Cancer Metastasis Rev DOI 10.1007/s10555-014-9503-7

NON-THEMATIC REVIEW

Advances in genomic characterization of circulating tumor cells Mark Jesus M. Magbanua & John W. Park

# Springer Science+Business Media New York 2014

Abstract Molecular characterization of circulating tumor cells (CTCs) found in the blood of cancer patients offers the potential to provide new insights into the biology of cancer metastasis. However, since they are rare and difficult to isolate, the molecular nature of CTCs remains poorly understood. In this paper, we reviewed a decade’s worth of scientific literature (2003–2013) describing efforts on isolation and genomic analysis of CTCs. The limited number of CTC genomic studies we found attested to the infancy of this field of study. These initial reports, however, provide an important framework for future comprehensive exploration of CTC biology. For CTCs to be broadly accepted as therapeutic targets and biomarkers of metastatic spread, further in-depth molecular characterization is warranted. Keywords Circulating tumor cells . Genomics . Copy number . Gene expression . Molecular characterization . Enrichment . Isolation

1 Introduction Metastatic spread involves the escape of tumor cells from primary tumors into the blood stream [1, 2]. These tumor cells, also known as circulating tumor cells (CTCs), can migrate to distant sites and initiate metastatic disease [1, 2]. Due to recent advances in rare-cell Electronic supplementary material The online version of this article (doi:10.1007/s10555-014-9503-7) contains supplementary material, which is available to authorized users. M. J. M. Magbanua (*) : J. W. Park (*) Division of Hematology/Oncology, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, 2340 Sutter St, San Francisco, CA 94115, USA e-mail: [email protected] e-mail: [email protected]

detection, CTCs can now be reliably detected and enumerated [3, 4]. Various clinical studies have demonstrated that the elevated numbers of CTCs before and during therapy are associated with reduced survival [5-9]. Although significant progress has been made in understanding the clinical value of CTCs, there is much to learn about the molecular nature of CTCs. The scarcity of information is in part due to the formidable technical challenges in detecting and isolating these extremely rare cells. The overwhelming number of hematopoietic cells in the background (1 CTC to 109 blood cells) also poses further technical barriers for direct molecular analysis of CTCs. Elucidation of CTC-specific signals therefore require prior enrichment of CTCs to reduce background noise coming from normal blood cells. Moreover, because of the limiting CTC inputs for downstream analysis, finding compatible molecular assays is very challenging. Although metastatic progression is the leading cause of death among patients with solid tumors, molecular analysis of metastatic sites is difficult to perform. Biopsy at initial presentation of metastasis is frequently not performed, and serial biopsy is usually not feasible. In contrast, CTCs can be obtained by standard blood collection. As such, “liquid biopsy” of CTCs can provide more opportunities for tumor molecular characterization as compared to analysis of solid metastatic tissue. In this paper, we review recent scientific literature describing efforts on genomic analysis of CTCs. We begin this paper with a discussion of different methods for enrichment and isolation of CTCs as well as techniques for CTC nucleic acid isolation and amplification. Next, we describe examples of genomic efforts to characterize CTCs. Lastly, we summarize biological information gleaned from these reports and discuss future directions for CTC molecular research.

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2 Literature search: methods and results We conducted a literature search to find scientific publications on genomic profiling of CTCs published between years 2003 and 2013 (Supplementary Figure 1). We found 867 entries in PubMed with titles containing the search term “circulating tumor cells.” Next, we reviewed abstracts to include only those reports with mid- to high-content RNA and DNA analyses of CTCs. Mid-content analyses refer to experiments with >10–1,000 analytes, e.g., multigene quantitative polymerase chain (QPCR) analyses. High-content analyses refer to experiments with >1,000 analyte measurements, e.g., microarray and next generation sequencing. We found 18 original articles that fit our search criteria. After further web searches, we found three additional papers. We included a total of 21 papers in this review (Table 1, Supplementary Figure 1). The studies include molecular characterization of CTCs from different types of epithelial cancers, including breast, prostate, colorectal, and pancreatic cancers as well as melanoma (Table 1). More than half of the studies were published in the previous 2 years. Fourteen of the 21 studies carried out high-content molecular analyses. Thirteen studies performed gene expression analysis and the rest performed DNA copy number analysis (Table 1 and Supplementary Figure 1).

3 Strategies for CTC enrichment Successful downstream molecular analyses of CTCs rely on the robustness of the enrichment methods utilized. High sensitivity and specificity are a prerequisite to effectively reduce the number of blood cells, resulting in the enrichment of CTCs by several orders of magnitude. Methods for CTC enrichment have been recently discussed in detail [2, 3, 10]. Most strategies are based on biological (e.g., protein expression) or physical (e.g., size and density) properties that differentiate CTCs from normal blood cells (Fig. 1, Table 2, and Supplementary Table 1). Current enrichment methods are mostly based on the detection of a cell surface protein called the epithelial cell adhesion marker or EPCAM (also known as TACSTD1). For example, 12 of the 21 studies discussed here utilized EPCAM-dependent enrichment methods (Supplementary Table 1). Furthermore, enriched samples (containing mostly blood cells) can be subjected to downstream molecular analysis without isolation of CTCs. Here, 9 of the 21 studies performed molecular analyses on enrichedCTC fractions (Supplementary Table 1). This approach is amenable for gene expression analyses because the background signal coming from the contaminating leukocytes can be computationally subtracted (e.g., in microarray studies) or specific PCR primers for epithelial- or tumor-associated genes can be designed to detect CTC-specific signals (e.g., in QPCR analysis). In contrast, copy number analysis requires

