Clinical Advances in Hematology & Oncology

January 2017 - Volume 15, Issue 1

Circulating Tumor Cells in Prostate Cancer: Beyond Enumeration

Jie-Fu Chen, MD, Yi-Tsung Lu, MD, Shirley Cheng, BS, Hsian-Rong Tseng, PhD, Robert A. Figlin, MD, and Edwin M. Posadas, MD

Dr Chen is affiliated with the Urologic Oncology Program and the Translational Oncology Program at the Samuel Oschin Comprehensive Cancer Institute at Cedars-Sinai Medical Center in Los Angeles, California. Dr Lu is affiliated with the Urologic Oncology Program at the Samuel Oschin Comprehensive Cancer Institute at Cedars-Sinai Medical Center and the Department of Internal Medicine at John H. Stroger, Jr. Hospital of Cook County in Chicago, Illinois. Dr Cheng is affiliated with the Urologic Oncology Program at the Samuel Oschin Comprehensive Cancer Institute at Cedars-Sinai Medical Center. Dr Tseng is affiliated with the California Nanosystems Institute and the Department of Molecular Pharmacology at the University of California, Los Angeles. Dr Figlin and Dr Posadas are affiliated with the Urologic Oncology Program, the Translational Oncology Program, and the Division of Hematology/Oncology in the Department of Medicine at Cedars-Sinai Medical Center. Drs Chen and Lu contributed equally to this article.

Corresponding author:
Edwin M. Posadas, MD
Director, Translational Oncology Program
Medical Director, Urologic Oncology Program
Samuel Oschin Comprehensive Cancer Institute
Cedars-Sinai Medical Center
8700 Beverly Blvd
Los Angeles, CA 90048
Tel: (310) 423-7600
Fax: (310) 967-3841


Abstract: Circulating tumor cells (CTCs) are a population of rare cancer cells that have detached from the primary tumor and/or metastatic lesions and entered the peripheral circulation. Enumeration of CTCs has demonstrated value as a prognostic biomarker, and newer studies have pointed to information beyond enumeration that is of critical importance in prostate cancer. Technologic advances that permit examination of the morphology, function, and molecular content of CTCs have made it possible to measure these factors as part of liquid biopsy. These advances provide a way to study tumor evolution and the development of resistance to therapy. Recent breakthroughs have created new applications for CTCs that will affect the care of patients with prostate cancer.


Prostate cancer (PC) continues to be the most common cancer affecting men in the United States and was the second leading cause of cancer death in 2016. This translates to 220,000 new diagnoses and 27,500 deaths1—figures that are unacceptable. Tremendous advances have been made in our understanding of this disease, and recent data are leading to new classification schema2,3 and prognostication tools4 that are based on molecular characteristics. These advances ultimately will result in the development and implementation of therapeutic strategies that will further reshape our approach to prostate cancer. Nonetheless, the clinical classification of PC in 2016 has not evolved significantly beyond Gleason grading and TNM (tumor, node, metastasis) staging.

Most of the advances in PC research stem from molecular profiling of tissue samples obtained from prostatectomy and core needle biopsies. As such, the bulk of the information is derived from historical and relatively untreated tissue. Even now, the current standard of practice in PC (in contrast to that for other solid and liquid malignancies) does not involve regular tissue biopsy for the molecular characterization of disease over time. Through carefully planned clinical studies involving tissue biopsies and a limited number of autopsy series, scientists in the field have gained biological insight into metastatic castration-resistant PC (mCRPC) at the time of death. However, few centers conduct tissue-oriented studies during the interval between diagnosis and death to investigate the dynamic and evolving biology of mCRPC in the face of newer therapies. Organizations such as the National Cancer Institute, the US Department of Defense, and the Prostate Cancer Foundation have supported important efforts to address this need.

Obtaining tumor tissues from patients with mCRPC is particularly challenging because most bone lesions are osteoblastic. First, most patients do not wish to undergo serial bone biopsies, especially those requiring significant instrumentation, such as drills for cutting through osseous metastases. Second, many interventional radiologists lack experience in sampling viable tumor cells from osteoblastic lesions. These procedures yield useful samples in approximately 60% to 70% of cases. Third, bone biopsies or bone marrow aspirates include solid pieces of bone that must be removed or decalcified, putting the valuable information within tumor cells at risk for loss or degradation during processing.

In contrast to the difficulties with tissue biopsy, blood-based characterization of disease behavior is fairly simple and extremely common in PC. Frequent measurement of serum prostate-specific antigen (PSA) levels is standard. Measurement of PSA has been used for decades to monitor responses to a variety of therapies, including surgery, radiation, androgen receptor (AR) inhibition, and even taxane-based chemotherapy. For certain forms of therapy, such as radionuclide therapy and immunotherapy, PSA changes have been less useful to predict therapeutic benefit. The Prostate Cancer Working Group 3 cautions against making decisions based solely on changes in serum PSA concentration early in therapy, when patients are clinically well.5 Use of serum PSA exemplifies the ease of blood-based monitoring. This generates interest in developing other blood tests to overcome the limitations of tumor biopsies.6,7

Another important limitation of conventional approaches based on blood PSA is the inability to monitor atypical or anaplastic carcinomas of the prostate gland that cause diminished or absent PSA production. An important feature of these aggressive variants is the potential for the development of visceral metastases (VMs). VMs often progress rapidly and culminate in end-organ failure and death. In some cases, mCRPC with VMs is less dependent on AR activation and therefore more resistant to conventional AR-targeted therapies.8-10 It is recognized that serum PSA cannot predict the onset of these lethal events. Moreover, soft-tissue organs (eg, liver and lungs) are routinely monitored far less frequently in PC than in other malignancies. Without imaging of the viscera, VMs typically are found late in the course of the disease. With the increasing use of potent AR inhibitors, the frequency of VM events has also increased.8 Thus, a blood-based tool for monitoring these cancers is an unmet need.

In contrast to that in many other common solid tumors, the DNA mutation rate in PC is relatively low.2,11 One of the most frequently mutated genes in PC is SPOP, which has a mutation rate of less than 15%. Much of the research in PC, particularly in mCRPC, has focused on the transcriptome. Therefore, finding ways to characterize delicate and disease-related alterations in RNA remains important to the field.

Circulating tumor cells (CTCs) may provide a way to address limitations in the care of men with PC. CTCs, which are a population of rare cancer cells in the bloodstream, are either shed by or detached from the primary tumor and/or metastatic lesions. There are usually fewer than 100 CTCs in 1 mL of whole blood, compared with 109 hematologic cells in the same volume of blood.12-14 Their extremely low abundance has made the detection and characterization of CTCs technically challenging. To address this issue, numerous technologies have been developed. These new methods for isolating and studying CTCs bring with them the hope of uniting the basic and clinical sciences to allow the real-time dynamic profiling of relevant biological information.

Enumeration: the Initial Clinical Application of CTCs

In 2004, the US Food and Drug Administration (FDA) cleared the first device for CTC enrichment and enumeration.15 This system uses cell surface expression of epithelial cell adhesion molecule (EpCAM) to achieve cell separation. Magnetic beads conjugated with anti-EpCAM interact with fixed blood cells such that any EpCAM-expressing cells are coated with the beads and can later be separated out. Captured cells are released and stained for CK8, CK18, and CK19, as well as for leukocyte common antigen (CD45). CTCs are defined as CK+/CD45- nucleated objects. This device and approach have been used as an embedded biomarker in several therapeutic clinical trials (Table 1).

