Advantages, disadvantages, and commercial status of technologies for enrichment, detection, and characterization of CTCs.
Abstract
A few years ago, the analysis of circulating tumor cells (CTCs) in the blood of patients with cancer was defined by the term “real-time liquid biopsy.” Blood samples can be obtained and analyzed at the time of diagnosis and repeatedly during the systemic treatment. The analysis of the liquid biopsy has provided new insights into the biology of metastasis with important implications for the clinical management of cancer patients. In this review, we updated all technical strategies developed to improve enrichment, detection, and characterization of CTCs. We also focused on their biological properties as well as on their clinical relevance in different cancer types. At the end, we opened the discussion to all the other circulating biomarkers used as liquid biopsy.
Keywords
- circulating tumor cells
- liquid biopsy
- clinical relevance
- circulating biomarkers
- precision medicine
1. Introduction
A few years ago, the analysis of circulating tumor cells (CTCs) in the blood of patients with cancer was defined by the term “
The analysis of the
Despite the remarkable advances made in recent years, so far,
Here, we will outline the advantages and challenges of CTCs as
2. Technical strategies for enrichment, detection, and characterization of CTCs
At the moment, in-depth investigation of CTCs still remains technically challenging as they are every rare events in blood circulation. Their identification and characterization require extremely sensitive and specific analytic methods, which are usually a combination of enrichment and detection procedures (Figure 2). The different strategies to analyze CTCs are described in this chapter, and all the advantages/disadvantages plus the commercial status are summarized in Table 1.
2.1 Strategies for CTC enrichment
Up to date, a large panel of technologies was designed to enrich CTCs from the surrounding normal hematopoietic cells. These enrichment methods rely on different properties of CTCs: (a) biological properties (e.g., surface protein expression) and (b) physical properties (e.g., size, density, electric charges, and deformability).
Biological properties are mainly used in immunological procedures with antibodies against either tumor-associated antigens (positive selection) or common leukocytes antigen CD45 (negative selection). Positive enrichment typically attains high cell purity, which depends on antibody specificity. Among the current positive systems, most of the technologies targeted the epithelial cell adhesion molecule (EpCAM) antigen, as the FDA-cleared CELLSEARCH® system which is frequently compared for all new CTC detection methods as the gold standard. However, capturing CTCs lacking EpCAM expression has involved the use of cocktails of antibodies against various other epithelial cell surface antigens (e.g., EGFR, MUC1) or against tissue-specific antigen (e.g., PSA, HER2) and against mesenchymal or stem-cell antigens (e.g., Snail, ALDH1) [7]. Positive selection of CTCs requires an assumption about the unknown nature of CTCs in an individual blood sample. This bias is avoided by negative selection in which the blood sample is depleted of unwanted cells. Indeed, negative enrichment targets and removes background cells, such as leukocytes, using antibodies against CD45 (which is not expressed on carcinomas or other solid tumors) and other leukocyte antigens, to achieve a CTC-enriched sample. Moreover, negative enrichment technologies evade some of the pitfalls of positive enrichment; for example, CTCs are not tagged with a difficult-to-remove antibody, they are not activated or modified via an antibody-protein interaction, and antibody selection does not bias the subpopulation of CTCs captured. However, these advantages come at the cost of purity, as negative enrichment strategies typically have a much lower purity than positive enrichment [8, 9, 10] and require a suitable CTC detection step.
These last years, numerous marker-independent techniques have been developed for CTC isolation and detection. Label-free enrichment process based on physical properties, such as density, size, deformability, and electric charge, have come to avoid molecular bias induced by variability of cell biomarker expression associated with tumor heterogeneity. Mostly used, size and density technologies like microfiltration technologies, based on the precedent that CTCs generally exhibit a larger morphology than leukocytes, or microfluidic devices using inertial focusing to separate CTCs from blood are developed by several companies such as ScreenCell® [11], ISET® [12], CellSieve™ [13, 14], Parsortix™ [15], or Vortex [16]. Such technologies or approaches have the advantages of being less complicated, sometimes rapid, and require minimal equipment. However, some of these approaches may be prone to clogging, and the release of the CTCs into suspension for further analysis is challenging.
2.2 Strategies for CTC detection
After enrichment, the CTC fraction still contains a substantial number of leukocytes, and CTCs need to be specifically identified at the single-cell level by a robust and reproducible method that can distinguish them from normal blood cells.
Immunological technologies are the most frequent methods used for CTC detection using a combination of membrane and/or intracytoplasmic anti-epithelial, anti-mesenchymal, and anti-tissue-specific marker or antitumor-associated antibodies [7]. However, many CTC assays use the same identification step as the CELLSEARCH® system: cells are fluorescently stained for cytokeratins (CK), the common leukocyte antigen CD45, and a nuclear dye (DAPI).
Nucleic acid-based CTC detection methods are the most widely used alternatives to immunological assays to identify CTCs. These techniques identify specific tumor DNA or mRNA to confirm the presence of CTCs indirectly [17]. Detection involves designing specific primers supposedly associated with CTC-specific genes. These genes either code for tissue-, organ-, or tumor-specific proteins or, more specifically, contain known mutations, translocations, or methylation patterns found in cancer cells [18]. These methods have the highest sensitivity but lack specificity, owing to the potential of captured noncancerous cells to generate false-positive signals, thus decreasing the overall accuracy. Considering the genetic heterogeneity of CTCs, multiplex PCR, such as the AdnaTest kit (AdnaGen AG), could overcome this limitation [19, 20].
