Detection of Circulating Tumor Cells Using Microfluidics - ACS

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Detection of circulating tumor cells using microfluidics Tiberiu Alecu Burinaru, Marioara Avram, Andrei Avram, C#t#lin M#rculescu, Bianca #încu, Vasilica #ucureanu, Alina Matei, and Manuella Militaru ACS Comb. Sci., Just Accepted Manuscript • DOI: 10.1021/acscombsci.7b00146 • Publication Date (Web): 24 Jan 2018 Downloaded from http://pubs.acs.org on January 25, 2018

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ACS Combinatorial Science

Detection of circulating tumor cells using microfluidics Tiberiu A. Burinaru*, Marioara Avram, Andrei Avram, Cătălin Mărculescu, Bianca Țîncu, Vasilica Țucureanu, Alina Matei, Manuella Militaru Abstract Metastasis is the main cause of death in cancer patients world-wide. During metastasis cancer cells detach from the primary tumor and invade distant tissue. The cells that undergo this process are called circulating tumor cells (CTCs). Studies show that the number of CTCs in the peripheral blood can predict progression-free survival and overall survival, and can be informative concerning the efficacy of treatment. Research is now concentrated on developing devices that can detect CTCs in the blood of cancer patients with improved sensitivity and specificity that can lead to improved clinical evaluation. This review focuses on devices that detect and capture CTCs using different cell properties (surface markers, size, deformability, electrical properties, etc.). We also discuss the process of tumor cell dissemination, the biology of CTCs, epithelial-mesenchymal transition (EMT) and several challenges and clinical applications of CTC detection. Keywords: Circulating tumor cells, microfluidics, lab-on-a-chip, metastasis, epithelialmesenchymal transition. Abbreviations: ALDH1 – aldehyde dehydrogenase 1 family; CD – cluster of differentiation; CEA – carcinoembryonic antigen; CK19 – cytokeratin 19; CRC – metastatic colorectal cancer; CRPC – castration-resistant prostate cancer; CTCs – circulating tumor cells; DAPI – 4’,6-diamidino-2-phenylindole; DEP – dielectrophoresis; DEP-FFF – dielectrophoresis field-flow fractionation; DFS – disease-free survival; EGFR – epidermal growth factor receptor; EMT – epithelial-mesenchymal transition; EpCAM – epithelial cell adhesion molecule; GCC – guanylyl cyclase; MAP – magnetophoresis; MET – mesenchymal-epithelial transition; MUC-1 – mucin-1; NSCLC – non-small-cell lung cancer; ODEP – optically induced dielectrophoresis; OS – overall survival; PANC – pancreatic cancer; PBS – phosphate-buffered saline;

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PCR – polymerase chain reaction PDMS – polydimethylsiloxane; PFS – progression free survival; PIPAAm – polymer brushes of poly (N-isopropylacrylamide); PLS3 – plastin-3; PMMA – poly(methyl methacrylate); PMPs – paramagnetic particles; SiNWS – silicon nanowire substrate; Introduction Metastasis is the primary cause of death for cancer patients world-wide, being estimated to rise to more than 20 million deaths per year by 2030, according to the World Health Organization.1 Metastasis is a multi-step process in which cancer cells from the primary tumor, detach and invade distant tissues by using the bloodstream as a transport system. First cancer cells infiltrate the adjacent tissue, then the tumor cells migrate into the bloodstream (intravasation), they escape the immune-system attack, they exit the bloodstream (extravasation) and then they proliferate and develop a newly formed tumor.2 The cells that detach themselves from the primary tumor and travel through the bloodstream are called circulating tumor cells (CTCs). CTCs are believed to play the main role in the metastatic disease. Understanding their part in this disease may contribute to better therapeutic management. Recent research suggests that CTCs can be discovered in the bloodstream in early stages of tumor growth.3,4 Husemann et al. states that CTCs can be detected before the primary tumor mass is detected by using conventional diagnostic methods.5 CTCs were first reported 150 years ago, in 1869 by Ashworth Thomas Ramsden, at that time resident physician at the Melbourne Hospital. He observed for the first time the presence of cells in blood that had the same size, shape and appearance as those in the tumors of his patient.6 Major leaps in detection and characterization of CTCs have been made in the last two decades, with new methods and devices appearing for CTCs analysis.7,8,9 CTC detection Modern detection methods rely on the expression of unique antigens on the CTC surface, or on physical properties such as size,10 density,11 or electrical properties.12 Circulating tumor cells of epithelial origin have been discovered in peripheral blood of cancer patients and they represent the source of the metastatic disease.13,14,15,16 CTCs detection and characterization may be a new method that can enhance or even replace invasive biopsies of non-hematologic cancers.17,18,19,20 CTCs where discovered in different types of cancer such as breast, lung, pancreatic, prostate, liver, and colon.20 The detection and analysis of CTCs can be used for early diagnosis of cancer,21 the management of cancer therapy,22 personalized treatment 23 and the research of metastasis mechanisms 24 which is not yet fully understood.25 The number of CTCs in the bloodstream can vary greatly, with a concentration of ~1100 cells/ml in whole blood.26 The concentration of CTCs has direct implications in the clinical diagnostic and prognostic.27,28,29,30 The morphology of the CTCs is variable with respect to their size, density, deformability and cell surface composition.31 CTCs in carcinomas, tumors of epithelial origin, can be identified by their expression of epithelial


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markers like cytokeratins (CK19), EpCAM (epithelial cell adhesion molecule), CD45 (common leucocyte marker) negativity and based on tumor-specific antigens like MUC1(mucin-1), HER-2(human epidermal growth factor receptor 2), etc.32 CTCs can be differentiated and captured from the other blood cells by physical properties (e.g., density and size)10,11 electrical properties12 and biological properties (e.g., expression of epithelial proteins or mesenchymal proteins).13,33 Today there are many research groups that have designed devices that can capture CTCs. Most of them rely on epithelial markers, because these can differentiate CTCs of epithelial origin from leukocytes. By culturing different types, populations or subpopulations of CTCs we can further asses and study them. Yu et al. demonstrated that CTCs can be cultured and analyzed. He obtained from six metastatic luminal breast cancer patients a set of oligoclonal CTC cultures that can be used for drug sensitivity testing. Three of these five CTC lines were tumorigenic in mice. They discovered pre-existing mutations in the PIK3CA gene and new mutations in the oestrogen receptor gene (ESR1), PIK3CA gene and in the fibroblast growth factor receptor gene (FGFR2).34 MicroRNAs (miRNAs) are non-coding RNAs that regulate the expression of target mRNAs.35 MicroRNAs controls biological processes, such as cellular development, differentiation, proliferation, apoptosis and metabolism.36,37,38 Overexpressed or under expressed miRNAs may function as oncogenes or tumor suppressor genes in cancer.39 Zhou et al. used real time reverse transcription-polymerase chain reaction in order to detect the levels of microRNA-106a (miR-106a) and microRNA-17 (miR-17), as a new molecular diagnostic method for detecting CTCs. They correlated the number of SGC-7901 cancer cells with levels of both miR-106a and miR-17. In pre- and post-operative patient with gastric cancer, miR-106a and miR-17 levels were higher than those in the control group. Their results indicated that the detection of miRNA in the peripheral blood may indicate the number of circulating tumor cells in patients with gastric cancer.40 Epithelial-to-mesenchymal transition The epithelial-mesenchymal transition (EMT) is a process of trans-differentiation of epithelial cells into motile mesenchymal cells. This is a physiological process in development, wound healing and stem cell behaviour. EMT is also a factor in pathological processes like fibrosis and cancer progression. EMT is mediated by transcription factors like SNAIL (a zinc finger protein), zinc-finger E-box-binding (ZEB) and basic helix-loop-helix transcription factors. Reprograming of gene expression during EMT is controlled by signaling pathways that respond to external stimuli.41 During embryonic development, epithelial and mesenchymal cells multiply and form the entire functioning body. The two phenotypes are not permanent and in the presence of transcription factors epithelial cells can convert into mesenchymal cells and vice versa. This process is called Epithelial-Mesenchymal Transition (EMT) and the revere process is called Mesenchymal-Epithelial transition (MET). This two processes are essential for body patterning and morphogenesis. The first step in metastatic dissemination is thought to be local invasion. Research showed that tumor cells undergo EMT process and acquire mesenchymal features in order to escape from the primary tumor. Thus EMT is hypothesized to help in tumor progression. There are similarities between developmental and oncogenic EMT and have common pathways which can be reactivated in breast cancer and could contribute to



tumor progression. The developmental EMT regulators Snail/Slug, Twist, Six1, and Cripto and the developmental signaling pathways TGF-β and Wnt/β-catenin, are miss expressed in breast cancer and correlate with poor clinical outcomes.42 During metastasis, cells undergo EMT and MET as part of their metastasis program. Armstrong et al. researched this process in CTCs from patients with progressive metastatic solid tumors, focusing on men with castration-resistant prostate cancer (CRPC) and women with metastatic breast cancer. They showed that 80% of the CTCs from metastatic CRPC patients co-express epithelial proteins like EpCAM, CK, E-cadherine and mesenchymal proteins like vimentin, N-cadherin, O-cadherin and the stem cell marker CD133. In metastatic breast cancer patients they found that more than 75% of CTCs co-express CK, vimentin and N-cadherin.43 Invading carcinoma cells can undergo EMT and gain stem cell markers and behaviour. It is uncertain if MET is essential in the metastatic process. Brabletz proposed two principal types of metastatic progression: phenotypic plasticity involving EMTMET processes and intrinsic genetic alterations keeping cells in an EMT and stemness state.44 One new marker that might overcome this problem is plastin-3, a protein that is not downregulated during EMT nor is it expressed in normal blood cells, thus the sensitivity of CTC assays may be improved.45 Ueo et al. examined the expression of plastin-3 (PLS3) in breast cancer cell lines and in CTCs from the peripheral blood of 594 cancer patients. They evaluated the clinical significance of PLS3. Hs578t, MCF-7, MDA-MB-468 and MDA-MB231 breast cancer cell lines and BC-M1 bone marrow derived cancer cell line, expressed PLS3. Also the CTCs of the breast cancer patients expressed PLS3. Poor overall and diseasefree survival was observed in PLS3-positive patients, compared with PLS3-negative patients.46 CTCs require more investigation to fully understand the mechanism behind tumor dissemination, survival in the bloodstream and their attachment and aggressive invasion of distant tissue. Studies show that animal models mimic the complex pathogenesis in human patients. Also the Mesenchymal – Epithelial Transition (MET) needs more research. Mesenchymal CTCs can revert back to their epithelial phenotype and express once again Ecadherin. By doing so, they invade distant sites and proliferate, forming a secondary tumor of epithelial origin.47 Preclinical studies show that the epithelial-mesenchymal transition (EMT) of adherent epithelial cells to a migratory mesenchymal state represents the starting point of metastasis. Yu et al. characterized EMT in CTCs in breast cancer patients. They discovered that rare primary tumor cells expressed simultaneously mesenchymal and epithelial markers, but CTCs express mainly mesenchymal markers. Eleven patients were monitored and the disease progression was correlated with mesenchymal CTCs. The captured CTCs expressed known EMT regulators like transforming growth factor (TGF)-β and FOXC1(Forkhead box C1) transcription factor.48 Besides EMT, the existence of cancer stem cell subpopulations is worth studying. It has been demonstrated that CD44 + /CD24 −/low breast cancer cell subpopulations can generate tumors much faster compared with other subpopulations.49 A pilot study found that in a group of 20 out of 30 breast cancer patients, 35.2% CTCs were CD44+/CD24-/low. In another group, breast cancer patients had 17.7% CTCs that expressed ALDH1+/CD24-/low.50 Clinical indications