The first large-scale trial involving CTC enumeration was conducted in 2004 in patients with metastatic breast cancer. Here, enumeration of CTCs before and during therapy predicted both progression-free survival (PFS) and overall survival (OS).16 In a very short period, similar studies were conducted in other cancer types, including colorectal cancer,17,18 melanoma,17 lung cancer,18 and prostate cancer,19,20 with similar findings.

In the IMMC-38 study (Circulating Tumor Cells and Survival in Hormone Refractory Prostate Cancer Patients Receiving Chemotherapy),21 CTC enumerations were performed in patients with mCRPC who were starting cytotoxic chemotherapy. In this study, 231 patients were evaluated by serial CTC collection. CTC enumerations were defined as “favorable” if fewer than 5 CTCs were identified in 7.5 mL of blood, and as “unfavorable” if at least 5 CTCs were identified. The investigators found that patients with an unfavorable pretreatment CTC count had shorter OS (median OS, 11.5 vs 21.7 months; Cox hazard ratio [HR], 3.3; P<.001). Unfavorable CTC counts after treatment also predicted shorter OS (median OS, 6.7-9.5 vs 19.6-20.7 months; HR, 3.6-6.5; P<.001). CTC enumeration provided prognostic insight for various groups of patients; those who converted from an unfavorable CTC count at baseline to a favorable CTC count had better OS, at 21.3 vs 6.8 months. The OS of patients who converted from a favorable to an unfavorable CTC count was poorer than the OS of those whose CTC count remained favorable, at 9.3 vs 26 months. The investigators concluded that CTC count predicted OS. This study led to the FDA clearance of the CellSearch Circulating Tumor Cell Kit for clinical use in PC in 2008.

A subgroup analysis of the IMMC-38 study22 focused on men starting docetaxel. Baseline CTC count was one of several factors correlated with risk for death (HR, 1.58; P<.001). Changes in CTC number were also strongly associated with risk for death (P≤.001). Changes in PSA level were only modestly associated with risk for death (P=.04-.8). Two additional studies have confirmed that a favorable CTC count at 3 weeks after treatment is predictive of improved OS for patients with mCRPC receiving docetaxel-based chemotherapy. Studies with this platform have continued to be performed in contemporary investigations, including the TOPARP study (A Phase II Trial of Olaparib in Patients With Advanced Castration Resistant Prostate Cancer), in which conversion of CTC status was part of the composite measurement of benefit from poly(adenosine diphosphate-ribose) polymerase (PARP) inhibitor therapy.23

In contrast to studies of mCRPC or metastatic castration-sensitive disease,24 those of localized PC have generated fewer data, possibly owing to insufficient detection of events with the CellSearch approach. One study using a modification of the CellSearch protocol reported on CTC enumerations in 35 patients with clinically high-risk localized PC as defined by National Comprehensive Cancer Network criteria (disease stage ≥cT3a, Gleason score of 8-10, and/or PSA level >20 ng/mL).25 The investigators were able to detect CTCs in 49% of patients. There was no correlation between CTC count and biochemical recurrence after surgery. Using additional immunofluorescence, the same investigators found that the percentages of CD133-negative and E-cadherin–positive CTC fragments correlated with biochemical recurrence at 1 year after surgery.

As the technology in the CTC field has evolved, a larger number of needs and possibilities are being addressed. Many of the new systems (Table 2) offer technical advantages that create additional clinical opportunities. First, increased sensitivity has been reported with many of the developing systems, which remains important for clinical application.26 Second, several of the developing systems are less dependent on EpCAM expression, making it possible to identify aggressive biological alterations such as cells undergoing an epithelial-to-mesenchymal transition (EMT). It is believed that EMT plays a key role in the generation of CTCs.27,28 Third, several newer systems incorporate methods of identifying various CTC subpopulations. In recent studies, CTCs with specific morphologic or biochemical features have been associated with metastatic pattern29 and drug sensitivity.11,12 These findings point toward the use of CTC biomarkers beyond enumeration. Fourth, many developing systems avoid fixation that can restrict the types of molecular analyses of isolated CTCs.

Technologies for CTC Enrichment and Isolation

Flow cytometry historically has been one of the most powerful technologies for the detection and isolation of subpopulations of cells.12 Many groups have used this approach to detect CTCs. The introduction of multicolor flow cytometry allows the simultaneous analysis and/or sorting of CTCs on the basis of protein expression.30,31 The low abundance of CTCs, particularly in patients with lower-volume disease or atypical biology, has been a major challenge in the use of flow cytometry, prompting the development of alternative methods of CTC isolation.

Affinity-Based CTC Enrichment/Isolation Technologies 

Affinity-based enrichment relies on the interaction between capture agents (antibodies in most cases) and molecules on the cellular surface to either capture CTCs (positive selection) or deplete hematologic cells (negative selection). Typically, anti-EpCAM antibody is used for positive selection32,33 and anti-CD45 antibody for the depletion of unwanted leukocytes. Although this interaction is highly specific, issues of sensitivity arise with many of the platforms in the setting of limited or absent EpCAM expression.

Immunomagnetic approaches to separation use the expression of molecules on the cell surface to achieve effective enrichment. Capture agents are conjugated onto magnetic beads for either positive or negative selection.16 The CellSearch, MACS (magnetic-activated cell sorting),34 and AdnaTest35 assays fall into this category. Several other groups have combined immunomagnetics with either flow cytometry37 or microfluidic devices, such as MagSweeper,36 IsoFlux,37 VerIFAST,38 and CTC-iChip,39 to improve sensitivity and specificity. To improve accuracy, an immunofluorescence staining process targeting cancer-specific markers is often needed after CTC enrichment.

Non–Affinity-Based Technologies

A number of groups have taken the approach of using non-affinity mechanisms to capture CTCs. This approach inherently avoids the limitations that may be caused by the loss of EpCAM in cells undergoing EMT, which may be at risk for failed capture. Non–affinity-based technologies instead are based on features such as cellular size, invasive capacity, and protein expression and typically use immunofluorescent staining to identify CTCs. Filtration-based methods, such as ISET (isolation by size of epithelial tumor cells),40 take advantage of size differences between CTCs and hematopoietic cells. A large collection of kits/systems are now commercially available to support research utility. A similar approach was adopted to develop a microfluidic device specifically for isolating CTC clusters.41 Another physical property–based technology uses a dielectrophoretic field to separate CTCs (ApoStream),42 given the fact that the dielectric properties of CTCs are different from those of the other cells in circulation.