higher purity since the presence of normal genomic DNA from leukocytes can mask true genomic aberrations present in tumor cells [11]. Below, we discuss enrichment methods that have led to successful mid- to high-content RNA and DNA profiling of CTCs. 3.1 Immunomagnetic methods CellSearch The CellSearch system (Veridex) is a US Food and Drug Administration (FDA)-cleared semi-automated method for enumeration of CTCs in blood of patients diagnosed with metastatic breast, prostate, and colon cancers [7, 9, 12]. This system provides two options for CTC enrichment: (a) the Epithelial Cell Kit, which involves an EPCAM-based immumomagnetic enrichment followed by fluorescence microscopy to detect and enumerate CTCs (defined as nucleated cells that express cytokeratins 8, 18+, and/or 19+ but not CD45); and (b) the Profiling Kit, which involves only the immunomagnetic enrichment portion without immunostaining. In both methods, the initial 7.5 ml of whole blood is reduced to ~300 ul volume cell suspension. After a 104 to 105-fold enrichment, the process results in an admixture of 1–10 CTCs per 103–104 leukocytes [13]. Magsweeper The Magsweeper (Illumina) is an automated immunomagnetic cell separator [14] equipped with magnetic rods that are robotically driven to “sweep” in a circular motion allowing contact and subsequent capture of tumor cells that are labeled with magnetic beads coated with EPCAM antibodies. Non-specifically bound cells are washed off and labeled cells are released by removing the plastic sheath covering the magnetic rods. This process of capture, wash, and release is repeated to further enrich (108-fold) for EPCAMexpressing cells. Alternatively, magnetic beads can be functionalized with antibodies against melanoma-associated chondroitin sulfate proteoglycan, CSPG4 (also known as NG2 or MCSP) to capture circulating melanoma cells [15]. Other immunomagnetic enrichment methods using beads Several commercially manufactured antibodyfunctionalized magnetic beads can be used for enrichment. A positive selection approach may be employed to enrich for cells expressing epithelial cell markers (e.g., CELLection™ Epithelial Enrich kit (Invitrogen, Dynal)) [16]. Negative immunomagnetic selection using anti-CD45 specific antibodies (e.g., Dynabeads M-450 CD45 Pan Leukocyte, Dynal Biotech) can also be used to deplete leukocytes [13]. 3.2 Microfluidic methods HB

CTC chip The HBCTC chip [17] is a second-generation “CTC-chip” [18] designed to increase throughput (i.e., higher blood volume) and improve capture efficiency. The original

Cancer Metastasis Rev Table 1 Scientific publications on genomic profiling of circulating tumor cells (CTCs) with mid- to high-content data published between 2003–2013 Study

Type of cancer

Type of molecular analysis

Throughput

Molecular assay utilized

Input for molecular analysis

O’Hara et al., Clin Chem 2004 [31] Smirnov et al., Cancer Res 2005 [30] Sieuwerts et al., Breast Cancer Res Treat 2009 [13] Lu et al., Int J Cancer 2010 [21] Sieuwerts et al., Clin Cancer Res 2011 [32] Barbazan et al., PLoS One 2012 [16] Cann et al., PLoS One 2012 [35] Powell et al., PLoS One 2012 [33] Ramskold et al., Nat Biotechnol 2012 [15] Yu et al., Nature 2013 [36] Chen et al., Prostate 2013 [39] Ozkumur et al., Sci Transl Med 2013 [19] Yu et al., Science 2013 [36] Ulmer et al., Clin Cancer Res 2004 [54] Paris et al., Cancer letters 2009 [22] Hannemann et al., Cancer letters 2009 [53] Magbanua et al., BMC Cancer 2012 [51] Mathiesen et al., Int J Cancer 2012 [25] Heitzer et al., Cancer Res 2013 [55]

PCa

Expression

Mid-content

Multigene RT-PCR

CTC-enriched

BCa, PCa and CRC BCa

Expression

High-content

CTC-enriched

Expression

Mid-content

Expression microarray and Multigene QPCR Multigene QPRC

CTC-enriched

BCa

Expression

High-content

Expression microarray

CTC-enriched

BCa

Expression

Mid-content

Mutigene QPCR

CTC-enriched

CRC

Expression

High-content

CTC-enriched

PCa

Expression

High-content

Expression microarray and Multigene QPCR RNAseq

Isolated CTCs

BCa

Expression

Mid-content

Multigene QPCR

Isolated CTCs

Melanoma

Expression

High-content

RNAseq

Isolated CTCs

PCa PCa

Expression Expression

High-content Mid-content

Digital gene expression Multigene QPCR

CTC-enriched Isolated CTCs

PCa

Expression

Mid-content

Multigene QPCR

Isolated CTCs

BCa Melanoma

Expression Copy number

High-content High-content

Digital gene expression Metaphase CGH

CTC-enriched CTC-enriched

PCa

Copy number

High-content

ACGH

CTC-enriched

BCa

Copy number

High-content

ACGH and QPCR

Isolated CTCs

PCa

Copy number

High-content

ACGH

Isolated CTCs

BCa

Copy number

High-content

ACGH

Isolated CTCs

CRC

High-content

ACGH and Target specific next generation sequencing

Isolated CTCs

BCa

Copy number and Mutation screening Copy number

High-content

ACGH

Isolated CTCs

Lung

Copy number

High-content

Next generation sequencing (WGS and WES)

Isolated CTCs

Magbanua et al., Cancer Res 2013 [50] Ni et al., PNAS 2013 [56]

Mid-content data refer to those derived from experiments with >10–1,000 analytes, e.g., multigene quantitative polymerase chain (QPCR) analyses; while high-content data refer to those derived from experiments with >1,000 analyte measurements, e.g., microarray and next generation sequencing. Abbreviations: PCa prostate cancer, BCa breast cancer, CRC colorectal cancer, ACGH array comparative genomic hybridization, QPCR quantitative polymerase chain reaction, RNAseq RNA sequencing, WGS whole genome sequencing, WES whole exome sequencing

design which incorporated ~78,000 microposts is replaced by herringbone-patterned microchannels. In this new configuration, microvortices are formed within the channels to allow more effective mixing, thus lengthening the contact time between EPCAM-expressing cells and the capture antibodies on the surface of the microfluidic device. In spike-in models, purity after HBCTC chip enrichment was approximately 14 % as opposed to the 9 % when enriched with CTC-chip [17].