Furthermore, functional assays that exploit aspects of live cellular activity for CTC detection have the particularity to focus on the discovery of the “metastasis-competent cells.” The functional epithelial immunospot (EPISPOT) assay was introduced for in vitro CTC detection and focuses only in viable CTCs [21]. This technology assesses the presence of CTCs based on secretion, shedding, or release of specific proteins during 24–48 h of short-term culture [22]. More recently, Tang et al. described a high-throughput metabolic-based assay for rapid detection of rare metabolically active tumor cells in pleural effusion and peripheral blood of lung cancer patients [23]. In vivo, important information can be obtained by transplantation of patient-derived CTCs into immunodeficient mice: tumors that could grow after xenotransplantation of enriched CTCs have the characteristics of metastasis-initiator cells [8].
2.3 Strategies for CTC characterization
CTCs hold the key to understand the biology of metastasis and provide a biomarker to noninvasively measure the evolution of tumor subclone during treatment and disease progression. Improvements in technologies to yield purer CTC populations make better cellular and molecular investigation. Characterization of CTCs allows better insight into tumor heterogeneity, within most assays, including immunofluorescence, array CGH, next-generation sequencing (NGS) of both DNA and RNA, and fluorescence in situ hybridization.
Protein analyses on single CTCs are currently performed by immunostaining with antibodies directed against protein of interest. Multiple labeling is possible but usually restricted to a few proteins of interest for tumor cell biology and cancer therapy. This may help to identify signaling pathways relevant to metastasis development and treatment responses. In breast cancer patient, the HER2 status of CTCs could be assessed and shows discrepancies with primary tumor status [24, 25]. More recently, immune checkpoint regulators such as programmed death-ligand 1 (PD-L1) have become exciting new therapeutic targets and could be used for
Immunological detection and characterization offer the advantage of allowing isolation of stained CTCs for subsequent molecular characterization. While manual isolation by micromanipulation of CTCs is possible [28], it is rather arduous and time-consuming. An alternative automated single-cell selection device has been therefore developed. The DEPArray™ technology based on a dielectrophoresis strategy by trapping single cells in DEP cages [29] is designed for single-cell recovery of CTCs. Multiple clinical studies have used DEPArray™ to detect and recover single CTCs for subsequent genetic analyses [30, 31, 32].
Among single-cell sequencing to identify genomic and transcriptomic characteristics of CTCs, most studies have focused on genomic analyses and carried out whole genome amplifications (WGAs) to increase the amount of DNA, which is subsequently subjected to the analyses of specific mutations and copies number variations using conventional and next-generation sequencing technologies [28, 33, 34]. As an example, CTCs with mutated KRAS genes will escape anti-EGFR therapy, and their early detection might help to guide therapy in individual patients. Besides isolation of single CTCs, a 3–4 log units enrichment step are enough to detect CTCs based on recently developed highly sensitive technologies (e.g., droplet digital PCR) [35].
Another approach is fluorescence in situ hybridization (FISH) analysis of single CTCs identified by immunocytochemistry [36, 37]. Such an immuno-FISH approach can be combined with automated detection of CTCs and might be easier to implement in future clinical diagnostics. Recently, padlock probe technology, which enables in situ analysis of AR-V7 in CTCs, showed that 71% (22 of 31) of CRPC patients had detectable AR-V7 expression ranging from low to high expression [38]. Patients with AR-V7-positive circulating tumor cells (CTCs) have greater benefit of taxane-based chemotherapy than novel hormonal therapies, indicating a treatment-selection biomarker [39, 40].
Finally, these last years, many teams tried to obtain CTC lines by culturing CTCs
3. Biology of CTCs
3.1 Epithelial to mesenchymal plasticity
Epithelial to mesenchymal transition (EMT), which is characterized by the downregulation of epithelial proteins and upregulation of mesenchymal proteins, is a complex process that supports the migratory capacity of epithelial tumor cells and is thought to play a crucial role in promoting cancer metastasis. EMT led to increased motility via rearrangements of cellular contact junctions and loss of cell adhesion (i.e., E-cadherin, N-cadherin, claudins), plus epithelial cell morphology through cytoskeleton modification (i.e., cytokeratin, vimentin, fibronectin, etc.) [48]. This invasive phenotype enables cancer cells to pass through the basal membrane and endothelial barriers of blood vessels to reach bloodstream. However, it is still unclear what degree of EMT is needed in tumor cells to attain the circulation.
Despite the wealth of experimental data, the exact role of EMT in cancer patients remains more controversial. Over the past 10 years, the development of sensitive technologies that allow the detection and molecular characterization of CTCs helped to shed new light into the importance of EMT for human tumor cell dissemination [7, 49]. All these data lead now to a new trend, focused on plasticity of tumor cell: epithelial to mesenchymal plasticity (EMP) associated with stemness. This process is today considered as a central actor of the metastatic cascade, providing tumor cells the ability to adapt to the different microenvironments encountered during metastatic spread to colonized organs (i.e., adjacent stroma, blood, newly colonized organs).
CTCs with mesenchymal and stemness features can be attributed in some clinical studies to higher disease stages and metastasis [50, 51, 52] and even to therapy response and worse outcome [53, 54, 55]. However, the published studies addressing the impact of mesenchymal-like CTCs show heterogeneity with regard to assay specificity, size of cancer and control groups, and endpoint parameters.
To conclude, evaluation of the EMT and stem-cell markers in CTCs may provide information of clinical interest, and using these markers to classify CTCs can elucidate CTC heterogeneity. Nevertheless, studies still suffer from lack of standardized procedures and small sample sizes. Therefore, larger well-designed clinical trials are needed to further illuminate the potential values of EMT markers in CTCs.