Aside from physical properties, the biological activities of cancer cells can also be used to enrich CTCs. The CAM (cell adhesion matrix) Vita-Assay isolates CTCs on the basis of the biological proclivity of metastatic tumor cells to invade collagenous matrices.43

Microfluidic Devices for CTC Enrichment/Isolation

Microfluidic devices facilitate the capture of CTCs by increasing the contact interactions between CTCs and capture agents. Typically, CTCs are immobilized when flowing through microfluidic channels coated with capture agents (usually anti-EpCAM). The nonselected blood components are washed through the channel and excluded.44-48 Variations on the physical device configuration have been used since the introduction of microfluidic devices, resulting in altered mechanical properties that have affected capture efficiency. Typical examples include herring bone structure (HBCTC-Chip)46 and patterned silicon nanowires (NanoVelcro Chip).49 Microfluidic devices can also be combined with other affinity-based or non–affinity-based CTC isolation mechanisms, such as immunomagnetic separation (CTC-iChip39 and VerIFAST38), size-based inertial focusing (Vortex50 and spiral microfluidics51), and acoustic separation.52,53 Recent advances in surface chemistry further allow efficient CTC release after capture.54-56

Direct CTC Identification

With the advances in high-throughput slide-scanning technologies and image-analyzing computer algorithms, it is now possible to identify CTCs with minimal enrichment. Platforms such as No Cell Left Behind57 and AccuCyte – CyteFinder58 use direct visualization and identification of CTCs after immunofluorescence staining of a blood smear. A variety of PC-related markers, including AR/AR-V7, PSA, and prostate-specific membrane antigen (PSMA), have been used to increase the chance of finding CTCs.59 Following the identification of CTCs, many of these platforms are now capable of recovering individual CTCs for further characterization.

Molecular and Phenotypic Profiling of CTCs

Improved methods of CTC capture have advanced our understanding of CTC biology. Several studies describe CTCs as a pool of tumor cells that are heterogeneous by morphology and biochemistry. Although enumeration of CTCs has already proved useful, additional information can be extracted from them. CTCs and the underlying tumor exist in a dynamic homeostasis based on the constant process of shedding and/or invasion/extrusion into the vasculature. Because of this balance between tumor and CTCs, they may be usable as an alternate source of cellular information to allow the minimally invasive and dynamic characterization of a cancer.

CTC Morphology

One study reported that in addition to ranging in size, CTCs cluster in groups of 2 to 50 cells. At times, these clusters contain tumor cells admixed not only with other tumor cells but also hematopoietic cells, such as leukocytes. CTC clusters were shown to be the precursor of metastases in breast cancer.60 As in classic cytopathology, these variations in morphology likely reflect functional and biological differences. Our group conducted a retrospective analysis of patients across a range of clinical PCs with varied metastatic burdens and sites of disease. In examining the distribution of cellular features, nuclear size correlated with metastatic behavior in mCRPC. In particular, CTCs with nuclei smaller than 9 μm were associated with VMs in mCRPC.29 In another study focusing on CTC morphology, Beltran and colleagues58 used the CTC platform from Epic Sciences and identified distinct features of CTCs from patients with neuroendocrine PC. These CTCs often present in clusters, exhibit reduced AR and cytokeratin (CK) expression, and are smaller than those from CRPC patients without atypical features, such as radiographic progression in the setting of a serum PSA of less than 1 ng/mL, VMs in the absence of PSA progression (defined by the Prostate Cancer Working Group 2 criteria), and/or elevated serum chromogranin A greater than 3-fold the upper limit of normal. These studies cast light on change in CTC morphology, which likely reflects the biology of the underlying PC and potentially can be a biomarker for the disease.

CTC Molecular Biology and Markers

Although much effort has been directed at obtaining pure CTC samples, some investigators have focused on the identification of key signals from CTCs to facilitate clinical translation. Several attempts have been made to detect genetic alterations commonly found in PC tumors. A typical example is the detection of TMPRSS2-ERG fusion in CTCs. This fusion event, the most common one among the ETS rearrangements, can be found in 27% to 79% of radical prostatectomy tissues61 and approximately 56% of biopsies from advanced PC.2 It leads to androgen-dependent expression of the ERG oncogene and exhibits prognostic value.62 In a study focusing on patients with mCRPC treated with abiraterone acetate (Zytiga, Janssen), Attard and colleagues demonstrated the detection of ERG rearrangements in CTCs by fluorescence in situ hybridization (FISH).63 The presence of ERG rearrangements in tumors and CTCs was associated with the magnitude of PSA decline in the patients receiving abiraterone. However, Danila and colleagues, in a later study of 48 patients, reported that TMPRSS2-ERG fusion in CTC alone does not predict the magnitude of PSA decline or clinical response to abiraterone.64 The prognostic value of CTC-based ERG rearrangements in clinical use is still unclear.

Another commonly tested genetic alteration in PC is the loss of PTEN, which has been associated with progression to CRPC. PTEN loss was often found coexisting with ERG rearrangements in both tumor tissues61 and CTCs.63 Although PTEN loss in CTCs seems to be associated with PTEN loss in tumor tissues in patients with mCRPC,65 the clinical significance of PTEN status in CTCs remains to be determined.

The search for CTC-derived biomarkers also puts substantial emphasis on the AR and its variants. In the field of AR biology, interest has developed in splice variants of AR that are of functional importance.66-68 AR splice variants (particularly the AR-V7 variant) have been associated with reduced efficacy of contemporary AR therapies, such as abiraterone and enzalutamide (Xtandi, Astellas/Medivation), in preclinical models.69,70 Given the highly focused nature of the molecular signal being pursued, Antonarakis and colleagues characterized AR-V7 expression in CTCs from men undergoing therapy with abiraterone and enzalutamide.35 By using a modification of the AdnaTest, they were able to measure AR-V7 expression in patients with mCRPC and found that AR-V7 expression was associated with a greater likelihood of resistance to AR-targeted therapy. This series has been expanded to 200 patients who are classified as positive or negative for CTCs; CTC-positive patients are further classified as positive or negative for AR-V7.71 The evolution is significant in understanding the importance of enrichment because CTC-negative patients are essentially unclassifiable with regard to AR-V7 status. This CTC-based biomarker may help physicians to select between AR-targeted therapy and taxanes because AR-V7 expression does not predict resistance to taxane therapy.72,73

The AR-V7 CTC assay was incorporated as part of ARMOR (A Study of Galeterone Compared to Enzalutamide in Men Expressing Androgen Receptor Splice Variant-7 mRNA Metastatic CRPC; NCT02438007), an attempted phase 3 study in a population expressing AR-V7 that its data-monitoring committee recently closed because of futility. The study was designed to measure the efficacy of galeterone in a population of patients with AR-V7 expression. Given the difficulty of establishing a molecular diagnosis in patients with mCRPC, ARMOR allowed the use of a CTC-based assay for AR-V7. The assay itself combined immunomagnetic separation and polymerase chain reaction (PCR)–based amplification of both AR-V7 and full-length AR (AR-FL). For the assay result to be read as positive, sufficient CTCs were required in the initial purification. Second, both AR-FL and AR-V7 had to be detected by PCR within a prespecified ratio. As such, a concern in the earlier-stage disease group was the number of CTCs detectable with this methodology and so the capacity to detect AR transcripts. Had the study been successful, it would have, as an additional aim, validated the AR-V7 CTC assay. Although the assay is now available through The Johns Hopkins Hospital, its usefulness in the clinical setting remains unclear. This experience highlights an unfulfilled need that may be met in the future by assays with better sensitivity in the detection of disease-relevant markers in CTCs. Studies also have been conducted to explore other AR variants in CTCs and their clinical significance.74

Recently, with the rapid development of immuno-oncology and immune checkpoint inhibitors, the expression of programmed death ligand 1 (PD-L1) on CTCs has been tested for its clinical significance. Several groups have demonstrated a high level of PD-L1 expression detected in CTCs from patients with PC that is resistant to enzalutamide,75 and it may be associated with shorter survival.76 However, these findings and the association with response or resistance to checkpoint blockade still require further investigation in larger studies.