CTC-iChip This third generation CTC-chip is an automated microfluidic separation system that combines immunomagnetic- and microfluidic-based enrichment and cell separation principles [19]. Whole blood labeled with antibody-functionalized magnetic beads is the input for CTC-iChip. The addition of either EPCAM or CD45/CD15immunomagnetic beads allows for positive or negative selection, respectively. When the labeled sample is injected to the CTC-iChip, hydrodynamic size-based separation occurs to

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Cells trapped on the membrane filter can be isolated for molecular analysis. For enumeration purposes, the filter may be laid down onto a glass slide for cytomorphological analysis using a microscope.

Enrichment

• • • •

Immunomagne c separa on Microfluidic separa on Cell size/density separa on CAM-adherence

RNA profiling • •

QPCR Microarray

Isola on

RNA profiling • QPCR • Microarray • RNAseq

• FACS • Micromanipula on • Microdissec on

DNA profilng • ACGH • DNAseq

Fig. 1 Strategies for enrichment, isolation, and mid- to high-content genomic profiling of circulating tumor cells (CTCs). Whole blood is enriched for CTCs, followed by purification to isolate CTCs. RNA profiling can be performed on enriched or purified samples. RNAseq and DNAseq refer to next generation (massive parallel) sequencing approaches. Abbreviations: QPCR quantitative polymerase chain reaction, FACS fluorescence-activated cell sorting, CAM collagen adhesion matrix, ACGH array comparative genomic hybridization

“debulk” whole blood, i.e., the removal of red blood cells and platelets. Next, inertial focusing aligns the retained nucleated cells (CTCs and leukocytes) in a single file, and labeled cells are then deflected via magnetophoresis into a collection chamber. The majority of deflected events are non-target cells thus achieving purity of >0.1 % [19]. 3.3 Size-based method Screen cell Tumor cell enrichment by filtration is based on the assumption that CTCs are larger than blood cells. In this method, a microporous membrane filter with circular pores (~7 microns in diameter) is used to filter diluted blood [20].

3.4 CAM-based method Vita-Cap A special blood collection tube called VitaCap (Vitatex) was designed [21, 22] based on the assumption that metastatic cells, including CTCs, have the ability to adhere and invade collagen adhesion matrix (CAM) [23]. In this method, whole blood is incubated in the Vita-Cap tube allowing the CTCs to adhere to the internal coating of CAM. Non-adhered blood cells are then washed away. The CAM is subsequently broken down by collagenase treatment to release the CTCs. Of note, the resulting enriched fraction also contains leukocytes that were non-specifically adhered to CAM [21, 22].

4 Strategies for CTC isolation Techniques for isolation of CTCs from enriched samples include fluorescence-activated cell sorting (FACS) or micromanipulation of cells (Fig. 1, Table 2, and Supplementary Table 1). Micromanipulation involves microscopy-based techniques to distinguish and isolate labeled target cells by manual picking using a micropipette or a micromanipulator. Cell sorting via FACS analysis allows semi-automated isolation of single or pools of cells [24]. Advantages of FACS over micromanipulation include less user-intervention and higher throughput. In addition, micromanipulation of cells into a reaction tube can be difficult because of their fragile nature and tendency to stick to the slide surface or to neighboring cells [25].

Table 2 Methods for enrichment and isolation of circulating tumor cells (CTCs) and principles behind each method including examples Methods

Basis

Enrichment Immunomagnetic (beads, rods, column, magnetophoresis) Microfluidic (functionalized surfaces) Microfluidic (inertial focusing, hydrodynamic size) Size/Density separation (filter and density centrifugation) Collagen adhesion matrix (CAM) adherence

Cell surface markers Cell surface markers Physical properties Physical properties Biological properties

Examples Cell Search, Magsweeper, IE/FACS, CTC-iChip HB CTC-Chip CTC-Chip Screencell, Ficoll separation Vita-Cap

Isolation Micromanipulation/micropipetting Flourescence-activated cell sorting (FACS)

Cellular markers Cellular markers

Detection Immunocytochemical/immunofluorescence Immunofluorescence

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5 Nucleic acid isolation The adoption of a nucleic acid isolation protocol into the workflow usually depends on the type of input for downstream molecular analyses (i.e., CTC-enriched versus isolated cells; Table 1, Supplementary Table 2). Column-based nucleic acid isolation often used for CTC-enriched samples may not be suitable for limited numbers of isolated cells due to a high potential for loss of nucleic acid material during liquid transfers. Alternatively, subsequent steps in the workflow, e.g., nucleic acid amplification, can be performed in whole cell lysates without nucleic acid purification, as in the case of the 11 studies described in this paper (Supplementary Table 2). Emerging methods that will allow for simultaneous isolation of DNA and RNA from the same limited number of cells also need to be evaluated [26, 27].

