliant study

Diagnostic liquid biopsy biomarkers in renal cell cancer

The clinical presentation of renal cell cancer (RCC) is shifting towards incidental and early detection, creating new challenges in RCC diagnosis. Overtreatment might be reduced with the development of new diagnostic biomarkers to distinguish benign from malignant small renal masses (SRMs). Differently from tissue biopsies, liquid biopsies are obtained from a patient's blood or urine and, therefore, are minimally invasive and suitable for longitudinal monitoring. The most promising types of liquid biopsy biomarkers for RCC diagnosis are circulating tumour cells, extracellular vesicles (EVs) and cell-free DNA. Circulating tumour cell assays have the highest specificity, with low processing time and costs. However, the biological characteristics and low sensitivity limit the use of these markers in SRM diagnostics. Cell-free DNA might complement the diagnosis of high-volume RCC, but the potential for clinical application in SRMs is limited. EVs have the highest biological abundance and the highest sensitivity in identifying low-volume disease; moreover, the molecular characteristics of these markers make EVs suitable for multiple analytical applications. Thus, currently, EV assays have the greatest potential for diagnostic application in RCC (including identification of SRMs). All these liquid biomarkers have potential in clinical practice, pending validation studies. Biomarker implementation will be needed to also improve characterization of RCC subtypes. Last, diagnostic biomarkers might be extended to prognostic or predictive applications.

Current role of intraoperative cell salvage techniques in the management of renal tumors with level III and IV inferior vena cava thrombus extension

Background

En bloc removal of the kidney with tumor thrombus excision in a multidisciplinary team remains the standard treatment for renal cell carcinoma (RCC) with tumor thrombus extension. In order to minimize the hemodynamic impact of the surgical blood loss, intraoperative cell salvage (IOCS) techniques can decrease the need for allogeneic blood and prevent blood transfusion related complications.

Objective

In this article, we evaluated the safety of IOCS during radical nephrectomy with inferior vena cava thrombectomy under cardiopulmonary bypass with or without deep hypothermic circulatory arrest.

Design and method

In this retrospective comparative multicenter analysis, clinical characteristics of 27 consecutive patients who underwent surgery with or without IOCS between 2012 and 2022 in three referral care units were collected into a database. The need for an allogenic blood transfusion (ABT) was also recorded, defined as any transfusion that occurred either intraoperatively or during the hospital stay.

Results

The need for ABT in the cell saver arm was significantly smaller due to the reinfusion of rescued blood (p < 0.015). In multivariate analysis, no cell saver usage was an independent predictor for complications ⩾3 Clavien 3a [odds ratio (OR) 18.71, 95% CI 1.056-331.703, p = 0.046]. No usage of IOCS was an independent predictor for a lower risk of death (OR 0.277, 95% CI 0.062-0.825, p = 0.024). During follow-up, patients who received salvaged blood did not experience an increased risk for developing local recurrence or distant metastases.

Conclusion

Transfusion of autologous blood is safe and can be using during nephrectomy and thrombectomy for advanced RCC.

Circulating Tumor Cells as Biomarkers for Renal Cell Carcinoma: Ready for Prime Time?

Renal cell carcinoma (RCC) is among the 15 most common cancers worldwide, with rising incidence. In most cases, this is a silent disease until it reaches advance stages, demanding new effective biomarkers in all domains, from detection to post-therapy monitoring. Circulating tumor cells (CTC) have the potential to provide minimally invasive information to guide assessment of the disease's aggressiveness and therapeutic strategy, representing a special pool of neoplastic cells which bear metastatic potential. In some tumor models, CTCs' enumeration has been associated with prognosis, but there is a largely unexplored potential for clinical applicability encompassing screening, diagnosis, early detection of metastases, prognosis, response to therapy and monitoring. Nonetheless, lack of standardization and high cost hinder the translation into clinical practice. Thus, new methods for collection and analysis (genomic, proteomic, transcriptomic, epigenomic and metabolomic) are needed to ascertain the role of CTC as a RCC biomarker. Herein, we provide a critical overview of the most recently published data on the role and clinical potential of CTCs in RCC, addressing their biology and the molecular characterization of this remarkable set of tumor cells. Furthermore, we highlight the existing and emerging techniques for CTC enrichment and detection, exploring clinical applications in RCC. Notwithstanding the notable progress in recent years, the use of CTCs in a routine clinical scenario of RCC patients requires further research and technological development, enabling multimodal analysis to take advantage of the wealth of information they provide.

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.