A Systematic Review of Circulating Tumor Cells in Renal Cell Carcinoma

Document Type : Systematic Review/ Meta-analysis

Authors

1 Urology Research Center, Tehran University of Medical Sciences, Tehran, Iran

2 Monoclonal antibody Research Center, Avicenna Research Institute, ACECR, Tehran, Iran

Abstract

Introduction
Renal cell carcinoma (RCC) is one of the most usual kidney’s tumors. The improvement of non-invasive biomarkers will make it feasible to investigate whose have high risk of recurrence after radical or partial nephrectomy and will expand the valuation of tumor response to several treatment strategies. In this perspective, liquid biopsy suggests a talented perception for cancer diagnosis and monitoring, with several benefits versus traditional RCC diagnostic processes and can be taken into account of the present RCC diagnosis and controlling strategies.
Method
In this systematic review, we considered both CTCs count and molecular markers in RCC patient management. A systematic search on several databases like PubMed, Scopus, Embase, and Web of Science was directed which led to the final 24 studies considering the impact of CTCs on both diagnosis and prognosis of RCC.
Results
Several primary studies consider the CTCs quantitation as the tumor representing components that are based on immunomagnetic separation procedure. The magnetic cell sorting (MACS) technique, cell search, Tapered-slit filter (photosensitive polymer-based microfilter), CELLection™ Dynabeads® coated with the monoclonal antibodies, and ISET® -Isolation by Size of Tumor cells.  If CTCs wanted to be recruited for the prognosis of RCC and progression-free survival (PFS) it is better to check by gene expression profile through quantitative polymerase chain reaction analysis (Real Time-PCR) or in situ hybridization of CTC’s RNA molecules.  
Conclusions
CTCs detection as the main liquid biopsy component has an excessive clinical impact on cancer management. Nevertheless, usual methods have some limitations when directing for the recognition of circulating tumor cells (CTCs) with high efficiency and low cost. Some CTCs molecular markers and gene expression profiling of CTCs should be considered for RCC prognosis. 

Highlights

  • Liquid biopsy suggests a talented tool for cancer diagnosis and monitoring, with several benefits versus traditional RCC diagnostic processes.
  • From 1990 to 2019 there are 24 articles in which the CTCs are considered in RCC.
  • Usual methods have some limitations when directing for the recognition of circulating tumor cells (CTCs) with high efficiency and low cost.

Keywords

Main Subjects


 Introduction

Renal Cell Carcinoma (RCC) accounts for approximately 85-90% of kidney malignancies with the origination of both the epithelium of proximal convoluted tubules (clear cell RCC) and intercalated cells of the distal nephron (chromophobe RCC) (1). RCC has a high fatality rate among urological malignancies despite tremendous improvement in surgical procedures (2). The clinical manifestations of RCC are indeed confusing owing to the similarity to other conditions' symptoms, which leads to diagnosis in the late stages (3). Given the fact that there is a close reverse association between the time of diagnosis and the overall survival of patients with RCC more than having no appropriate and accurate existing diagnostic tests, some studies were conducted to explore new diagnostic methods (4).

The problems that arise from traditional methods provoke great interest to take into consideration liquid biopsy or as it is called "circulating tumor cells" (CTCs) as either the alternative substitution or augmentation of the use of a biopsy, due to lack of invasive behavior and great potential to surpass the current challenges (5, 6). Widening of indications has underpinned the high capacity of CTCs in the identification of tumors, which are prone to recurrence, or resistance, that can readily aid physicians to be aware of changes occurring during patients' treatment and follow-up course (7). So far, several molecules are of proven value to be measured in body liquids mainly ranging from CTCs to cell-free DNA, that have drawn quite an amount of attention to themselves (8).

In the last decade, with advances in measuring methods that can sense scarce numbers of CTCs, the vast majority of studies were conducted to investigate the feasibility of using CTCs in malignancies. The clinical implications of CTCs in urological malignancies have been an area of plenty of studies' interest. Likewise, the other urological malignancies, the CTCs' count in RCC association with the degree of tumor aggressiveness and a chance of tumor metastasis, has been observed (9).   

