circulating tumor cells from different vascular sites ...hep3b were purchased from the shanghai cell...

Personalized Medicine and Imaging

Circulating Tumor Cells from Different VascularSites Exhibit Spatial Heterogeneity in Epithelialand Mesenchymal Composition and DistinctClinical Significance in HepatocellularCarcinomaYun-Fan Sun1,Wei Guo2, Yang Xu1, Yin-Hong Shi1, Zi-Jun Gong1, Yuan Ji3, Min Du3,Xin Zhang1, Bo Hu1, Ao Huang1, George G. Chen4, Paul B.S. Lai4,Ya Cao5, Shuang-Jian Qiu1,Jian Zhou1,6, Xin-Rong Yang1, and Jia Fan1,6

Abstract

Purpose: The spatial heterogeneity of phenotypic and molec-ular characteristics of CTCs within the circulatory system remainsunclear. Herein, we mapped the distribution and characterizedbiological features of CTCs along the transportation route inhepatocellular carcinoma (HCC).

ExperimentalDesign: In 73 localizedHCCpatients, bloodwasdrawn from peripheral vein (PV), peripheral artery (PA), hepaticveins (HV), infrahepatic inferior vena cava (IHIVC), and portalvein (PoV) before tumor resection. Epithelial and mesenchymaltransition (EMT) phenotype in CTCs were analyzed by a4-channel immunofluorescence CellSearch assay and microflui-dic quantitative RT-PCR. The clinical significance of CTCs fromdifferent vascular sites was evaluated.

Results: The CTC number and size gradient between tumorefferent vessels and postpulmonary peripheral vessels wasmarked. Tracking the fate of CTC clusters revealed that CTCsdisplayed an aggregated–singular-aggregated manner ofspreading. Single-cell characterization demonstrated that

EMT status of CTCs was heterogeneous across different vas-cular compartments. CTCs were predominantly epithelial atrelease, but switched to EMT-activated phenotype duringhematogeneous transit via Smad2 and b-catenin related sig-naling pathways. EMT activation in primary tumor cor-related with total CTC number at HV, rather than epithelialor EMT-activated subsets of CTCs. Follow-up analysis sug-gested that CTC and circulating tumor microemboli burdenin hepatic veins and peripheral circulation prognosticatedpostoperative lung metastasis and intrahepatic recurrence,respectively.

Conclusions: The current data suggested that a profoundspatial heterogeneity in cellular distribution and biologicalfeatures existed among CTCs during circulation. Multivascularmeasurement of CTCs could help to reveal novel mechanismsof metastasis and facilitate prediction of postoperative relapseor metastasis pattern in HCC. Clin Cancer Res; 24(3); 547–59.�2017 AACR.

IntroductionMetastasis remains the principal factor that hastens death in

patients withmalignant tumors, but the current understanding ofmetastasis is incomplete (1). The results of prior animal studieshave suggested that trafficking of tumor cells via bloodstream isinvolved in the induction of metastatic disease (2–6). However,the evidence derived from animal models differs significantlyfrom human cancer. Furthermore, because approaches for study-ing the hematogeneous metastasis in human are limited, theprecise mechanisms by which tumor cells migrate through circu-lation, reach specific distal organs, and form metastases remainunclear in human scenarios.

Circulating tumor cells (CTC) are the key to understandingcritical mechanisms of blood-borne metastasis that might not beapparent following analyses of primary or secondary tumors (7).Transportation of tumor cells via bloodstream is a dynamic pro-cess, and CTCs are theoretically a population of cells that displayprofound spatial heterogeneity (1). However, the current knowl-edge of the heterogeneity of CTCs is limited, and has been obtainedprimarily from the study of CTCs in peripheral venous blood,which may not be representative of the entire cell population.

1Department of Liver Surgery, Liver Cancer Institute, ZhongshanHospital, FudanUniversity; Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry ofEducation, Shanghai, P.R. China. 2Department of Laboratory Medicine, Zhong-shan Hospital, Fudan University, Shanghai, P.R. China. 3Department of Pathol-ogy, Zhongshan Hospital, Fudan University, Shanghai, P.R. China. 4Departmentof Surgery, The Chinese University of Hong Kong, Prince of Wales Hospital,Shatin, NT, Hong Kong, China. 5Cancer Research Institute, Xiangya School ofMedicine, Central South University; Key Laboratory of Carcinogenesis andCancer Invasion,Ministry of Education, Changsha, China. 6Institute of BiomedicalSciences, Fudan University, Shanghai, P.R. China.

Note: Supplementary data for this article are available at Clinical CancerResearch Online (http://clincancerres.aacrjournals.org/).

Y.-F. Sun and W. Guo contributed equally to this article.

Corresponding Authors: Jia Fan, Department of Liver Surgery, Liver CancerInstitute, ZhongshanHospital, FudanUniversity, 136Yi XueYuanRoad, Shanghai200032, P.R. China. Phone: 8602-1640-41990; Fax: 8602-1640-37181; E-mail:[email protected]; and Xin-Rong Yang, [email protected]

doi: 10.1158/1078-0432.CCR-17-1063

�2017 American Association for Cancer Research.

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Globally, hepatocellular carcinoma (HCC) is one of the mostfrequently diagnosed malignancies (8, 9). Although surgeryremains the primary treatment, HCC patients that undergocurative resection often experience a high incidence of intrahe-patic or extrahepatic metastases (10). Hematogeneous spread isthe major route of HCC metastasis (11), but the molecularevents that transpire during tumor cell migration require furtherelucidation.

Hepatic circulation is connected to systemic circulation by threemajor vessels including the hepatic veins (HV),which serves as theefferent pathway, and the hepatic artery and portal vein (PoV),which function as afferent vessels. Thus, it is feasible to explore thespatial heterogeneity of CTCs during themetastatic process by thedetection of CTCs in both the efferent and afferent tracts in thetumor-bearing liver. In this study, CTCs were identified andcharacterized in gross systemic and hepatic vascular compart-ments as well asmicroscopic hepatic vasculatures along the bloodflow pathway. The CELLSEARCH assay, considered the goldstandard in CTC enumeration and confirmed by our previousstudies (12–14), was used to investigate the differential localiza-tion of CTCs along their spreading route. The biological char-acteristics and potential clinical relevance of CTCs in differentvascular compartments was further investigated, which was notreported previously. The aim of this study was to explore thespatial heterogeneity ofCTCswithin the circulatory system,whichmight offer a novel perspective and aid in unraveling the enigmaof cancer metastasis.

Materials and MethodsPatients and specimens

From August 2013 to November 2015, 73 newly diagnosedHCC patients undergoing curative resection were recruited to thisstudy. The entrance criteria were: (i) definitive pathologic or

radiologic diagnosis according to American Association for Studyof Liver Disease guidelines; (ii) no extrahepatic metastasis at thetime of diagnosis; (iii) no prior anticancer treatment (14). Tumorstage was determined according the Barcelona Clinic Liver Cancer(BCLC) staging system, and tumor differentiation was definedaccording to the Edmondson grading system.