The Hopkins studies previously described, along with other findings in the field, point to the utility of CTC-based biomarkers and biology in the clinical setting. Within the pool of CTCs are subsets of cells with specific biological properties. These actively metastasizing cells have the capacity to invade and colonize secondary sites, driving the metastatic cascade via hematogenous dissemination. Chu and colleagues have proposed that within the population of CTCs exist metastasis-initiating cells, which possess not only metastatic potential but also the ability to recruit and reprogram dormant cells to become active metastatic cells.77-79 These rare events and molecular findings, such as metastasis-initiating cells and AR-splice variants in the pool of CTCs, point to the need to further investigate the genomic and transcriptomic content of CTCs.

Next-generation sequencing (NGS) technologies are now capable of using picograms of genomic material, so that they can be adapted for CTC analysis.80 Contemporary methods of RNA characterization have also been found to be adaptable for CTC analysis, including fluorescently labeled oligonucleotide hybridization,81 whole-transcriptome RNA microarrays,82 and single-cell RNA sequencing.83 Single-cell DNA sequencing after whole-genome amplification is now possible,84,85 although genomic amplification creates the potential for PCR-related errors and the preferential amplification of specific regions.86

There remains a need to characterize the degree to which CTC biology reflects underlying tumor biology. Several studies have compared CTCs and tumor tissues. Magbanua and colleagues demonstrated that CTCs possess copy number variations (CNVs) that mirror those of the associated primary tumor.87,88 Targeted sequencing studies also have been conducted to compare single-nucleotide variances in CTCs and those in tumor tissues. Studies have detected mutations in known oncogenes, including TP53 and BRAF, in single CTCs.89,90 To further demonstrate the similarity between CTCs and tumor tissues, both our group91,92 and Lohr and colleagues93 performed whole-genome and whole-exome sequencing on single CTCs as well as temporally related biopsy specimens, and they independently reported similarities between single CTCs and PC tumor tissues at the genomic level. These studies provide evidence supporting the use of EpCAM-based approaches to isolate CTCs and suggest the possibility of using CTCs as a window to obtain critical, disease-relevant information. Although NGS has been increasingly used for precision medicine,94-96 there are still barriers to be overcome before the use of NGS for CTCs is ready for clinical application. Technical challenges include the isolation of high-quality CTCs, the development of methods for high-uniformity and high-coverage whole-genome amplification, and the creation of strategies for accurate mutation identification. Another challenge is the heterogeneous nature of cancer and the CTC population.

As the number of CTC characterization studies grows, increasing data are showing discrepancies between CTCs and tumors, in addition to substantial heterogeneity within the pool of CTCs. Genomic studies have revealed that 14% to 30% of the mutations found in CTCs are CTC-specific.92,93 Discrepancies were also observed beyond the genomes as several groups made attempts to compare the transcriptomes of CTCs and of tumor tissues. Miyamoto and colleagues recently reported the results of RNA sequencing for single CTCs from patients with PC.83 Although the CTCs strongly clustered according to patient of origin, substantial heterogeneity was observed in signaling pathways, as well as transcriptional alterations involving resistance to antiandrogen therapies. These observations may have been related to the complex molecular evolution of metastatic PC, which has yet to be comprehensively studied,97 and to the technical difficulties encountered in verifying findings in single cells.90,91 However, the studies also clearly indicated molecular heterogeneity within the pool of CTCs from each patient and brought up several important issues to be addressed before CTCs can be used for liquid biopsy. These include (but are not limited to) the following: (1) the methodology required to effectively distinguish disease-related information from sequencing errors; (2) the number of CTCs required to obtain clinically relevant information; (3) the timing of CTC sampling in relation to the evolution of cancer and/or the effect of therapeutics.

Studies that appropriately address these issues will serve as the foundation for future studies designed to use CTCs as a means of describing and measuring the heterogeneity and dynamic biology of cancer.

Heterogeneity and Dynamic Biology: Future Applications of CTCs 

Heterogeneity, a classic hallmark of cancer, has been described at the phenotypic and molecular levels in PC. It exists between patients (interpatient), between tumors in one patient (intertumoral), and among the cells making up a tumor (intratumoral).98,99 Heterogeneity also evolves over time and physical space (temporospatial). It has been proposed that heterogeneity may be a driver of drug resistance and disease progression.100

Many historical studies in this area have relied on tumor samplings, including multiple-site samplings of freshly resected tissue. This is feasible in certain cancers, given that lesions may appear in soft-tissue areas that are amenable to safe and high-yield biopsies. PC and CRPC in particular tend to be less amenable to needle biopsies for the reasons previously noted. In the case of PC, serial liquid biopsy may provide an approach to study the dynamic aspects of tumor heterogeneity.29,90,100

Interest has been growing in the use of blood-borne components to develop a liquid biopsy. Analysis of circulating tumor DNA (ctDNA) has proved to be a convenient and effective means of detecting and monitoring key mutations in cancer.101 In addition, ctDNA has been used to study complex DNA alterations.102,103 The speed of sample acquisition and processing, as well as the relatively simple technology needed to obtain ctDNA for study, is very appealing. These factors have fueled enthusiasm for making ctDNA analysis an active area of research in PC and other solid malignant tumors. A fuller characterization of the biology of PC, especially CRPC, may require greater biological insight than can be obtained from DNA alone. With the advances in single-cell technologies, CTCs may provide additional information on the clonality of cancer because multiple layers of information (eg, DNA mutations, epigenetic alterations, RNA expression, protein levels, morphologic features, functional properties) can be extracted simultaneously.

We and others have proposed that CTCs may provide another dimension in cancer biology: dynamic biology.104 Serial blood sampling for CTC analysis can rapidly yield temporally discrete data that can provide dynamic insight into disease evolution and therapeutic resistance in PC. Analysis of serially collected CTCs has indicated that variations in CTC-derived biological information over time may reflect changes in the nature of disease and/or response to therapy.29,49,92,105


The introduction of technologies capable of capturing and enumerating CTCs is a first and important step in having the field of CTC research progress from theory to clinical practice. In PC, the CTC count serves as a prognostic biomarker for survival and a predictive biomarker. This finding is significant for PC and especially CRPC, in which biomarkers other than the serum PSA concentration may be of importance. Enumeration remains a useful type of data that can be derived from CTCs. Newer technologies that have been developed and introduced are now capable of examining CTCs in a fashion more akin to the way tissue biopsies are examined.

As the clinical care of men with PC becomes more personalized, the ability to conduct a dynamic characterization of the biology of this disease in real time will be increasingly important. This personalization of therapy is made feasible by advances in the basic sciences and pressured by the rising costs of therapy in the face of a long natural history of PC. Minimally invasive access to useful tissue for biological characterization may revolutionize the care of men with PC.