Generally, the RCCs' treatments are divided into three major categories: 1, anti-vascular endothelial growth factor (VEGF) agents, and 2, mammalian target of rapamycin (mTOR) agents 3, immunotherapeutic agents that can be administered solitary or in combination with anti-cytotoxic T-lymphocyte antigens. Hence, in view of both CTC's ability to select patients to receive specific treatment and RCC's targeting-based treatment approach, CTC can predict the best treatment for any individual (7, 10).

Even though expanding indications regarding the tremendous applicability of CTCs in RCC have been presented, the issue of suitable CTCs has yet to be addressed completely. Here we designed a systematic review of the studies focusing on CTC in RCC to clear the existing obstacles, which hindered us to bring them into routine practice.

 

Method

Search strategy

After submitting the protocol on the international prospective register of systematic reviews PROSPERO ID: 158222  the study was run and all relevant literature searches have done from four main databases: MEDLINE (PubMed), Scopus, EMBASE, and Web from January 1st, 1990, to the last April 2019 with words the key grouping of “Renal Cell Cancers”, “Adenocarcinoma Of Kidney”, “Nephroid Carcinomas”, “Renal Cell Carcinoma”, “Collecting Duct Carcinoma”, “Liquid Biopsies”, “Circulating Neoplastic Cells”, “Circulating Tumor Cells”, and “CTCs”. (Supplementary file 1). To diminish the selection bias, two colleagues (MN and SMKA) separately screened articles by checking titles, abstracts, and access to full-text articles for application. Some additional articles were retrieved from reference lists of selected articles. Grey literature was gotten from the system for information on the grey literature (SIGLE) database (opensigle.inist.fr) and healthcare management information consortium database. ( www.ovid.com/site/catalog/DataBase/99.jsp?top=2&mid=3&bottom=7&subsection=10)  Dissimilarities were solved by agreement and discussion with a third person (FKH). 

Eligibility criteria

All chosen documents were studied by two independent authors and agreeing to their title and abstract were considered as the included one or excluded one. The inclusion criteria were: 1) patients with pathologically confirmed renal cell carcinoma; 2) the control population was exactly specified; 3) all CTCs detection techniques such as cell search system, the NanoVelcro chips, ISET®-Isolation by the size of tumor cells, ScreenCell®, and real-time PCR were selected. Some articles were excluded because they; have no definition of case and controls, were the in vitro or in vivo studies and analyzed CTCs in animals or cell culture or not presented the detection method and indicated which molecular markers is targeted. 

Data extraction and quality assessment

The whole critical information over the CTCs studies in RCC was recorded in the excel file (data extraction file). Unfortunately, because of having no adequate quantity of homogenous studies related to RCC and CTCs, and having the wide methodological heterogeneity and noteworthy variations in study population characteristics doing the additional analysis which lead to the meta-analysis of the data was not applicable. Two main tools of quality assessment were retrieved including quality assessment of diagnostic accuracy assessment (QUADAS) and the Newcastle–Ottawa scale (NOS) assessment tools. All papers that scored 12/16 or more on the QUADOMICS tool together with 6/8 or more on NOS were reflected as the “high quality” ones, versus articles scoring 11/16, 5/8, or less were considered as the “low quality” ones.

 

Result

The selection algorithm and results of the study selection are presented in Figure 1. A total of 2185 documents were recovered after duplication removal, including 1318 articles from PubMed, 401 from Scopus, 300 from Web of Science, and 190 from Embase. All documents were screened two times by two reviewers through their title and abstract to find the related ones and reach 125 related documents (Figure 1). After deleting the review, in vivo/in vitro studies, and book or conference papers the final 24 articles were a candidate for data extraction and further considerations (Table 1).

 

Figure 1. Flow diagram of documents selection steps for the current systematic review based on PRISMA

 

 

 

Table 1. The information and data extracted from the final 24 related articles of CTCs detection, enumeration, and characterization in RCC

Title of Article First Author Year Country Sample size Mean age Metastatic CTC detection Method Molecular Marker of CTC

 Detection and enrichment of disseminated renal carcinoma cells from peripheral blood by immunomagnetic cell separation (11)

Udo Bilkenroth

2001

Germany

59

59 (32–80)

yes

MACS, CD45-conjugated microbeads

cytokeratin

 Detection of circulating tumor cells in  peripheral blood of patients with renal cell  carcinoma correlates with prognosis (12)