For all patients, 7.5 mL blood was drawn from peripheral vein(PV; the antecubital fossa) and peripheral artery (PA; radialartery), right before preoperative anesthesia, and hepatic veins(HV), infrahepatic inferior vena cava (IHIVC), and portal vein(PoV), intraoperatively, before the resection of primary HCCtumor. The HV, IHIVC, and PoV blood was obtained from adirect venous puncture aftermobilizationof portal triads and liverto exposedHV, PoV, and IHIVC during operation. Ethical approv-al for the use of human subjects was obtained from the ResearchEthics Committee of Zhongshan Hospital consistent with ethicalguidelines of the 1975 Declaration of Helsinki, and informedconsent was obtained from each patient.

Follow-up and tumor recurrencePostoperative patient surveillance was performed as described

(15). A diagnosis of intrahepatic recurrence (IHR) or extrahepaticmetastasis (EHM)was based onCT scans,MRI, digital subtractionangiography, and positron emission tomography scans, with orwithout histological confirmation. Follow-up was terminated onDecember 1, 2016. Time to recurrence (TTR) was defined as theinterval between resection and the diagnosis of any type ofrecurrence (16), with IHR or EHM defined as endpoints (17).Wedefined recurrencewithin1 year after surgical resection as earlyrecurrence (18).

CTC enumeration and characterizationCTC analysis was performed using CELLSEARH system

(Veridex) as described, without knowledge of patient clinicalcharacteristics. The criteria for an EpCAM-positive object to beidentified as aCTCwere nucleated (DAPIþ) intact cell, positive forpan-cytokeratin 8,18,19, and negative for CD45 (14). To preventfalse assignment of a mitotic CTC as a microembolus, circulatingtumor microemboli (CTM) was defined as clusters of CTCscontaining three or more distinct nuclei (19). The numbers ofsingle CTCs and CTM were enumerated separately (20). The sizeof CTC was represented as geometrical area of each positive cell,which was calculated according to the following formula: p� A/2� B/2 (A and B represented as the two longest perpendiculardiameters measured on screen; ref. 21). Detailed procedures forcharacterization of EMT-relatedmolecules in CTCs were includedin Supplementary Materials.

RNA expression profile of single CTCBlood samples drawn from PV, PA, HV, and IHIVC using BD

Vacutainer blood collection tubes (EDTA; BD Biosciences) wereprocessed using CELLSEARCH Profile kit (Veridex) to enrichCTCs, and unfixed CTCs were stained with a PE-labeled EpCAMantibody (Miltenyi Biotec, 130-098-113, diluted1:20) anda FITC-labeled CD45 antibody (BD Biosciences, 555482, diluted 1:20).EpCAMþ/CD45� cells were defined as CTCs. Three single CTCsfrom each patient were transferred under direct microscopicvisualization to individual PCR tubes with a robotic microma-nipulator (Eppendorf). Single-cell RNA was reversed transcribed,followed by specific target preamplification (Fluidigm Corp).Single-cell cDNA was loaded into a 48.48 Dynamic Array chip

Translational Relevance

As the dissemination of tumor cells in circulatory system is aspatially and temporally dynamic process, it is logical toassume that CTCs are a population of cells that displayspatiotemporal heterogeneity. However, current knowledgeof CTCs derived mostly from peripheral venous blood, whichis a snapshot of their entire circulatory process, representingonly the tip of the iceberg. Herein, we systemicallymapped theCTC distribution, characterized their EMT features and eval-uated their clinical significance across multiple vascular com-partments in localized HCC patients. We found CTCs werepredominantly epithelial at release, but dynamically activatedthe EMT-program during hematogeneous transit, via Smad2and b-catenin signaling pathways. Moreover, activation ofEMT in primary tumor unselectively promoted the dispatchof CTCs. CTC and circulating tumor microemboli burden inhepatic veins and peripheral circulation prognosticated post-operative lung metastasis and intrahepatic recurrence, respec-tively. This is thefirst study that illustrates spatial heterogeneityof CTCs in human circulatory system.Our data supported thatinterrogation of CTC fromdifferent vascular sites could furthercurrent knowledge of metastatic mechanisms and facilitateprediction of relapse/metastatic pattern in HCC.

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Clin Cancer Res; 24(3) February 1, 2018 Clinical Cancer Research548




(Fluidigm Corp). Microfluidic qRT-PCR was run by the BioMarkHDReal-Time PCR system (FluidigmCorp). The normalized geneexpression in each cell (�DCt) was calculated as the negative of thedifference between the Ct value for each gene and the GAPDH Ct

value for the cell. Heatmaps of normalized gene expression(�DCt) were generated with the HeatMap image module of GenePattern, with global color normalization. Hierarchical clusteringand principal component analysis (PCA)was based on the resultsfor 16 differentially expressed genes, and excluded results fromhousekeeping gene GAPDH.

Primers used in are shown below:

EPCAM: CGTCAATGCCAGTGTACTTCA; TTCTGCCTTCAT-CACCAAACA.VIM: TGCAGGAGGAGATGCTTCA; CCAGAGACGCATTGTC-AACA.SNAI1: CCCAATCGGAAGCCTAACTACA; GTAGGGCTGCTGG-AAGGTAAA.SOX2: CATGAAGGAGCACCCGGATTA; CGGGCAGCGTGT-ACTTATCC.CDH2: GCCAACCTTAACTGAGGAGTCA; TGGCCACTGTGCTT-ACTGAA.LEF: GAAGGCCATGAAGCAGTACAA; CTGTGACGTGACAA-GCTGAA.CTNNB1: AGCTCTTACACCCACCATCC; TGCATGATTTGCGGG-ACAAA.SMAD2: CCTTACCACTATCAGAGAGTTGAGAC; CCAGAGGC-GGAAGTTCTGTTA.TWIST1: TCAGCAGGGCCGGAGA; CCAGAGTCTCTAGACTG-TCCATT.CDH1: CGTCACCACAAATCCAGTGAAC; TACTGCTGCTTGG-CCTCAAA.KRT8: TGACCGACGAGATCAACTTCC; TGTGCCTTGACCTCA-GCAA.KRT18: GGGACCCCAGGTCAGAGAC; CAGCAAGACGGGCA-TTGTCA.KRT19: CCACTACTACACGACCATCCA; AGGACAATCCTGGA-GTTCTCAA.CD16: GGTTGAGGCAGGACCATACA; GCTATTTCTCAGCC-ATGCTTTCA.CD45: GTGGCTTAAACTCTTGGCATTT; GGGAAGGTGTTGGG-CTTT.GAPDH: GAACGGGAAGCTTGTCATCAA; ATCGCCCCACTTGA-TTTTGG.