3.2 Anoikis resistance
In normal tissue, adhesion to appropriate extracellular matrix proteins is essential for survival. Loss of this adhesion induces cell death which has been termed “anoikis.” Anoikis is a physiologically relevant process for tissue homeostasis and development because it prevents detached epithelial cells from colonizing elsewhere, thereby inhibiting dysplastic cell growth or attachment to an inappropriate matrix [56]. Dysregulation of anoikis, such as anoikis resistance, is a critical mechanism in tumor metastasis. If cells acquire oncogenic signals that are able to overcome this machinery, they gain the ability to survive outside their normal environment in the absence of adhesion to the extracellular matrix. The tumor cells that acquire anoikis resistance can survive detachment from their primary site, traveling through the circulatory and lymphatic systems to disseminate to ectopic locations [57]. Different studies have shown that the death receptor pathway of caspase activation mediates anoikis; thus, defects in this pathway such as overexpression of the caspase-8 inhibitor FLIP can turn cell resistant to anoikis. Similarly, resistance to anoikis can be conferred by roadblocks in the mitochondrial pathway, such as overexpression of the Bcl-2 family of anti-apoptotic proteins [57].
The investigation of molecular mechanisms involved in cancer cell survival while they are leaving the adherent microenvironment of the tumor to the circulatory system is important to understand the process by which cancer can spread to distant organs, as well as to design new therapeutics to inhibit the spread of the disease.
3.3 Escape to the immune system
Once in the bloodstream, CTCs face several natural obstacles that hinder the metastatic process. One of the main obstacles that CTCs face in the blood is the attack of the immune system. Lots of work was done to understand mechanisms involve in the battle between the immune system’s capabilities to fight cancer and the immune-suppressive processes that promote tumor growth. Several biomarkers showed up from this work; for example, in colorectal cancer, immune escape was observed by the upregulation of CD47, a “don’t eat me signal” that prevents CTCs from macrophage and dendritic cell attack [58]. The most clinically advanced biomarkers are the programmed death-1 (PD-1) and its ligand (PD-L1). PD-L1 expressed in tumors has been highlighted to function as a key component of the cancer-immunity cycle by preventing the immune system from destroying cancer cells. PD-1 receptor is a surface protein expressed on activated T-cells, and its ligand PD-L1 is expressed on the surface of antigen-presenting cells. The formation of the PD-1/PD-L1 complex induces a strong inhibitory signal in the T-cell, which leads to a reduction of cytokine production and a suppression of T-cell proliferation [59]: the immune system is misled by the cancer cells expressing PD-L1 and does not destroy them. That understanding led to the development of immune checkpoint inhibitor therapies, antibodies against both PD-1 and PD-L1, and remarkable clinical responses which have been seen in several different malignancies including, but not limited to, melanoma, lung, kidney, and bladder cancers [59].
However, CTCs can use several mechanisms to survive in the circulatory system. For example, these cells can couple to reactive platelets. Several hypotheses propose that the surface coating of platelets may serve as a shield against immune assault or that platelets may load the major histocompatibility complex to CTCs to imitate host cells and therefore avoid immune surveillance [60]. The aggregation of CTCs with platelets, stromal fibroblasts, and leukocytes leads to the formation of floating complexes and increases the survival of CTCs in the bloodstream by avoiding anoikis and killing by immune cells [61]. In addition, the vascular endothelial growth factor (VEGF), secreted by platelets, is able to affect the maturation of dendritic cells that play a key role in antigen presentation [62].
3.4 CTC microemboli
An alternative mechanism for metastasis has emerged from recent studies, the collective migration of tumor cells by clusters of CTCs. CTC clusters are defined as groups of tumor cells (more than two or three cells, varied among studies) that travel together in the bloodstream. Thus, in the blood circulation, CTCs can be found both as single tumor cells and clusters of tumor cells in patients with an advanced stage of the cancer. Study using mouse models with tagged mammary tumors demonstrates that these clusters arise from oligoclonal tumor cell groupings and not from intravascular aggregation events [63]. Moreover, CTC clusters have 23- to 50-fold increased metastatic potential. Even fewer in number, clusters of CTCs possess much higher metastatic potential than individual CTCs.
Patients with CTC microemboli or clusters in their bloodstream have significantly worse overall and progression-free survival than those with only individually migrating single CTCs [63]. The prognostic value of CTC clusters can be estimated by clinical observations.
Current studies have partially elucidated the reasons for CTC clusters to have higher potential of metastasis. First, tumor cells within CTC clusters showed prolonged survival and decreased apoptosis [64]. Second, the physical specialty of CTC clusters allows for a greater likelihood of it residing in distant organs. Microvasculature of viscera can retain large CTCs; thus, it can retain CTC clusters more easily [65].
4. Clinical relevance of CTCs
Despite many clinical validation studies, CTCs have not been included yet into the clinical guidelines (e.g., ASCO guidelines at http://www.asco.org/practice-guidelines/quality-guidelines/guidelines). Although CTC enumeration can improve current tumor staging and contribute to the early assessment of therapy effects, the clinical utility of CTCs remains to be addressed in interventional studies (i.e., its capacity to decide adopting or to rejecting a therapeutic action).
In this chapter, we highlighted the clinical relevance of CTCs in breast, prostate, colon, and lung cancer. Figure 3 illustrates how CTCs as
4.1 Breast
More advanced studies, regarding clinical utility of CTCs, are related to metastatic breast cancer (MBC). Sequential CTC enumeration has been shown in a large multicenter prognostic study to be superior to conventional serum protein markers (CA-15-3, CEA) for early detection of therapy failure in MBC [5]. However, in the interventional trial SWOG 0500 (NCT00382018), although the prognostic significance of CTCs was confirmed, the CTC-driven switch to an alternate cytotoxic therapy was not effective in prolonging overall survival for MBC patients with persistently increased CTCs after 21 days of therapy [66]. The inconvenient of these kinds of interventional biomarker-driven studies is the fact that the result is dependent of the therapy efficacy. This strategy can only work if there is an efficient therapy for the cohort identified by the test.
Another promising approach is the stratification of patients to chemotherapy or hormonal therapy based on CTC enumeration like in the interventional STIC CTC METABREAST clinical trial (NCT0 1,710,605) for MBC patients [67]. Besides CTC enumeration, stratification based on CTC phenotype might become also an important strategy. Stratification of MBC patients based on HER2 status of CTCs is currently tested in the DETECT III trial [67].