Karen Bluemke

2009

Germany

154

-

-

Immunomagnetic circulating tumor cell enrichment by depletion of CD45-positive lymphocytes followed by epithelial cell–specific cytokeratin immunocytochemistry

cytokeratin 8/18 (CK+)

 Detection of circulating tumor cells from renal carcinoma patients: experiences of a two-center study (13)

KAREN BLUMKE

2005

Germany

214

-

yes

Negative immunomagnetic cell enrichment of tumor cells via leukocyte-specific CD45 depletion

cytokeratin (CK)/ CK8/18 antibody

 Single-cell genetic analysis validates cytopathological identification of circulating cancer cells in patients with clear cell renal cell carcinoma (14)

Lucile Broncy

2018

France

30

68.5 (52–78)

yes

ISET® - Isolation by Size of Tumor cells

 

 Are morphological criteria sufficient for the identification of circulating tumor cells in renal cancer?(15)

Amin El-Heliebi

2013

Graz, Austria

30

68; (30–83)

yes

ScreenCell® filtration

carbonic anhydrase IX (CAIX) was used as a marker

 Circulating tumor cells and "suspicious objects" evaluated through CellSearch(R) in metastatic renal cell carcinoma (16)

Angela Gradilone

2011

Italy

25

60

yes

CELLection™ Dynabeads® coated with the monoclonal antibody BerEp4

cytokeratin (CK) 8, 18, 19 and CD44

 Detection of circulating tumour cells and their potential use as a biomarker for advanced renal cell carcinoma (17)

Tae Heon Kim

2019

Korea

34

61 (54-68)

yes

Tapered-slit filter (photosensitive polymer-based microfilter)

CD45-, cytokeratin [CK]+, and epithelial cell adhesion molecules [EpCAM]

 Circulating tumour cells in patients with urothelial tumours: Enrichment and in vitro culture  (18)

Katarina Kolostova

2014

Prague, Poland

8

52

yes

Capillary-action driven

cell origin (pancytokeratin
1–FITC conjugated antibody [Sigma], cytokeratin7
antibody [Dako])

 Cadherin-6 gene expression in conventional renal cell carcinoma: a useful marker to detect circulating tumor cells (19)

GUORONG LI

2005

France

46

 

yes

Real Time-PCR.

Cadherin-6

 New applications of the acridine orange fluorescence staining method: Screening for circulating tumor cells (20)

MIN LIU

2017

China

112

58.47±11.26

yes

alcidine orange fluorescence (AO‑F) staining method

 

 Combined cell surface carbonic anhydrase 9 and CD147 antigens enable high-efficiency capture of circulating tumor cells in clear cell renal cell carcinoma patients (21)

Shijie Liu

2016

china

76

56 (16-78)

yes

The NanoVelcro chips

CA9 and CD147

 Circulating Tumor Cell Composition in Renal Cell Carcinoma (22)

Ivonne Nel

2016

Germany

14

61 (38–78)

yes

quantitative  Real Time-PCR and MPIM

 High expression of HIF1A, VEGFA, VEGFR and FGFR and the presence of N-cadherin-positive and CD133-positive CTC.

 Dynamic changes of live/apoptotic circulating tumour cells as predictive marker of response to sunitinib in metastatic renal cancer (23)

E Rossi

2012

Italy

53

26–90

yes

   Total and M30-positive CTC and CEC count by Cell Search System

 

EpCAM+, CK+,DAPI+ and CD45- or CD146+, CD105+, DAPI+ and CD45-,

 The level of cadherin-6 mRNA in peripheral blood is associated with the site of metastasis and with the subsequent occurrence of metastases in renal cell carcinoma (24)

Toru Shimazui

2004

Japan

66

 

yes

  Quantitative polymerase chain reaction analysis

Adherin-6 mRNA in circulating tumor cells

 Dynamic changes of different phenotypic and genetic circulating tumor cells as a biomarker for evaluating the prognosis of RCC  (25)

Zhen-Long Wang

2019

china

69

57.5 ± 11.1

yes

RNA in situ hybridization

EpCAM, CK8, CK18 and
CK19. Mesenchymal CTCs were tested by labeling mesenchymal
markers, including Vimentin and Twist.