Characterization of CTCs for EMT-related moleculesEMTprogram inCTCswas further characterized by the addition

of a FITC labeled anti-vimentin (Novus Biologicals, NBP1-92688F, diluted 1:30) antibody analyzed in the fourth channelof CELLSEARH system. The expression of EMTmolecules in HCCcell lines used in system calibration was first analyzed byWesternblot analysis. The immunofluorescence intensity of epithelial(cytokeratin) and mesenchymal (vimentin) markers (22) wascalibrated through peripheral blood spiking experiments using3 HCC cell lines, MHCC97H, Hep3B, Huh7. The HCC cell line,MHCC97H was established at our institute, while Huh7 andHep3B were purchased from the Shanghai Cell Bank, ChineseAcademy of Sciences. It was passaged for less than 6 monthsafter receipt and used in spiking experiments of this study. Thecell line was characterized by the cell bank based on cellmorphology, postfreeze viability, isoenzyme analysis, DNA

fingerprinting analysis, mycoplasma contamination test, andbacterial and fungal contamination. Briefly, approximately1,000 cells from each of these cell lines were spiked into 7.5-mLblood from healthy donors and processed under identical con-ditions by semiautomated CellPrep system and then scanned onthe CellTracks analyzer II fluorescent microscope using protocoldescribed above. Using this assay, the CTCs fell into three cate-gories as E > M for CTC with predominant cytokeratins staining,E ¼M for CTCs with equal staining intensity of cytokeratins andvimentin, andE<MforCTCwithpredominant vimentin staining.The staining algorithm described above was further validated byconventional immunofluorescence assay. Briefly, blood samplesspiked with HCC cell lines were processed using the CELLSEARHProfile kit (Veridex). Collected cell fractions were then preparedby cytospin (Thermo Fisher Scientific) and subjected to immu-nofluorescence staining for cytokeratins-PE (Novus Biologicals,NBP2-33200PE, diluted 1:20), or vimentin-FITC (Novus Biolo-gicals, NBP1-92688F, diluted 1:20), CD45-APC (BioLegend,304012, diluted 1:20), and DAPI.

To further verify EMT-related molecule expression inCELLSEARH-isolated CTCs, cell fractions were retrieved fromCELLSEARH cartridge, prepared by cytospin (Thermo FisherScientific) and then subjected to immunofluorescence analysisas previous described (23). All samples were analyzedwith a Zeissconfocal microscope (Carl Zeiss).

Establishment of the microfluidic systemTo investigate the effect of hemodynamic shear stress (SS) on

CTCEMTphenotype, we fabricated amicrofluidic system thatwascomposed of a Hamilton syringe pump, a microfluidic chip, andsilicone tubing with a channel. SS was calculated according to theperistaltic speed of circulation and the geometry of microfluidicchannel. This system can generate various level of hemodynamicSS that CTCs may encounter in the human vascular system. Tosimulate arterial and venous condition, 2 � 105 Huh7 cells werepumped into chip and circulated under SS of 12.5 dynes/cm2 and2 dynes/cm2, respectively (24). The circulation times were 5minutes, 30 minutes and 1 hour. Total RNA was extracted fromcirculated Huh7 cells using TRIzol reagent. RNA reverse transcrip-tion was performed and the cDNA reaction products were sub-jected to RT-PCR assay. Five EMT-related signatureswere detected,including E-cadherin, N-cadherin, Vimentin, Snail, and Slug.Primers used in are shown below:

SNAI1: TCGGAAGCCTAACTACAGCGA; AGATGAGCATTGG-CAGCGAG.SLUG: AAAAGCCAAACTACAGCGAACTG; AGGATCTCTGGTT-GTGGTATGACA.CDH1: AAAGGCCCATTTCCTAAAAACCT, TGCGTTCTCTATCC-AGAGGCT.CDH2: CAAACAGCAACGACGGGTTA, TCCCTTGGCTAATGG-CACTT.VIM: AAAACACCCTGCAATCTTTCAGA; CACTTTGCGTTCAA-GGTCAAGAC

IHCTumor and peritumor tissue was available in all 73 patients.

The primary antibodies used in IHCwere anti-E-cadherin (diluted1:300, DAKO), anti-vimentin (DAKO, M3612, diluted 1:300),anti-cytokeratin 18 (DAKO, Z0622, diluted 1:300), and anti-CD45 (DAKO, M0742, diluted 1:300) antibodies. IHC was

The Spatial Heterogeneity of Circulating Tumor Cells

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carried out on4%paraformaldehyde-fixed, paraffin-embedded 4-mm serial tissue sections using a two-step protocol. Briefly, aftermicrowave antigen retrieval, tissue sections were incubated withprimary antibodies for 60minutes at room temperature. Then, thedual-color antigen staining was performed using EnVision G/2Double stain system (DAKO). All tissues were counterstainedwith hematoxylin. Isotype controls used were rabbit immuno-globulin fraction and mouse IgG1 from DAKO. The whole tissuesections were imaged by using a LeicaSCN400 histology scanner(Leica Microsystems). Ten different fields were examined in eachtumor section. Cells that stained positive for Emarkers, negativelyor dimly stained for M marker, and negative for CD45 weredefined as the epithelial (E > M) phenotype; equal intensity forE and M markers, but negative for CD45 were defined as theintermediate (E¼M) phenotype; positive for Mmarker, negativeor dimly stained for E markers, and negative for CD45 weredefined as the mesenchymal (E < M) phenotype. Numbers ofepithelial, intermediate, and mesenchymal HCC cells in eachmicroscopic field were scored separately under 200� magnifica-tion. The proportion of epithelial, intermediate, and mesenchy-mal HCC cells were calculated by dividing their cell counts withtotal HCC cell counts enumerated.

Statistical analysisStatistical analyses were performed using SPSS version 19.0 for

windows (IBM). Data were presented as means, medians, SDs,and ranges. The numbers of CTCs and CTM and the proportion ofCTC EMT-related phenotypes among different vascular sitesincluding microscopic vessels were compared in pair using theWilcoxon signed-rank test. TheMann–WhitneyU test was used toexamine the differences of CTC distribution among clinicopath-ologic variables. The relationship between the TTR and CTC orCTMcountswas analyzedusingKaplan–Meier survival curves anda log-rank test. Univariate and multivariate analyses were basedon the Cox proportional hazards regression model. The optimalCTC or CTM cutoff for prognosis analysis was explored by sub-jecting the data to receiver operating characteristic (ROC) curveanalysis to incorporate both the sensitivity and specificity of theclassifier with an endpoint of intrahepatic recurrence or lungmetastasis at 1 year. CTC or CTM number with the greatest areaunder the curve (AUC)when compared with the other cutoffs waschosen as optimal cut-off value (Supplementary Fig. S7). A two-sided P < 0.05 was considered statistically significant.

ResultsDistribution of CTCs and CTM varied along the disseminationpathway

The distribution patterns of CTCs andCTMwere investigated in73 patients undergoing HCC resection by measuring respectivecounts at five gross vascular sites, including the PV and PA, theHVs, Portal vein (PoV), and the IHIVC (Fig. 1A). The proportionof patients with CTCs detected in PV, PA, HV, IHIVC, and PoVwere 68.49%, 45.21%, 80.82%, 39.72%, and 58.90%, respective-ly (Fig. 1B). The median number of CTCs was 2 (range, 0–26) forPV, 0 (range, 0–11) for PA, 6 (range, 0–31) for HV, 0 (range, 0–6)for IHIVC, and 1 (range, 0–8) for PoV (Supplementary Table S1).Pairwise analyses revealed that the CTC count in HV was signif-icantly higher than counts in other compartments (all P values <0.001; Supplementary Table S2). Moreover, PV retained a greaternumber of CTCs than PA, IHIVC, and PoV (all P values < 0.05;Supplementary Table S2).

Variation in CTC size among the vascular sites was also ana-lyzed. Overall, the mean CTC area was 49.69 � 29.09 mm2 in PV,40.3 � 24.82 mm2 in PA, 100.58 � 73.54 mm2 in HV, 87.21 �52.10 mm2 in IHIVC, and 65.87 � 46.43 mm2 in PoV. The size ofCTCs in HV was significantly larger than in PV, PA, and PoV (all Pvalues <0.05, Fig. 1C). There was no significant difference in CTCsize among PV, PA, and PoV (all P values > 0.05, Fig. 1C).