6 DNA and RNA amplification The DNA/RNA available from scarce CTCs isolated from blood is usually not sufficient for the nano- to microgram input requirements for genomic analyses like microarrays and next generation sequencing. Therefore, amplification of nucleic acids is most often necessary prior to any gene expression or copy number assessment. Supplementary Table 2 lists some examples of amplification methods. It is important that the amplification protocol can amplify RNA or DNA from as little as a single cell (high sensitivity), ultimately yielding an accurate representation of the original input material (high specificity) [28]. Artifacts and biases of the amplification methods should also be assessed [15]. For example, in next generation sequencing, the rates of sequencing errors introduced by the amplification method must be evaluated and should be considered when interpreting results [29].

7 RNA profiling of CTCs Early efforts on CTC transcriptome analyses were performed on admixtures of CTCs and leukocytes. More recently, there has been a special focus on isolated single cells (Fig. 1, Table 1, Supplementary Tables 1 and 2). Noteworthy is the demonstration of the feasibility of single CTC RNA sequencing (RNAseq) analysis allowing detailed interrogation of CTC transcriptomes [15]. Below, we discuss various methods of enrichment and isolation approaches that have successfully yielded CTC-specific expression profiles. 7.1 Immunomagnetic enrichment CellSearch Initial transcriptional profiling experiments using the CellSearch system were performed on CTC-enriched

samples prepared using an automated immunomagnetic enrichment platform (CellTracks Autoprep System and CellSearch Profile Kit) [30-32, 13]. Blood samples from healthy individuals were subjected in parallel to mock enrichment, and served as negative controls to determine a normal baseline gene expression. O’Hara et al. [31] applied this technique to detect CTCspecific transcripts in 9 castration resistant prostate cancer patients (CRPC). Following whole transcriptome amplification, a multigene RT-PCR analysis was performed on 37 genes. Detection of amplicons of expected size assessed via gel electrophoresis and densitometry were considered positive for expression. High detection rates were observed for genes associated with prostate cancer including KLK3 (encodes prostate specific antigen, PSA), FOLH1 (encodes prostatespecific membrane antigen, PSMA), and the AR (androgen receptor) genes. The expression of these genes was not detected in 13 healthy control samples. In a study performed by Smirnov et al. [30] using the same enrichment process, 3 index patients with metastatic colorectal, prostate, and breast cancers with high CTCs counts were chosen for an initial experiment to determine candidate CTCspecific genes for each cancer type. RNA samples extracted from CTC-enriched and corresponding CTC-depleted fractions were subjected to independent gene expression microarray analysis. Differential expression analysis of CTC-enriched versus CTC-depleted yielded CTC gene expression signature consisting of 35 genes which was subsequently validated via QPCR analysis in 74 metastatic patients (colorectal=30; prostate=31; breast=13) and 50 healthy controls. Sieuwerts and colleagues [13] optimized a method for multiplex QPCR analysis in CTC-enriched samples. They performed extensive testing to find optimal protocols for cDNA synthesis and linear amplification from limited cell inputs. Following evaluation in cell line spike-in models and blood cells from healthy donor, the optimized protocol was used to study CTC-specific gene expression in clinical samples. RNA was isolated from CTC-enriched fractions derived from blood of 10 metastatic breast cancer patients. The transcript-specific amplification of 16 exploratory genes was performed, and the resulting amplified cDNAs were subjected to multiplex QPCR analysis. Results revealed that expression profiles in five samples positive for CTCs (enumerated via CellSearch) were clearly distinct from those with no detectable CTCs. For example, epithelial markers (e.g., EPCAM and cytokeratins KRT7, KRT17, and KRT18) were highly expressed in CTC-positive samples as compared to those that were CTC-negative. A follow-up study [32] evaluated the expression of a gene panel of CTC-associated mRNA (55) and microRNA (10) in the blood of 50 metastatic breast cancer patients and 53 healthy donors. 14 mRNAs (including KRT19, S100A16)

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and one microRNA (hsa-miR-183) were highly expressed in patients that were positive for CTCs (n=32) compared to those that did not have detectable CTCs (n=9). Exploratory analysis also revealed distinct CTC clusters characterized by different global gene expression patterns. Unsupervised hierarchical clustering analysis revealed that CTC expression profiles clustered well with those from matched primary tumors (n=8 pairs). A significant discordance between ER (ESR1) and HER2 (ERBB2) gene expression in CTCs and the known clinical status of the primary tumors (n=36) was observed. Magsweeper The first application of the Magsweeper for CTC molecular characterization involved single cell QPCR analysis [33]. After enrichment, the resulting cell suspension of EPCAM-captured cells was visually inspected using a microscope to identify putative CTCs. Manual pipet aspiration was performed to transfer single cells in the reaction tubes. RNA in cell lysates was reverse transcribed and 87 specific transcripts were subjected to target specific amplification. Parallel real-time QPCR reactions of individually amplified cDNA were performed using a microfluidic dynamic array (Fluidigm). After validation using primary and metastatic breast cancer cell lines, single cells from 50 breast cancer patients (primary=20; metastatic=30) were subjected to expression profiling. About 20 % of the isolated cells was nonspecifically captured leukocytes (positive for expression of CD45). Of the 87 genes, 31 (36 %) were reliably detected and were used to classify single CTC samples by hierarchical clustering analysis. Two distinct clusters containing single cells from both primary and metastatic patients were observed. Also, single cell samples from the same patient were also represented in both clusters. Genes associated with epithelial phenotype, epithelial-mesenchymal transition (EMT), metastasis, PI3K/AKT/mTOR pathway, apoptosis, cell proliferation, DNA repair, cell metabolism, and stem cellness were commonly expressed in CTCs. The Magsweeper device was also used to isolate single circulating melanoma cells for RNAseq analysis [15]. Since melanoma cells do not have detectable EPCAM expression, magnetic beads coated with CSPG4 (or NG2) antibodies were used for enrichment. Labeled cells were then isolated using a micropipette. The mRNA from single cells was amplified using a method that generates full-length cDNA (SmartSeq). Amplified cDNA was then used for library construction for next generation sequencing. Applying the method for isolated single NG2+ cells from blood of a patient diagnosed with recurrent metastatic melanoma, the global and gene setspecific expression patterns provided support that NG2+ cells were circulating malignant cells of melanoma origin. The improved read coverage also facilitated the detection of SNPs, including those previously documented in melanoma. In addition, up- and down-regulated plasma-membrane genes