Other possible uses for CTC detection include prognostication in early stage patients, identifying patients requiring adjuvant therapy. The SUCCESS study provides strong evidence of the prognostic relevance of CTCs in early breast cancer before and after adjuvant chemotherapy in a large patient cohort [68]. This study outlines the potential of the CTC analysis at primary diagnostic to evaluate individual risk and points that they may use for treatment management in early stage of cancer. These data have been confirmed by Bidard et al. who conducted a meta-analysis in nonmetastatic breast cancer patients treated by neoadjuvant chemotherapy (NCT) to assess the clinical validity of CTC detection as a prognostic marker [69]. They showed that CTC count is an independent and quantitative prognostic factor in early breast cancer patients treated by NCT.
4.2 Prostate
For men with metastatic castration-resistant prostate cancer (mCRPC), the CELLSEARCH® system method for CTCs enumeration is the only FDA-cleared CTC test available clinically. The CTC count has been shown to provide prognostic value and was associated with treatment response in mCRPC patients, in several recent studies [4, 71, 72, 73], indicating a clear value as a patient-level indicator of survival. However, despite increasing evidence that CTCs could be used to monitor disease progression in mCRPC [18], CTC use is still limited to clinical trials in academic centers. Clinical utility of CTCs, reflecting the ability of this test to favorably change outcomes, is still an unmet clinical need in prostate cancer [74]. The first interventional clinical trial in prostate cancer that will show the clinical utility of CTCs should start in 2019 (TACTIK project—NCT03101046).
Moreover new data suggest that CTCs may harbor genetic information (such as the androgen receptor splice variant 7, AR-V7) relevant to changing clinical management and predicting treatment sensitivity or resistance to cancer therapies such as enzalutamide, abiraterone, and taxane-based chemotherapies [39].
Regarding nonmetastatic cancer patient, a recent European TRANSCAN study CTC-SCAN investigated the feasibility of detecting CTCs in nonmetastatic high-risk prostate cancer (PCa) patients by combining the CELLSEARCH® platform, the in vivo CellCollector® capture system, and the EPISPOT assay. The observed correlation, with established risk factors and the persistence of CTCs 3 months after surgery, suggested a potential clinical relevance of CTCs as markers of minimal residual disease (MRD) in PCa [75]. CTC-based liquid biopsies have the potential to monitor MRD in patients with nonmetastatic prostate cancer although follow-up evaluations are now required to assess how to provide independent prognostic information. A new European project (Transcan—PROLIPSY) will assess whether CTCs in combination with exosomes and ctDNA as noninvasive
4.3 Colon
In 2008, Cohen et al. demonstrated the independent prognostic and predictive value of CTCs for patients initiating chemotherapy for metastatic colorectal cancer (mCRC) [2]. Since this first publication defining a cutoff of three CTCs, different meta-analyses have confirmed that baseline levels of CTC count is an important prognostic factor for PFS and OS in patients with mCRC [76, 77, 78].
Despite the strong evidence of a prognostic significance of CTC count, there is no solid evidence demonstrating the interest of CTC count for therapeutic strategy, and this biomarker is rarely used in the management of patients with mCRC. However, patients with high CTC counts recruited in a phase II study could benefit from a more intense chemotherapeutic regimen [79]. These preliminary data require validation in randomized trials. Moreover, Lalmahomed et al. failed to show a prognostic effect of CTCs for early relapse after the resection of colorectal liver metastases [80].
4.4 Lung
The role of CTCs in non-small cell lung cancer (NSCLC) has been addressed in several clinical trials. More specifically, the prediction of the outcome of patients with early and advanced NSCLC based on the CTC enumeration has been explored. The CTC count with the CELLSEARCH® system in advanced NSCLC patients who received standard chemotherapy was associated with a shorter PFS and OS, but standardize cutoff could not be observed [81, 82, 83, 84]. Furthermore, analysis of CTCs from patients with metastatic NSCLC identified the expected EGFR-activating mutation in CTCs from 11 of 12 patients (92%) and in matched free plasma DNA from 4 of 12 patients (33%) [85]. The T790 M mutation, which confers drug resistance, was revealed in CTCs from patients who had received tyrosine kinase inhibitors, suggesting the strong potential gain of noninvasive liquid biopsy. Moreover, serial increases in CTC counts were associated with tumor progression, with the emergence of additional EGFR mutations in some cases. Recently, KRAS and EGFR mutations, relevant for treatment decisions, could be detected in CTCs and in the corresponding primary tumors of the same patients [86].
5. Other circulating biomarkers as liquid biopsy
Even if the term “
5.1 Circulating tumor DNA
Apoptotic and necrotic tumor cells are known to discharge cell-free nucleic acid fragments into the bloodstream of cancer patients. Although most circulating DNA is believed to originate from nonmalignant cells, an increased level of cfDNA was observed in blood of patients with late stage cancer [87]. Among the pool of total cfDNA, there is circulating tumor DNA (ctDNA) which cannot be specifically isolated from the total pool but can be detected by tumor-specific mutations [88]. In general, cfDNA can be analyzed from plasma by targeted or untargeted approaches. The targeted approaches involve the detection of known genetic changes, e.g., “druggable” mutations, with impact on therapy decisions [89]. The interest of cfDNA was demonstrated by Douillard et al. [90] by determining the EGFR mutational status in NSCLC and can represent a substitute for tissue biopsies when these are not available. Moreover, in 2016, the detection of EGFR gene mutations in cfDNA using the cobas EGFR Mutation Test v2 achieved FDA approval as a companion diagnostic for erlotinib, becoming the first blood-based biopsy test approved for implementation in clinical decisions [91].