CTM were identified in PV, HV, and IHIVC compartments atfrequencies of 15.06%, 20.55%, and 4.11% respectively(Fig. 1A and B). CTM was identified in HV (median, 2; range,1–7; mean, 2.73 � 1.91) but not PA in 15 patients, whereas 5patients exhibited reemergence of CTM in PV (median, 2; range,1–4; mean, 2.4 � 1.14; Fig. 1D and Supplementary Fig. S1A).Among 58 patients with no CTM in both the HV and PAcompartments, 6 patients had CTM in PV (median, 2; range,1–2; mean, 1.67 � 0.51; Fig. 1E; Supplementary Fig. S1B).Moreover, at the microscopic level, an abundance of CTCaggregates was identified in the microscopic hepatic veins(mHV), whereas singular CTCs were detected in the microscop-ic hepatic artery (mHA), which was similar to observations ingross vessels (Supplementary Fig. S2).

CTCs exhibited profound phenotypic changes duringdissemination

We previously reported that peripheral venous CTCs detectedby CELLSEARCH in HCC patients displayed considerable varia-tion in epithelial–mesenchymal transition (EMT) features (14). Inthis study, we applied a single-cell RNA expression assay to furtherprofile EMT-associated genes in individual CTCs captured byCELLSEARCH system. Results indicated that peripheral venousCTCs were heterogeneous in EMT status and two-thirds of CTCsshowed higher expression of mesenchymal genes than epithelialones (Fig. 2A). Therefore, it is feasible to use CELLSEARCH systemto interrogate EMT phenotypic dynamics within CTCs duringdissemination.

To measure EMT phenotypes within individual CTCs, a quan-titative 4-channel immunofluorescence CELLSEARCH assay, cal-ibrated usingHCC cell lines spiked into control blood specimens,was established on the basis of expression of the epithelial markerCytokeratin 8/18/19 and the mesenchymal marker vimentin(Supplementary Fig. S3A and S3B). Patient-derived CTCs wereclassified into three subsets as epithelial (E > M), intermediate(E¼M), ormesenchymal (E <M; Fig. 2B). Verification of isolatedCTCs was repeated using conventional confocal microscopy(Supplementary Fig. S4A and S4B).

The CTCs with different EMT phenotypes were comparedamong the five gross vascular compartments in 73 HCC patients.The median number of epithelial, intermediate, and mesenchy-mal CTCs in PV, PA, HV, IHIVC, and PoV was 0 (range, 0–2), 0(0–2), 4 (0–26), 0 (0–4), and 0 (0–4) for epithelial; 0 (range,0–4), 1 (0–6), 0 (0–6), 0 (0–2), and 0 (0–2) for intermediate; and1 (range, 0–20), 0 (0–3), 1 (0–11), 0 (0–2), and 0 (0–3) formesenchymal, respectively. The number of epithelial or interme-diate CTCs was significantly higher in HV, while a greater numberof mesenchymal CTCs were observed in PV compared with theother four compartments (Supplementary Fig. S5, all P values <0.05). In addition, we also observed that CTM inHVwas clusteredby epithelial CTCs, while CTM detected in PV was mainly com-posed of mesenchymal CTCs (Supplementary Fig. S1C).

The proportion of EMT phenotypes among CTCs fromdifferent vascular compartments was investigated, which

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revealed striking intra- and interpatient heterogeneity (Sup-plementary Fig. S6). The most abundant CTCs in HV wereepithelial (median 66.67%; range, 0%–100%) and interme-diate (median 16.67%; range, 0%–100%), whereas a rela-tively small fraction had mesenchymal identity (median,9.67%; range, 0%–64.71%). Conversely, CTCs isolated fromPV were predominantly mesenchymal (median 61.54%;

range, 0%–100%), compared with epithelial (median 0%;range, 0–33.33%) and intermediate (median 0%; range, 0%–

50%) phenotypes. Pairwise comparison of EMT phenotypesin CTCs indicated that HV contained the highest proportionof epithelial CTCs (P values <0.001), whereas mesenchymalCTCs were predominantly localized to the PV (Fig. 2C, all Pvalues < 0.001).

Figure 1.

Distribution patterns of CTCs and CTM along the dissemination pathway. A, Representative images of CTCs detected in PV, PA, HV, IHIVC, and PoV, andCTMs identified in HV, IHIVC, and PV. B, The proportions of patients with CTC or CTM detected at five key vascular sites. C, Equation for the cellular area ofa single CTC as a gauge for size. Comparison of cellular size of single CTCs among PV, PA, HV, IHIVC, and PoV compartments (data are shown as the mean � SD,� , P < 0.05; �� , P < 0.01, n.s. ¼ not significant, t test). D, Spatial dynamics of CTC clustering along the dissemination route in 15 patients with CTM in HV.E, Spatial dynamics of CTC clustering along the dissemination route in 58 patients with no CTM in HV.






Figure 2.

Spatial regulation of the CTC epithelial–mesenchymal transition (EMT) program at gross vascular sites. A, Immunofluorescence and bright-field images of12 single EpCAMþ/CD45� CTCs enriched by CELLSEARCH Profile kit from 4 HCC patients. Heatmap of normalized gene expression (�DCt) of 16 genes ineach of the single CTCs measured by microfluidic qRT-PCR assay. The data represent three technical replicates. NTC, no template control. Scale bar, 10 mm.B, Representative images of three EMT-related CTC phenotypes from patients with localized HCC, identified by CELLSEARCH and immunofluorescencestaining of epithelial (E) and mesenchymal (M) markers. C, Scatter plots showing the comparison of the EMT-related CTC phenotype proportions at the fivevascular sites (� , P < 0.05; ��, P < 0.01, n.s. ¼ not significant, Wilcoxon signed-rank test). D, Box plots displaying the comparison of the EMT-related CTCphenotype proportions at HV, PA, and PV compartments, representing the CTC spreading route from the primary tumor to peripheral circulations. All 16patients had at least 3 CTCs detected in all three vascular compartments. E, Hierarchical clustering of single-CTC PCR gene expression analysis data from4 HCC patients visualized three distinct cell populations, including CTCs predominantly expressing epithelial genes (E < M phenotype), CTCs characterized byexpression of both epithelial and mesenchymal genes (E ¼ M phenotype), and CTCs predominantly expressing mesenchymal genes (E < M phenotype). F,Principal component analysis of single-CTC PCR gene expression data confirmed hierarchical clustering results, visualizing three CTC subtypes. IndividualCTCs was colored by their derivation of vascular compartments. The blue circle surrounds one population, and the red circle surrounds another population.The orange circle surrounds a third intermediate population. G, The expression difference of EMT-related signatures under arterial and venous shear stresscondition in 5 minutes, 30 minutes, and 1 hour (�, P < 0.05, n.s. ¼ not significant, Wilcoxon signed-rank test).

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Analysis of data from16patientswith at least 3CTCs inHV, PA,and PV compartments respectively revealed that CTCs exhibiteddynamic changes in epithelial and mesenchymal compositionduring travel from HCC in situ to PV (Fig. 2D). The epithelialproportion underwent a significant decline when CTCs flowedthrough lung capillaries and entered PA (P < 0.001) and PV (P ¼0.003). There was a significant proportional increase in mesen-chymal CTCs in PV compared with HV (P < 0.001) and PA (P <0.001).