were examined to identify candidate biomarkers for melanoma CTC detection. Interestingly, cadherin 1 (CHD1) expression was not detected in CTCs. CDH1 loss is associated with cancer progression [34]. Genes involved in immune surveillance (e.g., HLAs) were also downregulated, suggesting a mechanism on how CTCs escape the immune system. A similar application of the Magsweeper involved the isolation of 67 single putative EPCAM-positive CTCs from 13 metastatic prostate cancer patients for RNAseq analysis [35]. Amplified cDNA libraries generated from 20 single CTCs representing 4 patients were subjected to next generation RNA sequencing. Reliable detection of prostate marker expression including the AR (androgen receptor), KLK3 (encodes prostate specific antigen), TMPRSS2, and the lack of CD45 expression confirmed that isolated single cells were malignant prostate CTCs. In general, global expression profiles of CTCs from the same patients clustered together. Differential expression analysis between CTCs and normal prostate tissues revealed 181 candidate CTC-specific markers. Ontology and pathway analysis revealed significant enrichment of genes involved in metabolic processes and the cell cycle. CELLection An EPCAM-based immunomagnetic bead enrichment method (CELLection Epithelial Enrich kit, Invitrogen) was used to enrich for CTCs to study gene expression of these cells in metastatic colorectal cancer [16]. RNA isolated from CTC-enriched fraction from blood of 6 cancer patients and mock-enriched blood samples from three healthy donors (non-CTC control) was subjected to whole transcriptome amplification and to microarray expression analysis. To identify CTC specific expression, the non-CTC background was computationally subtracted resulting in the detection of 410 differentially expressed genes. Pathway analysis revealed that the CTC-specific gene set was enriched for genes related to cell survival (e.g., CLU and TIMP1) and signaling pathways involved in cellular movement (e.g., TGFB1) and cell adhesion (e.g., ITGB5). QPCR validation of a subset of 11 genes in an independent cohort of 20 metastatic colorectal cancer patients and 10 healthy volunteers revealed consistent results. In addition, these genes were shown to be up-regulated in liver and lung metastases as compared to primary tumors. Analysis of the genes’ prognostic value confirmed their potential as candidate markers for disease progression in colorectal cancer. 7.2 Microfluidic-based enrichment HB

CTC chip Yu et al. [36] utilized HBCTC-chips to enrich for EPCAM-expressing pancreatic CTCs. Enumeration studies in cancer patients (n=15) and normal healthy controls (n=10) revealed specific detection of CTCs. Molecular profiling of CTCs was performed by subjecting CTC-enriched blood

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samples to digital gene expression (DGE) profiling using next-generation RNA sequencing compatible with limited inputs. A parallel mock-enrichment using IgG-functionalized HB CTC-chip was also performed. To determine CTC-specific expression, DGE data from leukocyte background of paired mock-enriched samples were subtracted. Using this approach, initial studies in mice (genetically engineered pancreatic cancer model) demonstrated Wnt2 expression in CTCs. RNA-ISH studies in human pancreatic CTCs also showed Wnt2 expression in a subset of CTCs. Although DGE analyses (12 cancer, 4 healthy) at the individual gene level did not reveal overexpression of Wnt2, gene set enrichment analysis revealed a significant enrichment of genes involved in non-canonical Wnt signaling pathway, WNT- and TGFβ-driven signatures. This approach was also applied to CTCs with low EPCAM expression such as those undergoing EMT [37]. So, in addition to the EPCAM antibody, the HBCTC-chip was functionalized with antibodies against EGFR and HER2. Five serial samples from one patient were analyzed and compared to samples from 10 healthy donors. 45 CTC associated transcripts were detected, including epithelial markers KRT8, KRT19, and breast tumor markers, mammaglobins (SCGB2A2 and SCGB2A1), and trefoil factors 1 and 3 (TFF1 and TFF3). Interestingly, gene set enrichment analysis revealed a significant bone relapse signature consistent with the patient’s bone metastasis. Comparison of gene expression profiles between a serial sample containing high levels of mesenchymal CTCs versus 4 other samples containing mostly epithelial CTCs revealed 170 transcripts associated that were differentially expressed. Gene set enrichment analysis revealed high representation of EMT-related pathways as well as TGFβ gene signatures in mesenchymal CTCs. Interestingly, individual gene analysis showed that the upregulation of FOXC1, a transcription factor promoting EMT in cell culture. CTC-iChip In a proof of concept study utilizing the CTCiChip, a blood sample from a metastatic castration resistant prostate cancer was subjected to negative selection to deplete hematopoietic cells [19]. EPCAM staining of the enriched sample was performed to detect and isolate putative CTCs via micromanipulation. Fifteen EPCAM-positive single cells were isolated from the enriched sample. Targeted amplification was performed for 43 genes and then subjected to expression profiling using a microfluidic dynamic array (Fluidigm). Results confirmed the epithelial nature of the single cells with a subset exhibiting dual EMT properties. Notable heterogeneity in cell proliferation and stem cell marker expression was observed. AR signaling status (on=PSA+, off=PSMA+or mixed=PSA+/PSMA+) [38] was also heterogeneous among the single cells.