Interest has been growing in the use of blood-borne components to develop a liquid biopsy. Concerns over cost, technologic requirements, and the slow sample processing have led to a decreased interest in CTCs and a greater interest in ctDNA. Although important and informative, because of its biological nature, PC will likely require more than DNA-based analysis. As technology improves, the cost and time required to isolate and analyze CTCs will decrease, making these platforms more accessible to physicians and scientists. Importantly, the study of plasma and the study of the cellular components in blood samples are not mutually exclusive, and they may serve as effective complementary tests in the future as both types of clinical biomarkers are explored.

Genomic medicine and liquid biopsies have been heralded as the future of modern oncology. Advances in both areas are critically important in a disease such as PC, in which mortality continues to be an issue and in which current approaches fail to unite modern biology with clinical practice. With the timely advances in both CTC isolation technology and molecular profiling, CTC research is turning to liquid biopsies to promote genomic medicine. The union of these disciplines may be supra-additive by allowing a characterization of the dynamic nature of PC and other malignancies, given the existing capabilities to draw blood frequently and even conduct CTC isolation within hours of phlebotomy. By gaining insight into the changes of biological behavior and heterogeneity of malignancies, a physician may be better equipped to navigate therapies and/or prognosticate. Such information may also provide an understanding of emerging resistance to therapy.

Exciting developments in the field of CTC research in PC and other cancers raise new and important questions and challenges. Given the rarity of these cellular events in the bloodstream and the precision of the measurements being made (down to the level of single cells), standards of collection and analysis will need to be established. Given the wide variation in the approaches to CTC isolation, it is unlikely that a single cross-platform approach will ever be established. For the optimization of each advanced platform, understanding the volume of blood and/or numbers of tumor cells needed to conduct the best possible comparisons remains important. Moreover, the timing of blood sampling likely needs to vary with the rate of disease progression. The frequency of sample collection also may depend on the analyte of interest and the methodology used. Although these may represent important issues in technology development, they will not substantially hinder progress in this exciting and important field of biomedical research.

CTCs have become a resource available to oncologists and researchers in the area of PC. Although issues of cost and utility have limited the wide application of their use, an increasing number of studies are showing their potential usefulness in the clinic. With further refinements in technology, their applications will extend beyond enumeration and will help to shape the future of cancer research and personalized oncology. CTC-based approaches will certainly improve the care of men
with PC.


The authors extend their thanks to the following organizations and groups for their continued support of CTC research efforts at the Samuel Oschin Comprehensive Cancer Institute: the St. Anthony Fund for Prostate Cancer Research and Discovery, the CD McKinnon Memorial Fund for Aggressive Variant Prostate Cancers, the Michael & Trisha Berns Family Fund for Discovery, the Steven Spielberg Family Prostate Cancer Discovery Fund, the CDMRP (Congressionally Directed Medical Research Programs) Prostate Cancer Research Program of the US Department of Defense, the Prostate Cancer Foundation, the NCI Alliance for Nanotechnology in Cancer, and the National Cancer Institute. 


1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin. 2016;66(1):7-30.

2. Robinson D, Van Allen EM, Wu YM, et al. Integrative clinical genomics of advanced prostate cancer. Cell. 2015;161(5):1215-1228.

3. You S, Knudsen BS, Erho N, et al. Integrated classification of prostate cancer reveals a novel luminal subtype with poor outcome. Cancer Res. 2016;76(17):4948-4958.

4. Zhao SG, Evans JR, Kothari V, et al. The landscape of prognostic outlier genes in high-risk prostate cancer. Clin Cancer Res. 2016;22(7):1777-1786.

5. Scher HI, Morris MJ, Stadler WM, et al; Prostate Cancer Clinical Trials Working Group 3. Trial design and objectives for castration-resistant prostate cancer: updated recommendations from the Prostate Cancer Clinical Trials Working Group 3. J Clin Oncol. 2016;34(12):1402-1418.

6. Collette L, Burzykowski T, Carroll KJ, Newling D, Morris T, Schröder FH; European Organisation for Research and Treatment of Cancer; Limburgs Universitair Centrum; AstraZeneca Pharmaceuticals. Is prostate-specific antigen a valid surrogate end point for survival in hormonally treated patients with metastatic prostate cancer? Joint research of the European Organisation for Research and Treatment of Cancer, the Limburgs Universitair Centrum, and AstraZeneca Pharmaceuticals. J Clin Oncol. 2005;23(25):6139-6148.

7. Scher HI, Morris MJ, Kelly WK, Schwartz LH, Heller G. Prostate cancer clinical trial end points: “RECIST”ing a step backwards. Clin Cancer Res. 2005;11(14):5223-5232.

8. Beltran H, Tagawa ST, Park K, et al. Challenges in recognizing treatment-related neuroendocrine prostate cancer. J Clin Oncol. 2012;30(36):e386-e389.

9. Yuan X, Cai C, Chen S, Chen S, Yu Z, Balk SP. Androgen receptor functions in castration-resistant prostate cancer and mechanisms of resistance to new agents targeting the androgen axis. Oncogene. 2014;33(22):2815-2825.

10. Lipianskaya J, Cohen A, Chen CJ, et al. Androgen-deprivation therapy-induced aggressive prostate cancer with neuroendocrine differentiation. Asian J Androl. 2014;16(4):541-544.

11. Barbieri CE, Baca SC, Lawrence MS, et al. Exome sequencing identifies recurrent SPOP, FOXA1 and MED12 mutations in prostate cancer. Nat Genet. 2012;44(6):685-689.

12. Racila E, Euhus D, Weiss AJ, et al. Detection and characterization of carcinoma cells in the blood. Proc Natl Acad Sci U S A. 1998;95(8):4589-4594.

13. Krivacic RT, Ladanyi A, Curry DN, et al. A rare-cell detector for cancer. Proc Natl Acad Sci U S A. 2004;101(29):10501-10504.

14. Zieglschmid V, Hollmann C, Böcher O. Detection of disseminated tumor cells in peripheral blood. Crit Rev Clin Lab Sci. 2005;42(2):155-196.

15. Gutman, SI. K031588. Evaluation of Automatic Class III Designation, CellSearch Epithelial Cell Kit/Cell Spotter Analyzer, Regulation Number: 21 CFR 866.6020, Classification: II, Product Code: NQI [letter to Veridex from US Food and Drug Administration]. September 29, 2004.

16. Cristofanilli M, Budd GT, Ellis MJ, et al. Circulating tumor cells, disease progression, and survival in metastatic breast cancer. N Engl J Med. 2004;351(8):781-791.

17. Hoshimoto S, Shingai T, Morton DL, et al. Association between circulating tumor cells and prognosis in patients with stage III melanoma with sentinel lymph node metastasis in a phase III international multicenter trial. J Clin Oncol. 2012;30(31):3819-3826.

18. Hofman V, Ilie MI, Long E, et al. Detection of circulating tumor cells as a prognostic factor in patients undergoing radical surgery for non-small-cell lung carcinoma: comparison of the efficacy of the CellSearch Assay™ and the isolation by size of epithelial tumor cell method. Int J Cancer. 2011;129(7):1651-1660.

19. Shaffer DR, Leversha MA, Danila DC, et al. Circulating tumor cell analysis in patients with progressive castration-resistant prostate cancer. Clin Cancer Res. 2007;13(7):2023-2029.

20. Danila DC, Heller G, Gignac GA, et al. Circulating tumor cell number and prognosis in progressive castration-resistant prostate cancer. Clin Cancer Res. 2007;13(23):7053-7058.