Single CTC transcriptional profiling revealed dynamicexpression of EMT-related genes during dissemination

We then applied single-cell PCR in four HCC patients to studythe dynamic expression of EMT-related genes in CTCs duringhematogeneous dissemination. A total of 102 CTCs fromHV, PA,PV, and PoV compartments from 4 patients were individuallyisolated and subjected to single-cell RNA expression assay, pro-filing for a panel of transcripts implicated in epithelial (CDH1,KRT8, KRT18, and KRT19) and mesenchymal (VIM, SNAI1,SOX2, CDH2, LEF1, CTNNB1, SMAD2, and TWIST1) phenotypesand leukocyte-specific lineage (CD45 and CD16). CTCs isolatedfrom four vascular sites displayed amarked heterogeneity in EMT-related gene expression. Hierarchical clustering analysis visual-ized three distinct cell populations, including subset predomi-nantly expressing epithelial genes (E >M), subset expressing bothepithelial and mesenchymal genes (E ¼ M) and subset charac-terized by exclusively high expression of mesenchymal genes(E < M; Fig. 2E). Majority of E > M cells (62.5%–90%) werecomposed of CTCs isolated from HV, while most E < M cells(50%–100%) were composed of CTCs from PV. Among EMTregulator genes, SMAD2 andCTNNB1were highly upregulated inCTCs clustered into E ¼ M and E<M subsets (Fig. 2E). Principalcomponent analysis (PCA) of single-CTC PCR gene expressiondata further confirmed hierarchical clustering results that CTCfrom different vascular compartments could be subdivided intothree distinct populations basedon their EMT-related gene expres-sion profile (Fig. 2F).

Hemodynamic shear stress induced theEMTphenotype inCTCsWe next reasoned that high shear stress in blood vessels might

induce the EMT phenotype in CTCs. To test this hypothesis, wefabricated amicrofluidic system thatwas composedof aHamiltonsyringe pump, a microfluidic chip, and silicone tubing with achannel to study the effect of arterial and venous shear stress (SS)on circulating Huh7 liver cancer cells. Five EMT-related signatureswere detected, including E-cadherin, N-cadherin, Vimentin, Snail,and Slug. The data indicated that EMT transcript factor Snailstarted to upregulate in 5 minutes under arterial SS condition incomparison with venous SS condition. The expression of othermesenchymal phenotype signatures as Slug, N-cadherin, andVimentin started to increase after 30 minutes circulating underarterial SS condition in comparison with venous SS condition,while epithelial phenotype related signature as E-cadherin startedto downregulate after 30 minutes of circulation (Fig. 2G). Theseresults further supported that EMT programwas activated in CTCswhen they flew through arterial vessels.

EMT features of CTCs in efferent and afferent primary tumormicrovessels

To further elucidate the spatial regulation of EMT in CTCs,EMT analysis was extended to quantification of the number of

epithelial, mesenchymal, and intermediate CTCs in efferent andafferent microvessels in HCC specimens (Fig. 3A; SupplementaryFig. S2). Detached tumor cells drained into systemic circulationthrough mHV, where CTCs stained predominantly for epithelialmarkers (Fig. 4B). CTCshomed to the original tumor-bearing livervia mHA, where more intermediate CTCs were identified com-pared with mHV andmicroscopic portal vein (mPoV; all P values<0.05; Fig. 4B). Interestingly, unlike gross PoV,mPoV functions asan efferent vessel (25) and the vastmajority ofCTCs inmPoVwereepithelial.

Activation of EMT in primary HCC unselectively promotedtumor cell intravasation

The expression of EMT-related markers in tumor tissues andcorrelation with CTCs in gross efferent vessels was analyzed todetermine the influence of EMT activation on tumor cell intra-vasation. Primary HCC tissues were scored for numbers of epi-thelial, intermediate, andmesenchymal cells (Fig. 4C). Themajor-ity of HCC cells were epithelial (mean 95.95%; range 39.13%–

99.88%), whereas a small fraction of HCC cells displayed mes-enchymal (mean 3.30%, range 0.12%–15.80%) or intermediatephenotypes (mean 0.52%, range 0%–53.05%). The total CTCcount in HV was positively correlated with the proportion ofmesenchymal HCC cells, but not with epithelial or intermediatecells (Fig. 4D; Supplementary Table S3). Patients that developedmetachronous lung metastasis tended to have a larger mesenchy-mal population in primary HCC (Fig. 4E). These results wereconsistent with previous reports that EMT promoted tumor cells'intravasation and metastasis (26–29). The potential impact ofEMT activation in the primary tumor on the release of a specificCTC phenotype was evaluated, but mesenchymal and interme-diate primary tumor cells failed to demonstrate a correlation withany subsets of CTCs isolated from HV or mHV (SupplementaryTable S3).

CTCs at gross vascular sites correlated with clinicopathologicvariables

Patient demographics are provided in Table 1. Postoperativerecurrence ensued in 33 of 73 patients, with a mean follow-uptime of 21.9 � 7.3 months (median, 24.4 months; range, 12.9–42.43. months). Among 33 patients with diagnosed recurrence,24 exhibited intrahepatic recurrence (IHR) only, 4 displayed lungmetastasis only, 4 suffered both IHR and lungmetastasis, and onewas diagnosed with bone metastasis.

The abundance of HV CTC, PV CTCs, and PoV CTCs in patientswith tumor size >5 cm were significantly greater than those inpatients with tumor size�5 cm (P ¼ 0.013 for HV, P ¼ 0.025 forPV, P¼ 0.020 for PoV; Table 1).Occurrence of satellite lesionswassignificantly correlatedwithCTCs identified in PA (P¼ 0.004). PVCTC was significantly correlated with increased serum alpha-fetoprotein (AFP) level (P ¼ 0.020). CTCs in PV and PA werepositively correlated with microvascular invasion (P ¼ 0.044 forPV and P ¼ 0.031 for PA). Heightened CTC abundance in PV(P < 0.001) or PA (P < 0.001) was indicative of increased risk ofIHR (Fig. 4A), whereas patients with lung metastasis exhibitedgreater numbers of CTC in HV (P < 0.001) or IHIVC(P¼ 0.001; Fig. 4B). Furthermore, IHR was observed in 48% and63.33% of patients with CTCs identified in PV and PA, respec-tively, while only 17.39% and 17.50% of patients absent of CTCsin PV and PA relapsed. CTCs were detected in HV in all 8 patientswho developed lung metastasis.






Figure 3.