7.3 Size-based enrichment ScreenCell Size-based microfiltration and subsequent micromanipulation was used to select for cells (CD45negative) that were retained on filter membranes [39]. A total of 38 single CTCs were isolated from 7 metastatic prostate cancer patients. The expression of 84 genes including prostate-specific markers, EMT-related genes, stem-cell markers, and drug targets was measured via multiplex QPCR using a microfluidic dynamic array (Fluidigm). EPCAM expression was observed in majority of the single cells while only a fifth expressed prostate specific markers such KLK3 (PSA) and FOLH1 (PSMA). Stem cell marker gene expression was infrequent. A subset of EMT-related genes had significan tly high er expre ssio n in CTCs from castration-resistant compared to those from castrationsensitive prostate cancer patients. 7.4 CAM-based enrichment Vita-Cap In a study by Lu et al. [21], blood samples from early and metastatic breast cancer patients and healthy donors were subjected to enumeration using CAM-based enrichment followed by staining for epithelial markers, EPCAM and cytokeratins. A separate aliquot of blood from 9 cancer patients with ≥60 CTCs per ml were subjected to further molecular analysis. Since the enriched samples also contained ~1,000 normal leukocytes, mock-enriched blood from 7 healthy volunteers with no detectable CTCs were used as reference controls. RNA from enriched samples were isolated and subjected to gene expression analysis using oligomicroarrays. To generate CTC-specific gene expression from this training set, data generated from healthy blood was used to subtract normal leukocyte expression from those that were obtained from blood of 9 breast cancer patients. For further validation, the resulting 21-gene panel was evaluated in a test set consisting of 9 normal and 20 breast cancer samples. The panel included 11 epithelial/leukocyte markers, 3 internal control genes present on the array, and 7 epithelial markers chosen from >1,000 genes that were significantly upregulated in cancer patients relative to healthy controls. Of the 21 genes, 12 genes were shown to be upregulated in cancer samples, including 4 cytokeratin genes, EPCAM and 7 other cancerassociated genes, e.g., TERT, ESR1, and PGR.

8 DNA profiling of CTCs Malignant cells most often exhibit alterations in genomic copy number [40]. Early efforts to detect genomic aberrations in occult tumor cells were focused on disseminated tumor cells

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(DTCs) isolated from the bone marrow [41-45, 25, 46]. The higher numbers of DTCs as compared to CTCs may have facilitated such efforts [47-49]. With more sensitive methods, recent efforts have included copy number profiling of CTCs. In contrast to expression profiling, copy number assays are more sensitive to the presence of contaminating normal genome from blood cells. Therefore, a subsequent purification step after the enrichment process is necessary. Below, we discuss studies which utilized FACS analysis or micromanipulation to isolate CTCs for downstream genomic analyses (Fig. 1, Table 1, Supplementary Tables 1 and 2). With one exception, copy number analysis was reported for CAMenriched samples without purifying CTCs [22]. 8.1 CAM-based enrichment Paris and colleagues [22] used a CAM-adherence approach (Vita-Cap) to enrich for tumor cells from blood of 13 metastatic prostate cancer patients. DNA was isolated from CAMcaptured cells including co-purified background leukocytes and was then subjected to array comparative genomic hybridization (ACGH). Analysis of recurrent aberrations in CTCs from 9 patients revealed copy number alterations in cancer related genes (e.g., POTE15 and GSTT1). Comparison of genomic profiles CTCs, primary tumor and metastatic tumors from two patients revealed high concordance. Of note, all the samples in this study were considered positive for CTCs, and the detection of high molecular weight DNA after nucleic acid purification from enriched samples was used as a surrogate marker for CTC presence. 8.2 FACS-based isolation An example for CTC isolation using FACS analysis is the IE/ FACS method [24]. It is a two-step process composed of immunomagnetic enrichment using EPCAM antibodycoated magnetic beads followed by FACS analysis. Simultaneous labeling of blood samples with two distinct EPCAM monoclonal antibodies, one attached to magnetic beads and the other to a fluorochrome, is performed during the enrichment step. The enriched samples are then stained to facilitate cell sorting of nucleated cells that express EPCAM away from those that express the CD45 leukocyte marker. Two studies have demonstrated the use of IE/FACS analysis to isolate pooled or single CTCs for ACGH analysis [50, 51]. In both studies, blood samples were pre-screened for the presence of CTCs via the CellSearch system. A separate aliquot of blood was subjected to IE/FACS if ≥1 CTC per mL of blood was detected. First, a feasibility study involving 20 castration resistant prostate cancer patients was performed to demonstrate the isolation of highly pure CTCs from blood. Genomic DNA from small pools of IE/FACS-isolated CTCs was subjected to whole genome amplification followed by copy number analysis using