21. de Bono JS, Scher HI, Montgomery RB, et al. Circulating tumor cells predict survival benefit from treatment in metastatic castration-resistant prostate cancer. Clin Cancer Res. 2008;14(19):6302-6309.

22. Scher HI, Jia X, de Bono JS, et al. Circulating tumour cells as prognostic markers in progressive, castration-resistant prostate cancer: a reanalysis of IMMC38 trial data. Lancet Oncol. 2009;10(3):233-239.

23. Mateo J, Carreira S, Sandhu S, et al. DNA-repair defects and olaparib in metastatic prostate ancer. N Engl J Med. 2015;373(18):1697-1708.

24. Yu EY, Li H, Higano CS, et al. SWOG S0925: a randomized phase II study of androgen deprivation combined with cixutumumab versus androgen deprivation alone in patients with new metastatic hormone-sensitive prostate cancer. J Clin Oncol. 2015;33(14):1601-1608.

25. Pal SK, He M, Wilson T, et al. Detection and phenotyping of circulating tumor cells in high-risk localized prostate cancer. Clin Genitourin Cancer. 2015;13(2):130-136.

26. Fischer KE, Alemán BJ, Tao SL, et al. Biomimetic nanowire coatings for next generation adhesive drug delivery systems. Nano Lett. 2009;9(2):716-720.

27. Gorges TM, Tinhofer I, Drosch M, et al. Circulating tumour cells escape from EpCAM-based detection due to epithelial-to-mesenchymal transition. BMC Cancer. 2012;12:178.

28. Yu M, Bardia A, Wittner BS, et al. Circulating breast tumor cells exhibit dynamic changes in epithelial and mesenchymal composition. Science. 2013;339(6119):580-584.

29. Chen JF, Ho H, Lichterman J, et al. Subclassification of prostate cancer circulating tumor cells by nuclear size reveals very small nuclear circulating tumor cells in patients with visceral metastases. Cancer. 2015;121(18):3240-3251.

30. Reyes EE, Gillard M, Duggan R, et al. Molecular analysis of CD133-positive circulating tumor cells from patients with metastatic castration-resistant prostate cancer. J Transl Sci. 2015;1(1):

31. Kerr BA, Miocinovic R, Smith AK, et al. CD117⁺ cells in the circulation are predictive of advanced prostate cancer. Oncotarget. 2015;6(3):1889-1897.

32. Jacob K, Sollier C, Jabado N. Circulating tumor cells: detection, molecular profiling and future prospects. Expert Rev Proteomics. 2007;4(6):741-756.

33. Yang L, Lang JC, Balasubramanian P, 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. Biotechnol Bioeng. 2009;102(2):521-534.

34. Schmidt H, DeAngelis G, Eltze E, Gockel I, Semjonow A, Brandt B. Asynchronous growth of prostate cancer is reflected by circulating tumor cells delivered from distinct, even small foci, harboring loss of heterozygosity of the PTEN gene. Cancer Res. 2006;66(18):8959-8965.

35. Antonarakis ES, Lu C, Wang H, et al. AR-V7 and resistance to enzalutamide and abiraterone in prostate cancer. N Engl J Med. 2014;371(11):1028-1038.

36. Talasaz AH, Powell AA, Huber DE, et al. Isolating highly enriched populations of circulating epithelial cells and other rare cells from blood using a magnetic sweeper device. Proc Natl Acad Sci U S A. 2009;106(10):3970-3975.

37. Harb W, Fan A, Tran T, et al. Mutational analysis of circulating tumor cells using a novel microfluidic collection device and qPCR assay. Transl Oncol. 2013;6(5):528-538.

38. Casavant BP, Guckenberger DJ, Berry SM, Tokar JT, Lang JM, Beebe DJ. The VerIFAST: an integrated method for cell isolation and extracellular/intracellular staining. Lab Chip. 2013;13(3):391-396.

39. Karabacak NM, Spuhler PS, Fachin F, et al. Microfluidic, marker-free isolation of circulating tumor cells from blood samples. Nat Protoc. 2014;9(3):694-710.

40. Vona G, Sabile A, Louha M, et al. Isolation by size of epithelial tumor cells: a new method for the immunomorphological and molecular characterization of circulatingtumor cells. Am J Pathol. 2000;156(1):57-63.

41. Sarioglu AF, Aceto N, Kojic N, et al. A microfluidic device for label-free, physical capture of circulating tumor cell clusters. Nat Methods. 2015;12(7):685-691.

42. Gupta V, Jafferji I, Garza M, et al. ApoStream(™), a new dielectrophoretic device for antibody independent isolation and recovery of viable cancer cells from blood. Biomicrofluidics. 2012;6(2):24133.

43. Friedlander TW, Ngo VT, Dong H, et al. Detection and characterization of invasive circulating tumor cells derived from men with metastatic castration-resistant prostate cancer. Int J Cancer. 2014;134(10):2284-2293.

44. Nagrath S, Sequist LV, Maheswaran S, et al. Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature. 2007;450(7173):1235-1239.

45. Stott SL, Lee RJ, Nagrath S, et al. Isolation and characterization of circulating tumor cells from patients with localized and metastatic prostate cancer. Sci Transl Med. 2010;2(25):25ra23.

46. Stott SL, Hsu CH, Tsukrov DI, et al. Isolation of circulating tumor cells using a microvortex-generating herringbone-chip. Proc Natl Acad Sci U S A. 2010;107(43):18392-18397.

47. Adams AA, Okagbare PI, Feng J, et al. Highly efficient circulating tumor cell isolation from whole blood and label-free enumeration using polymer-based microfluidics with an integrated conductivity sensor. J Am Chem Soc. 2008;130(27):8633-8641.

48. Dharmasiri U, Njoroge SK, Witek MA, et al. High-throughput selection, enumeration, electrokinetic manipulation, and molecular profiling of low-abundance circulating tumor cells using a microfluidic system. Anal Chem. 2011;83(6):2301-2309.

49. Lu YT, Zhao L, Shen Q, et al. NanoVelcro Chip for CTC enumeration in prostate cancer patients. Methods. 2013;64(2):144-152.

50. Mach AJ, Kim JH, Arshi A, Hur SC, Di Carlo D. Automated cellular sample preparation using a Centrifuge-on-a-Chip. Lab Chip. 2011;11(17):2827-2834.

51. Warkiani ME, Khoo BL, Wu L, et al. Ultra-fast, label-free isolation of circulating tumor cells from blood using spiral microfluidics. Nat Protoc. 2016;11(1):134-148.

52. Antfolk M, Magnusson C, Augustsson P, Lilja H, Laurell T. Acoustofluidic, label-free separation and simultaneous concentration of rare tumor cells from white blood cells. Anal Chem. 2015;87(18):9322-9328.

53. Antfolk M, Antfolk C, Lilja H, Laurell T, Augustsson P. A single inlet two-stage acoustophoresis chip enabling tumor cell enrichment from white blood cells. Lab Chip. 2015;15(9):2102-2109.

54. Shen Q, Xu L, Zhao L, et al. Specific capture and release of circulating tumor cells using aptamer-modified nanosubstrates. Adv Mater. 2013;25(16):2368-2373.