IHC of epithelial–mesenchymal transition (EMT) features in CTCs identified in tumor efferent and afferent microvessels and their correlation with activationof EMT in primary tumor. A, Dual color IHC of E (E-cad and CK) and M (vit) markers in CTCs from the microscopic hepatic veins (mHV), microscopichepatic artery (mHA), and microscopic portal vein (mPoV). CD45 were counterstained to exclude white blood cell (WBC). Cells that stained positive for Emarkers, negatively or dimly stained forMmarker were defined as the epithelial (E >M); equal intensity for E andMmarkerswere defined as the intermediate (E¼M);positive for M marker, negative or dimly stained for E markers were defined as the mesenchymal (E < M). Scale bar: original magnification, 250 mm; inserts, 25 mm.B, Box plots showing the comparison of the EMT-related phenotype proportions among CTCs from three microvasculatures (� , P < 0.05; �� , P < 0.01, n.s. ¼ notsignificant). C, Dual color IHC analysis of EMT features in primary hepatocellular carcinoma (HCC) tissues. CD45 were counterstained to exclude tumor-infiltrating lymphocytes. Top, HCC cells with the epithelial phenotype (E > M); middle, HCC cells with the intermediate phenotype (E ¼ M); bottom, HCC cellswith the mesenchymal feature (E < M). Scale bar: 100 mm. D, The correlation between mesenchymal HCC cells and total CTC counts in HVs was assessed bylinear regression (P ¼ 0.002). E, Comparison of mesenchymal HCC cell proportions between patients with no lung metastasis (met) and those that developedpostoperative lung met (P < 0.001, n.s. ¼ not significant).

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CTC and CTM counts at gross vascular sites were correlatedwith prognosis

The optimal cut-off value of CTCs in each vascular compart-ment for evaluating prognostic significance was explored by

receiver operating characteristic curve (ROC) analysis (Supple-mentary Fig. S7). In univariate analysis, significantly shorter TTRfor IHR and higher IHR rates were observed in patients with CTCcounts�2 inPVor�1 in PA comparedwithpatientswith<2CTCs

Figure 4.

Prognostic significance of CTCs and CTM at five gross vascular sites. A, Comparison of CTC burden at gross vascular sites in patients without intrahepaticrecurrence (IHR) and patients diagnosed with IHR. (� , P < 0.05; �� , P < 0.01, n.s. ¼ not significant, Mann–Whitney U test). B, Comparison of CTC burden atgross vascular sites in patientswithout lungmetastasis and patients diagnosedwith postoperative lungmetastasis. (��, P <0.01, n.s.¼ not significant, Mann–WhitneyU test). C, Kaplan–Meier analysis of PV CTC counts (left) and peripheral artery (PA) CTC counts (right) for predicting early IHR (P < 0.001 for PV, P ¼ 0.014 for PA,log-rank test). D, Kaplan–Meier analysis of HVs CTC counts (left) and IHIVC CTC counts (right) for predicting postoperative lung metastasis (P < 0.001 for HV,P ¼ 0.004 for IHIVC, log-rank test). E, Kaplan–Meier analysis of PV CTCs with the presence of CTM (left) and HV CTC with the presence of CTM (right) forpredicting early IHR and postoperative lung metastasis, respectively (P < 0.001 for PV and HV, log rank test). F, Schematic of spatial dynamics of circulatingtumor cells (CTC) during their hematogeneous metastasis.






in PV or <1 CTC in PA (PV, P < 0.001; PA, P < 0.001; Fig. 4C). CTCcounts�18 in HV or�3 in IHIVC were associated with decreasedTTR for lungmetastasis andhigher lungmetastasis rates comparedwith patients with <18 CTCs in HV or <3 CTC in IHIVC (HV, P <0.001; IHIVC, P ¼ 0.004, Fig. 4D). Considering CTCs and CTMtogether, patients with �2 CTCs and CTM detected in PV(Group 3) showed significantly shorter TTR for IHR and higherIHR rates compared with those with �2 CTCs and no CTMdetected in PV (Group 2, P ¼ 0.004, Fig. 4E). Patients with�18 CTCs and CTM detected in HV (Group 3) showed signifi-cantly shorter TTR for lung metastasis and higher lung metastasisrates compared with those with �18 CTCs and no CTM detectedin HV (Group 2, P ¼ 0.004, Fig. 4E).

The clinical factors significant for IHR in univariate analysiswere AFP level, vascular invasion, PV CTC, PA CTC, and PV CTCwith the presence CTM. Inmultivariate analysis, PVCTCswith thepresenceCTMwas the only independent prognostic factor for IHR[HR, 3.48; 95% confidence interval (CI), 1.40–8.61; P ¼0.007, Table 2]. For lungmetastasis, the significant clinical factors

in univariate analysis were HV CTCs, IHIVC CTCs, and HV CTCswith the presence of CTM. Multivariate analysis showed thatonly HV CTCs with the presence of CTM was the onlyindependent prognostic factor lung metastasis (HR, 42.20;95% CI, 3.73–477.80; P ¼ 0.003; Table 2).

DiscussionRecently, CTCs have garnered significant interest as the poten-

tial "seeds" that initiate cancer metastasis (2, 3, 30). Prior to thecurrent study, the spatial heterogeneity of CTCswas only assumedon the basis of animal models. To our knowledge, this is the firstcomprehensive study that have mapped the CTC spreading routeand characterized CTCs in patients with localized tumors. CTCswere remarkably heterogeneous in number, size, and clusteringstatus along thedissemination pathway.We further demonstratedthat activation of the EMT program in CTCs occurred primarilyduringmigration rather than prior to bloodstream entry (Fig. 4F).The current results likewise suggested that the spatial distribution

Table 1. Associations of clinical characteristics with CTCs detected in different anatomic vascular compartments of HCC patients

Systemic circulation Hepatic circulationNo. of CTCs No. of CTCs

PV PA HV IHIVC PoV

CharacteristicsNo. of patients(n ¼ 73)

Median(range) P

Median(range) P

Median(range) P

Median(range) P

Median(range) P

Age 0.015 0.159 0.579 0.949 0.391�50 57 2 (0–26) 0 (0–7) 6 (0–31) 0 (0–5) 0 (0–6)>50 16 2 (0–5) 0.5 (0–11) 6 (0–30) 0 (0–6) 1 (0–8)

Gender 0.600 0.130 0.172 0.123 0.466Male 29 1 (0–14) 0 (0–11) 8 (0–31) 0 (0–5) 1 (0–8)Female 44 3 (0–26) 0 (0–3) 5 (0–21) 0 (0–6) 1 (0–4)

HBsAg 0.780 0.683 0.689 0.311 0.211Negative 17 3 (0–11) 0 (0–5) 6 (0–31) 1 (0–6) 2 (0–8)Positive 56 1.5 (0–26) 0 (0–11) 6 (0–30) 0 (0–6) 1 (0–7)

Liver cirrhosis 0.820 0.298 0.416 0.945 0.839No 31 3 (0–13) 0 (0–5) 6 (0–31) 0 (0–5) 1 (0–8)Yes 42 1.5 (0–26) 0.5 (0–11) 7.5 (0–30) 0 (0–6) 1 (0–7)

AFP 0.020 0.127 0.573 0.546 0.748�20 30 1 (0–11) 0 (0–6) 6.5 (0–31) 0 (0–6) 1 (0–7)>20 43 3 (0–26) 1 (0–11) 6 (0–30) 0 (0–6) 1 (0–8)

Tumor number 0.228 0.595 0.188 1.000 0.932Single 58 1.5 (0–26) 0 (0–11) 5.5 (0–31) 0 (0–6) 1 (0–8)Multiple 15 3 (0–14) 1 (0–7) 9 (0–24) 0 (0–5) 1 (0–6)

Tumor size, cm 0.025 0.064 0.013 0.141 0.020�5 20 0 (0–7) 0 (0–5) 4.5 (0–26) 0 (0–6) 0 (0–3)>5 53 3 (0–26) 1 (0–11) 8 (0–31) 0 (0–6) 1 (0–8)

Satellite lesion 0.063 0.004 0.864 0.451 0.839No 52 1 (0–26) 0 (0–7) 6 (0–31) 0 (0–5) 1 (0–8)Yes 21 3 (0–10) 2 (0–11) 6 (0–26) 0 (0–6) 1 (0–5)

Microvascular invasion 0.044 0.031 0.672 0.950 0.051No 33 1 (0–10) 0 (0–5) 6 (0–31) 0 (0–6) 1 (0–7)Yes 40 3 (0–26) 1 (0–11) 6 (0–30) 0 (0–6) 1.5 (0–8)

Edmondson stage 0.496 0.372 0.598 0.255 0.087I–II 37 1 (0–11) 0 (0–6) 6 (0–31) 0 (0–6) 0 (0–8)III–IV 36 3 (0–26) 1 (0–11) 6 (0–30) 0.5 (0–6) 1.5 (0–6)

BCLC stage 0.942 0306 0.670 0.367 0.1550-A 56 2 (0–26) 0 (0–7) 6.5 (0–31) 0 (0–6) 1 (0–7)B-C 17 2 (0–14) 1 (0–11) 6 (0–24) 0 (0–6) 1 (0–8)

Intrahepatic recurrence <0.001 <0.001 0.066 0.187 0.113No 45 1 (0–10) 0 (0–6) 6 (0–31) 0 (0–6) 1 (0–8)Yes 28 4 (0–26) 2.5 (0–11) 8 (0–30) 0.5 (0–6) 1.5 (0–6)

Lung metastasis 0.256 0.985 <0.001 0.001 0.439No 65 2 (0–26) 0 (0–11) 6 (0–31) 0 (0–6) 1 (0–8)Yes 8 3.5 (0–13) 0 (0–5) 22.5 (18–30) 3.5 (0–6) 2 (0–5)

NOTE: The bold text is indicative of a statistical significance (P value < 0.05).Abbreviation: HBsAg, hepatitis B surface antigen.

Sun et al.





patterns of CTCs and CTM had unique prognostic relevance forpostoperative IHR or lung metastasis. The results established thatCTCs exhibited dramatic phenotypic plasticity during hematoge-neous trafficking, and that their spatial phenotypic disparities aswell as anatomic distribution patterns determined the preferentialsite ofmetastasis. Consequently, thesefindings offer a newavenuefor understanding human tumormetastasis by interrogatingCTCsfrom multiple vascular sites.

Recent studies compared CTC counts among multiple vas-cular compartments in breast cancer and colorectal cancer, butthe clinical relevance of CTC anatomic distribution patterns inHCC still remains unclear (21, 31). In this study, we prospec-tively measured CTCs at five key vascular sites in patients withlocalized HCC. The results revealed that HV CTC numbers weresignificantly higher than IHIVC and PoV, which indicated HVwas the chief outlet for the entry of primary tumor cells intocirculation. The number and positive rate of CTC and CTMdropped dramatically after pulmonary circulation. Larger CTCstended to be lodged in lung capillary bed. Smaller CTCs mightpass through lung circulation and circulate in PA, PV, and PoV,explaining the size similarity observed among those threecompartments. Furthermore, patients who had both �18 CTCsand CTM detected in HV exhibited the highest risks of post-operative lung metastasis. The data indicated that an abun-dance of large CTCs and CTM released by primary HCC wereretained in pulmonary capillaries, which supported the clinicalfinding that lung metastasis accounted for nearly half the totalEHM in HCC (Fig. 4F; ref. 18). Thus, implanting a cell filterwithin HV might be an option for blocking the disseminationpathway of CTCs that are released due to surgical manipulationduring liver resection, which could lower the risk of postoper-ative lung metastasis in HCC patients. Furthermore, patientswith CTC counts �2 and CTM in PV suffered significantlyearlier IHR, which might explain the propensity of CTCs to

home to their original organ and reseed, causing satellite orrecurrent lesions (Fig. 4F; refs. 6, 32).

The ability of CTCs to survive the anoikis and shear forces in thebloodstream is critical for successful metastasis (33, 34). Previousstudies have shown that collective migration endows CTCs withan additional survival advantage aswell as increasedpropensity togenerate metastases (19, 20, 35, 36). However, the mechanismdriving CTM formation in the human bloodstream remainsunclear. CTM were detected in tumor efferent vessels in approx-imately half of the patients, which was consistent with resultsfrom a previous mouse study that indicated CTM arose whenmulticellular aggregates broke off from the primary tumor mass(36). The absence of CTM in PA implied that most CTM wereeither arrested in pulmonary capillaries or torn apart by shearforces in the arterial system. Interestingly, CTM reemerged in PV inone third of patients, including those without CTM in HV, whichsuggested that singular CTCs might be able to reaggregate inbloodstream (Fig. 4F). The clinical data did not support the"grouped migration" approach proposed in mouse models inwhich CTC clusters maintained cohesive status throughout dis-semination (36). Instead, singular CTCs might spontaneouslyaggregate to attenuate the unfavorable cellular fate induced bythe bloodstreammicroenvironment. Thus, the findings indicatedthat CTC clustering might represent a dynamic rather than sto-chastic process.

The initial step in the metastatic cascade is local tumor cellinvasion and intravasation into the bloodstream (37). EMTprogram is recognized as the driving force for the initialmetastaticstep, giving rise to the dissemination of single carcinoma cells (22,26, 38). The traditional EMT model suggested that most CTCsintravasate into circulation with mesenchymal traits, and main-tained the phenotype until arrival to secondary sites (19, 39).Nevertheless, evidence from this study indicated that in CTCs, theEMT program might be manipulated in a different fashion. CTCs

Table 2. Univariate and multivariate Cox proportional regression analysis of factors associated with intrahepatic recurrence and lung metastasis

Intrahepatic recurrence Lung metastasisUnivariate analysis Multivariate analysis Univariate analysis Multivariate analysis

Variables HR (95% CI) P HR (95% CI) P HR (95% CI) P HR (95% CI) P

Age (>50 y vs. �50 y) 2.17 (0.92–5.12) 0.077 N.A. N.A. 1.04 (0.25–4.36) 0.954 N.A. N.A.Gender (male vs. female) 0.63 (0.24–1.68) 0.362 N.A. N.A. 0.51 (0.06–4.17) 0.532 N.A. N.A.HBsAg (Positive vs. Negative) 0.63 (0.41–2.51) 0.937 N.A. N.A. 0.91 (0.18–4.49) 0.906 N.A. N.A.Liver cirrhosis (Yes vs. No) 1.26 (0.58–2.74) 0.560 N.A. N.A. 2.23 (0.45–11.05) 0.326 N.A. N.A.AFP (>20 ng/mL vs. �20 ng/mL) 3.25 (1.36–7.77) 0.008 2.01 (0.78–5.19) 0.150 2.17 (0.43–10.73) 0.344 N.A. N.A.Tumor number (multiple vs. single) 1.08 (0.46–2.65) 0.873 N.A. N.A. 0.56 (0.07–4.55) 0.587 N.A. N.A.Tumor size (>5 cm vs. �5 cm) 1.44 (0.61–3.40) 0.410 N.A. N.A. 2.78 (0.34–22.61) 0.339 N.A. N.A.Satellite lesion (yes vs. no) 1.39 (0.64–3.02) 0.401 N.A. N.A. 0.79 (0.16–3.91) 0.772 N.A. N.A.Vascular invasion (yes vs. no) 2.29 (1.02–5.11) 0.044 0.73 (0.28–1.92) 0.533 1.40 (0.34–5.87) 0.644 N.A. N.A.Edmondson stage (III–IV vs. I–II) 1.21 (0.57–2.56) 0.627 N.A. N.A. 3.25 (0.66–16.11) 0.149 N.A. N.A.BCLC stage (BþC vs. 0þA) 0.53 (1.81–1.53) 0.240 N.A. N.A. 0.45 (0.06–3.62) 0.449 N.A. N.A.PV CTC (�2 vs. <2) 7.87 (2.87–21.59) <0.001 0.77 (0.14–5.19) 0.765 N.A. N.A. N.A. N.A.PA CTC (�1 vs. <1) 5.55 (2.34–13.19) <0.001 2.54 (0.87–7.42) 0.089 N.A. N.A. N.A. N.A.HV CTC (�18 vs. <18) N.A. N.A. N.A. N.A. 54.99 (6.71–450.63) <0.001 0.59 (0.04–9.54) 0.712IHIVC CTC (�18 vs. <18) N.A. N.A. N.A. N.A. 16.47 (3.31–81.92) 0.001 0.67 (0.10–4.40) 0.680PV CTC with the presence of CTM

1: CTC<2 without CTM2: CTC�2 without CTM3: CTC�2 with CTM 4.33 (2.54–7.38) <0.001 3.48 (1.40–8.61) 0.007 N.A. N.A. N.A. N.A.

HV CTC with the presence of CTM1: CTC<18 without CTM2: CTC�18 without CTM3: CTC�18 with CTM N.A. N.A. N.A. N.A. 28.76 (4.54–182.38) <0.001 42.20 (3.73–477.80) 0.003

NOTE: Clinicopathologic variables were adopted for their prognostic significance by univariate analyses.Abbreviations: HBsAg, hepatitis B surface antigen; N.A., not applicable.






in gross HV and mHV were predominantly epithelial, whichsuggested that CTCs retained epithelial traits following initialrelease. Thedynamic changes in theEMT status ofCTCsduringHVto PV migration implied that the acquisition of mesenchymalcharacteristics withinCTCs took place in the bloodstream and notin the primary tumor. Finally, although the primary tumor EMTstatus positively correlated with total CTC burden in HV, it failedto correlate with any CTC subtypes. One explanation is that theengagement of the EMT in primary tumors might influencethe spread but not the type of tumor cells. A prior in vivo studyalso confirmed that the epithelial tumor cell population was ableto escape primary sites following the breakdown of the extracel-lular matrix by stromal and mesenchymal-like tumor cells (40).Previous experimental data (40), in conjunction with currentresults, supported the novel EMT program paradigm that CTCsentered circulation with epithelial identity, but dynamicallyswitched cellular phenotype to mesenchymal during circulation(Fig. 4F). Interruption of CTC EMT activation in peripheralcirculation might inhibit their metastatic potential, which in turnimprove patient's outcome.

The limitations of this study are a small cohort size, shortfollow-up time, and data from a single study center. A prospec-tive, multicenter, and randomized clinical trial should bedesigned to further validate the prognostic significance of CTCsat different vascular compartments. Despite our preliminarydata revealed a spatial heterogeneity of CTCs during theirhematogeneous spreading, the molecular mechanism underly-ing this phenomenon is still unclear. However, with the aid ofCTC single-cell sequencing, we may be able to determine theunderlying mechanisms, which is an ongoing study subject inour laboratory.

Collectively, the current data suggested that a profound spatialheterogeneity in cellular distribution and biological featuresexisted among CTCs during hematogeneous transportation. Enu-meration of CTCs at different vascular sites could be of highclinical relevance for selectively predicting postoperative relapseormetastasis pattern inHCC,which deserves validation in a largerindependent cohort of patients. Furthermore, the study proposeda multidimensional analysis of CTCs, which may offer deeperinsight into the mechanisms of cancer metastasis, and facilitatethe design of novel therapeutics for suppressing the blood-bornespread of cancer.

Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.

Authors' ContributionsConception and design: Y. Sun, W. Guo, Y. Xu, Y. Ji, Y. Cao, J. Zhou,X.-R. Yang, J. FanDevelopment of methodology: Y. Sun, W. Guo, Y. JiAcquisition of data (provided animals, acquired and managed patients,provided facilities, etc.): Y. Sun, Y.-H. Shi, Z. Gong, Y. Ji, M. Du, A. Huang,G.G. Chen, P.B.S. Lai, S.-J. QiuAnalysis and interpretation of data (e.g., statistical analysis, biostatistics,computational analysis): Y. Sun, Z. Gong, B. Hu, G.G. Chen, X.-R. YangWriting, review, and/or revision of the manuscript: Y. Sun, W. Guo,G.G. Chen, X.-R. YangAdministrative, technical, or material support (i.e., reporting or organizingdata, constructing databases): X. Zhang, J. Zhou, X.-R. Yang, J. FanStudy supervision: Y. Xu, P.B.S. Lai, Y. Cao, J. Zhou, J. FanOther (proofreading the manuscript): Y. Cao

AcknowledgmentsThe authors are grateful to the patients and their families. The authors also

thankDr. Guo-Dong Sui andDr. Lu-Lu Zheng for establishment ofmicrofluidicsystem.

Y.F. Sunwas supported by theNationalNatural Science Foundation of China(81602543) and the Sailing Program from the Shanghai Science and Technol-ogy Commission (16YF1401400). Y. Xuwas supported by the National NaturalScience Foundation of China (81372317). J. Zhou was supported by theNational Natural Science Foundation of China (81572823, 81772578). X.R.Yang was supported by the National Natural Science Foundation of China(81672839, 81472676), National Key Research and Development Program(2016YFF0101405), the Projects from the Shanghai Science and TechnologyCommission (14DZ1940302, 14411970200, 14140902301), and The StrategicPriority ResearchProgramof theChineseAcademyof Sciences (XDA12020103).J. Fan was supported by the National High Technology Research and Devel-opment Program (863 Program) of China (2015AA020401), the State KeyProgram of National Natural Science of China (81530077), SpecializedResearch Fund for the Doctoral Program of Higher Education and ResearchGrants Council Earmarked Research Grants Joint Research Scheme(20130071140008), the Projects from the Shanghai Science and TechnologyCommission (14DZ1940300, 14411970200), and The Strategic PriorityResearch Program of the Chinese Academy of Sciences (XDA12020105).

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received April 12, 2017; revised August 9, 2017; accepted October 18, 2017;published OnlineFirst October 25, 2017.

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2018;24:547-559. Published OnlineFirst October 25, 2017.Clin Cancer Res Yun-Fan Sun, Wei Guo, Yang Xu, et al. and Distinct Clinical Significance in Hepatocellular CarcinomaSpatial Heterogeneity in Epithelial and Mesenchymal Composition Circulating Tumor Cells from Different Vascular Sites Exhibit

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circulating tumor cells from different vascular sites ...hep3b were purchased from the shanghai cell...

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