bacterial artificial chromosome CGH arrays. Successful genomic analysis of CTCs from 9 patients revealed profiles containing aberrations frequently seen in primary prostate tumors. However, additional aberrations were also observed including high level gains in the androgen receptor (AR) locus in the X chromosome, consistent with observations in castration resistant prostate solid tumors [52]. In addition, comparison of genomic profiles between CTCs from two patients with corresponding pretreatment primary tumors revealed clonalrelatedness but with some divergence including amplification of the AR region in CTCs. Second, a larger study was conducted in 181 metastatic breast cancer patients [50]. CTCs from 102 patients successfully analyzed by ACGH revealed copy number aberrations similar to that observed in previously published cohorts of primary breast cancers. Clonal relationships were observed between breast CTCs and corresponding primary tumors from 5 patients. Analysis of CTCs from serial samples confirmed the reproducibility of the assay and revealed genomic changes over time. 8.3 Micromanipulation of CTCs Micromanipulation is another approach for purification of single CTCs. Here, CTC-enriched cell suspensions are examined under a microscope, and cells of interest are isolated using a micromanipulator or a micropipette. Criteria used to select cells are usually based on morphology and/or staining characteristics. Below are examples of studies that have used micromanipulation to isolate CTCs for DNA analysis followi n g d e n s i t y g r a d i e n t c e n t r i f u g a t io n [ 5 3 , 2 5] o r immunomagnetic techniques [54-56]. Immunomagnetic enrichment followed by microscopy and micromanipulation was used to obtain circulating melanoma cells for metaphase CGH analysis [54]. This report included 15 CSPG4-positive individual cells from 7 melanoma patients with Stage III and IV disease. Genomic analysis revealed chromosomal gains and losses in these cells. In contrast, normal profiles were observed in control cells (CSPG4negative) isolated from the same enriched samples. Additionally, single cells from the same patient revealed similar aberrations providing evidence for clonality. Copy number analysis of the EGFR gene, a putative therapeutic target in CTCs and DTCs, was performed in individually isolated CTCs and DTCs [53]. This study first assayed EGFR copy number using ACGH in single cells from cancer cell lines with known EGFR copy number status. Results revealed cell-to-cell heterogeneity of EGFR copy number. The ACGH data were then used to calibrate a QPCR method to measure EGFR copy number in single CTCs and DTCs from 3 metastatic breast cancer patients. Moderate and high copy number gains in EGFR were consistently observed in single DTCs from one patient, and less so in DTCs and CTCs from the other two patients.

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Feasibility studies performed on DNA from single and pooled breast cancer cells from culture demonstrated the robust detection of major copy number gains or losses via ACGH [25]. 28 single CTCs from 6 patients were successfully profiled. In one patient, 4 CTCs showed similar genomic aberrations on chromosome 11 while 6 showed a normal profile suggesting that different tumor clones may be present in the blood. A study performed by Heitzer and colleagues [55] demonstrated the feasibility of copy number analysis and mutation screening in CTCs from patients diagnosed with metastatic colorectal cancer patients. DNA from 37 CTCs isolated from 6 patients was subjected to whole genome amplification followed by ACGH analysis. Results revealed copy number aberrations in CTCs that were commonly seen in colorectal cancer. Although some divergent genomic aberrations were present, major similarities in genomic profiles were observed between CTCs, matched primary tumors and metastatic lesions. ACGH profiles also revealed “private” aberrations that were unique to single cells. Amplified CTC genomic DNA samples from 2 patients were screened for mutations in a panel of 68 colorectal cancer-associated (frequently mutated >3 %) single nucleotide variants using next generation sequencing. This was then compared to the corresponding archival primary tumor and metastatic tissue. In one patient, mutations on APC, KRAS, PIK3CA, and TP53 were shared in CTCs and matched primary and metastatic tissues. Sequencing analysis of archival tumors revealed that private mutations observed in CTCs were also present in subclones of tumor cells in primary tumors and metastatic lesions. Ni et al. [56] subjected single cell DNA to whole genome amplification using the multiple annealing and looping based amplification cycles (MALBAC) method [57]. Next generation low-pass whole genome sequencing (0.1x coverage) on single CTCs isolated from 11 lung cancer patients and additional deep whole exome sequencing were performed on a subset of 5 patients. Copy number analysis revealed high similarities of genomic profiles among single CTCs from the same patient and among different patients. However, distinct global copy number profiles were observed between lung adenocarcinoma (ADC) and small-cell lung cancer (SCLC). Exome sequencing analysis revealed single nucleotide variants and insertion/deletions previously known to be associated with drug resistance and ADC-to-SCLC transition.

characterization, reviewed above, are now beginning to provide initial insights into these questions. The role of CTCs in the metastatic process remains an open and tantalizing question. Solid tumors vary widely in their ability to shed CTCs into circulation. CTC levels are different across tumor types; but even with a given tumor type such as breast cancer, CTC levels can range from 0 to >100 per ml of blood. CTCs are much more frequently detected in metastatic vs. early stage cancer patients, but in metastatic disease CTC levels are not closely correlated with disease burden. Overall, it appears that only a very small fraction of CTCs ever give rise to distant metastases [58, 59]. A significant proportion of shed cells are probably eliminated via a poorly understood phenomenon regarded as “metastatic inefficiency” [60]. Preclinical studies have provided some insights into potential mechanisms involved in metastatic inefficiency, including poor survival and increased apoptosis after extravasation of solitary CTCs in distant sites [59, 60]. Furthermore, only a small subset of CTCs has been characterized as having high metastatic potential [61]. How CTCs home to different organs as sites for potential metastasis is largely unknown. Proto-metastatic phenotypes are being actively investigated in primary tumor tissue (for review, see Ref [62]); it will be of much interest to assess these phenotypes in CTCs. Interestingly, Kim and colleagues demonstrated in preclinical studies that CTCs can survive by homing back to the primary tumor or originating metastasis via a process called “self-seeding” [63]. Other facets of CTC biology remain poorly understood as well, such as the mechanisms by which CTCs persist in circulation and avoid apoptosis and host immunity. A recent study showed that CTCs might defend themselves from immune clearance by up-regulating the anti-phagocytotic gene CD47, which encodes the “don't eat me” signal [64]. Another study showed that up-regulation of the anti-apoptotic gene BCL2 might contribute to CTC survival [65]. It has also been postulated that CTCs can persist in circulation without active growth for prolonged periods, representing a potentially important aspect of tumor dormancy. For example, Ki-67 has been observed to be down-regulated in CTCs, indicating reduced proliferative activity and consistent with a dormant state [66].