55. Hou S, Zhao H, Zhao L, et al. Capture and stimulated release of circulating tumor cells on polymer-grafted silicon nanostructures. Adv Mater. 2013;25(11):1547-1551.

56. Reátegui E, Aceto N, Lim EJ, et al. Tunable nanostructured coating for the capture and selective release of viable circulating tumor cells. Adv Mater. 2015;27(9):1593-1599.

57. Beltran H, Jendrisak A, Landers M, et al. The initial detection and partial characterization of circulating tumor cells in neuroendocrine prostate cancer. Clin Cancer Res. 2016;22(6):1510-1519.

58. Campton DE, Ramirez AB, Nordberg JJ, et al. High-recovery visual identification and single-cell retrieval of circulating tumor cells for genomic analysis using a dual-technology platform integrated with automated immunofluorescence staining. BMC Cancer. 2015;15:360.

59. Scher HI, Lu D, Schreiber NA, 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 Oncol. 2016;2(11):1441-1449.

60. Aceto N, Bardia A, Miyamoto DT, et al. Circulating tumor cell clusters are oligoclonal precursors of breast cancer metastasis. Cell. 2014;158(5):1110-1122.

61. Barbieri CE, Bangma CH, Bjartell A, et al. The mutational landscape of prostate cancer. Eur Urol. 2013;64(4):567-576.

62. Tomlins SA, Bjartell A, Chinnaiyan AM, et al. ETS gene fusions in prostate cancer: from discovery to daily clinical practice. Eur Urol. 2009;56(2):275-286.

63. Attard G, Swennenhuis JF, Olmos D, et al. Characterization of ERG, AR and PTEN gene status in circulating tumor cells from patients with castration-resistant prostate cancer. Cancer Res. 2009;69(7):2912-2918.

64. Danila DC, Anand A, Sung CC, et al. TMPRSS2-ERG status in circulating tumor cells as a predictive biomarker of sensitivity in castration-resistant prostate cancer patients treated with abiraterone acetate. Eur Urol. 2011;60(5):897-904.

65. Punnoose EA, Ferraldeschi R, Szafer-Glusman E, et al. PTEN loss in circulating tumour cells correlates with PTEN loss in fresh tumour tissue from castration-resistant prostate cancer patients. Br J Cancer. 2015;113(8):1225-1233.

66. Hu R, Dunn TA, Wei S, et al. Ligand-independent androgen receptor variants derived from splicing of cryptic exons signify hormone-refractory prostate cancer. Cancer Res. 2009;69(1):16-22.

67. Guo Z, Yang X, Sun F, et al. A novel androgen receptor splice variant is up-regulated during prostate cancer progression and promotes androgen depletion-resistant growth. Cancer Res. 2009;69(6):2305-2313.

68. Dehm SM, Schmidt LJ, Heemers HV, Vessella RL, Tindall DJ. Splicing of a novel androgen receptor exon generates a constitutively active androgen receptor that mediates prostate cancer therapy resistance. Cancer Res. 2008;68(13):5469-5477.

69. Nadiminty N, Tummala R, Liu C, et al. NF-κB2/p52 induces resistance to enzalutamide in prostate cancer: role of androgen receptor and its variants. Mol Cancer Ther. 2013;12(8):1629-1637.

70. Mostaghel EA, Marck BT, Plymate SR, et al. Resistance to CYP17A1 inhibition with abiraterone in castration-resistant prostate cancer: induction of steroidogenesis and androgen receptor splice variants. Clin Cancer Res. 2011;17(18):5913-5925.

71.  Antonarakis ES, Lu C, Luber B, et al. AR-V7 and efficacy of abiraterone (Abi) and enzalutamide (Enza) in castration-resistant prostate cancer (CRPC): expanded analysis of the Johns Hopkins cohort [ASCO abstract 5012]. J Clin Oncol. 2016;34(15)(suppl).

72. Antonarakis ES, Lu C, Luber B, et al. Androgen receptor splice variant 7 and efficacy of taxane chemotherapy in patients with metastatic castration-resistant prostate cancer. JAMA Oncol. 2015;1(5):582-591.

73. Onstenk W, Sieuwerts AM, Kraan J, et al. Efficacy of cabazitaxel in castration-resistant prostate cancer is independent of the presence of AR-V7 in circulating tumor cells. Eur Urol. 2015;68(6):939-945.

74. Sperger JM, Strotman LN, Welsh A, et al. Integrated analysis of multiple biomarkers from circulating tumor cells enabled by exclusion-based analyte isolation [published online July 11, 2016]. Clin Cancer Res. pii: clincanres.1021.2016.

75. Bishop JL, Sio A, Angeles A, et al. PD-L1 is highly expressed in Enzalutamide resistant prostate cancer. Oncotarget. 2015;6(1):234-242.

76. Satelli A, Batth IS, Brownlee Z, et al. Potential role of nuclear PD-L1 expression in cell-surface vimentin positive circulating tumor cells as a prognostic marker in cancer patients. Sci Rep. 2016;6:28910.

77. Ziaee S, Chu GC, Huang JM, Sieh S, Chung LW. Prostate cancer metastasis: roles of recruitment and reprogramming, cell signal network and three-dimensional growth characteristics. Transl Androl Urol. 2015;4(4):438-454.

78. Chu GC, Zhau HE, Wang R, et al. RANK- and c-Met-mediated signal network promotes prostate cancer metastatic colonization. Endocr Relat Cancer. 2014;21(2):311-326.

79. Chu GC, Chung LW. RANK-mediated signaling network and cancer metastasis. Cancer Metastasis Rev. 2014;33(2-3):497-509.

80. Tang F, Barbacioru C, Wang Y, et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods. 2009;6(5):377-382.

81. Raj A, van den Bogaard P, Rifkin SA, van Oudenaarden A, Tyagi S. Imaging individual mRNA molecules using multiple singly labeled probes. Nat Methods. 2008;5(10):877-879.

82. Klein CA, Seidl S, Petat-Dutter K, et al. Combined transcriptome and genome analysis of single micrometastatic cells. Nat Biotechnol. 2002;20(4):387-392.

83. Miyamoto DT, Zheng Y, Wittner BS, et al. RNA-Seq of single prostate CTCs implicates noncanonical Wnt signaling in antiandrogen resistance. Science. 2015;349(6254):1351-1356.

84. Navin N, Kendall J, Troge J, et al. Tumour evolution inferred by single-cell sequencing. Nature. 2011;472(7341):90-94.

85. Xu X, Hou Y, Yin X, et al. Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor. Cell. 2012;148(5):886-895.

86. Treff NR, Su J, Tao X, Northrop LE, Scott RT Jr. Single-cell whole-genome amplification technique impacts the accuracy of SNP microarray-based genotyping and copy number analyses. Mol Hum Reprod. 2011;17(6):335-343.

87. Magbanua MJ, Sosa EV, Scott JH, et al. Isolation and genomic analysis of circulating tumor cells from castration resistant metastatic prostate cancer. BMC Cancer. 2012;12:78.

88. Magbanua MJ, Sosa EV, Roy R, et al. Genomic profiling of isolated circulating tumor cells from metastatic breast cancer patients. Cancer Res. 2013;73(1):30-40.

89. Heitzer E, Auer M, Gasch C, et al. Complex tumor genomes inferred from single circulating tumor cells by array-CGH and next-generation sequencing. Cancer Res. 2013;73(10):2965-2975.