 Expression of CK19, CD105 and CD146 are associated with early metastasis in patients with renal cell carcinoma (26)

XIAOJIE YANG

2018

china

200

60 ( 40 - 79 )

yes

The CellSearch system

cytokeratin 19 (CK19), endoglin (CD105) and cluster of differentiation 146 (CD146)

 Development of a Novel c-MET–Based CTC Detection Platform  (27)

Tian Zhang

2016

USA

59

≥18

yes

anti-c-MET ferrofluid for the
immunomagnetic capture of CTCs

CD45, cytokeratins 8, 18, and 19

 Detection of tumor-associated cells in cryopreserved peripheral blood mononuclear cell samples for retrospective analysis (28)

Peixuan Zhu

2016

USA

214

 

yes

CellSieve™ CTC Enumeration Kits (Creatv MicroTech, Inc) were used for
recovery and fluorescence antibody staining of the filtercaptured cells

cytokeratins
8, 18, 19, EpCAM, and CD45

 eTumorType, An Algorithm of Discriminating Cancer Types for Circulating Tumor Cells or Cell-free DNAs in Blood (29)

Jinfeng Zou

2017

Canada

30

 

yes

 TumorType, to identify cancer types based on copy number variations (CNVs)

cytokeratin

 Comparison of two detection systems for circulating tumor cells among patients with renal cell carcinoma (30)

Menglin Bai

2014

China

36

58.0 ± 9.06 (33–72)

yes

ISET,CSS

carbonic anhydrase-9and Cadherin-6, as CTC biomarkers in the peripheral blood

 Melanoma presenting as circulating tumor cells associated with failed angiogenesis (31)

Richard T. Lee

2008

USA

1

36

yes

NA

CD45 and CDW-41

 Comparison of isolation platforms for detection of circulating renal cell carcinoma cells (32)

Yvonne Maertens

2017

Germany

61

-

yes

EpCAM based enrichment, leukocyte depletion, and size-based enrichment

Epcam,panCK

 Detection of circulating tumor cells in patients with renal cell carcinoma by reverse transcriptase-polymerase chain reaction for G250/MNCA-9: Results of a prospective trial (33)

Carsten-Henning Ohlmann,

2005

Germany

55

62

yes

Real Time-PCR

G250/MNCA-9

positive  Real Time-PCR signals for MNCA-9

 Candle soot-templated silica nano-bio interface chip for detecting circulating tumor cells from patients with urologic malignancies (34)

Tianying Xing

2018

China

33

-

yes

Candle soot-templated silica nano-bio interface chip

EpCAM,anti-carbonic anhydrase 9 (CA9) and CD147

Capillary-action-driven filtration: The size-based enrichment process is based on the filtration of peripheral blood through a porous polycarbonate membrane (pores with 8 μm diameter. EpCAM: Epithelial Cell Adhesion Molecule; MACS: Magnetic Cell Sorting; iFISH: Immunostaining-Fluorescence in Situ Hybridization; MPIM: Multi-Parameter Immunofluorescence Microscopy; Real Time-PCR: Real-Time Polymerase Chain Reaction

 

Despite our search strategy covering the time from 1990 to 2019, the first published research related to CTCs detection in RCC was in 2001. After that one study was published in 2004, two in 2005, one in 2008, 0ne in 2009, and other 16 articles were published after 2010. Studies were run mainly in China (7 articles), Germany (4 articles), France, Italy, Canada, Japan, Poland, the USA (2 articles), Austria. Most studies were focused on detection and quantification of CTCs (ISET® - Isolation by size of tumor cells), some others studied the molecular markers and gene expression profile. One study by Amin El-Heliebi just focused on the morphological criteria (15). Some CTCs detection methods were based on the CTC‘s surface marker and gene expression pattern. The most common methods were based on the immunomagnetic separation procedure for the detection of CTCs in the peripheral blood based on the magnetic cell sorting (MACS) technique. The CTC detection methods lacking the enrichment step named direct recognition of CTCs including; line-confocal microscope and SERS. The CellSearch® (Veridex, Raritan, NJ) is the only U.S. food and drug administration (FDA) approved method. However, it cannot isolate CTCs based on phenotype classification and molecular analysis. The CellCollector® (GILUPI GmbH, Potsdam, Germany) is a CE (French phrase “Conformité Européene” which exactly is equal to “European Conformity”) permitted medical method as the first universal CTC separation instrument (35). Structurally it is made of a needle, which is inserted into the patient’s vein for the CTC separation. On the hydrogel coating layer, the anti-EpCAM-antibodies are coated to recognize and separate the EpCAM-positive CTCs. Contrary to the CellSearch®, it does not require costly practical equipment, and the sensitivity and selectivity are advanced because of more blood volume and feasibility of phenotypic characterization of and molecular analysis of the captured CTCs. The enrichment phase states the separation of CTCs from the blood. Subsequently, the CTCs can be identified by fluorescence (e.g. fluorescent microscope, fluorescent spectrophotometer, and flow cytometer), surface-enhanced Raman scattering (SERS), or electrical impedance.

Moreover, CD45-conjugated microbeads, antic-MET Ferrofluid for the immunomagnetic capture of CTCs, EpCAM based enrichment, and real-time polymerase chain reactions were recruited for CTCs quantitation. Several antibodies against CTC molecular markers were targeting for detection including cytokeratin (CK)/CK8/18/19, CD45, CD133, CDW-41,  carbonic anhydrase IX (CAIX), epithelial cell adhesion molecules (EpCAM), cadherin-6, Hypoxia Inducible Factor 1 Subunit Alpha (HIF1A), vascular endothelial growth factor A (VEGFA), vascular endothelial growth factor receptors (VEGFR), and fibroblast growth factor receptors (FGFR) and the presence of N-cadherin. Some detection methods were based on the physical characteristics of CTCs like their size including immunomagnetic circulating tumor cell enrichment, ISET®-Isolation by the size of tumor cells, ScreenCell® filtration, tapered-slit filter (photosensitive polymer-based microfilter), and NanoVelcro chips.

 

Discussion

CTCs are circulating tumor cells that are released from original or metastatic solid tumors and shed into the bloodstream which can potentially lead to new fatal metastasis. CTCs are real-time representatives of the tumor so they became a hotspot research topic over the last years. CTCs uncovering, as the main liquid biopsy component, can be taken into account of early RCC diagnosis, sooner assessment of cancer recurrence and treatment efficacy, and a special assessment of individual sensitive anti-cancer drugs (personalized medicine). Therefore, CTC detection is a crucial tool in to fight against cancer. Herein we represented the first study on the several CTCs' impacts on both diagnosis and prognosis of RCC. Studies of CTCs in RCC were mostly focused on CTC detection and quantifications based on immunomagnetic cell enrichment of tumor cells through leukocyte-specific reduction. It was shown by Udo Bilkenroth and colleagues that there was a  direct connection between tumor cell number and grading (G2 vs. G3) and an augmented quantity of CK+ patients with progressive tumor stage (11). In 2001, it was MACS reported as an efficient technique to detect CTCs in peripheral blood (11). The same result indicated that immunomagnetic cell enrichment and cytokeratin 8/18 (CK+) targeting as the CTCs marker can be taken into account in CTCs detection in RCC patients (12, 13, 16). The total number of 233 peripheral blood samples from 154 RCC patients were examined for the existence of dispersed tumor cells by automatics technique and immunocytochemical staining of cytokeratin. It was shown that CTCs are correlated to lymph node grade and the existence of synchronous metastases in RCC. Detection of CK+ CTCs in a patient’s blood is suggested as a noteworthy and autonomous prognostic feature for RCC (12).

A recent study by Lucile Broncy, et al., has matched genetic mutation analysis of circulating rare cells (CRC) and tumor sections with CRC cyto-pathological diagnosis. It was done by the blood sample of thirty patients with clear cell RCC tested by ISET® for CRC separation, cytopathology, and single-cell VHL mutations analysis, achieved blindly and matched to VHL mutations to the equivalent tumor tissues and leukocytes (14). The recent study by Tianying Xing and his colleagues represented a new and strange method for CTC detection (34). They recruited the simply equipped silica nano-bio interface chip for CTCs detection in prostate cancer (PCa) and clear cell RCC patients with high productivity. The silica nano-bio interface chip was extraordinarily invented by placing candle soot on a glass slide, tracked by chemical vapor statement, and then by adjusting EpCAM antibodies. These silica nano-bio interface chips presented outstanding capacities to capture PC3PCa cell lines, with typical efficacy of 81.2±1.4%. The solid topographic contact between targeted cells and the nanostructured surface was serious to improving CTCs capturing potential. Tianying Xing and his colleagues additionally checked the peripheral blood samples from 10 preoperative PCa and 7 ccRCC patients. Their results displayed that CTCs were successfully detected and suggested that the nano-bio interface chip will offer the excessive probable potential for the clinical application of CTC (34).

However, some studies debate the morphological characteristics of CTCs and ask the question of whether morphological criteria are sufficient for the identification of circulating tumor cells in RCC (15). The majority of circulating non-hematologic cells (CNHCs)-clusters, putative circulating tumor microemboli (CTMs), recovered by ScreenCell filtration may be of endothelial origin indicate that morphological criteria seem to be insufficient to distinguish malignant from non-malignant cells in renal cancer (15). Circulating tumor cells and "suspicious objects" evaluated through Cell search (R) in metastatic RCC indicated that the low number of CTCs detected through Cell search in renal cell carcinoma may be due to the presence of a CTC population with atypical characteristics and a peculiar gene expression profile, characterized by lack of cytokeratin expression and gain of CD44 (16).

Some advanced molecular techniques like quantitative real-time PCR, RNA in situ hybridization, and copy number variations (CNVs) can solve the weak points of CTCs detection just based on morphological characteristics.  Cadherin-6 mRNA is suggested as the new molecular marker for the detection of circulating renal cancer cells disseminated from conventional RCC (19). The connection of dynamic variations of CTCs and Beclin-1 expression of CTCs with RCC prognosis has been proven (25). The recurrence or metastasis of RCC was dependent on initial CTCs quantitation but may be associated with the variation trend of CTCs, particularly mesenchymal CTCs and Beclin1 positive CTCs (25). Prosperous application in metastatic RCC (mRCC) is very restricted. Extraordinary elasticity and heterogeneity of CTC morphology experiments currently make the enrichment and detection techniques with EpCAM not satisfying in mRCC. The CTC recognition with epithelial, mesenchymal, stem cell-like, or mixed-cell features at several time-points through anti-angiogenic therapy in RCC patients indicated that the amount of N-cadherin-positive or CD133-positive CTC can be associated with lower PFS. However, there was an opposite connection between HIF1A, VEGFA, VEGFR, and FGFR  overexpression and the existence of N-cadherin-positive and CD133-positive (22). CTC Patients with mRCC show different CTC outlines and molecular markers that can indicate differences in therapeutic outcomes (22).

 

Conclusions

CTCs detection as the main liquid biopsy component has unlimited experimental implications in cancer diagnosis and prognosis, especially in RCC. But traditional techniques still encounter limitations when targeting CTCs with high efficiency and low cost. The CTCs detection and quantitation can represent the tumor and to some extent the tumor stage/ metastasis. Some CTCs molecular markers and gene expression profiling of CTCs can be taken into account for RCC prognosis.

 

Authors’ contribution

All authors contributed equally.

 

Acknowledgments

Special thanks to the Urology Research Center (URC), Tehran University of Medical Sciences (TUMS).

 

Conflict of interest

All authors declare that there is not any kind of conflict of interest.

 

Funding

There is no funding.

 

Ethical statement

Not applicable.

 

Data availability

Data will be provided by the corresponding author on the request.

 

Abbreviation

CAIX               Carbonic anhydrase IX

CNHCs            Circulating non-hematologic cells

CNVs              Copy number variations

CTCs               Circulating tumor cells

CTMs              Circulating tumor microemboli

CRC                Circulating rare cells

EpCAM           Epithelial cell adhesion molecules

FGFR              Fibroblast growth factor receptors

HIF1A             Hypoxia-inducible factor 1 subunit alpha

MACS             Magnetic cell sorting

mRCC             Metastatic RCC

mTOR             Mammalian target of rapamycin

NOS                Newcastle–Ottawa scale

PCa                  Prostate cancer

PFS                  Progression-free survival

QUADAS        Quality assessment of diagnostic accuracy assessment

RCC                 Renal cell carcinoma

SERS               Surface-enhanced Raman scattering

SIGLE              System for information on grey literature

VEGF               Vascular endothelial growth factor

VEGFA            Vascular endothelial growth factor A

VEGFR            Vascular endothelial growth factor receptors

1.Prasad SR, Humphrey PA, Catena JR, Narra VR, Srigley JR, Cortez AD, et al. Common and uncommon histologic subtypes of renal cell carcinoma: imaging spectrum with pathologic correlation. Radiographics. 2006;26(6):1795-806.
2.Hollingsworth JM, Miller DC, Daignault S, Hollenbeck BK. Rising incidence of small renal masses: a need to reassess treatment effect. Journal of the National Cancer Institute. 2006;98(18):1331-4.
3.Wahner-Roedler DL, Sebo TJ, editors. Renal cell carcinoma: diagnosis based on metastatic manifestations. Mayo Clinic Proceedings; 1997: Elsevier.
4.Yamamoto Y, Uemura M, Nakano K, Hayashi Y, Wang C, Ishizuya Y, et al. Increased level and fragmentation of plasma circulating cell-free DNA are diagnostic and prognostic markers for renal cell carcinoma. Oncotarget. 2018;9(29):20467.
5.Barwari K, de la Rosette JJ, Laguna MP. The penetration of renal mass biopsy in daily practice: a survey among urologists. Journal of endourology. 2012;26(6):737-47.
6.García-Casas A, García-Olmo DC, García-Olmo D. Further the liquid biopsy: Gathering pieces of the puzzle of genometastasis theory. World journal of clinical oncology. 2017;8(5):378.
7.Santoni M, Cimadamore A, Cheng L, Lopez-Beltran A, Battelli N, Massari F, et al. Circulating tumor cells in renal cell carcinoma: recent findings and future challenges. Frontiers in oncology. 2019;9:228.
8.Di Meo A, Bartlett J, Cheng Y, Pasic MD, Yousef GM. Liquid biopsy: a step forward towards precision medicine in urologic malignancies. Molecular cancer. 2017;16(1):80.
9.Reduzzi C, Vismara M, Gerratana L, Silvestri M, De Braud F, Raspagliesi F, et al., editors. The curious phenomenon of dual-positive circulating cells: Longtime overlooked tumor cells. Seminars in Cancer Biology; 2019: Elsevier.
10.Apolo AB, Mortazavi A, Hu ZI, Schonhoft J, Chu L, Anderson AK, et al. Circulating tumor cell (CTC) enumeration in patients (pts) with metastatic genitourinary (mGU) tumors treated in a phase I study of cabozantinib and nivolumab (CaboNivo)+/-ipilimumab (CaboNivoIpi). American Society of Clinical Oncology; 2019.
11.Bilkenroth U, Taubert H, Riemann D, Rebmann U, Heynemann H, Meye A. Detection and enrichment of disseminated renal carcinoma cells from peripheral blood by immunomagnetic cell separation. international Journal of Cancer. 2001;92(4):577-82.
12.Bluemke K, Bilkenroth U, Meye A, Fuessel S, Lautenschlaeger C, Goebel S, et al. Detection of circulating tumor cells in peripheral blood of patients with renal cell carcinoma correlates with prognosis. Cancer Epidemiology and Prevention Biomarkers. 2009;18(8):2190-4.
13.Blümke K, Bilkenroth U, Schmidt U, Melchior A, Füssel S, Bartel F, et al. Detection of circulating tumor cells from renal carcinoma patients: experiences of a two-center study. Oncology reports. 2005;14(4):895-9.
14.Broncy L, Njima BB, Méjean A, Béroud C, Romdhane KB, Ilie M, et al. Single-cell genetic analysis validates cytopathological identification of circulating cancer cells in patients with clear cell renal cell carcinoma. Oncotarget. 2018;9(28):20058.
15.El-Heliebi A, Kroneis T, Zöhrer E, Haybaeck J, Fischereder K, Kampel-Kettner K, et al. Are morphological criteria sufficient for the identification of circulating tumor cells in renal cancer? Journal of translational medicine. 2013;11(1):214.
16.Gradilone A, Iacovelli R, Cortesi E, Raimondi C, Gianni W, Nicolazzo C, et al. Circulating tumor cells and “suspicious objects” evaluated through CellSearch in metastatic renal cell carcinoma. Anticancer research. 2011;31(12):4219-21.
17.Kim TH, Kang Y-T, Cho Y-H, Kim JH, Jeong BC, Seo SI, et al. Detection of circulating tumor cells and their potential use as a biomarker for advanced renal cell carcinoma. Canadian Urological Association Journal. 2019;13(9):E285.
18.Kolostova K, Cegan M, Bobek V. Circulating tumour cells in patients with urothelial tumours: Enrichment and in vitro culture. Canadian Urological Association journal. 2014;8(9-10):E715.
19.LI G, PASSEBOSC-FAURE K, GENTIL-PERRET A, LAMBERT C, GENIN C, TOSTAIN J. Cadherin-6 gene expression in conventional renal cell carcinoma: a useful marker to detect circulating tumor cells. Anticancer research. 2005;25(1A):377-81.
20.Liu M, Li R, Tang Y, Chang J, Han R, Zhang S, et al. New applications of the acridine orange fluorescence staining method: Screening for circulating tumor cells. Oncology letters. 2017;13(4):2221-9.
21.Liu S, Tian Z, Zhang L, Hou S, Hu S, Wu J, et al. Combined cell surface carbonic anhydrase 9 and CD147 antigens enable high-efficiency capture of circulating tumor cells in clear cell renal cell carcinoma patients. Oncotarget. 2016;7(37):59877.
22.Nel I, Gauler TC, Bublitz K, Lazaridis L, Goergens A, Giebel B, et al. Circulating tumor cell composition in renal cell carcinoma. PloS one. 2016;11(4).
23.Rossi E, Fassan M, Aieta M, Zilio F, Celadin R, Borin M, et al. Dynamic changes of live/apoptotic circulating tumour cells as predictive marker of response to sunitinib in metastatic renal cancer. British journal of cancer. 2012;107(8):1286-94.
24.Shimazui T, Yoshikawa K, Uemura H, Hirao Y, Saga S, Akaza H. The level of cadherin‐6 mRNA in peripheral blood is associated with the site of metastasis and with the subsequent occurrence of metastases in renal cell carcinoma. Cancer. 2004;101(5):963-8.
25.Wang Z-L, Zhang P, Li H-C, Yang X-J, Zhang Y-P, Li Z-L, et al. Dynamic changes of different phenotypic and genetic circulating tumor cells as a biomarker for evaluating the prognosis of RCC. Cancer biology & therapy. 2019;20(4):505-12.
26.Yang X, Zhang D, Chong T, Li Y, Wang Z, Zhang P. Expression of CK19, CD105 and CD146 are associated with early metastasis in patients with renal cell carcinoma. Oncology letters. 2018;15(4):4229-34.
27.Zhang T, Boominathan R, Foulk B, Rao C, Kemeny G, Strickler JH, et al. Development of a novel c-met–based ctc detection platform. Molecular cancer research. 2016;14(6):539-47.
28.Zhu P, Stanton ML, Castle EP, Joseph RW, Adams DL, Li S, et al. Detection of tumor-associated cells in cryopreserved peripheral blood mononuclear cell samples for retrospective analysis. Journal of translational medicine. 2016;14(1):198.
29.Zou J, Wang E. eTumorType, An algorithm of discriminating cancer types for circulating tumor cells or cell-free DNAs in blood. Genomics, proteomics & bioinformatics. 2017;15(2):130-40.
30.Bai M, Zou B, Wang Z, Li P, Wang H, Ou Y, et al. Comparison of two detection systems for circulating tumor cells among patients with renal cell carcinoma. International urology and nephrology. 2018;50(10):1801-9.
31.Lee RT, Fallarino F, Ashikari A, Gajewski TF. Melanoma presenting as circulating tumor cells associated with failed angiogenesis. Melanoma research. 2008;18(4):289-94.
32.Maertens Y, Humberg V, Erlmeier F, Steffens S, Steinestel J, Bögemann M, et al. Comparison of isolation platforms for detection of circulating renal cell carcinoma cells. Oncotarget. 2017;8(50):87710.
33.Ohlmann C-H, Özgür E, Schrader AJ, Konrad L, Hofmann R, Engelmann U, et al., editors. Detection of circulating tumor cells in patients with renal cell carcinoma by reverse transcriptase polymerase chain reaction for G250/MNCA-9: results of a prospective trial. Urologic Oncology: Seminars and Original Investigations; 2006: Elsevier.
34.Xing T, Wang B, Song Y, Zhang S, Ma L. Candle soot-templated silica nanobiointerface chip for detecting circulating tumour cells from patients with urologic malignancies. RSC advances. 2018;8(60):34566-72.
35.Shen Z, Wu A, Chen X. Current detection technologies for circulating tumor cells. Chemical Society reviews. 2017;46(8):2038-56.