10 Discussion 9 Towards an understanding of the biology of CTCs The biology of CTCs is not very well understood. For example, mechanisms involved in their dissemination and survival, homing to distant sites, and metastatic potential have yet to be elucidated. Technical advances in CTC isolation and

The field of CTC profiling is in its infancy. While initial efforts have focused on detection and enumeration of CTCs, relatively few studies involving molecular characterization of CTCs have been reported to date. In this review, we have surveyed recent advances in CTC isolation and molecular profiling.

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Early in the field of CTC study, researchers questioned whether epithelial cells found in the blood of cancer patients were indeed tumor cells [2]. This question was especially crucial in conjunction with CTC detection methods based upon epithelial-specific markers such as EPCAM, MUC1, and epithelial cytokeratins. Transcriptional profiling has demonstrated the up-regulation of cancer-related genes, e.g., AR in prostate CTCs and ERBB2 and ESR1 in breast CTCs, respectively. In addition to providing evidence of the malignant nature of CTCs, these results indicate that therapeutic targets can be characterized in CTCs. However, given the complexities inherent in transcriptional analysis of rare cells and the limited number of studies to date, the clinical r e l e v a n c e o f s u c h r e s u l t s r e m a i n s u n c l e a r. Transcriptional analyses of important target genes and pathways in CTCs warrant further investigation. Recent studies have performed genome-wide copy number analysis on CTCs, and thereby have shown that CTCs contain significant genomic aberrations [55, 50, 53, 25, 51, 56]. Further studies directly compared the genomic aberrations in CTCs with those in primary tumors. For example, gains in 1q and 8q and losses in 8p and 16q were common in both breast CTCs and primary tumors [50]. These findings provide unequivocal evidence of the malignant nature of circulating epithelial cells, confirming that they are indeed circulating tumor cells. Studies that have compared copy number data from CTCs and with corresponding primary and/or metastatic lesions in the same patient have clearly demonstrated clonal relationships [55, 50, 54, 51, 56]. Furthermore, genomic analysis of single CTCs from the same patient revealed similar copy number profiles indicating clonality [55, 56]. However, cell-to-cell heterogeneity was also observed as demonstrated by the presence of genomic aberrations that were unique to single CTCs [55]. Although it has been critical to confirm the presence of established genomic aberrations (e.g., those observed in primary tumors) in CTCs, studies designed to explore the evolution of CTC-specific alterations will be important in elucidating mechanisms involved in cancer progression and perhaps discovering novel therapeutic targets and biomarkers [1, 67, 2]. Efforts in molecular characterization of CTCs face numerous technical challenges. Currently, studies have been focused on metastatic cancers where CTCs numbers may be elevated. For CTC detection in early stages of cancer, where tumor burden is lower and curative treatment is available, improvements in sensitivity and specificity of enrichment/isolation methods are necessary for reliable detection, and especially, isolation. In addition, the scalability of the processes involved in CTC isolation should also be addressed to increase throughput [e.g., number of samples processed (Supplementary Table 3) and volume of blood processed] via improvements in assay configuration, including automation. An additional problem intrinsic to transcriptional profiling is the labile

nature of RNA. Limiting RNA inputs may be prone to quality problems, for example, RNA degradation issues were often observed in single cell RNAseq studies [35, 15]. Technical advances in the preservation and stabilization of RNA (as well as cell surface proteins used for detection) will benefit gene expression profiling efforts especially those involving multicenter studies that require shipment of blood samples. CTC enrichment protocols employ varying biological and/ or physical parameters for CTC capture and therefore may be subject to method-specific limitations [68, 3]. Currently, EPCAM-dependent approaches are the predominant methods for enrichment of tumor cells in the blood. However, this approach may miss CTCs that express lower levels of EPCAM, e.g., mesenchymal CTCs. Additional cell surface markers for CTC capture may facilitate the enrichment of this subpopulation of CTCs [37]. Similar questions arise in the enrichment of particular CTC phenotypes [69, 70]. For example, CTCs from castration-resistant prostate cancer patients captured via CAM-adherence [22] and EPCAM-based [51] methods revealed distinct genomic profiles. New methods being developed for CTC enrichment and isolation may complement existing methods. However, it will be important for new methodologies to show clinical relevance, such as the demonstration of prognostic or predictive associations for CTC detection or correlation with existing methods (e.g., CellSearch) that have shown such associations. Moreover, all approaches will require rigorous validation and standardization if they are to be adopted in the clinic to guide therapy. Recent CTC genomic efforts have begun to focus on single cell analysis. Indeed, improvements in single cell sequencing [71] may provide new and helpful tools for analysis of the CTC genome. However, the clinical utility of single cell diagnostics remains unclear. Although single cell analysis may further reveal heterogeneity, the heterogeneity issue itself massively complicates interpretation of results obtained from single cells. It may be preferable to study populations of CTCs or to aggregate single cell data. Analysis of a cell population provides greater statistical power and less bias, and predominant phenotypes can be assessed. For example, current tumor diagnostics, including standard pathology, immunohistochemistry (IHC), fluorescence in-situ hybridization (FISH), expression and copy number arrays, and mutation testing, do not use single cell analysis for many reasons beyond technical limitations alone. Standard clinical practice is to evaluate tumors based on the observable phenotypes present in a tissue specimen, and to make therapeutic decisions accordingly. Whether single cell analysis can supplement analysis of tumor cell populations and tissues remains an interesting question for further study. Parallel improvements in rare-cell/CTC capture and genomics technologies have now enabled detailed genomic profiling of CTCs. This advance represents an important step towards understanding the biology of cancer metastasis and

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progression, and provides a promising new avenue for biomarker discovery and validation. Acknowledgments We thank Prithi Polavarapu for assistance in manuscript preparation and Rishi Das and Nak Joon Kim for assistance in the literature search. Disclosure of potential conflicts of interest JWP: Research Grant (Veridex). No potential conflicts of interest were disclosed by MJMM.

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