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Cristofanilli et al. showed that the number of CTCs predicts treatment efficiency, progression-free survival (PFS) and overall survival (OS) in patients who were diagnosed with metastatic breast cancer and in patients that are starting therapy. In their study 177 patients with MBC diagnostic were enrolled. Eighty-tree of them were entering first-line treatment. CTCs were isolated and enumerated from 7.5 mL of whole blood, before the start of the treatment and every month thereafter for 6 months. Forty-three patients (52%) had ≥ 5 CTCs at baseline. The median OS was > 18 months and the median PFS was 7.2 months. Patients that had ≥ 5 CTCs at baseline and at the first follow-up, had a worse prognosis than patients with less than 5 CTCs. They concluded that the number of CTCs before and after treatment start is a strong and independent prognostic factor.51 Circulating tumor cells have also been found to predict drug targeted therapy response in lung cancer patients. Maheswaran et al. found that in 11 of 12 patients with metastatic nonsmall-cell lung cancer had mutated epidermal growth factor receptor gene, T790M mutation, which conferred drug resistance to tyrosine kinase inhibitors. When this mutation was detected in pretreatment tumor-biopsy specimens, its presence was correlated with reduced progression-free survival.52 The detection of CTCs could predict postoperative cancer recurrence and the efficiency of therapy strategies.40 It has been shown that in primary and metastatic colorectal cancer (CRC), tumor cells express specific markers like guanylyl cyclase (GCC), cytokeratins like CK19 and CK20 and carcinoembryonic antigen (CEA), thus these markers have been used for CTC detection in the peripheral blood of CRC patients.53,54,55 GCC is a member of the guanylyl cyclases family, specific for intestines 56,57,58,59 and it has been used as a marker for the detection of occult colorectal micro-metastasis in the peripheral blood.60,61 Also, in the primary colorectal cancer and its metastasis, tumor cells express CK20 which is a member of the cytokeratin family of proteins.62,63 The levels of GCC and CK20 mRNA (messenger RNA) in peripheral blood are CTC associated factors in colorectal cancer patients.64 Liu et al. studied the levels of GCC mRNA and CK20 mRNA in peripheral blood and the serum level of carcinoembryonic antigen in 92 colorectal cancer (CRC) patients, by quantitative RT-PCR and ELISA. They evaluated their association with overall survival (OS) and disease-free survival (DFS). They found that OS and DFS are associated with GCC and CK20 mRNA levels, but not with CEA levels. Lower OS was associated with higher levels of GCC and CK20 mRNA levels.65 Studies show that EGFR (epidermal growth factor receptor) is overexpressed in NSCLC (Non-small-cell lung cancer) patients in a later evolution stage66. Also studies show that 90% of PANC cells overexpress CEA (carcinoembryonic antigen)67. Studies show that tumor cells can undergo EMT transformation which downregulates epithelial markers and upregulates mesenchymal markers like vimentin.68,69,70,71,72 Satelli et al. reported the development of a monoclonal antibody that can be used as a universal marker for detecting CTCs with origin in sarcomas that develop in the soft tissue and bone. Sarcomas are cancers that occur in soft tissues like fat, nerves, blood vessels, muscles and in skin, and in the bone like osteosarcomas. There is also the Ewing sarcoma that manifest in bone and in the soft tissues as well. This antibody developed by the research team targets cell surface vimentin on the circulating tumos cells with 100% specificity during tests. They tested the antibody on samples with spiked LM7 osteosarcoma cells and on CTCs derived from mice and canine sarcoma models. They also tested the antibody on blood samples from healthy volunteers and from patients with osteosarcoma, Ewing sarcoma,



angiosarcoma, leiomyosarcoma, and undifferentiated pleomorphic sarcoma. They detected no CTCs in the samples from the healthy volunteers. They concluded that the number of CTCs from patients diagnosed with metastasis was grater in comparison to patients without diagnosed metastasis. Also the CTC count was lower for patients that underwent chemotherapy. They also characterized the captured CTCs from sarcoma patients. They characterized them by single cell mutation analysis or fluorescence in situ hybridization (FISH) by using specific markers. Circulating tumor cells that were captured from angiosarcoma patients were tested for mutations in FLT4 and TP53 genes that were detected in the primary tumors. They discovered that the circulating tumor cells possessed only the TP53 mutation. The researchers also analyzed the amplification of MDM-2 and KRAS genes in osteosarcoma patients using FISH. They concluded that these two genes were amplified in patients with diagnosed metastasis and that the amplification of these genes in CTCs can predict the onset of metastatic lesions.72

Detection challenges The major challenges in the detection of CTCs in the blood, are the cellular heterogeneity and low concentration of CTCs. Their number in blood can be 65%, for all the cell lines, even for the T-24 cell line, which had the lowest value of EpCAM antigen expression. After they optimized the device they tested it on blood samples from cancer patients. The device tested 116 whole blood samples from sixty-eight patients with carcinomas. They also tested blood samples from 20 healthy volunteers as controls. The device detected CTCs in 115 out of 116 samples from patients with metastatic lung, prostate, pancreatic, breast and colon cancer. The number of detected CTCs ranged from 5 to 1,281 cells/mL with a 50% purity. CTCs were also detected in 7/7 patients with early-stage prostate cancer. They also tested the change in the number of CTCs correlated with the treatment of a cohort of patients with metastatic cancer undergoing treatment. They found that the number of CTCs fluctuated with the clinical course of the disease.80 Zhao et al. describes a CTC counting method based on microfluidics and lineconfocal microscopy, named eDAR. The PDMS microfluidic channel was 200 µm wide, 50 µm tall and 3 cm long. To detect single CTC in a volume of nano-litres of blood in the microchannel, they developed a line confocal detection system. Their system consisted in two lasers, 488 and 633 nm, focused in a 20X objective. Blood samples were directly labelled with multiple antibodies each antibody conjugated with different fluorophores and pumped through a microfluidic channel, and interrogated by a line-confocal microscope. CTCs were counted on the basis of fluorescence signals and labelling schemes. The avalanche photodiodes (APDs) collected the fluorescence signal from the region. APD1 detected yellow fluorescence (560-590 nm) of the monoclonal anti-EpCAM labelled with phycoerythrin (PE). APD2 recorded the green wavelength range (negative control) of FITC-anti-CD45 (500-550 nm). ADP3 detected the red wavelength band of the anti-pancytokeratin antibodies labelled with Alexa 647 (640-690 nm). They analyzed 1 mL of blood in 30 seconds from 90 stage IV breast cancer patients. Using this method they detected 15 to 3375 CTCs in 7.5 mL of blood. They also demonstrated the ability to detect CTCs from breast cancer patients that were positive for Her2 and CD44+/CD24−.81 Lin et al. developed “NanoVelcro”, a nanostructured substrate, silicon nanowire, coated with anti-EpCAM antibodies (Fig. 1). They developed three generations of NanoVelcro CTC chips with different clinical utilities. The first generation of the device is composed of a nano-structured substrate with silicon nanowires (SiNS) with a PDMS overlaid chaotic mixer. The addition of the PDMS mixer was done in order to increase the chances of contact between CTCs and the anti-EpCAM antibodies that are linked to the nanowires. The chaotic mixer induces vertical flows in the blood sample, thus increasing the



contact of the circulating tumor cells and the antibody functionalized nano-structured substrate. The research team did validation studies using blood samples spiked with cancer cells. They achieved more than 85% cell capture efficiency. They also designed an immunocytochemistry protocol that stains and identifies circulating tumor cells. The protocol contains three different stains for parallel marking of 4’, 6-diamidino-2-phenylindole (DAPI), CD45 and citokeratin (CK). The expression of citokeratin (CK) and CD45 and the size of the captured cells can be used to differentiate non-specifically captured white blood cells (WBC) and other debris from circulating tumor cells.82 To test the first-gen NanoVelcro chip, the research team compared the efficiency of their device with CellSearch, the first and only FDA approved CTC detection system. They used blood samples from prostate cancer patients with different cancer progression stages. They tested 26 blood samples of only 1 ml. In seventeen out of twenty-six patients the first-gen chip had greater sensitivity than the CellSearch assay and with a superior dynamic range.83 They further configured their device and they obtained a smaller footprint of their chip which means that this device is a costefficient diagnostic method from which cancer patients can benefit. They tested the new device in a research done by Uro-Oncology teams from UCLA Hospital and Cedars-Sinai Medical Center. They tested forty prostate cancer patients, of which thirty-two had metastatic disease and eight had localized disease. The tests revealed the presence of circulating tumor cells in all forty patients. They performed follow-up CTC detection tests while patients were undergoing treatment. The tests revealed that the patients with a positive response to treatment had fewer CTCs detected in their blood, compared to the first tests.84 To further improve their device they replaced the anti-EpCAM antibodies with aptamers designed using the in vitro cell-SELEX (systematic evolution of ligands by exponential enrichment) selection method. The aptamers were designed to capture the A549 non-small-cell lung cancer cells. The device can not only capture circulating tumor cells but it can release them after a treatment with nuclease solutions. To test it, they spiked blood samples with A549 cells and achieved a recovery rate of >80%. After 15 min enzymatic treatment with benzonase nuclease, they achieved a >85% release efficiency.85 The second generation of the NanoVelcro device developed by Lin et al. allows single cell capture and molecular analysis, unlike the first generation device which was made for circulating tumor cells quantification.82 The second device uses laser microdissection (LMD) techniques and a transparent nano-substrate covered with PLGA (poly lactic-co-glycolic acid) nanofibers. By coupling this technologies they can detect and capture single cells, followed by multiple molecular analysis like RT-PCR (reverse transcription polymerase chain reaction), Sanger sequencing and Next-generation sequencing (NGS). The substrate of the PLGA NanoVelcro device was made by depositing electrospun PLGA nanofibers on a LMD slide. The device is composed of two functional components, an overlaid PDMS chaotic mixer and a PLGA nanofibers covered PN-nanovelcro substrate. They first attached streptavidin onto the PLGA nanofibers and then they attached the biotinylated antibodies.86,87 The device was first tested with melanoma cells. The melanoma cells were isolated in order to detect a signature oncogenic mutation, BRAFV600E. This mutation is present in 60% of melanomas and specific inhibitors like vemurafenib, are used to target these kind of cancers. In order to isolate the melanoma cells the anti-CD146 antibody has been used. The tests were performed on blood samples from two stage-IV melanoma patients, with melanomas that contained the BRAFV600E mutation. First in order to optimize and validate the performance of the device, they used suspensions with M299 human melanoma cell line. They also


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evaluated how different electrospinning times effected the capture efficiency. The optimal deposition time was of 3 hours that corresponded to a 3 µm thick PLGA nanofiber membrane. This led to achieving a capture rate of 87% when using 0.5 mL/h-1 flow rate. The isolated melanoma cells were analyzed by whole genome amplification (WGA) and PCR for the BRAF gene. To detect the BRAFV600E mutation in the melanoma CTCs Sanger sequencing was used.86 To improve the collection process, they replaced the LMD technology with laser capture microdissection (LCM)88. They coupled the NanoVelcro chip with ArcturusXT™ laser capture microdissection (LCM) technology. This allows for capture of CTCs from patients with prostate cancer (PC) that are suited for next generation sequencing (NGS). They validated the device by testing it with three different cell lines: PC3, C4-2 and LNCaP. The cells were spiked in PBS and in blood samples. They achieved a capture efficiency of 80.5% for PBS samples and 74.7% in blood samples. This device can help analyze and understand the heterogeneity and clonal evolution that occurs within a tumor. It can also evaluate tumor progression and response to specific treatments.82,87 The researchers tried to further improve the NanoVelcro device and developed the third generation of NanoVelcro device (Fig. 2). Because of the low percentage of recovered cells and poor cell viability after enzymatic treatment, the researchers came with the idea to link thermally responsive polymer brushes of poly (N-isopropylacrylamide) (PIPAAm) on the silicon nanowire substrate (SiNWS). They also functionalized the brushes with biotin groups. By using the biotin-streptavidin interaction they linked anti-EpCAM antibodies to efficiently capture CTCs. At 37oC the functionalized domain is present on the surface of the biotin –PIPAAm- SiNWS, thus CTCs that interact with the substrate will be captured. When the temperature drops at 4oC the PIPAAm substrate undergoes conformational changes, which leads to the internalization of the anti-EpCAM antibodies. Thus the captured CTCs will be released from the device. To test their device they used cell suspensions containing three cancer cell lines that are positive for EpCAM expression, MCF7 cells, LnCAP and PC, and two cancer cell lines negative for EpCAM expression, HeLa and Jurkat cell lines. They subjected 1000 MCF7 cancer cells to CTC capture. At 37oC 90% of them were captured and released at 4oC. After release, 90% of the cells were viable and could be subjected to further analyses.88 Zamay et al. used DNA aptamers as specific affinity probes for lung adenocarcinoma cells derived from postoperative tissues. Because there are no universal markers for detecting circulating tumor cells from different tumors, they used DNA to bind to CTC known and unknown markers. For the aptamer selection they used the cell-SELEX technique. This technique uses eleven rounds of selection. It starts by incubating DNA with healthy lung tissue, and extraction of the unbound DNA. Then they incubate the unbound DNA with blood cells from a healthy person. They again extract the unbound DNA and incubate it for positive selection with lung cancer tissue. After that they collect the bound DNA and then they amplify the DNA by using symmetric and asymmetric PCR and then they purify the PCR product. They tested and selected DNA aptamers for lung adenocarcinoma cells that were derived from the tissue removed after surgery. They chose an adeno-carcinoma because it is a highly heterogeneous tumor that contain non-invasive and invasive tumor cells and because they had no prior knowledge on protein markers on the surface of the CTCs. They used normal lung cells and lymphocytes as negative cells for the counter selection of the desired aptamers. They observed that the aptamers did not bind to normal lung cells and that they had low affinity to A549 lung adenocarcinoma culture. When they applied these aptamers to



clinical samples of peripheral blood of lung cancer and metastatic lung cancer patients, they identified aptamer associated protein biomarkers for lung cancer like vimentin, annexin A2, annexin A5, histone 2B, neutrophil defensin and clusterin. By producing tumor specific aptamers for individual patients, they can be synthesized as needed to monitor anticancer therapy and cancer evolution, making them an ideal tool for personalized diagnostic. They tested their method on one hundred and five patients, eighteen healthy individuals and eightyseven patients with primary and secondary lung cancer, other lung diseases, breast diseases and glioblastoma. They calculated a sensitivity of their device of 86% and a specificity of 76%.89 Maremanda et al. fabricated a PDMS microfluidic device for detection and capture of CTCs, functionalized with locked nucleic acid (LNA) modified aptamers that are targeting EpCAM and nucleolin. They used RNA aptamers to target the extracellular domain of the EpCAM marker and DNA aptamers to target nucleolin marker. They made the aptamers by using the SELEX method. They immobilized the aptamers on silylated glass slides by using the formation of a Schiff base between the aromatic amines and the aldehyde or carbonyl group that were present on the silylated glass. They tested the efficiency of this method by analyzing the surface roughness by using atomic force microscopy (AFM). After the immobilization of the aptamers they registered a two fold increase in the surface roughness, which meant that the immobilization method was working well. Their device had a capture sensitivity of 92% and a 100 % specificity, after using a blood samples spiked with human colorectal adenocarcinoma cells (Caco-2 cells) with a concentration of 10–100 cells/ml. They also tested their device on twenty-five head and neck cancer patients. They captured and average of 5 ± 3 CTCs/mL of blood in 22/25 samples (88%).90 Watanebe et al. reported that during carcinogenesis, intracellular nucleolin is translocated to the cell surface.91 Dickson et al. developed a microfluidic device called Cell Enrichment and ExtractionTM. It uses biotin-tagged antibodies that bind selectively to circulating tumor cells in the blood sample. The device allows freedom in the choice of antibodies, so that researchers can study any kind of heterogeneous tumor cell populations. After immobilization of the CTCs further investigations such as fluorescence in situ hybridization (FISH) can be performed. These biotin-tagged antibodies are introduced into the blood samples, thus CTCs will display biotin molecules. The samples will be further passed through a microfluidic channel that will contain 9000 streptavidin coated posts. CTCs are trapped to the posts by the biotin-streptavidin reaction. This technology needs a pre-enrichment step of the blood samples in order to remove red blood cells. This is done by using density centrifugation. The enriched fraction of interest is further incubated with biotin labelled anti-EpCAM antibodies. The microchannel is done in polydimethylsiloxane (PDMS) and bonded to a glass coverslip. The channel contains 9000 transverse posts, with random different sizes and positioning. The size of the posts vary from 75 to 150 µm in diameter. The posts occupy 25% of the volume of the microchannel. The entire channel has a volume of 15 µl. The height of the channel is equal to the height of the posts, 55 µm, thus the posts are spanning the entire height. The posts have a minimum distance between them of 70 µm to avoid clogging. After the circulating tumor cells are captured, they are fluorescently stained and counted. To test their device, they cultured SKOV3 (human ovarian cancer cells) and spiked the samples to a concentration of 150 cells/µL. By using fluorescence activated cell sorting (FACS) method, the EpCAM expression of the SKOV3 tumor cells has been determined to be 60,000 antigen molecules per cell. They achieved a capture efficiency of > 70% at flow rates of 18 µL/min


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when the density of the antibodies was above 30000, otherwise the capture efficiency drops with the decrease of the concentration of antibodies and lower flow rates.92 Weissenstein et al. used an already existing technology, but they modified it in order to increase its sensibility and specificity, and used a combination of anti-EpCAM and anticitokeratin covered magnetic beads. They spiked blood samples from healthy volunteers with HCC1937 breast cancer cell to test the accuracy and specificity of the method. They also tested the CTC levels of ten healthy volunteers and of fifty-nine patients with metastatic breast cancer (MBC) and correlated with overall survival (OS). The samples were prepared by combining the Carcinoma Cell Enrichment with the Carcinoma Cell Depletion Kit and supplemented with CD326 EpCAM MicroBeads. They incubated the enriched cells with anticitokeratin and anti-EpCAM microbeads. This method was used because the former experiments with testing kits based only on CK-microbeads, had a mean efficiency of 44% and thus a big number of CTCs missed the magnetic attachment. They achieved an average percentage of HCC1937 cell recovery of 84%. Out of the fifty-nine MBC patients, twenty patients had no CTCs, fifteen patients had 1-4 CTCs and twenty-four had ≥ 5 CTCs/7.5 ml blood.93 Lara et al. developed a CTC capture technology using only negative selection steps. The process that they presented consists of three separation stages. The first separation step consists of a density-gradient separation, or a lysis process to remove erythrocytes. The second stem consists of an immunomagnetic separation and removal of leukocytes. The third step consists of a filtration method to concentrate and evaluate the desired cell population. They tested their method on blood samples from healthy volunteers spiked with MCF-7 tumor cells. The density separation of erythrocytes was done by using Ficoll-Hypaque with a gradient density of 1.077 g/mL. They determined the cell density of the MCF-7 tumor cells to be 1.066 g/mL, by using a continuous Percoll gradient. This determination indicates that the cancer cells will sediment with the population of leucocytes at the interface between plasma and neutrophil cells. The erythrocyte lysis protocol consists in adding 40 mL of lysing buffer (154 mM NH4Cl, 10 mM KHCO3, 0.1 mM EDTA) to a blood sample of 2 mL spiked with a concentration of MCF-7 tumor cells of 1 MCF-7 cell/108 total cells. The immunomagnetic labelling of the leucocyte population was done by using a double step method. They used as primary antibody mouse anti-CD45-PE and as secondary antibody an anti-PE MACS microbeads were used. To detect and differentiate the cancer cells after the final filtration step, they used anti-human HEA-FITC. This negative depletion method produced an enrichment of CTCs of 5.17 log10 and a recovery rate of 46%.94 Adams et al. developed a microfluidic device that selectively and specifically isolates small numbers of CTCs from whole blood, named HTMSU, by functioning the microfluidic channels with EpCAM monoclonal antibodies. The device can process volumes of whole blood of ≥ 1 mL in a period of less than 37 minutes. Circulating tumor cells were concentrated in small volumes (190 nL) and their number was counted without any labelling agents, by using an integrated conductivity sensor. The microfluidic device is composed of 51 microchannels with 35 µm width and 150 µm depth. These microchannels were made in PMMA, poly(methyl methacrylate), using a metal mold. The microchannels were functionalized with anti-EpCAM antibodies for the capture of breast cancer tumor cells that are overexpressing epithelial cell adhesion molecule (EpCAM). After their capture, CTCs were released using trypsin and enumerated on-device using a label free solution conductivity route designed to detect single CTCs passing through the detection electrodes. The



assessment of the numbers of CTCs is done by using an integrated conductivity sensor that detects CTCs based of the specific electrical signature, without the use of any other cell staining or microscopic visualization. The conductivity sensors were made out of Pt wires with a diameter of ~75 µm, and placed into guide channels and positioned orthogonal to the output channel. They used the MCF-7 breast cancer tumor cells as a CTCs detection model. The cells have a mean diameter of 24 µm and EpCAM expression of 5.1 × 105 EpCAM molecules/cell. After optimizing the flow velocity, processing time, capture cell geometry and the design of the surface in order to minimize nonspecific adsorption, they achieved an efficient capture of >97% and a conductivity readout with ~100% detection efficiency and very good CTC specificity.95 Hwang et al. designed quantum dot-based aptamer beacons to detect extracellular antigens EpCAM and MUC-1. For this they created quantum dots functionalized with an EpCAM or MUC-1 binding sequence and a black hole quencher. Together they form a QDEpCAM/MUC-1 aptamer linker beacon (ALB). They were designed by using a singlestranded oligonucleotide with amine parts at the ends, linked afterwards with a beacon linker sequence. The EpCAM ALB contain 64 nucleotides and had the following structure: aminegggacacaatggacgtccgtagttctggctgactggttacccctctaacggccgacatgagag-BHQ2. The structure of the MUC-1 ALB is composed of 57 nucleotides: amine-aaccgcccaaatccctaagctttggataccctggcacagacacactacacacgcaca-BHQ. The bold nucleotide sequences indicate the binding regions for EpCAM or MUC-1 targeted molecules. The QD-EpCAM/MUC-1 ALB reacts only in the presence of the targeted molecules, otherwise the two fluorescence quenching molecules BHQ1 and BHQ2 prevents the activation of the aptamers. They tested the selectivity of their QD –EpCAM ALB by using breast adenocarcinoma cell line MDAMB-231 and gastric cancer cells Kato III. The both lines express EpCAM molecules on their surface. As negative control they used the human embrionic kidney cell line HEK-293T which does not express EpCAM antigens on their surface. By using the QD565-labeled ALB aptamer they obtained a positive signal of up to 98.8 % for the two cancer cell lines and a 0% positive signals for the HEK-293T normal cell line.96 Wang et al. presents a device for CTC capture and detection that integrates a microfluidic silicon nanowire (SiNW) array with multifunctional magnetic up-conversion nanoparticles (MUNPs). They conjugated the MUNPs with anti-EpCAM antibodies, so that they could recognize the CTCs in the blood samples and drag them down and isolate them under an external magnetic field. They achieved a 90% capture rate.97 Alix-Panabières designed the EPISPOT assay which detects CTCs by the proteins secreted, released or shed from single epithelial cancer cells. In this assay cells are cultured on a membrane coated with antibodies that capture proteins, which are then detected using secondary antibodies labelled with fluorochromes. By using this assay, the release of cytokeratin-19 (CK19) and mucin-1 (MUC-1) has been measured. Also it has been demonstrated that patients with localized tumors (stage M-0) present circulating tumor cells (CTCs). Patients with CTCs that release CK19 have unfavorable outcome. In M1 breast cancer patients, the presence of CTCs or CK-19 secreting cells in the peripheral blood, suggests a worse clinical outcome. The EPISPOT assay can be used to characterize viable CTCs in cancer patients, thus revealing their protein fingerprint.98 Yoon et al. used an anti-EpCAM antibody functionalized graphene oxide nanosheets on a patterned gold surface to selectively capture CTCs. They isolated CTCs from pancreatic,


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breast and lung cancer patients, with a high sensitivity of 73+32.4% at 3–5 cells per ml of blood.99 Stott et al. developed the HB-Chip, a microfluidic mixing device for CTC isolation. Their device generates microvortices in the sample flow in order to mix the blood and increase the interaction between CTCs and the antibodies linked on the surface of the chip. The device captured CTCs in fourteen out of fifteen patients (93%) with metastatic prostate cancer. By using transparent materials they viewed captured CTCs with the help of histopathological stains and immunofluorescence-conjugated antibodies. They achieved a 91.8% ± 5.2% capture efficiency for PC3 cells spiked in samples of whole blood with a purity of 14.0%±0.1%.100 Chang et al. developed a chip for isolation and detection of CTCs that uses immonomagnetics, microfluidics and size-based filtration. They use antibody functionalized magnetic beads to target CTCs. Against MCF-7 breast cancer cells they use anti-EpCAM antibodies, anti-EGFR antibodies for non-small cell lung cancer CTCs and anti-CEA antibodies for pancreatic CTCs. To tackle the EMT process anti-vimentin antibodies have also been used for the blood samples from NSCLC patients. The sample is mixed with the functionalized magnetic beads and run through a microfluidic chip while a magnetic field is generated underneath the chip, thus capturing CTCs. They had an 89% capture efficiency for MCF-7 breast cancer cells spiked samples. After that they tested the device on 50 blood samples obtained from non-small cell lung cancer (NSCLC) and pancreatic cancer patients (PANC). The device detected CTCs in forty-nine out of fifty patients. The device detected 2 to 122 CTCs per 8 mL of blood.33 In order to study subsets of cells from large heterogeneous populations one must first specifically isolate them. Some methods require transfer or wash steps that may result in loss of targeted cells. Casavant et al. proposes a device called VerIFAST, based on the simplified workflow of the Immiscible Filtration Assisted by Surface Tension (IFAST) and paramagnetic particles (PMPs) functionalized with biotinylated anti-EpCAM antibodies. This device also integrates methods for cell staining. By using this device, they achieved a capture rate of >80%, with a purity >70%. After isolation they perform complex multi-step washing procedures on-device, without transfer steps that can result in loss of CTCs. Also staining procedures can be performed on-device for EpCAM, intracellular pan-cytokeratins, and Ki67.101 Saucedo-Zeni et al. functionalized a structured medical Seldinger guidwire (FSMW) with anti-EpCAM antibodies, in order to capture CTCs directly in the bloodstream. The efficiency of the device was teste in twenty-four patients with breast cancer or non-small cell lung cancer (NSCLC) and in twenty-nine healthy individuals. The device is inserted for 30 minutes in the cubital veins. CTCs were identified in twenty-two au out of twenty-four patients, by staining with EpCAM or cytokeratin and DAPI. CTCs were detected in breast cancer patients with a median of 5.5 CTCs and in NSCLC with a median of 16 CTCs. Circulating tumor cells were detected in all tumor stages, as well as in early stage cancer with no distant metastases diagnosed. No CTCs were detected in any of the healthy volunteers.102 Kirby et al. developed a microfluidic device that uses geometrically enhanced differential immunocapture (GEDI) in order to detect CTCs. It also uses anti-prostate specific membrane antigen (PSMA) and a 3D geometry that captures CTCs and minimizes leukocytes adhesion. They detected a median of 54 CTCs/mL in castrate-resistant prostate cancer (CRPC) patients, compared to a median of 3 CTCs/mL in healthy patients.103



Most of the CTCs detection methods rely on epithelial markers or other specific surface markers. As discussed earlier, in the metastasis process CTCs undergo epithelial to mesenchymal transformation (EMT) and they can express mesenchymal markers.89 Also tumor cells from a subpopulation of cancer stem cells which express stem cell markers can become CTCs.104 Thus all these methods can be subjected to errors because the CTCs heterogeneity is high and the cellular phenotype can vary from patient to patient and can even vary in the same tumor.105 Hofman et al. compared the efficiency of CellSearch Assay (CS) and the ISET method in isolating CTCs in patients before radical surgery for NSCLC, using double immunolabelling with anti-citokeratin and anti-vimentin antibodies. They detected CTCs in one hundred and four out of two hundred and ten (50%) patients using the ISET method and in eighty-two out of two hundred and ten (39%) patients using CellSearch. They also detected vimentin-positive cells in twenty-three out of two hundred and ten (11%) patients by using ISET. The presence of CTCs detected by CS or ISET correlated with a worse disease-free survival (DFS). Thus the detection of CTCs in NSCLC patients, may be used as a prognostic biomarker and it may be used to improve therapeutic strategies.106 Hyun et al. developed a two stage microfluidic chip for the selective isolation of CTCs. The first stage consists of a microfluidic activated cell sorting chip (µ-MACS) that is meant to elute white blood cells. The second stage has a geometrically activated surface interaction (GASI) chip for the specific capture of CTCs. They achieved a 763-fold enrichment of cancer cells that were spiked into 5 mL of blood at a 400 µL/min flow rate. CTCs were separated with an efficiency ranging from 10.19% to 22.91%, based on the cells expression of EpCAM or HER2 surface proteins, at a 100 µL/min flow rate. Their device not only isolates CTCs, but also it can classify CTCs based on their heterogeneity, leading to a personalized cancer treatment and to CTC heterogeneity research.107

Table 1. Devices that use epithelial cell markers as antigen molecules to detect CTCs Name Recovery rate Specificity CellSearch©77 80-82% 100% ©78 MagSweeper 62% ± 7% 51% ± 18% Lab-on-a-Disc (eLoaD©)79 87% 100% CTC-chip©80 >65% 50% ©81 eDAR 94% NanoVelcro©82 >85% 89 Zamey et al. 86% 76% Maremanda et al.90 92% 100% Cell Enrichment and Extraction© 92 >70% 93 Weissenstein et al. 84% Lara et al.94 46% HTMSU©95 97% 100% Hwang et al.96 98.8% 100% Wang et al. 97 90% Yoon et al.99 73+32.4% ©100 HB-Chip 91.8% ± 5.2% 14.0%±0.1% Chang et al.33 89% ©101 VerIFAST >80% >70%


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GEDI©103 µ-MACS©107

>90% 90%

-

Devices that use physical properties of cancer cells in order to detect them Circulating tumor cells (CTCs), after cytological analyses, have a greater nucleus-tocytoplasm ratio, they are larger in size and their nuclear morphology is different than normal cells. The area of tumor cancer cell lines HepG2, Hep3B, MCF-7, HeLa, and LNCaP ranges from 396 µm2 (MCF-7) to 796 µm2 (Hep3B), and the mean tumor cell/leukocyte area ratio was 5.7 for Hep3B, 4.5 for HepG2 and HeLa, 4.1 for LNCaP, and 2.8 for MCF-7.108 Coumans et al. determined the size of 9 different cell lines and leukocytes. He used SKBR-3, MDA-231, MDA-468 and MCF-7 carcinoma breast cells, PC3-9 prostate carcinoma cell line, COLO-320 and SW-480 colorectal carcinoma and HL-60, K-562 hematopoietic cell lines. The mean size of leucocytes was 8.1 µm and the size of recaptured cells from the tumor cell lines ranged from 10.9 to 19 µm. The median size of EpCAM+CK+DNA+CD45- CTC captured by using the CellSearch system in metastatic breast, prostate and colorectal cancer is 13.1, 10.7 and 11 µm respectively, which are much smaller compared to the tumor cells from the tumor cell lines.109 Park et al. concluded that CTCs captured from the blood samples of sixteen prostate cancer patients, are much smaller than prostate cancer cell lines. The captured CTCs have 7.97±1.81 µm and cultured cancer cell lines have 13.38±2.54 µm. Also CTCs have more elongated shapes and greater nucleus/cytoplasm ratio that the cultured cell lines.110 Also CTCs have different deformability than normal blood cells.111 Cross et al. reported that, by using atomic force microscopy (AFM), metastatic cancer cells from patients with lung, breast and pancreas cancer, are 70% softer than benign cells from the body cavity.112 Chen et al. studied the mechanical properties of the immortalized BPH-1 prostate cells and prostate cancer cell lines LNCap-AD, LNCap-A1 and PC-3 and single isolated CTCs using AFM. Using the Young modulus they determined that the noncancerous BPH-1 were the least elastic, 3.7 kPa, while the highly metastatic PC-3 cells where nearly 30× more elastic, 0.13 kPa, that BPH-1 cells. Also the LNCap-AD cells were more elastic than LNCapA1, 0.88 kPa and 1.2 kPa respectively. The elasticity of the isolated CTCs was similar to that of PC-3 cells, but much higher than BPH-1 cells. The Young moduli for the isolated CTCs ranged from 0.23 kPa to 1.1 kPa.113 Michael Mak and David Erikson developed an automated micropipette system that can record the deformation and relaxation using the MDA-MB-231 metastatic breast cancer cell line. They matched the spatial, temporal and force scales with physiological and



biomechanical processes that normally occur during the metastasis process. Their device has parallel microchannels. Each of them has several micro-constrictions that will deform the cells multiple times. The maximum width of the microchannel is 15 µm (~ the size of the cells) and the smallest constriction region is 3.3 µm (size smaller than the cell nucleus). The constrictions have two different lengths that are meant to mimic short physiological barriers, 10 µm long (extracellular matrix pores) and long physiological barriers, 60 µm long (microvessels). Their study indicates that after the passage through the first constriction, tumor cells pass more quickly through the other constrictions. This results suggests that tumor cells that undergo deformation while infiltrating the extracellular matrix with subnucleus pore sizes, may further invade with much less effort.114

Figure 3: Exemplification of CTC detection and capture based on the size of the CTCs. An poly-dimethylsiloxane microfiltration membrane (PMM) integrated in a microfluidic device developed by Fan et al. (Reprinted from Biosensor and Bioelectronics, Vol. 71, Xiaoyun Fan, Chunping Jia, Jun Yang, Gang Li, Hongju Mao, Qinghui Jin, Jianlong Zhao, A microfluidic chip integrated with a high-density PDMS-based microfiltration membrane for rapid isolation and detection of circulating tumor cells, 380-386, 2015, with permission from Elsevier).115 Babahosseini et al. describes a microfluidic biosensor called iMECH (iterative mechanical characteristics) which differentiates between metastatic and non-metastatic cancer cell lines based on the biomechanical properties of cells. The iMECH simulates a dynamic microenvironment with channels with narrow deformations and wider relaxation regions which are meant to test the deformation of cells. They discovered that the cells from non-metastatic breast cell lines 184A1 and MCF10A become more resistant to deformation as they pass through cyclic deformations, their average velocity through the channels drops after each relaxation. Cells from MDA-MB-231 and MDA-MB-468, highly metastatic breast cancer cell lines after each relaxation loose resistance, they become more elastic and thus they pass faster through the channels.116 Park et al. developed a microfluidic device that separates CTCs based on their distinct deformability relative to all the other blood cells. They made tapered micrometer scale constrictions and combined them with an oscillatory flow in order to produce specific flow paths for each of the blood cell populations including CTCs. They demonstrated the capacity of their device to separate circulating tumor cells from whole blood based on their


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deformability and in a label free manner. They achieved a CTC recovery rate of a >90%, thus achieving a 104-fold enrichment of CTCs in regard to leukocytes.117 Fan et al. reported a polydimethylsiloxane (PDMS) membrane filter-based microdevice for CTC isolation from peripheral blood (Fig. 3). They integrated a PDMS microfilter into the microfiltration chip. They achieved a recovery rate of lung cancer cells from spiked blood samples of > 90%, with a processing throughput of 10 mL/h.115 Tan et al. used a label-free microdevice which isolates CTCs from whole blood by their different physical properties such as deformability and size. Their recovery rate was 80% for tests performed on breast and colon cancer cells. They use crescent-shaped isolation wells to capture CTCs, while more deformable leukocytes sieve through the isolation wells. The device has 900 isolation structures.118 Hosokawa et al. developed a microfluidic device for the detection of CTCs, equipped with a size-selective microcavity array. The microcavity array can specifically separate tumor cells from whole blood based on the size and deformability difference between CTCs and hematologic cells. Their device detected ~ 97% of lung carcinoma NCI-H358 cells in 1 mL whole blood spiked with 10-100 NCI-H358 cells.119 Zheng et al. reported a 3D microfilter device that can enrich circulating tumor cells from blood. This device is made out of two layers of parylene membrane with pores shifted between the top and bottom membrane. The role of the bottom membrane is to support the captured CTCs. They tested the device by spiking blood with MCF-7 breast cancer cells. They spiked 1 mL of blood with 342±58 MCF-7 cells. They achieved a capture efficiency of 86.5±5.3%. The blood sample is limited to 1 mL, larger volumes led to the clogging of the filtration membrane.120 Huang et al. developed a microfluidic chip which uses filtration microchannels in order to isolate CTCs from whole blood. They use the different size of the CTCs compared to the other blood cells. Their chip consists in more than 80 paired and parallel microchannels coupled to an array of filtrations microchannels at regular intervals. They used 3 lung cancer cell lines spiked in blood samples. At an optimal flow rate of 0.4 mL/h they recovered CTCs at an average rate of 96% for A549 cell line, 95% for SK-MES-1 and 92% for H446. They also validated the functionality of their device by isolating CTCs from fifty-nine lung cancer patients. The tests were positive in 96.7% of patients. Using the microfluidic chip they detected a mean number of 18.6 cells/mL.121 Lin et al. developed a portable microdevice based on a parylene filter membrane for size-based isolation of CTCs from human peripheral blood. The captured CTCs can be characterized directly on-chip. They fixed the filtering membrane between to slabs of PDMS and clamped between acrylic jigs, thus forming a fluidic chamber. The microdevice achieved a >90% recovery rate. Using this microdevice they detected CTCs in fifty-one out of fiftyseven patients, compared to only twenty-six patients using the CellSearch method. Their study demonstrated that CTCs can be detected at higher sensitivity bay using a size-based detection method, instead of relying on EpCAM cell expression.122 Harouaka et al. demonstrated that by using a size-based approach mesenchymal phenotype CTCs can also be detected, instead of only detecting CTCs that express EpCAM. They designed a flexible micro-spring array (FMSA) size-based device for CTCs detection. It has a 90% capture efficiency. The FMSA detected CTCs in 16 out of 21 clinical samples.123 Vona et al. developed a CTC detection device, ISET (isolation by size of epithelial tumor cells), which counts, immunomorphological and molecular characterizes CTCs from



carcinoma patients, by using blood samples of 1 mL. CTCs are larger in size compared to leukocytes. The difference in size allows the CTCs to be isolated by filtration. They used spiked peripheral blood with tumor cell lines like HepG2, Hep3B, MCF-7, HeLa, and LNCaP. According to the developers ISET can detect a single micro-pipetted CTC in 1 mL of blood. They also demonstrated that they can perform chromosomal analyses on captured CTCs by using fluorescence in situ hybridization (FISH) and polymerase chain reaction (PCR) genetic analyses. Vona et al. demonstrated the deletion of p53 gene in Hep3B cells after filtration and laser microdissection. They also tested the device on seven patients with hepatocellular carcinoma undergoing surgical liver resection. They used 9 mL of blood for RT-PCR CTC detection tests and 6 mL for the ISET assay. Between the two assays, ISET had more sensitivity and specificity.108 CTC isolation by physical properties still needs improvement, because of the CTC size heterogeneity and deformability. Some CTCs that went multiple deformations might have a reduced resistance and thus it may bypass filtration membranes or other capture microstructures. Hydrodynamic sorting of cells is a separation technique that enables a continuous and label-free sorting of particles without the application of external forces.124 Blood cells can be separated using shear-induced migration.125,126,127 Because the hydrodynamic separation process depends on the interaction between the targeted particle and the wall or the fluid in the microchannel, this process can be divided in interaction between the particle and the walls, and in interaction between the particle and the fluid. The particle and the wall interaction can be subdivided in regard to different types of wall into continuous wall, discrete wall and biomarker on wall. The discrete wall can further subdivided into posts and ridges. The particle and the fluid interactions can be further subdivided into laminar flow, inertial flow and biomimetic flow. Based on these particle flow interactions three basic mechanisms for particle separation arise: streamline following, inertial drifting and biometric interaction. In the streamline following mechanism, in a constant flow, the particles will follow the streamline. Depending on the size of the particles, the size of the channel and the size of the output channels, and according to the basic principle of size determined distribution in a laminar flow the particles can be separated in different outlets. Inertial drifting can be seen in a centrifuge used for separating different particles like cells or molecules. By making a microfluidic device with a spiral geometry or asymmetrical curved channels, one can make the suspended particles to migrate across streamlines and to focus in specific positions in the microchannel due to the inertial forces that arise in the microfluidic channel. In biomimetic flow, different properties (deformability, affinity for a certain environment, natural behaviour) of the cells are exploited in order to separate them from each other.128


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Figure 4: (a) Design of a hydrodynamic, microfluidic cell sorter and (b) and a picture of the actual cell sorter developed by Sun et al. (Reprinted from Sun, J.; Liu, C.; Li, M.; Wang, J.; Xianyu, Y.; Hu, G.; Jiang, X. Size-Based Hydrodynamic Rare Tumor Cell Separation in Curved Microfluidic Channels. Biomicrofluidics., published online January 7, 2013; DOI: 10.1063/1.4774311”, with the permission of AIP Publishing.).129 Kim et al. developed a sheath-less cascade spiral microfluidic device to continuously isolate CTCs. They successfully extracted CTCs from leukocytes with a recovery rate of 86.76% and 97.91% leukocyte depletion rate. The captured CTCs also sustained their viability.130 Moon et al. developed a multi-stage multi-orifice flow fractionation (MS-MOFF) device formed by combining three single-stage multi-orifice segments designed for CTCs capture from blood. They achieved a CTC recovery rate of 98.9%. This technique and set up has an increased operational flow rate, 100-300 µL/min, compared to other microfluidic separators.131 Sun et al. proposed a continuous and rapid CTC separation based on hydrodynamic effects. Cell separation is based on the competition between the inertial lift force and Dean drag-force inside a double spiral microchannel. With a high throughput of 2.5x108 cells/min, they achieved an efficient HeLa cell separation of 90%.129 Sollier et al. designed the Vortex© technology. They combined the use of micro-scale vortices and inertial focusing for the extraction of CTCs from blood. Their device extracted 25-51 CTCs/7.5 mL of blood, from breast cancer patients and 23-317 CTCs/7.5 mL of blood, from lung cancer patients. The device achieved a 36.8% recovery rate, with a 57–94% purity. This device offers a superior processing time of 20 min for 7.5mL of whole blood.132 Dhar et al. created the Vortex Cip. This device has the ability to enrich CTCs from large volumes of blood by selective capture in microvortices. The device has a narrow channel flowed by a series of reservoirs. They use the orbital trajectories and the channel cross sectional area in order to control the size of trapped particles. They also introduced a new lab-on-a-chip called Vortex HE Chip with a higher capture efficiency for cells in a smaller size (>12µm) range than the first Vortex Chip. It has a 69% recovery rate, with 66% purity.133 One problem that can arise from the hydrodynamic sorting of cells could be the formation of cell aggregates that will modify cell’s individual physical properties and thus the newly formed particle, with different physical properties, will act differently than the original cell, making the sorting method less efficient. Table 2. Devices that use physical properties of cancer cells in order to detect them



Name iMECH©116

Park et al.117 Fan et al.115 Tan et al.118 Hosokawa et al.119 Zheng et al.120 Huang et al.121 Lin et al.122 FMSA©123 ISET©108 Kim et al.130 MS-MOFF©131 Sun et al.129 Vortex©132 Vortex HE Chip©133

Recovery rate 95% identified as metastatic >90% >90% 80% 97% 86.5±5.3% >92% >90% 90% 100% 86.76% 98.9% 90% 36.8% 69%

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Specificity 95%

>80% 100% 95% 57–94% 66%

Devices that use electrical properties of CTCs or other methods in order to detect them Dielectrophoresis (DEP) is an electrokinetic process in which dielectric particles move in inhomogeneous electric field. The electric field can be DC or AC. This process was first used in 1971, by H.A. Pohl,134 who manipulated yeasts in a nonuniform electric field. This principle can be applied to microfluidics by placing metal electrodes at the walls of the channel, thus creating an inhomogeneous electric field in the microchannel. In this case the dielectric particles that are flown through the microchannel are represented by blood cells like erythrocytes and leukocytes, and especially circulating tumor cells. The suspended cells will be attracted towards the electrode in regard to their dielectric constant, thus altering their flow trajectory, and if DEP force is stronger than the viscous drag force the particles can even be trapped by the electrodes. By using this method different suspended populations of cells can be redirected and captured in different outlets. This method in which DEP forces are combined with the drag flow to separate different type of particles from the same sample, is called dielectrophoresis field-flow fractionation (DEP-FFF).


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Figure 5: The working principle of a DEP-FFF CTC cell isolation continuous-flow microfluidic device. (Reprinted from Shim, S.; Stemke-Hale, K.; Tsimberidou, A. M.; Noshari, J.; Anderson, T. E.; Gascoyne, P. R. C. Antibody-Independent Isolation of Circulating Tumor Cells by Continuous-Flow Dielectrophoresis. Biomicrofluidics, published online January 16, 2013, DOI: 10.1063/1.4774304, with the permission of AIP Publishing).135 The electrical properties of tumor cells like breast cancer cells and melanoma cells was investigated using impedance spectroscopy and electrorotation.12,136,137,138 Also Shim et al. studied the dielectric properties of the NCI-60 panel of cancer cell types, by using the above mentioned type of dielectrophoresis, called dielectrophoresis field-flow fractionation. They also studied and compared these dielectric properties with the dielectric properties of the normal blood cells. They showed that based on this properties, CTCs can be separated from the other blood cells. They also concluded that tumor cells that grew in adherent cultures, had very different dielectric properties than blood cells.139 Qiao et al., investigated the impedance of four breast cancer cell lines, MCF-10A, MCF-7, MDA-MB-231 and MDA-MB-435S. These cell lines are normal cells to late stage cancer cells respectively. They analyzed the cell suspensions using a chamber with four electrodes that were connected to an HP impedance analyzer. The electrical properties of single cells were extracted from the impedance of the cell suspensions and parameters such as whole cell conductivity, cytoplasm conductivity, relaxation frequency and membrane capacitance were extracted. They revealed that every cell line has its one electrical properties that offers them a specific signature which can be used for cell differentiation, as well as for the assessment of the stage of malignant cells. For example normal MCF-10A cells have a whole cell conductivity of 5.58 mS/cm and a membrane capacitance of 3.94 µF/cm2, while MDA-MB-435S late stage cancer cells have 3.97 mS/cm and 1.10 µF/cm2, respectively. 136



Han et al. developed a device that can capture a single cell and measure its impedance. He characterized MCF-10A, MCF-7, MDA-MB-231 and MDA-MB-435 cell lines. The membrane capacitance of these cell lines was 1.94 ± 0.14, 1.86 ± 0.11, 1.63 ± 0.17, and 1.57 ± 0.12 µF/cm2, respectively.138 Avram A. et al. presents the development of an interdigitated microelectrode array (IDMEA) biosensor which uses electrochemical impedance spectroscopy and cyclic voltammetry to study the B16 melanoma cell line. They obtained an impedance spectra for the B16 melanoma cells and they studied the adhesion and spreading of cells on IDMEA.137 Becker et al. investigated the electric properties of the MDA231 breast cancer cell line in contrast to erythrocytes and T lymphocytes, by using the ROT method. They concluded that the MDA231 cancer cell line had a membrane capacitance of 26 ± 4.2 µF/cm2, while T lymphocytes and erythrocytes have a membrane capacitance of 11 ± 1.1 and 9 ± 0.8 µF/cm2.12 Again we can see a specific signature of cell types that can be used for cell differentiation and characterization by applying this principle to dielectrophoresis. Avram M. et al. developed a label-free diagnostic method of melanoma cells based on the dielectric properties of the melanoma cells and on the properties of gold nanoparticles. They prepared the colloidal gold nanoparticles by the NaBH4 method. The gold nanoparticles had a mean diameter of 5.6 nm and a zeta potential of -50.93 mV. They inoculated C57BL/6 mice with mouse melanoma B16 cells (1×106) suspended in 0.1 mL of PBS. The mice were injected intravenously with 200 µL of 200 nM AuNP in phosphate buffer. During the histopathology examination of the tumor tissue the researchers observed that there is a big difference between the scattering spectra of the gold nanoparticles in the melanoma cells and the gold nanoparticles in the normal tissue. This difference is attributed to the localized surface plasmon resonance (LSPR) principle. The B16 melanoma cells with gold nanoparticles present in their cytoplasm had a unique blue colour in UV fluorescence. This method could be used as a label-free diagnostic method.140 Another type of dielectrophoresis is represented by optically induced dielectrophoresis (ODEP). This microparticle manipulation method consists in applying an AC produced uniform electric field between two indium-tin-oxide (ITO) glass substrates. The bottom ITO glass substrate is usually coated with a photoconductive layer like an amorphous silicon layer. The cells that are present in the electric field become electrically polarized. In this system a light image can be used as an electrode in order to induce dielectrophoretic forces. If the photoconductive layer is illuminated, the light excites its electron-hole pairs, thus decreasing the electrical impedance of that specific area. Thus the voltage that was applied will drop across the liquid layer to the illuminated zone. This event will induce a nonuniform distribution of the electric field between the two layers. By using this principle, cells can be manipulated by using optically induced electrodes that are illuminated on the photoconductive layer.141,142 Magnetophoresis (MAP) is the magnetic counterpart to dielectrophoresis (DEP). Instead of using the dielectric properties of cells, magnetophoresis uses the induced or permanent magnetic properties of particles. Thus particles that poses magnetic properties can be moved inside a microfluidic channel by applying an inhomogeneous magnetic field, just as in dielectrophoresis. In order to separate different cell populations from blood samples, cell populations which do not possess natural magnetic properties, you must first attach magnetic particles to the cell population you want to separate. Thus a sample preparation protocol is needed. This protocol enables you to specifically link magnetic particles to the cell


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population that you are interested in by using antibodies or other methods. By doing this you will achieve a specific control over the desired cell subpopulation. In the case of CTC separation process using magnetophoresis, you must first tag the circulating tumor cells with magnetic particles. Park et al. used magnetophoresis to separate CTCs from normal blood cells by attaching nano-sized immunomagnetic particles functionalized with anti-EpCAM antibodies that will link to MCF-7 breast epithelial cancer cells.143

Figure 6: The schematics of the CTC-iChip, which uses magnetophoresis to separate beadlabeled white blood cells from unlabelled CTCs. (Reprinted by permission from Macmillan Publishers Ltd: Nature Protocols144 2014.) Karabacak et al. developed the CTC-iChip, a microfluidic platform that uses deterministic lateral displacement, inertial focusing, magnetic beads functionalized with CD45 and magnetophoresis, in order to deplete leukocytes and enrich and separate circulating tumor cells. The CTC-iChip consist of 2 microfluidic devices, CTC-iChip1 and CTC-iChip2, each with different roles. CTC-iChip1 consist of patterned silicon microposts, which separates nucleated cells from the blood sample, by using DLD as a working principle (deterministic lateral displacement). The microposts are designed with a size and array offset to deflect particles of a certain size. This design is based on critical deflection diameter (Dc) which represents the minimum hydrodynamic diameter of the particles deflected by the DLD array. CTC-iChip2 is made out of PDMS, by soft lithography and is in charge of magnetic separation of the cells that exit the first device. It uses inertial focusing and magnetophoresis to sort the targeted cells based on their previous load with antibody functionalized magnetic beads. The inertial focusing is used to increase the accuracy of the sorting strategy and the analysis of cells. This method makes it possible to align all the cells in a single row in a certain position in the microchannel. Positioning all the cells, the labelled and unlabelled, to the same position, makes the magnetophoretic sorting process highly sensitive. It is capable of sorting 107 cells/s, with a processing rate of 8 mL of whole blood/h. They achieved a 3.8log depletion of leukocites and a cancer cell capture rate of 97% ± 2.7%.144



Alshareef et al. used a dielectrophoretic lab-on-a-chip device for the separation of different cancer cells of epithelial origin for CTCs detection. This device distinguishes and separates MCF-7 human breast cancer cells from HTC-116 colorectal cancer cells using dielectrophoresis. By optimizing the parameters such as AC frequency, voltage and flow rate they achieved a 93% recovery rate.145 Marchalot et al. presented a polymeric microfluidic device with integrated electrodes made out of Carbon-Poly Dimethyl Siloxane composite (C-PDMS), with the role of trapping low abundance cells by dielectrophoresis. They achieved a recovery efficiency for the MDAMB-231 breast cancer cell line cells of 97% at 20 µl/h and 78.7% at 80 µl/h, for 100 µm thick electrodes.146 Shim et al. described a continuous flow microfluidic processing chamber in which CTCs, under forces of diffusion, dielectrophoresis, sedimentation and hydrodynamic lift force, are transported close to the floor of the chamber, thus separating them from the rest of the blood cells (Fig. 5). They achieved an isolation of tumor cells of 70-80%, regardless of tumor cells spiking density.135 Park et al. developed a microfluidic device that uses a lateral magnetophoresis method based on immunomagnetic nano-beads with anti-EpCAM antibodies that bind to CTCs. The isolation is based on a gradient magnetic field. Using this method they achieved a 93% recovery rate at a flow rate of 40/100 mL/min. The device processes 400 mL of whole blood in 10 min.143 Because recent research indicates that the chemotherapeutic drug resistance of CTCs can be evaluated by analyzing the gene expression of multi drug resistance related proteins (MRPs),147,148 Chiu et al. developed a microfluidic device that integrates optically induced dielectrophoretic (ODEP) force-based cell manipulation and fluorescent microscopy, in order to obtain purified CTCs populations for further gene expression analysis for MRPs. The device was designed to separate semi-continuously CTCs from leukocytes by using ODEP force-based cell manipulation in a laminar flow. For this they designed a T shaped microchannel, in which the side microchannel was used for CTC collection. The CTC isolation zone was placed at the junction of the two microchannels. They tested their device using the PC-3 prostate cancer cell line. A sample of leukocytes and PC-3 cells with fluorescent dyes were stained for EpCAM (green), CD45 (red) and DAPI (blue). The sample was further loaded in the microfluidic system. The CTCs isolation zone was observed by fluorescent microscopy in order to detect CTCs (green dot images). When a green dot was observed the flow was stopped. After analyzing the cells with the other optical filters for red and blue dot images, the target CTCs cells were enclosed with the ODEP force-based cell manipulation and moved in the collecting microchannel. They obtained 8 ml blood samples from three healthy volunteers and spiked them with PC-3 cancer cells in order to obtain different CTCs concentrations. They achieved a CTC recovery rate of 41.5%, with an isolation purity of 100 %.142 Chou et al. integrated ODEP in a microfluidic system in order to improve the isolation of CTCs. They designed a cascade isolation process by using four optical light-based virtual cell filters. These light based cell filters represent four different selection conditions. After conducting experiments the researchers determined the optimal light bar width to be 40 µm, the gap 80 µm and the optimal number of light bars of four. The optimal sample flow rate was 0.4 µl min-1. Their method achieved a CTC recovery rate of 54±7% with a cell purity of 94.9±0.3%.149


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Fischera et al. stated that by using diagnosis leukapheresis (LA), which targets mononuclear cells in the peripheral blood, cells that have a similar density to CTCs, and because leukapheresis processes the whole circulating blood, it can be used to detect CTCs. After analysing the products generated by the LA from 25 L of blood, they concluded that CTCs can be detected in more than 90% of non-metastatic breast cancer patients. They determined a median number of 7,500 CTCs per patients.150 Table 3. Devices that use electrical properties of CTCs or other methods in order to detect them Name CTC-iChip©144 Alshareef et al.145 Marchalot et al.146 Shim et al.135 Park et al. 143 Chiu et al.142 Chou et al.149

Recovery rate 97% ± 2.7% 93% 97% 70-80% 93% 41.5% 54±7%

Specificity 99.9% 90% 100 % 94.9±0.3%

Conclusions In the past two decades a lot of research has been done on circulating tumor cells and how their presence and morphology influences progression-free survival and overall survival. Research collectives have developed devices that can detect and characterize this small population of cells in the blood of cancer patients. The most studied detection methods are based on specific surface antigens, on physical properties and on the electric properties of CTCs. All these detection methods have advantages and disadvantages because of the low number of CTCs in the peripheral blood and morphologic heterogeneity. Another problem that the detection methods encounter is the epithelial-mesenchymal transition that occurs during the process of metastasis. Further research is needed in order to develop a universal diagnostic device that will detect the development of cancer even before it can be discovered by conventional means.

There are no conflicts to declare. Bibliography: (1) (2) (3) (4)

Jemal, A.; Bray, F.; Center, M. M.; Ferlay, J.; Ward, E.; Forman, D. Global Cancer Statistics. CA. Cancer J. Clin. 2011, 61 (2), 69–90. van Zijl, F.; Krupitza, G.; Mikulits, W. Initial Steps of Metastasis: Cell Invasion and Endothelial Transmigration. Mutat. Res. 2011, 728 (1–2), 23–34. Klein, C. A. Parallel Progression of Primary Tumours and Metastases. Nat Rev Cancer 2009, 9 (4), 302–312. Lloyd, J. M.; McIver, C. M.; Stephenson, S.-A.; Hewett, P. J.; Rieger, N.; Hardingham, J. E. Identification of Early-Stage Colorectal Cancer Patients at Risk of Relapse Post-Resection by Immunobead Reverse Transcription-PCR Analysis of



(5)

(6) (7) (8) (9) (10)

(11)

(12)

(13)

(14) (15) (16) (17)

(18)

(19)

(20)

(21)

Peritoneal Lavage Fluid for Malignant Cells. Clin. Cancer Res. 2006, 12 (2), 417–423. Hüsemann, Y.; Geigl, J. B.; Schubert, F.; Musiani, P.; Meyer, M.; Burghart, E.; Forni, G.; Eils, R.; Fehm, T.; Riethmüller, G.; Klein, C. A. Systemic Spread Is an Early Step in Breast Cancer. Cancer Cell 2008, 13 (1), 58–68. Ashworth, T. R. A Case of Cancer in Which Cells Similar to Those in the Tumors Were Seen in the Blood after Death. Aust Med J 1869, 14, 146–149. Hajba, L.; Guttman, A. Circulating Tumor-Cell Detection and Capture Using Microfluidic Devices. TrAC Trends Anal. Chem. 2014, 59 (Supplement C), 9–16. Alix-Panabières, C.; Pantel, K. Challenges in Circulating Tumour Cell Research. Nat. Rev. Cancer 2014, 14, 623. Ferreira, M. M.; Ramani, V. C.; Jeffrey, S. S. Circulating Tumor Cell Technologies. Mol. Oncol. 2016, 10 (3), 374–394. Zheng, S.; Lin, H.; Liu, J.-Q.; Balic, M.; Datar, R.; Cote, R. J.; Tai, Y.-C. Membrane Microfilter Device for Selective Capture, Electrolysis and Genomic Analysis of Human Circulating Tumor Cells. J. Chromatogr. A 2007, 1162 (2), 154–161. Gertler, R.; Rosenberg, R.; Fuehrer, K.; Dahm, M.; Nekarda, H.; Siewert, J. R. Detection of Circulating Tumor Cells in Blood Using an Optimized Density Gradient Centrifugation. Recent results cancer Res. Fortschritte der Krebsforsch. Prog. dans les Rech. sur le cancer 2003, 162, 149–155. Becker, F. F.; Wang, X. B.; Huang, Y.; Pethig, R.; Vykoukal, J.; Gascoyne, P. R. Separation of Human Breast Cancer Cells from Blood by Differential Dielectric Affinity. Proceedings of the National Academy of Sciences of the United States of America. January 1995, pp 860–864. Cristofanilli, M.; Budd, G. T.; Ellis, M. J.; Stopeck, A.; Matera, J.; Miller, M. C.; Reuben, J. M.; Doyle, G. V; Allard, W. J.; Terstappen, L. W. M. M.; Hayes, D. F. Circulating Tumor Cells, Disease Progression, and Survival in Metastatic Breast Cancer. N. Engl. J. Med. 2004, 351 (8), 781–791. Steeg, P. S. Tumor Metastasis: Mechanistic Insights and Clinical Challenges. Nat. Med. 2006, 12 (8), 895–904. Gupta, G. P.; Massague, J. Cancer Metastasis: Building a Framework. Cell 2006, 127 (4), 679–695. Reya, T.; Morrison, S. J.; Clarke, M. F.; Weissman, I. L. Stem Cells, Cancer, and Cancer Stem Cells. Nature 2001, 414 (6859), 105–111. Mocellin, S.; Hoon, D.; Ambrosi, A.; Nitti, D.; Rossi, C. R. The Prognostic Value of Circulating Tumor Cells in Patients with Melanoma: A Systematic Review and MetaAnalysis. Clin. Cancer Res. 2006, 12 (15), 4605–4613. Smerage, J. B.; Hayes, D. F. The Measurement and Therapeutic Implications of Circulating Tumour Cells in Breast Cancer. British Journal of Cancer. January 2006, pp 8–12. Rolle, A.; Gunzel, R.; Pachmann, U.; Willen, B.; Hoffken, K.; Pachmann, K. Increase in Number of Circulating Disseminated Epithelial Cells after Surgery for Non-Small Cell Lung Cancer Monitored by MAINTRAC(R) Is a Predictor for Relapse: A Preliminary Report. World J. Surg. Oncol. 2005, 3 (1), 18. Braun, S.; Marth, C. Circulating Tumor Cells in Metastatic Breast Cancer--toward Individualized Treatment? The New England journal of medicine. United States August 2004, pp 824–826. Ilie, M.; Hofman, V.; Long-Mira, E.; Selva, E.; Vignaud, J.-M.; Padovani, B.; Mouroux, J.; Marquette, C.-H.; Hofman, P. “Sentinel” circulating Tumor Cells Allow Early Diagnosis of Lung Cancer in Patients with Chronic Obstructive Pulmonary Disease. PLoS One 2014, 9 (10), e111597.


Page 28 of 39

Page 29 of 39 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(22)

(23) (24) (25) (26)

(27) (28)

(29)

(30)

(31)

(32)

(33)

(34)

(35) (36) (37) (38)

Bidard, F. C.; Vincent-Salomon, A.; Sigal-Zafrani, B.; Diéras, V.; Mathiot, C.; Mignot, L.; Thiery, J. P.; Sastre-Garau, X.; Pierga, J. Y. Prognosis of Women with Stage IV Breast Cancer Depends on Detection of Circulating Tumor Cells rather than Disseminated Tumor Cells. Ann. Oncol. 2008, 19 (3), 496–500. de Bono, J. S.; Ashworth, A. Translating Cancer Research into Targeted Therapeutics. Nature 2010, 467 (7315), 543–549. Mego, M.; Mani, S. A.; Cristofanilli, M. Molecular Mechanisms of Metastasis in Breast Cancer--Clinical Applications. Nat. Rev. Clin. Oncol. 2010, 7 (12), 693–701. Chaffer, C. L.; Weinberg, R. A. A Perspective on Cancer Cell Metastasis. Science 2011, 331 (6024), 1559–1564. Hou, H. W.; Warkiani, M. E.; Khoo, B. L.; Li, Z. R.; Soo, R. A.; Tan, D. S.-W.; Lim, W.-T.; Han, J.; Bhagat, A. A. S.; Lim, C. T. Isolation and Retrieval of Circulating Tumor Cells Using Centrifugal Forces. Sci. Rep. 2013, 3, 1259. Dotan, E.; Cohen, S. J.; Alpaugh, K. R.; Meropol, N. J. Circulating Tumor Cells: Evolving Evidence and Future Challenges. Oncologist 2009, 14 (11), 1070–1082. Lianidou, E. S.; Markou, A.; Strati, A. Molecular Characterization of Circulating Tumor Cells in Breast Cancer: Challenges and Promises for Individualized Cancer Treatment. Cancer Metastasis Rev. 2012, 31 (3–4), 663–671. Scher, H. I.; Jia, X.; de Bono, J. S.; Fleisher, M.; Pienta, K. J.; Raghavan, D.; Heller, G. Circulating Tumour Cells as Prognostic Markers in Progressive, CastrationResistant Prostate Cancer: A Reanalysis of IMMC38 Trial Data. Lancet. Oncol. 2009, 10 (3), 233–239. Wicha, M. S.; Hayes, D. F. Circulating Tumor Cells: Not All Detected Cells Are Bad and Not All Bad Cells Are Detected. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. United States April 2011, pp 1508–1511. Jin, C.; McFaul, S. M.; Duffy, S. P.; Deng, X.; Tavassoli, P.; Black, P. C.; Ma, H. Technologies for Label-Free Separation of Circulating Tumor Cells: From Historical Foundations to Recent Developments. Lab Chip 2014, 14 (1), 32–44. Witzig, T. E.; Bossy, B.; Kimlinger, T.; Roche, P. C.; Ingle, J. N.; Grant, C.; Donohue, J.; Suman, V. J.; Harrington, D.; Torre-Bueno, J.; Bauer, K. D. Detection of Circulating Cytokeratin-Positive Cells in the Blood of Breast Cancer Patients Using Immunomagnetic Enrichment and Digital Microscopy. Clin. Cancer Res. 2002, 8 (5), 1085–1091. Chang, C.-L.; Huang, W.; Jalal, S. I.; Chan, B.-D.; Mahmood, A.; Shahda, S.; O’Neil, B. H.; Matei, D. E.; Savran, C. A. Circulating Tumor Cell Detection Using a Parallel Flow Micro-Aperture Chip System. Lab Chip 2015, 15 (7), 1677–1688. Yu, M.; Bardia, A.; Aceto, N.; Bersani, F.; Madden, M. W.; Donaldson, M. C.; Desai, R.; Zhu, H.; Comaills, V.; Zheng, Z.; Wittner, B. S.; Stojanov, P.; Brachtel, E.; Sgroi, D.; Kapur, R.; Shioda, T.; Ting, D. T.; Ramaswamy, S.; Getz, G.; Iafrate, A. J.; Benes, C.; Toner, M.; Maheswaran, S.; Haber, D. A. Cancer Therapy. Ex Vivo Culture of Circulating Breast Tumor Cells for Individualized Testing of Drug Susceptibility. Science 2014, 345 (6193), 216–220. Ambros, V. MicroRNA Pathways in Flies and Worms: Growth, Death, Fat, Stress, and Timing. Cell 2003, 113 (6), 673–676. He, L.; Hannon, G. J. MicroRNAs: Small RNAs with a Big Role in Gene Regulation. Nat. Rev. Genet. 2004, 5 (7), 522–531. Kloosterman, W. P.; Plasterk, R. H. A. The Diverse Functions of microRNAs in Animal Development and Disease. Dev. Cell 2006, 11 (4), 441–450. Perera, R. J.; Ray, A. MicroRNAs in the Search for Understanding Human Diseases. BioDrugs 2007, 21 (2), 97–104.



(39)

(40)

(41) (42)

(43)

(44) (45)

(46)

(47) (48)

(49)

(50)

(51)

Calin, G. A.; Dumitru, C. D.; Shimizu, M.; Bichi, R.; Zupo, S.; Noch, E.; Aldler, H.; Rattan, S.; Keating, M.; Rai, K.; Rassenti, L.; Kipps, T.; Negrini, M.; Bullrich, F.; Croce, C. M. Frequent Deletions and down-Regulation of Micro- RNA Genes miR15 and miR16 at 13q14 in Chronic Lymphocytic Leukemia. Proc. Natl. Acad. Sci. U. S. A. 2002, 99 (24), 15524–15529. Zhou, H.; Guo, J.-M.; Lou, Y.-R.; Zhang, X.-J.; Zhong, F.-D.; Jiang, Z.; Cheng, J.; Xiao, B.-X. Detection of Circulating Tumor Cells in Peripheral Blood from Patients with Gastric Cancer Using microRNA as a Marker. J. Mol. Med. (Berl). 2010, 88 (7), 709–717. Lamouille, S.; Xu, J.; Derynck, R. Molecular Mechanisms of Epithelial-Mesenchymal Transition. Nat. Rev. Mol. Cell Biol. 2014, 15 (3), 178–196. Micalizzi, D. S.; Farabaugh, S. M.; Ford, H. L. Epithelial-Mesenchymal Transition in Cancer: Parallels between Normal Development and Tumor Progression. J. Mammary Gland Biol. Neoplasia 2010, 15 (2), 117–134. Armstrong, A. J.; Marengo, M. S.; Oltean, S.; Kemeny, G.; Bitting, R. L.; Turnbull, J. D.; Herold, C. I.; Marcom, P. K.; George, D. J.; Garcia-Blanco, M. A. Circulating Tumor Cells from Patients with Advanced Prostate and Breast Cancer Display Both Epithelial and Mesenchymal Markers. Mol. Cancer Res. 2011, 9 (8), 997–1007. Brabletz, T. To Differentiate or Not--Routes towards Metastasis. Nature reviews. Cancer. England May 2012, pp 425–436. Yokobori, T.; Iinuma, H.; Shimamura, T.; Imoto, S.; Sugimachi, K.; Ishii, H.; Iwatsuki, M.; Ota, D.; Ohkuma, M.; Iwaya, T.; Nishida, N.; Kogo, R.; Sudo, T.; Tanaka, F.; Shibata, K.; Toh, H.; Sato, T.; Barnard, G. F.; Fukagawa, T.; Yamamoto, S.; Nakanishi, H.; Sasaki, S.; Miyano, S.; Watanabe, T.; Kuwano, H.; Mimori, K.; Pantel, K.; Mori, M. Plastin3 Is a Novel Marker for Circulating Tumor Cells Undergoing the Epithelial-Mesenchymal Transition and Is Associated with Colorectal Cancer Prognosis. Cancer Res. 2013, 73 (7), 2059–2069. Ueo, H.; Sugimachi, K.; Gorges, T. M.; Bartkowiak, K.; Yokobori, T.; Muller, V.; Shinden, Y.; Ueda, M.; Ueo, H.; Mori, M.; Kuwano, H.; Maehara, Y.; Ohno, S.; Pantel, K.; Mimori, K. Circulating Tumour Cell-Derived plastin3 Is a Novel Marker for Predicting Long-Term Prognosis in Patients with Breast Cancer. Br. J. Cancer 2015, 112 (9), 1519–1526. Kang, Y.; Pantel, K. Tumor Cell Dissemination: Emerging Biological Insights from Animal Models and Cancer Patients. Cancer Cell 2013, 23 (5), 573–581. Yu, M.; Bardia, A.; Wittner, B. S.; Stott, S. L.; Smas, M. E.; Ting, D. T.; Isakoff, S. J.; Ciciliano, J. C.; Wells, M. N.; Shah, A. M.; Concannon, K. F.; Donaldson, M. C.; Sequist, L. V; Brachtel, E.; Sgroi, D.; Baselga, J.; Ramaswamy, S.; Toner, M.; Haber, D. A.; Maheswaran, S. Circulating Breast Tumor Cells Exhibit Dynamic Changes in Epithelial and Mesenchymal Composition. Science 2013, 339 (6119), 580–584. Al-Hajj, M.; Wicha, M. S.; Benito-Hernandez, A.; Morrison, S. J.; Clarke, M. F. Prospective Identification of Tumorigenic Breast Cancer Cells. Proc. Natl. Acad. Sci. U. S. A. 2003, 100 (7), 3983–3988. Theodoropoulos, P. A.; Polioudaki, H.; Agelaki, S.; Kallergi, G.; Saridaki, Z.; Mavroudis, D.; Georgoulias, V. Circulating Tumor Cells with a Putative Stem Cell Phenotype in Peripheral Blood of Patients with Breast Cancer. Cancer Lett. 2010, 288 (1), 99–106. Cristofanilli, M.; Hayes, D. F.; Budd, G. T.; Ellis, M. J.; Stopeck, A.; Reuben, J. M.; Doyle, G. V; Matera, J.; Allard, W. J.; Miller, M. C.; Fritsche, H. A.; Hortobagyi, G. N.; Terstappen, L. W. M. M. Circulating Tumor Cells: A Novel Prognostic Factor for Newly Diagnosed Metastatic Breast Cancer. J. Clin. Oncol. 2005, 23 (7), 1420–1430.


Page 30 of 39

Page 31 of 39 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(52)

(53)

(54)

(55)

(56)

(57)

(58)

(59)

(60)

(61)

(62)

(63)

(64)

Shyamala, M.; V., S. L.; Sunitha, N.; Lindsey, U.; Brian, B.; V., C. C.; Elizabeth, I.; Sven, D.; John, I. A.; W., B. D.; Subba, D.; Alona, M.; Daniel, I.; Jeffrey, S.; G., T. R.; J., L. T.; Mehmet, T.; A., H. D. Detection of Mutations in EGFR in Circulating LungCancer Cells. N. Engl. J. Med. 2008, 359 (4), 366–377. Friederichs, J.; Gertler, R.; Rosenberg, R.; Dahm, M.; Nekarda, H.; Holzmann, B.; Siewert, J. R. Correlation of CK-20-Positive Cells in Peripheral Venous Blood with Serum CEA Levels in Patients with Colorectal Carcinoma. World J. Surg. 2007, 31 (12), 2329–2334. Lucas, K. A.; Pitari, G. M.; Kazerounian, S.; Ruiz-Stewart, I.; Park, J.; Schulz, S.; Chepenik, K. P.; Waldman, S. A. Guanylyl Cyclases and Signaling by Cyclic GMP. Pharmacol. Rev. 2000, 52 (3), 375–414. Gradilone, A.; Gazzaniga, P.; Silvestri, I.; Gandini, O.; Trasatti, L.; Lauro, S.; Frati, L.; Agliano, A. M. Detection of CK19, CK20 and EGFR mRNAs in Peripheral Blood of Carcinoma Patients: Correlation with Clinical Stage of Disease. Oncol. Rep. 2003, 10 (1), 217–222. Birbe, R.; Palazzo, J. P.; Walters, R.; Weinberg, D.; Schulz, S.; Waldman, S. A. Guanylyl Cyclase C Is a Marker of Intestinal Metaplasia, Dysplasia, and Adenocarcinoma of the Gastrointestinal Tract. Hum. Pathol. 2005, 36 (2), 170–179. Carrithers, S. L.; Barber, M. T.; Biswas, S.; Parkinson, S. J.; Park, P. K.; Goldstein, S. D.; Waldman, S. A. Guanylyl Cyclase C Is a Selective Marker for Metastatic Colorectal Tumors in Human Extraintestinal Tissues. Proceedings of the National Academy of Sciences of the United States of America. December 1996, pp 14827– 14832. Chen, G.; McIver, C. M.; Texler, M.; Lloyd, J. M.; Rieger, N.; Hewett, P. J.; Sen Wan, D.; Hardingham, J. E. Detection of Occult Metastasis in Lymph Nodes from Colorectal Cancer Patients: A Multiple-Marker Reverse Transcriptase-Polymerase Chain Reaction Study. Dis. Colon Rectum 2004, 47 (5), 679–686. Steinbrecher, K. A.; Mann, E. A.; Giannella, R. A.; Cohen, M. B. Increases in Guanylin and Uroguanylin in a Mouse Model of Osmotic Diarrhea Are Guanylate Cyclase C-Independent. Gastroenterology 2001, 121 (5), 1191–1202. Frick, G. S.; Pitari, G. M.; Weinberg, D. S.; Hyslop, T.; Schulz, S.; Waldman, S. A. Guanylyl Cyclase C: A Molecular Marker for Staging and Postoperative Surveillance of Patients with Colorectal Cancer. Expert Rev. Mol. Diagn. 2005, 5 (5), 701–713. Schulz, S.; Hyslop, T.; Haaf, J.; Bonaccorso, C.; Nielsen, K.; Witek, M. E.; Birbe, R.; Palazzo, J.; Weinberg, D.; Waldman, S. A. A Validated Quantitative Assay to Detect Occult Micrometastases by Reverse Transcriptase-Polymerase Chain Reaction of Guanylyl Cyclase C in Patients with Colorectal Cancer. Clin. Cancer Res. 2006, 12 (15), 4545–4552. Bustin, S. A.; Gyselman, V. G.; Siddiqi, S.; Dorudi, S. Cytokeratin 20 Is Not a TissueSpecific Marker for the Detection of Malignant Epithelial Cells in the Blood of Colorectal Cancer Patients. Int. J. Surg. Investig. 2000, 2 (1), 49–57. Cohen, S. J.; Alpaugh, R. K.; Gross, S.; O’Hara, S. M.; Smirnov, D. A.; Terstappen, L. W. M. M.; Allard, W. J.; Bilbee, M.; Cheng, J. D.; Hoffman, J. P.; Lewis, N. L.; Pellegrino, A.; Rogatko, A.; Sigurdson, E.; Wang, H.; Watson, J. C.; Weiner, L. M.; Meropol, N. J. Isolation and Characterization of Circulating Tumor Cells in Patients with Metastatic Colorectal Cancer. Clin. Colorectal Cancer 2006, 6 (2), 125–132. Cohen, S. J.; Punt, C. J. A.; Iannotti, N.; Saidman, B. H.; Sabbath, K. D.; Gabrail, N. Y.; Picus, J.; Morse, M.; Mitchell, E.; Miller, M. C.; Doyle, G. V; Tissing, H.; Terstappen, L. W. M. M.; Meropol, N. J. Relationship of Circulating Tumor Cells to Tumor Response, Progression-Free Survival, and Overall Survival in Patients with



(65)

(66)

(67)

(68)

(69)

(70)

(71)

(72)

(73)

(74)

(75) (76)

(77)

Metastatic Colorectal Cancer. J. Clin. Oncol. 2008, 26 (19), 3213–3221. Liu, Y.; Qian, J.; Feng, J.-G.; Ju, H.-X.; Zhu, Y.-P.; Feng, H.-Y.; Li, D.-C. Detection of Circulating Tumor Cells in Peripheral Blood of Colorectal Cancer Patients without Distant Organ Metastases. Cell. Oncol. 2013, 36 (1), 43–53. Selvaggi, G.; Novello, S.; Torri, V.; Leonardo, E.; De Giuli, P.; Borasio, P.; Mossetti, C.; Ardissone, F.; Lausi, P.; Scagliotti, G. V. Epidermal Growth Factor Receptor Overexpression Correlates with a Poor Prognosis in Completely Resected Non-SmallCell Lung Cancer. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 2004, 15 (1), 28–32. Cen, P.; Ni, X.; Yang, J.; Graham, D. Y.; Li, M. Circulating Tumor Cells in the Diagnosis and Management of Pancreatic Cancer. Biochim. Biophys. Acta 2012, 1826 (2), 350–356. Mani, S. A.; Guo, W.; Liao, M.-J.; Eaton, E. N.; Ayyanan, A.; Zhou, A. Y.; Brooks, M.; Reinhard, F.; Zhang, C. C.; Shipitsin, M.; Campbell, L. L.; Polyak, K.; Brisken, C.; Yang, J.; Weinberg, R. A. The Epithelial-Mesenchymal Transition Generates Cells with Properties of Stem Cells. Cell 2008, 133 (4), 704–715. Rhim, A. D.; Mirek, E. T.; Aiello, N. M.; Maitra, A.; Bailey, J. M.; McAllister, F.; Reichert, M.; Beatty, G. L.; Rustgi, A. K.; Vonderheide, R. H.; Leach, S. D.; Stanger, B. Z. EMT and Dissemination Precede Pancreatic Tumor Formation. Cell 2012, 148 (1–2), 349–361. Steinmetz, N. F.; Cho, C.-F.; Ablack, A.; Lewis, J. D.; Manchester, M. Cowpea Mosaic Virus Nanoparticles Target Surface Vimentin on Cancer Cells. Nanomedicine (Lond). 2011, 6 (2), 351–364. Weidle, U. H.; Maisel, D.; Klostermann, S.; Schiller, C.; Weiss, E. H. Intracellular Proteins Displayed on the Surface of Tumor Cells as Targets for Therapeutic Intervention with Antibody-Related Agents. Cancer Genomics Proteomics 2011, 8 (2), 49–63. Satelli, A.; Mitra, A.; Cutrera, J. J.; Devarie, M.; Xia, X.; Ingram, D. R.; Dibra, D.; Somaiah, N.; Torres, K. E.; Ravi, V.; Ludwig, J. A.; Kleinerman, E. S.; Li, S. Universal Marker and Detection Tool for Human Sarcoma Circulating Tumor Cells. Cancer Res. 2014, 74 (6), 1645–1650. Krebs, M. G.; Metcalf, R. L.; Carter, L.; Brady, G.; Blackhall, F. H.; Dive, C. Molecular Analysis of Circulating Tumour Cells - Biology and Biomarkers. Nat Rev Clin Oncol 2014, 11 (3), 129–144. Powell, A. A.; Talasaz, A. H.; Zhang, H.; Coram, M. A.; Reddy, A.; Deng, G.; Telli, M. L.; Advani, R. H.; Carlson, R. W.; Mollick, J. A.; Sheth, S.; Kurian, A. W.; Ford, J. M.; Stockdale, F. E.; Quake, S. R.; Pease, R. F.; Mindrinos, M. N.; Bhanot, G.; Dairkee, S. H.; Davis, R. W.; Jeffrey, S. S. Single Cell Profiling of Circulating Tumor Cells: Transcriptional Heterogeneity and Diversity from Breast Cancer Cell Lines. PLoS One 2012, 7 (5), 1–11. Zieglschmid, V.; Hollmann, C.; Bocher, O. Detection of Disseminated Tumor Cells in Peripheral Blood. Crit. Rev. Clin. Lab. Sci. 2005, 42 (2), 155–196. de Bono, J. S.; Scher, H. I.; Montgomery, R. B.; Parker, C.; Miller, M. C.; Tissing, H.; Doyle, G. V; Terstappen, L. W. W. M.; Pienta, K. J.; Raghavan, D. Circulating Tumor Cells Predict Survival Benefit from Treatment in Metastatic Castration-Resistant Prostate Cancer. Clin. Cancer Res. 2008, 14 (19), 6302–6309. Riethdorf, S.; Fritsche, H.; Müller, V.; Rau, T.; Schindlbeck, C.; Rack, B.; Janni, W.; Coith, C.; Beck, K.; Jänicke, F.; Jackson, S.; Gornet, T.; Cristofanilli, M.; Pantel, K. Detection of Circulating Tumor Cells in Peripheral Blood of Patients with Metastatic Breast Cancer: A Validation Study of the CellSearch System. Clin. Cancer Res. 2007, 13 (3), 920 LP-928.


Page 32 of 39

Page 33 of 39 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(78)

(79)

(80)

(81)

(82)

(83)

(84)

(85)

(86)

(87)

(88)

(89)

Talasaz, A. H.; Powell, A. A.; Huber, D. E.; Berbee, J. G.; Roh, K.-H.; Yu, W.; Xiao, W.; Davis, M. M.; Pease, R. F.; Mindrinos, M. N.; Jeffrey, S. S.; Davis, R. W. Isolating Highly Enriched Populations of Circulating Epithelial Cells and Other Rare Cells from Blood Using a Magnetic Sweeper Device. Proc. Natl. Acad. Sci. U. S. A. 2009, 106 (10), 3970–3975. Nwankire, C. E.; Venkatanarayanan, A.; Glennon, T.; Keyes, T. E.; Forster, R. J.; Ducree, J. Label-Free Impedance Detection of Cancer Cells from Whole Blood on an Integrated Centrifugal Microfluidic Platform. Biosens. Bioelectron. 2015, 68, 382– 389. Nagrath, S.; Sequist, L. V; Maheswaran, S.; Bell, D. W.; Irimia, D.; Ulkus, L.; Smith, M. R.; Kwak, E. L.; Digumarthy, S.; Muzikansky, A.; Ryan, P.; Balis, U. J.; Tompkins, R. G.; Haber, D. A.; Toner, M. Isolation of Rare Circulating Tumour Cells in Cancer Patients by Microchip Technology. Nature. December 2007, pp 1235–1239. Zhao, M.; Schiro, P. G.; Kuo, J. S.; Koehler, K. M.; Sabath, D. E.; Popov, V.; Feng, Q.; Chiu, D. T. An Automated High-Throughput Counting Method for Screening Circulating Tumor Cells in Peripheral Blood. Anal. Chem. 2013, 85 (4), 2465–2471. Lin, M.; Chen, J.-F.; Lu, Y.-T.; Zhang, Y.; Song, J.; Hou, S.; Ke, Z.; Tseng, H.-R. Nanostructure Embedded Microchips for Detection, Isolation, and Characterization of Circulating Tumor Cells. Acc. Chem. Res. 2014, 47 (10), 2941–2950. Wang, S.; Liu, K.; Liu, J.; Yu, Z. T.-F.; Xu, X.; Zhao, L.; Lee, T.; Lee, E. K.; Reiss, J.; Lee, Y.-K.; Chung, L. W. K.; Huang, J.; Rettig, M.; Seligson, D.; Duraiswamy, K. N.; Shen, C. K.-F.; Tseng, H.-R. Highly Efficient Capture of Circulating Tumor Cells by Using Nanostructured Silicon Substrates with Integrated Chaotic Micromixers. Angew. Chemie Int. Ed. 2011, 50 (13), 3084–3088. Lu, Y. T.; Zhao, L.; Shen, Q.; Garcia, M. A.; Wu, D.; Hou, S.; Song, M.; Xu, X.; OuYang, W. H.; OuYang, W. W. L.; Lichterman, J.; Luo, Z.; Xuan, X.; Huang, J.; Chung, L. W. K.; Rettig, M.; Tseng, H. R.; Shao, C.; Posadas, E. M. NanoVelcro Chip for CTC Enumeration in Prostate Cancer Patients. Methods 2013, 64 (2), 144–152. Shen, Q.; Xu, L.; Zhao, L.; Wu, D.; Fan, Y.; Zhou, Y.; OuYang, W.-H.; Xu, X.; Zhang, Z.; Song, M.; Lee, T.; Garcia, M. A.; Xiong, B.; Hou, S.; Tseng, H.-R.; Fang, X. Specific Capture and Release of Circulating Tumor Cells Using Aptamer-Modified Nanosubstrates. Adv. Mater. 2013, 25 (16), 2368–2373. Hou, S.; Zhao, L.; Shen, Q.; Yu, J.; Ng, C.; Kong, X.; Wu, D.; Song, M.; Shi, X.; Xu, X.; OuYang, W.-H.; He, R.; Zhao, X.-Z.; Lee, T.; Brunicardi, F. C.; Garcia, M. A.; Ribas, A.; Lo, R. S.; Tseng, H.-R. Polymer Nanofiber-Embedded Microchips for Detection, Isolation, and Molecular Analysis of Single Circulating Melanoma Cells. Angew. Chemie Int. Ed. 2013, 52 (12), 3379–3383. Zhao, L.; Lu, Y.-T.; Li, F.; Wu, K.; Hou, S.; Yu, J.; Shen, Q.; Wu, D.; Song, M.; OuYang, W.-H.; Luo, Z.; Lee, T.; Fang, X.; Shao, C.; Xu, X.; Garcia, M. A.; Chung, L. W. K.; Rettig, M.; Tseng, H.-R.; Posadas, E. M. High-Purity Prostate Circulating Tumor Cell Isolation by a Polymer Nanofiber-Embedded Microchip for Whole Exome Sequencing. Adv. Mater. 2013, 25 (21), 2897–2902. Hou, S.; Zhao, H.; Zhao, L.; Shen, Q.; Wei, K. S.; Suh, D. Y.; Nakao, A.; Garcia, M. A.; Song, M.; Lee, T.; Xiong, B.; Luo, S.-C.; Tseng, H.-R.; Yu, H. Capture and Stimulated Release of Circulating Tumor Cells on Polymer-Grafted Silicon Nanostructures. Adv. Mater. 2013, 25 (11), 1547–1551. Zamay, G. S.; Kolovskaya, O. S.; Zamay, T. N.; Glazyrin, Y. E.; Krat, A. V; Zubkova, O.; Spivak, E.; Wehbe, M.; Gargaun, A.; Muharemagic, D.; Komarova, M.; Grigorieva, V.; Savchenko, A.; Modestov, A. A.; Berezovski, M. V; Zamay, A. S. Aptamers Selected to Postoperative Lung Adenocarcinoma Detect Circulating Tumor



Cells in Human Blood. Mol. Ther. 2015, 23 (9), 1486–1496. Maremanda, N. G.; Roy, K.; Kanwar, R. K.; Shyamsundar, V.; Ramshankar, V.; Krishnamurthy, A.; Krishnakumar, S.; Kanwar, J. R. Quick Chip Assay Using Locked Nucleic Acid Modified Epithelial Cell Adhesion Molecule and Nucleolin Aptamers for the Capture of Circulating Tumor Cells. Biomicrofluidics 2015, 9 (5), 54110. (91) Watanabe, T.; Hirano, K.; Takahashi, A.; Yamaguchi, K.; Beppu, M.; Fujiki, H.; Suganuma, M. Nucleolin on the Cell Surface as a New Molecular Target for Gastric Cancer Treatment. Biol. Pharm. Bull. 2010, 33 (5), 796–803. (92) Nora Dickson, M.; Tsinberg, P.; Tang, Z.; Bischoff, F. Z.; Wilson, T.; Leonard, E. F. Efficient Capture of Circulating Tumor Cells with a Novel Immunocytochemical Microfluidic Device. Biomicrofluidics 2011, 5 (3), 34119–3411915. (93) Weissenstein, U.; Schumann, A.; Reif, M.; Link, S.; Toffol-Schmidt, U. D.; Heusser, P. Detection of Circulating Tumor Cells in Blood of Metastatic Breast Cancer Patients Using a Combination of Cytokeratin and EpCAM Antibodies. BMC Cancer 2012, 12 (1), 206. (94) Lara, O.; Tong, X.; Zborowski, M.; Chalmers, J. J. Enrichment of Rare Cancer Cells through Depletion of Normal Cells Using Density and Flow-Through, Immunomagnetic Cell Separation. Exp. Hematol. 2004, 32 (10), 891–904. (95) Adams, A.; Okagbare, P. I.; Feng, J.; Hupert, M. L.; Patterson, D.; Go, J.; Mccarley, R. L.; Nikitopoulos, D. Highly Efficient Circulating Tumor Cell Isolation from Whole Blood and Label-Free Enumeration Using Polymer-Based Microfluidics with an Integrated Conductivity Sensor. Chem Soc 130 2008, 27 (5), 8633–8641. (96) Hwang, J. