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Year : 2021  |  Volume : 17  |  Issue : 4  |  Page : 1047-1051

Analysis of intrapatient heterogeneity of circulating tumor cells at the single-cell level in the cerebrospinal fluid of a patient with metastatic gastric cancer

1 Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul; Department of Internal Medicine, Division of Hemato-Oncology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Incheon, Korea
2 Department of Medicine, Division of Hematology-Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea

Date of Submission12-Feb-2019
Date of Decision23-Aug-2019
Date of Acceptance14-Oct-2019
Date of Web Publication10-Jun-2020

Correspondence Address:
Seung Tae Kim
Department of Medicine, Division of Hematology-Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro, Gangnam-Gu, Seoul 135-710
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jcrt.JCRT_108_19

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 > Abstract 

Background: The aims of this study were to detect circulating tumor cells (CTCs) at the single-cell level in cerebrospinal fluid (CSF) and to identify intrapatient heterogeneity of CTCs in a patient with gastric cancer (GC) with leptomeningeal metastasis (LM) using Di-Electro-Phoretic Array technology.
Materials and Methods: The CSF samples were drawn from a patient who was diagnosed with GC with LM. The CSF samples were centrifuged and stained with antibody cocktail to recognize 4',6-diamidino-2-phenylindole, cytokeratin, and epithelial cell adhesion molecule (EpCAM). Gene sequencing was also conducted to evaluate the status of the gene alteration profile of CSFCTCs as compared with those of the CSF non-CTCs and the primary tumor tissue.
Results: Among total 38 cells from the samples, 25 cells represented CK+ (EpCAM+), which boiled down to 0.53 CTCs in 1 mL of CSF. Each CTC was heterogeneous in terms of morphology and degree of marker expression. Some CTCs have a spindle-like shape, whereas others have a round shape. Based on molecular profiling between the 25 CK+ (EpCAM+) CTCs and 13 CK−/EpCAM− cells (i.e., the non-CTCs), CSFCTCs harbored mutations such as MDM2, TP53, KRAS, STK11, and ALK, whereas mutation of these genes was not observed in the CSF non-CTCs. Four genes of nine mutational genes totally observed in the CSFCTCs were also noted in the primary tumor tissue.
Conclusions: We enriched CTCs through a single-cell sorting process in CSF samples of a GC patient with LM. We also demonstrated the intrapatient heterogeneity of the CTCs at the single-cell level.

Keywords: Cerebrospinal fluid, circulating tumor cells, gastric cancer, leptomeningeal metastasis

How to cite this article:
Cho JH, Sim MH, Kim SY, Kim K, Lee T, Lee J, Kang WK, Kim ST. Analysis of intrapatient heterogeneity of circulating tumor cells at the single-cell level in the cerebrospinal fluid of a patient with metastatic gastric cancer. J Can Res Ther 2021;17:1047-51

How to cite this URL:
Cho JH, Sim MH, Kim SY, Kim K, Lee T, Lee J, Kang WK, Kim ST. Analysis of intrapatient heterogeneity of circulating tumor cells at the single-cell level in the cerebrospinal fluid of a patient with metastatic gastric cancer. J Can Res Ther [serial online] 2021 [cited 2022 Dec 4];17:1047-51. Available from: https://www.cancerjournal.net/text.asp?2021/17/4/1047/286447

 > Introduction Top

Circulating tumor cells (CTCs) are defined as tumor- or metastasis-derived cells in the bloodstream. CTCs have been detected in blood from patients with gastric cancer (GC).[1],[2],[3] Detection of CTCs can identify patients who are at risk of developing metastasis. Previous studies have reported the use of various CTC detection methods, such as reverse transcriptase-polymerase chain reaction (RT-PCR) analysis, in patients with GC.[4] In the present study, we used the Di-Electro-Phoretic Array (DEPArray) technology to identify CTCs directly in cerebrospinal fluid (CSF) samples obtained from a patient with leptomeningeal metastasis (LM) of GC. DEPArray is a dielectrophoresis-based method that is used in the isolation and molecular characterization of single-tumor cells, including CTCs.[5],[6],[7],[8] This device analyzes and sorts single and rare cells using cell entrapment inside dielectrophoretic cages and image-based selection processes. Each selected cell can be moved by software-controlled electrical fields and eventually isolated downstream for molecular analysis.[5]

LM is a rare metastatic form of GC that occurs in <5% of patients with adenocarcinoma of the upper gastrointestinal tract.[9],[10] Despite its infrequent presentation, however, LM causes poor prognosis. Notably, it is hard to diagnose the condition at an earlier stage and thus apply effective treatment. LM can be diagnosed by CSF cytologic analysis or magnetic resonance imaging (MRI) according to the National Comprehensive Cancer Network guidelines.[11] Although CSF cytology analysis provides LM confirmation and has high specificity, low diagnostic sensitivity (about 50% at the first lumbar puncture)[12],[13] is still a problem. It is sometimes required that repeated lumbar punctures should be completed to diagnose LM.[14],[15],[16] Brain MRI, another LM diagnostic method, also showed low sensitivity (53%) in a previous large study.[17] Therefore, the sensitive and specific diagnosis of LM remains difficult.[18],[19],[20] Because the early diagnosis of LM and extensive treatment can improve neurological symptoms and gain survival benefit, diagnostic methods that can detect LM earlier are desperately needed.[21],[22],[23]

Herein, we intended to identify CTCs and demonstrate intrapatient heterogeneity of CTCs through a single-cell sorting process with DEPArray technology from CSF samples in a GC patient with LM.

 > Materials and Methods Top

Patients and ethical statement

This investigation was conducted in accordance with the ethical standards of the Declaration of Helsinki and national and international guidelines and was approved by the Institutional Review Board at Samsung Medical Center in Seoul, Korea.

Collection of cerebrospinal fluid samples

CSF samples were collected from a patient diagnosed in GC with LM. These serial CSF samplings were conducted to help avoid increased intracranial pressure. CSF sampling was conducted through the Ommaya. After cytological confirmation by a pathologist, the samples were centrifuged for 5 min at 400×g at room temperature and then were analyzed for CTC detection using the DEPArray technology (Silicon Biosystems, Bologna, Italy).

Circulating tumor cell detection in cerebrospinal fluid samples using the DEPArray technology

We obtained single-cell pellets from 47 mL of CSF from a patient for DEPArray technology loading. A schematic showing the workflow for isolating CTCs from the CSF is shown in [Supplementary Figure 1]. The sample was washed with running buffer (Miltenyi Biotec, Germany) and added to Inside Perm solution (Miltenyi Biotec). After 10 min, the cells were stained with cytokeratin (PE-conjugated pan cytokeratin antibody [C-11]; Abcam) and epithelial cell adhesion molecule (EpCAM) (APC-conjugated CD326 EpCAM human antibody; Miltenyi Biotec) and labeled with Alexa Fluor 488 dye (Invitrogen).

Cell sorting experiments were performed using the DEPArray technology, as described in the manufacturer's instructions. In short, DEPArray cartridges (A300K) were manually loaded with 14 μl of cells and 830 μl of Sodium Borate (SB) buffer. After loading the cartridge into the DEPArray system, the sample was injected into a microchamber, where the cells were exposed to an electric field consisting of 16,000 electrical cages in which the individual cells could be trapped. The chip was scanned, and image frames for each of the four fluorescent filters (i.e., FITC, PE, APC, and DAPI) and bright-field images were captured. Cell detection was based on a DAPI fluorescence threshold, and a unique identification number was assigned for each cell. Captured images were processed and presented by the CellBrowser software that enabled the selection of cells of interest by the operator. Nucleated CK/EpCAM-stained cells were chosen independently based on single- or double-positive expression and were moved to a parking area in the cartridge. Individual cells were then moved to a recovery area, where a final visual confirmation of cell presence was performed. Pools of CTCs (CK+/EpCAM+ or CK−/EpCAM− cells) were recovered into the 200 μL of PCR tubes.

Whole genome amplification

The Ampli1™ whole genome amplification (WGA) procedure (Silicon Biosystems) is a highly concentrated DNA library based on ligation-mediated PCR that provides site-specific DNA degradation and which can be used for target gene analysis. The DNA from the isolated CSFCTCs and negative cells was amplified using the Ampli1™ WGA kit according to the manufacturer's instructions. Briefly, the isolated CTCs were thawed on ice and transferred to 1 μL of phosphate-buffered saline. All tubes were reacted according to the procedure of the source, such as cell lysis, DNA degradation, ligation, and primary PCR. A final volume of 50 μL of WGA product was achieved. Genome integrity was evaluated using the Ampli1™ -QC kit, as previously described.[21]

Targeted gene sequencing

Next-generation sequencing (NGS) of amplified genomic DNA from the CSFCTCs was performed using the Archer® VariantPlex® Comprehensive Thyroid and Lung (CTL) assay kit, which is a targeted NGS assay for the detection of single-nucleotide variants, indels, and copy number variants (CNVs) across 33 genes implicated in thyroid and lung cancers. As part of this, 200 ng of DNA was used as input for library generation using the Molecular Barcode Adapters for Illumina® instruments and the VariantPlex® CTL Panel gene-specific primer (GSP) according to the manufacturer's instructions. The MiniSeq™ system (Illumina, USA) was used for sequencing with open-ended amplification of genomic DNA fragments from Anchored Multiplex PCR (AMP™). The mutation analysis of the primary tumor sample was also carried out using a commercially available NGS cancer panel (Macrogen, Seoul, Korea).

Data processing and statistical analysis

Somatic variants were identified and annotated using the Archer Analysis 5.0.6 software (ArcherDX, Boulder, CO, USA) for point mutations, indels, and CNVs, respectively. To ensure reliable and robust mutation calling, we performed a visual inspection of reads and “somatic variant” filtered the (1) Alternate allele observation count (AO) ≥5; (2) allele fraction ≥ 0.05; (3) consequences such as “coding_sequence_variant,” “feature_elongation,” “feature_truncation,” “frameshift_variant,” “incomplete_terminal_codon_variant,” “inframe_deletion,” “inframe_insertion,” “missense_variant,” “protein_altering_variant,” “splice_acceptor_variant,” “splice_donor_variant,” “splice_region_variant,” “start_lost,” “stop_gained,” and “stop_lost;” and (4) variant call was not “.NO CALL” and “homozygous reference.” In addition, “somatic CNV” filtered was (1) amplification threshold ≥2.5; (2) deletion threshold ≤0.3333; and (3) P < 0.01.

 > Results Top

The patient was a 59-year-old male and his performance status was 1. The patient was diagnosed with metastatic GC with peritoneal seeding and lung metastasis in September 2016. Endoscopic biopsy was done on primary GC. The pathology result was tubular adenocarcinoma, poorly differentiated. The standard combination chemotherapy regimen of capecitabine plus oxaliplatin was tried. After two cycles of chemotherapy, however, the disease had progressed. In November 2016, he reported suffering from headache and was diagnosed with LM after considering a brain MRI scan [Figure 1] and CSF tapping cytology findings. The patient received an Ommaya reservoir for diagnosis and treatment. CSF samplings were conducted through the Ommaya reservoir. Because he was treated with intrathecal methotrexate, we were able to obtain CSF samples just before methotrexate injection.
Figure 1: Magnetic resonance imaging scans of a patient diagnosed with advanced gastric cancer with leptomeningeal metastasis. These images were obtained in November 2016. Axial contrast-enhanced fluid-attenuated inversion recovery magnetic resonance imaging scan shows intense sulcal enhancement (a) and internal auditory canal enhancement (b) in the bilateral hemisphere

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We obtained CK+ and EpCAM+ CTCs through the DEPArray technology, as described in the Materials and Methods section. Among a total of 38 cells obtained from the samples, 25 cells represented CK+ (EpCAM+), which was essentially 0.53 CTCs in 1 mL of CSF [Figure 2]a. The morphological phenotypes of CTCs and the CTC clusters were highly heterogeneous with CK+ staining variations in shape, size, and degree of expression. Representative images from the samples are illustrated in [Figure 2]b.
Figure 2: (a and b) Detection of cerebrospinal fluid circulating tumor cells in a patient with leptomeningeal metastasis of gastric cancer

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Twenty-five CK+ (EpCAM+) CTCs and 13 CK−/EpCAM− cells (non-CTCs) were evaluated using the Ampli1™ WGA kit, and genome integrity was confirmed by PCR with the DNA fragments [Supplementary Figure 2]. We conducted targeted sequencing with amplified genomic DNA through the method described in the Materials and Methods section. Based on molecular profiling between 25 CK+ (EpCAM+) CTCs and 13 CK−/EpCAM− cells (non-CTCs), the CSFCTCs harbored mutations such as MDM2, TP53, KRAS, STK11, and ALK, whereas mutations of these genes were not observed in the CSF non-CTCs [Table 1] and [Figure 3]. Gene alterations such as TP53, STK11, ALK, IDH1, and CDKN2A mutations were furthermore detected in the patient tumor tissue [Supplementary Table 1]. Interestingly, four genes (TP53, AKT1, STK11, and ALK) of nine mutational genes observed in the CSFCTCs were also noted in the primary tumor tissue [Figure 3].

Table 1: Molecular profile of isolated cerebrospinal fluid circulating tumor cells

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Figure 3: Molecular profile of isolated cerebrospinal fluid circulating tumor cells

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 > Discussion Top

We successfully isolated CTCs from the CSF of a GC patient with LM using the DEPArray technology and found that the shapes and marker expressions of each CTC were heterogeneous. Notably, some CTCs have a spindle-like shape and others have a round shape. These findings suggested the intrapatient heterogeneity of the CTCs. We also conducted molecular profiling of isolated CTCs in the CSF using targeted gene sequencing. Interestingly, there were different molecular profiles between the CSFCTCs and the CSF non-CTCs.

The features of CTCs were heterogeneous in terms of shape, size, and expression of markers. Intratumor heterogeneity was caused by differences among cell surface markers, (epi) genetic abnormality, growth rates, and apoptosis among tumor cells.[24] In this study, we found that some CTCs had a spindle cell shape. This morphological change to the spindle shape might be caused by the effects of chemotherapy and/or the evolution of the tumor cell itself. In a cancer stem cell perspective, chemotherapy acts as a selection mechanism that promotes tumor evolution.[24] As cancer stem cells are thought to be inherently refractory to chemotherapy, this population can be selected during therapy, changing the intratumor heterogeneity in manner such as that consistent with morphological changes.[25] In another perspective, the process of epithelial-to-mesenchymal transition (EMT) produces phenotypical and structural changes that lead to increased motility and invasiveness.[26],[27],[28],[29]

The majority of the current studies use single CTC sampling at one time point. However, this strategy does not reflect changes in terms of the phenotypic and molecular characteristics of CTCs that occur according to tumor progression. Thus, research using serial single CTC sampling is needed for evaluating the characteristics of tumor cells resistant to previous treatment. The investigation of CTC heterogeneity can also inform the preclinical design of rational drug combinations. Our findings are limited here because our results were based on a single patient case and do not give the temporal sequence of change in CTCs. Moreover, we did not confirm the correlation of the heterogeneity between CSFCTC and tumor tissues due to the availability of tumor tissue. Therefore, a large study is necessary for the purpose of strengthening our results. Moreover, other novel markers other than CK and EpCAM are needed for more accurate analysis. It is also necessary to analyze EMT markers, which can reflect the effect of chemotherapy and the progression of cancer.

The detection of CSFCTCs by the DEPArray technology may be a novel option for detecting single CTCs and evaluating the heterogeneity of tumor cells. The detection of CSFCTCs may increase the understanding of LM not only in GC but also in the case of other solid tumors. This will contribute to more accurate diagnosis and effective treatment. Collectively, we verified the relevant workflow using an image-based approach to isolate CSFCTCs using the DEPArray platform and further molecular profiling analysis.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

 > References Top

Kubisch I, de Albuquerque A, Schuppan D, Kaul S, Schaich M, Stölzel U. Prognostic role of a multimarker analysis of circulating tumor cells in advanced gastric and gastroesophageal adenocarcinomas. Oncology 2015;89:294-303.  Back to cited text no. 1
Uenosono Y, Arigami T, Kozono T, Yanagita S, Hagihara T, Haraguchi N, et al. Clinical significance of circulating tumor cells in peripheral blood from patients with gastric cancer. Cancer 2013;119:3984-91.  Back to cited text no. 2
Yeh KH, Chen YC, Yeh SH, Chen CP, Lin JT, Cheng AL. Detection of circulating cancer cells by nested reverse transcription-polymerase chain reaction of cytokeratin-19 (K19) – Possible clinical significance in advanced gastric cancer. Anticancer Res 1998;18:1283-6.  Back to cited text no. 3
Bertazza L, Mocellin S, Marchet A, Pilati P, Gabrieli J, Scalerta R, et al. Survivin gene levels in the peripheral blood of patients with gastric cancer independently predict survival. J Transl Med 2009;7:111.  Back to cited text no. 4
Fabbri F, Carloni S, Zoli W, Ulivi P, Gallerani G, Fici P, et al. Detection and recovery of circulating colon cancer cells using a dielectrophoresis-based device: KRAS mutation status in pure CTCs. Cancer Lett 2013;335:225-31.  Back to cited text no. 5
Gupta V, Jafferji I, Garza M, Melnikova VO, Hasegawa DK, Pethig R, et al. ApoStream(), a new dielectrophoretic device for antibody independent isolation and recovery of viable cancer cells from blood. Biomicrofluidics 2012;6:24133.  Back to cited text no. 6
Peeters DJ, De Laere B, Van den Eynden GG, Van Laere SJ, Rothé F, Ignatiadis M, et al. Semiautomated isolation and molecular characterisation of single or highly purified tumour cells from cellSearch enriched blood samples using dielectrophoretic cell sorting. Br J Cancer 2013;108:1358-67.  Back to cited text no. 7
Shim S, Stemke-Hale K, Tsimberidou AM, Noshari J, Anderson TE, Gascoyne PR. Antibody-independent isolation of circulating tumor cells by continuous-flow dielectrophoresis. Biomicrofluidics 2013;7:11807.  Back to cited text no. 8
Blay C, Chiforeanu DC, Boucher E, Cabillic F, Desgrippes R, Leconte B, et al. Incidence of brain metastases in HER2+gastric or gastroesophageal junction adenocarcinoma. Acta Oncol 2015;54:1833-5.  Back to cited text no. 9
Wadhwa R, Taketa T, Correa AM, Sudo K, Campagna MC, Blum MA, et al. Incidence of brain metastases after trimodality therapy in patients with esophageal or gastroesophageal cancer: Implications for screening and surveillance. Oncology 2013;85:204-7.  Back to cited text no. 10
Brem SS, Bierman PJ, Brem H, Butowski N, Chamberlain MC, Chiocca EA, et al. Central nervous system cancers. J Natl Compr Canc Netw 2011;9:352-400.  Back to cited text no. 11
Chamberlain MC, Glantz M, Groves MD, Wilson WH. Diagnostic tools for neoplastic meningitis: Detecting disease, identifying patient risk, and determining benefit of treatment. Semin Oncol 2009;36:S35-45.  Back to cited text no. 12
Chamberlain MC. Leptomeningeal metastasis. Curr Opin Neurol 2009;22:665-74.  Back to cited text no. 13
Glass JP, Melamed M, Chernik NL, Posner JB. Malignant cells in cerebrospinal fluid (CSF): The meaning of a positive CSF cytology. Neurology 1979;29:1369-75.  Back to cited text no. 14
Gleissner B, Chamberlain MC. Neoplastic meningitis. Lancet Neurol 2006;5:443-52.  Back to cited text no. 15
Le Rhun E, Taillibert S, Chamberlain MC. Carcinomatous meningitis: Leptomeningeal metastases in solid tumors. Surg Neurol Int 2013;4:S265-88.  Back to cited text no. 16
Chamberlain MC. Leptomeningeal metastases in the MRI era. Neurology 2011;76:200.  Back to cited text no. 17
Chamberlain MC. Neoplastic meningitis: A guide to diagnosis and treatment. Curr Opin Neurol 2000;13:641-8.  Back to cited text no. 18
Hyun JW, Jeong IH, Joung A, Cho HJ, Kim SH, Kim HJ. Leptomeningeal metastasis: Clinical experience of 519 cases. Eur J Cancer 2016;56:107-14.  Back to cited text no. 19
Palma JA, Fernandez-Torron R, Esteve-Belloch P, Fontes-Villalba A, Hernandez A, Fernandez-Hidalgo O, et al. Leptomeningeal carcinomatosis: Prognostic value of clinical, cerebrospinal fluid, and neuroimaging features. Clin Neurol Neurosurg 2013;115:19-25.  Back to cited text no. 20
Oechsle K, Lange-Brock V, Kruell A, Bokemeyer C, de Wit M. Prognostic factors and treatment options in patients with leptomeningeal metastases of different primary tumors: A retrospective analysis. J Cancer Res Clin Oncol 2010;136:1729-35.  Back to cited text no. 21
Riess JW, Nagpal S, Iv M, Zeineh M, Gubens MA, Ramchandran K, et al. Prolonged survival of patients with non-small-cell lung cancer with leptomeningeal carcinomatosis in the modern treatment era. Clin Lung Cancer 2014;15:202-6.  Back to cited text no. 22
Wasserstrom WR, Glass JP, Posner JB. Diagnosis and treatment of leptomeningeal metastases from solid tumors: Experience with 90 patients. Cancer 1982;49:759-72.  Back to cited text no. 23
Prasetyanti PR, Medema JP. Intra-tumor heterogeneity from a cancer stem cell perspective. Mol Cancer 2017;16:41.  Back to cited text no. 24
Colak S, Medema JP. Cancer stem cells – Important players in tumor therapy resistance. FEBS J 2014;281:4779-91.  Back to cited text no. 25
Krawczyk N, Meier-Stiegen F, Banys M, Neubauer H, Ruckhaeberle E, Fehm T. Expression of stem cell and epithelial-mesenchymal transition markers in circulating tumor cells of breast cancer patients. Biomed Res Int 2014;2014:415721.  Back to cited text no. 26
Lamouille S, Xu J, Derynck R. Molecular mechanisms of epithelial-mesenchymal transition. Nat Rev Mol Cell Biol 2014;15:178-96.  Back to cited text no. 27
Forte VA, Barrak DK, Elhodaky M, Tung L, Snow A, Lang JE. The potential for liquid biopsies in the precision medical treatment of breast cancer. Cancer Biol Med 2016;13:19-40.  Back to cited text no. 28
Zhang C, Guan Y, Sun Y, Ai D, Guo Q. Tumor heterogeneity and circulating tumor cells. Cancer Lett 2016;374:216-23.  Back to cited text no. 29


  [Figure 1], [Figure 2], [Figure 3]

  [Table 1]

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