However, despite the evidence of potential clinical utility and even if it has been recommended (e.g., by the FDA) that the blood could be analyzed first to reduce the number of invasive biopsies in cancer patients, the lower sensitivity of ctDNA analyses prevents its use in clinical management for the moment, and the primary tumor analysis still remains the gold standard in NSCLC diagnostics of EGFR mutations.
5.2 MicroRNAs
MicroRNAs (miRNAs, miR-x), consisting in approximately 22 nucleotides, represent another potential blood biomarker in oncology. These noncoding small RNAs are master regulators of genic expression and consequently of many cellular processes. Alterations in the expression of microRNA genes have been shown to play in important role in human malignancies. These alterations can be caused by a variety of mechanisms, including deletions, amplifications, or mutations involving microRNA loci, by epigenetic silencing or by dysregulation of transcription factors targeting specific microRNAs [92]. The three major detection techniques for circulating cell-free miRNA (cfmiRNA) analysis, following RNA extraction, comprise quantitative RT-PCR, microarray analyses, and deep sequencing. The assessment of cfmiRNA has been suggested for early diagnosis, prognosis, therapy monitoring, and therapeutic response prediction in different cancer types (e.g., lung, breast, colon, prostate, and ovary cancers and melanoma), as reviewed by Armand-Labit and Pradines [93].
5.3 Exosomes
Tumor and normal cells are known to release microvesicles such as exosomes (40–150 nm) into the circulation, discharging cellular content. Currently, one challenge for the analyses of circulating cell-free nucleic acids in blood is their instability. Thus, due to their protective environment, the exosomes represent a valuable source for analysis of proteins, DNA, RNA, miRNA, lipids, and metabolites [94]. Ultracentrifugation, density-based separation, or immune-affinity capture using magnetic beads coated with anti-EpCAM antibodies can be used to isolate exosomes [95]. They are important regulators of the cellular niche, and their altered characteristics in many diseases, such as cancer, suggest their importance for diagnostic and therapeutic applications and as drug delivery vehicles. Hoshino et al. demonstrated that the composition of exosomal integrins could predict organ-specific metastasis and that tumor-derived exosomes participate in preparing the pre-metastatic niche [96]. Correspondingly, the same group shows that a pro-metastatic phenotype of bone marrow progenitor cells is promoted by education through melanoma exosomes [97].
5.4 Tumor-educated platelets
A new emerging class of components for
Furthermore, biomarkers (MET or HER2 expression/KRAS, EGFR, and PIK3CA mutations) were identified in surrogate TEP mRNA profiles, which might be tested in future studies as potential predictors for targeted therapies. Recently, Diem et al. showed that elevated pretreatment platelet-to-lymphocyte ratios correlate with a reduced response rate to nivolumab anti-PD-L1 immunotherapy in NSCLC [100], indicating that circulating platelets may enhance a pro-tumorigenic effect in the presence of an antitumor immune response.
6. Conclusion
CTC as
Additionally, an extensive work has been made to understand biological processes of cancer dissemination and metastasis, underlying different aspects for CTCs survival in bloodstream. This knowledge could improve pharmaceutical drug researches and therapeutic strategies for better clinical management of cancer patients.
Beside CTC analysis several other circulating biomarkers are under investigations and demonstrate real valuable data. It is now well accepted that there is not a perfect unique biomarker and that combining different circulating biomarkers can bring a huge benefit for precision medicine for cancer patients.
In conclusion,
Acknowledgments
The authors received support from (1) the National Institute of Cancer (INCa, http://www.e-cancer.fr), (2) CANCER-ID, an Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115749, resources of which are composed of financial contribution from the European Union’s Seventh Framework Program (FP7/2007-2013) (www.cancer-id.eu) and EFPIA companies’ in-kind contribution, (3) ARC Foundation, (4) Ligue contre le cancer, and (5) the ELBA—Innovative Training Networks (ITN) H2020—European Liquid Biopsies Academy project—Toward widespread clinical application of blood-based diagnostic tools. H2020-MSCA-ITN-2017 (http://elba.uni-plovdiv.bg).
References
- 1.
Pantel K, Alix-Panabieres C. Circulating tumour cells in cancer patients: Challenges and perspectives. Trends in Molecular Medicine. 2010; 16 (9):398-406 - 2.
Cohen SJ et al. Relationship of circulating tumor cells to tumor response, progression-free survival, and overall survival in patients with metastatic colorectal cancer. Journal of Clinical Oncology. 2008; 26 (19):3213-3221 - 3.
Cristofanilli M et al. Circulating tumor cells, disease progression, and survival in metastatic breast cancer. New England Journal of Medicine. 2004; 351 (8):781-791 - 4.
de Bono JS et al. Circulating tumor cells predict survival benefit from treatment in metastatic castration-resistant prostate cancer. Clinical Cancer Research. 2008; 14 (19):6302-6309 - 5.
Bidard FC et al. Clinical validity of circulating tumour cells in patients with metastatic breast cancer: A pooled analysis of individual patient data. The Lancet Oncology. 2014; 15 (4):406-414 - 6.
Zhang L et al. Meta-analysis of the prognostic value of circulating tumor cells in breast cancer. Clinical Cancer Research. 2012; 18 (20):5701-5710 - 7.
Alix-Panabieres C, Mader S, Pantel K. Epithelial-mesenchymal plasticity in circulating tumor cells. Journal of Molecular Medicine. 2017; 95 (2):133-142 - 8.
Baccelli I et al. Identification of a population of blood circulating tumor cells from breast cancer patients that initiates metastasis in a xenograft assay. Nature Biotechnology. 2013; 31 (6):539-544 - 9.
Yang L et al. Optimization of an enrichment process for circulating tumor cells from the blood of head and neck cancer patients through depletion of normal cells. Biotechnology and Bioengineering. 2009; 102 (2):521-534 - 10.