90. Hou S, Zhao L, Shen Q, et al. Polymer nanofiber-embedded microchips for detection, isolation, and molecular analysis of single circulating melanoma cells. Angew Chem Int Ed Engl. 2013;52(12):3379-3383.

91. Zhao L, Lu YT, Li F, et al. High-purity prostate circulating tumor cell isolation by a polymer nanofiber-embedded microchip for whole exome sequencing. Adv Mater. 2013;25(21):2897-2902.

92. Jiang R, Lu YT, Ho H, et al. A comparison of isolated circulating tumor cells and tissue biopsies using whole-genome sequencing in prostate cancer. Oncotarget. 2015;6(42):44781-44793.

93. Lohr JG, Adalsteinsson VA, Cibulskis K, et al. Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer. Nat Biotechnol. 2014;32(5):479-484.

94. Stockley TL, Oza AM, Berman HK, et al. Molecular profiling of advanced solid tumors and patient outcomes with genotype-matched clinical trials: the Princess Margaret IMPACT/COMPACT trial. Genome Med. 2016;8(1):109.

95. Cheng HH, Klemfuss N, Montgomery B, et al. A pilot study of clinical targeted next generation sequencing for prostate cancer: consequences for treatment and genetic counseling. Prostate. 2016;76(14):1303-1311.

96. Hovelson DH, McDaniel AS, Cani AK, et al. Development and validation of a scalable next-generation sequencing system for assessing relevant somatic variants in solid tumors. Neoplasia. 2015;17(4):385-399.

97. Gundem G, Van Loo P, Kremeyer B, et al; ICGC Prostate UK Group. The evolutionary history of lethal metastatic prostate cancer. Nature. 2015;520(7547):353-357.

98. Jamal-Hanjani M, Quezada SA, Larkin J, Swanton C. Translational implications of tumor heterogeneity. Clin Cancer Res. 2015;21(6):1258-1266.

99. Burrell RA, McGranahan N, Bartek J, Swanton C. The causes and consequences of genetic heterogeneity in cancer evolution. Nature. 2013;501(7467):338-345.

100. Swanton C. Intratumor heterogeneity: evolution through space and time. Cancer Res. 2012;72(19):4875-4882.

101. Mok T, Wu YL, Lee JS, et al. Detection and dynamic changes of EGFR mutations from circulating tumor DNA as a predictor of survival outcomes in NSCLC patients treated with first-line intercalated erlotinib and chemotherapy. Clin Cancer Res. 2015;21(14):3196-3203.

102. Wyatt AW, Azad AA, Volik SV, et al. Genomic alterations in cell-free DNA and enzalutamide resistance in castration-resistant prostate cancer. JAMA Oncol. 2016;2(12):1598-1606.

103. Azad AA, Volik SV, Wyatt AW, et al. Androgen receptor gene aberrations in circulating cell-free DNA: Biomarkers of therapeutic resistance in castration-resistant prostate cancer. Clin Cancer Res. 2015;21(10):2315-2324.

104. Almufti R, Wilbaux M, Oza A, et al. A critical review of the analytical approaches for circulating tumor biomarker kinetics during treatment. Ann Oncol. 2014;25(1):41-56.

105. Nakazawa M, Lu C, Chen Y, et al. Serial blood-based analysis of AR-V7 in men with advanced prostate cancer. Ann Oncol. 2015;26(9):1859-1865.

106. Attard G, Reid AH, A’Hern R, et al. Selective inhibition of CYP17 with abiraterone acetate is highly active in the treatment of castration-resistant prostate cancer. J Clin Oncol. 2009;27(23):3742-3748.

107. Smith MR, Sweeney CJ, Corn PG, et al. Cabozantinib in chemotherapy-pretreated metastatic castration-resistant prostate cancer: results of a phase II nonrandomized expansion study. J Clin Oncol. 2014;32(30):3391-3399.

108. Goldkorn A, Ely B, Quinn DI, et al. Circulating tumor cell counts are prognostic of overall survival in SWOG S0421: a phase III trial of docetaxel with or without atrasentan for metastatic castration-resistant prostate cancer. J Clin Oncol. 2014;32(11):1136-1142.

109. Scher HI, Heller G, Molina A, et al. Circulating tumor cell biomarker panel as an individual-level surrogate for survival in metastatic castration-resistant prostate cancer. J Clin Oncol. 2015;33(12):1348-1355.

110. Azim HA Jr, Rothé F, Aura CM, et al. Circulating tumor cells and response to neoadjuvant paclitaxel and HER2-targeted therapy: a sub-study from the NeoALTTO phase III trial. Breast. 2013;22(6):1060-1065.

111. Bidard FC, Huguet F, Louvet C, et al. Circulating tumor cells in locally advanced pancreatic adenocarcinoma: the ancillary CirCe 07 study to the LAP 07 trial. Ann Oncol. 2013;24(8):2057-2061.

112. Cann GM, Gulzar ZG, Cooper S, et al. mRNA-Seq of single prostate cancer circulating tumor cells reveals recapitulation of gene expression and pathways found in prostate cancer. PLoS One. 2012;7(11):e49144.

113. Todenhöfer T, Hennenlotter J, Feyerabend S, et al. Preliminary experience on the use of the Adnatest® system for detection of circulating tumor cells in prostate cancer patients. Anticancer Res. 2012;32(8):3507-3513.

114. Lin M, Chen JF, Lu YT, et al. Nanostructure embedded microchips for detection, isolation, and characterization of circulating tumor cells. Acc Chem Res. 2014;47(10):2941-2950.

115. Chen JF, Zhu Y, Lu YT, et al. Clinical applications of NanoVelcro rare-cell assays for detection and characterization of circulating tumor cells. Theranostics. 2016;6(9):1425-1439.

116. Harb W, Fan A, Tran T, et al. Mutational analysis of circulating tumor cells using a novel microfluidic collection device and qPCR assay. Transl Oncol. 2013;6(5):528-538.

117. Kirby BJ, Jodari M, Loftus MS, et al. Functional characterization of circulating tumor cells with a prostate-cancer-specific microfluidic device. PLoS One. 2012;7(4):e35976.

118. Ozkumur E, Shah AM, Ciciliano JC, et al. Inertial focusing for tumor antigen-dependent and -independent sorting of rare circulating tumor cells. Sci Transl Med. 2013;5(179):179ra47.

119. Saucedo-Zeni N, Mewes S, Niestroj R, et al. A novel method for the in vivo isolation of circulating tumor cells from peripheral blood of cancer patients using a functionalized and structured medical wire. Int J Oncol. 2012;41(4):1241-1250.

120. Farace F, Massard C, Vimond N, et al. A direct comparison of CellSearch and ISET for circulating tumour-cell detection in patients with metastatic carcinomas. Br J Cancer. 2011;105(6):847-853.

121. Zhu P, Stanton ML, Castle EP, et al. Detection of tumor-associated cells in cryopreserved peripheral blood mononuclear cell samples for retrospective analysis. J Transl Med. 2016;14(1):198.

122. Marrinucci D, Bethel K, Kolatkar A, et al. Fluid biopsy in patients with metastatic prostate, pancreatic and breast cancers. Phys Biol. 2012;9(1):016003.