Lara O et al. Enrichment of rare cancer cells through depletion of normal cells using density and flow-through, immunomagnetic cell separation. Experimental Hematology. 2004; 32 (10):891-904 - 11.
Desitter I et al. A new device for rapid isolation by size and characterization of rare circulating tumor cells. Anticancer Research. 2011; 31 (2):427-441 - 12.
Farace F et al. A direct comparison of CellSearch and ISET for circulating tumour-cell detection in patients with metastatic carcinomas. British Journal of Cancer. 2011; 105 (6):847-853 - 13.
Adams DL et al. The systematic study of circulating tumor cell isolation using lithographic microfilters. RSC Advances. 2014; 9 :4334-4342 - 14.
Adams DL et al. Cytometric characterization of circulating tumor cells captured by microfiltration and their correlation to the CellSearch((R)) CTC test. Cytometry. Part A. 2015; 87 (2):137-144 - 15.
Xu L et al. Optimization and evaluation of a novel size based circulating tumor cell isolation system. PLoS One. 2015; 10 (9):e0138032 - 16.
Lemaire CA et al. Fast and label-free isolation of circulating tumor cells from blood: From a research microfluidic platform to an automated fluidic instrument, VTX-1 liquid biopsy system. SLAS Technology. 2018; 23 (1):16-29 - 17.
Esmaeilsabzali H et al. Detection and isolation of circulating tumor cells: Principles and methods. Biotechnology Advances. 2013; 31 (7):1063-1084 - 18.
Riethdorf S, Wikman H, Pantel K. Review: Biological relevance of disseminated tumor cells in cancer patients. International Journal of Cancer. 2008; 123 (9):1991-2006 - 19.
Chebouti I et al. ERCC1-expressing circulating tumor cells as a potential diagnostic tool for monitoring response to platinum-based chemotherapy and for predicting post-therapeutic outcome of ovarian cancer. Oncotarget. 2017; 8 (15):24303-24313 - 20.
Fehm T et al. Detection and characterization of circulating tumor cells in blood of primary breast cancer patients by RT-PCR and comparison to status of bone marrow disseminated cells. Breast Cancer Research. 2009; 11 (4):R59 - 21.
Soler A et al. EpCAM-independent enrichment and detection of viable circulating tumor cells using the EPISPOT assay. Methods in Molecular Biology. 2017; 1634 :263-276 - 22.
Cayrefourcq L et al. Establishment and characterization of a cell line from human circulating colon cancer cells. Cancer Research. 2015; 75 (5):892-901 - 23.
Tang Y et al. High-throughput screening of rare metabolically active tumor cells in pleural effusion and peripheral blood of lung cancer patients. Proceedings of the National Academy of Sciences USA. 4 Apr 2017; 114 (14):E2983. DOI: 10.1073/pnas.1703650114. Epub 2017 Mar 27 - 24.
Riethdorf S et al. Detection and HER2 expression of circulating tumor cells: Prospective monitoring in breast cancer patients treated in the neoadjuvant GeparQuattro trial. Clinical Cancer Research. 2010; 16 (9):2634-2645 - 25.
Jaeger BAS et al. The HER2 phenotype of circulating tumor cells in HER2-positive early breast cancer: A translational research project of a prospective randomized phase III trial. PLoS One. 2017; 12 (6):e0173593 - 26.
Topalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: A common denominator approach to cancer therapy. Cancer Cell. 2015; 27 (4):450-461 - 27.
Mazel M et al. Frequent expression of PD-L1 on circulating breast cancer cells. Molecular Oncology. 2015; 9 (9):1773-1782 - 28.
Heitzer E et al. Complex tumor genomes inferred from single circulating tumor cells by array-CGH and next-generation sequencing. Cancer Research. 2013; 73 (10):2965-2975 - 29.
Abonnenc M et al. Programmable interactions of functionalized single bioparticles in a dielectrophoresis-based microarray chip. Analytical Chemistry. 2013; 85 (17):8219-8224 - 30.
Fabbri F et al. Detection and recovery of circulating colon cancer cells using a dielectrophoresis-based device: KRAS mutation status in pure CTCs. Cancer Letters. 2013; 335 (1):225-231 - 31.
Mesquita B et al. Molecular analysis of single circulating tumour cells following long-term storage of clinical samples. Molecular Oncology. 2017; 11 (12):1687-1697 - 32.
Paolillo C et al. Detection of activating Estrogen receptor gene (ESR1) mutations in single circulating tumor cells. Clinical Cancer Research. 2017; 23 (20):6086-6093 - 33.
Paoletti C et al. Comprehensive mutation and copy number profiling in archived circulating breast cancer tumor cells documents heterogeneous resistance mechanisms. Cancer Research. 2018; 78 (4):1110-1122 - 34.
Sho S et al. Precision oncology using a limited number of cells: Optimization of whole genome amplification products for sequencing applications. BMC Cancer. 2017; 17 (1):457 - 35.
Denis JA, Lacorte JM. Detection of RAS mutations in circulating tumor cells: Applications in colorectal cancer and prospects. Annales de Biologie Clinique. 2017; 75 (6):607-618 - 36.
Obermayr E et al. Circulating tumor cells: Potential markers of minimal residual disease in ovarian cancer? A study of the OVCAD consortium. Oncotarget. 2017; 8 (63):106415-106428 - 37.
Podolak J et al. Androgen receptor amplification is concordant between circulating tumor cells and biopsies from men undergoing treatment for metastatic castration resistant prostate cancer. Oncotarget. 2017; 8 (42):71447-71455 - 38.
El-Heliebi A et al. In situ detection and quantification of AR-V7, AR-FL, PSA, and KRAS point mutations in circulating tumor cells. Clinical Chemistry. 2018; 64 (3):536-546 - 39.
Antonarakis ES et al. Androgen receptor splice variant 7 and efficacy of taxane chemotherapy in patients with metastatic castration-resistant prostate cancer. JAMA Oncology. 2015; 1 (5):582-591 - 40.
Scher HI et al. Association of ar-v7 on circulating tumor cells as a treatment-specific biomarker with outcomes and survival in castration-resistant prostate cancer. JAMA Oncology. 2016; 2 (11):1441-1449 - 41.
Zhang L et al. The identification and characterization of breast cancer CTCs competent for brain metastasis. Science Translational Medicine. 2013; 5 (180):180ra48 - 42.
Yu M et al. Circulating tumor cells: Approaches to isolation and characterization. The Journal of Cell Biology. 2011; 192 (3):373-382 - 43.
Gao D et al. Organoid cultures derived from patients with advanced prostate cancer. Cell. 2014; 159 (1):176-187 - 44.
Zhang Z et al. Expansion of CTCs from early stage lung cancer patients using a microfluidic co-culture model. Oncotarget. 2014; 5 (23):12383-12397 - 45.
Kulasinghe A et al. Short term ex-vivo expansion of circulating head and neck tumour cells. Oncotarget. 2016; 7 (37):60101-60109 - 46.
Alix-Panabieres C et al. Molecular portrait of metastasis-competent circulating tumor cells in colon cancer reveals the crucial role of genes regulating energy metabolism and DNA repair. Clinical Chemistry. 2017; 63 (3):700-713 - 47.
Soler A et al. Autologous cell lines from circulating colon cancer cells captured from sequential liquid biopsies as model to study therapy-driven tumor changes. Scientific Reports. 2018; 8 (1):15931 - 48.
Nieto MA et al. EMT: 2016. Cell. 2016; 166 (1):21-45 - 49.
Jie XX, Zhang XY, Xu CJ. Epithelial-to-mesenchymal transition, circulating tumor cells and cancer metastasis: Mechanisms and clinical applications. Oncotarget. 2017; 8 (46):81558-81571 - 50.
Kallergi G et al. Epithelial to mesenchymal transition markers expressed in circulating tumour cells of early and metastatic breast cancer patients. Breast Cancer Research. 2011; 13 (3):R59 - 51.
Papadaki MA et al. Co-expression of putative stemness and epithelial-to-mesenchymal transition markers on single circulating tumour cells from patients with early and metastatic breast cancer. BMC Cancer. 2014; 14 :651 - 52.
Alonso-Alconada L et al. Molecular profiling of circulating tumor cells links plasticity to the metastatic process in endometrial cancer. Molecular Cancer. 2014; 13 :223 - 53.
Chang K et al. Combination of circulating tumor cell enumeration and tumor marker detection in predicting prognosis and treatment effect in metastatic castration-resistant prostate cancer. Oncotarget. 2015; 6 (39):41825-41836 - 54.
Polioudaki H et al. Variable expression levels of keratin and vimentin reveal differential EMT status of circulating tumor cells and correlation with clinical characteristics and outcome of patients with metastatic breast cancer. BMC Cancer. 2015; 15 :399 - 55.
Zhao R et al. Expression and clinical relevance of epithelial and mesenchymal markers in circulating tumor cells from colorectal cancer. Oncotarget. 2017; 8 (6):9293-9302 - 56.
Kim YN et al. Anoikis resistance: An essential prerequisite for tumor metastasis. International Journal of Cell Biology. 2012; 2012 :306879 - 57.
Simpson CD, Anyiwe K, Schimmer AD. Anoikis resistance and tumor metastasis. Cancer Letters. 2008; 272 (2):177-185 - 58.
Steinert G et al. Immune escape and survival mechanisms in circulating tumor cells of colorectal cancer. Cancer Research. 2014; 74 (6):1694-1704 - 59.
Ohaegbulam KC et al. Human cancer immunotherapy with antibodies to the PD-1 and PD-L1 pathway. Trends in Molecular Medicine. 2015; 21 (1):24-33 - 60.
Lou X-L et al. Interaction between circulating cancer cells and platelets: Clinical implication. Chinese Journal of Cancer Research. 2015; 27 (5):450-460 - 61.
Hong Y, Fang F, Zhang Q. Circulating tumor cell clusters: What we know and what we expect (review). International Journal of Oncology. 2016; 49 (6):2206-2216 - 62.
Abbott NJ, Rönnbäck L, Hansson E. Astrocyte–endothelial interactions at the blood–brain barrier. Nature Reviews Neuroscience. 2006; 7 :41 - 63.
Aceto N et al. Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis. Cell. 2014; 158 (5):1110-1122 - 64.
Hou JM et al. Circulating tumor cells as a window on metastasis biology in lung cancer. The American Journal of Pathology. 2011; 178 (3):989-996 - 65.
Peeters DJ et al. Circulating tumour cells and lung microvascular tumour cell retention in patients with metastatic breast and cervical cancer. Cancer Letters. 2015; 356 (2 Pt B):872-879 - 66.
Smerage JB et al. Circulating tumor cells and response to chemotherapy in metastatic breast cancer: SWOG S0500. Journal of Clinical Oncology. 2014; 32 (31):3483-3489 - 67.
Bidard FC et al. Clinical application of circulating tumor cells in breast cancer: Overview of the current interventional trials. Cancer Metastasis Reviews. 2013; 32 (1-2):179-188 - 68.
Rack B et al. Circulating tumor cells predict survival in early average-to-high risk breast cancer patients. JNCI Journal of the National Cancer Institute. 2014; 106 (5):dju066 - 69.
Bidard FC et al. Circulating tumor cells in breast cancer patients treated by neoadjuvant chemotherapy: A meta-analysis. Journal of the National Cancer Institute. 2018; 110 (6):560-567 - 70.
Trapp E et al. Presence of circulating tumor cells in high-risk early breast cancer during follow-up and prognosis. Journal of the National Cancer Institute. 11 Oct 2018. DOI: 10.1093/jnci/djy152. [Epub ahead of print] - 71.
Scher HI et al. Circulating tumor cell biomarker panel as an individual-level surrogate for survival in metastatic castration-resistant prostate cancer. Journal of Clinical Oncology. 2015; 33 (12):1348-1355 - 72.
Scher HI et al. Circulating tumor cell number as a prognostic marker in progressive castration-resistant prostate cancer: Use in clinical practice and clinical trials. The Lancet Oncology. 2009; 10 (3):233-239 - 73.
Scher HI et al. Circulating tumour cells as prognostic markers in progressive, castration-resistant prostate cancer: A reanalysis of IMMC38 trial data. The Lancet Oncology. 2009; 10 (3):233-239 - 74.
Lorente D et al. Interrogating metastatic prostate cancer treatment switch decisions: A multi-institutional survey. European Urology Focus. 2018; 4 (2):235-244 - 75.
Kuske A et al. Improved detection of circulating tumor cells in non-metastatic high-risk prostate cancer patients. Scientific Reports. 2016; 6 :39736 - 76.
Groot Koerkamp B et al. Circulating tumor cells and prognosis of patients with Resectable colorectal liver metastases or widespread metastatic colorectal cancer: A meta-analysis. Annals of Surgical Oncology. 2013; 20 (7):2156-2165 - 77.
Huang X et al. Meta-analysis of the prognostic value of circulating tumor cells detected with the CellSearch System in colorectal cancer. BMC Cancer. 2015; 15 :202 - 78.
Rahbari NN et al. Meta-analysis shows that detection of circulating tumor cells indicates poor prognosis in patients with colorectal cancer. Gastroenterology. 2010; 138 (5):1714-1726 - 79.
Krebs MG et al. Circulating tumor cell enumeration in a phase II trial of a four-drug regimen in advanced colorectal cancer. Clinical Colorectal Cancer. 2015; 14 (2):115-122.e1-2 - 80.
Lalmahomed ZS et al. Prognostic value of circulating tumour cells for early recurrence after resection of colorectal liver metastases. British Journal of Cancer. 2015; 112 (3):556-561 - 81.
Hirose T et al. Relationship of circulating tumor cells to the effectiveness of cytotoxic chemotherapy in patients with metastatic non-small-cell lung cancer. Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics. 2012; 20 (2-3):131-137 - 82.
Krebs MG et al. Evaluation and prognostic significance of circulating tumor cells in patients with non-small-cell lung cancer. Journal of Clinical Oncology. 2011; 29 (12):1556-1563 - 83.
Muinelo-Romay L et al. Evaluation of circulating tumor cells and related events as prognostic factors and surrogate biomarkers in advanced NSCLC patients receiving first-line systemic treatment. Cancers. 2014; 6 (1):153 - 84.
Xu YH, Zhou J, Pan XF. Detecting circulating tumor cells in patients with advanced non-small cell lung cancer. Genetics and Molecular Research. 2015; 14 (3):10352-10358 - 85.
Maheswaran S et al. Detection of mutations in EGFR in circulating lung-cancer cells. The New England Journal of Medicine. 2008; 359 (4):366-377 - 86.
Gorges TM et al. Enumeration and molecular characterization of tumor cells in lung cancer patients using a novel in vivo device for capturing circulating tumor cells. Clinical Cancer Research. 2016; 22 (9):2197-2206 - 87.
Leon SA et al. Free DNA in the serum of cancer patients and the effect of therapy. Cancer Research. 1977; 37 (3):646-650 - 88.
Pantel K, Alix-Panabières C. Real-time liquid biopsy in cancer patients: Fact or fiction? Cancer Research. 2013; 73 (21):6384-6388 - 89.
Heitzer E, Ulz P, Geigl JB. Circulating tumor DNA as a liquid biopsy for cancer. Clinical Chemistry. 2015; 61 (1):112-123 - 90.
Douillard JY et al. Gefitinib treatment in EGFR mutated Caucasian NSCLC: Circulating-free tumor DNA as a surrogate for determination of EGFR status. Journal of Thoracic Oncology. 2014; 9 (9):1345-1353 - 91.
Webb S. The cancer bloodhounds. Nature Biotechnology. 2016; 34 (11):1090-1094 - 92.
Croce CM. Causes and consequences of microRNA dysregulation in cancer. Nature Reviews. Genetics. 2009; 10 (10):704-714 - 93.
Armand-Labit V, Pradines A. Circulating cell-free microRNAs as clinical cancer biomarkers. Biomolecular Concepts. 2017; 8 (2):61-81 - 94.
Kalluri R. The biology and function of exosomes in cancer. The Journal of Clinical Investigation. 2016; 126 (4):1208-1215 - 95.
Greening DW et al. A protocol for exosome isolation and characterization: Evaluation of ultracentrifugation, density-gradient separation, and immunoaffinity capture methods. Methods in Molecular Biology. 2015; 1295 :179-209 - 96.
Hoshino A et al. Tumour exosome integrins determine organotropic metastasis. Nature. 2015; 527 (7578):329-335 - 97.
Peinado H et al. Melanoma exosomes educate bone marrow progenitor cells toward a pro-metastatic phenotype through MET. Nature Medicine. 2012; 18 (6):883-891 - 98.
Best MG et al. RNA-Seq of tumor-educated platelets enables blood-based Pan-cancer, multiclass, and molecular pathway cancer diagnostics. Cancer Cell. 2015; 28 (5):666-676 - 99.
Stone RL et al. Paraneoplastic thrombocytosis in ovarian cancer. The New England Journal of Medicine. 2012; 366 (7):610-618 - 100.
Diem S et al. Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) as prognostic markers in patients with non-small cell lung cancer (NSCLC) treated with nivolumab. Lung Cancer. 2017; 111 :176-181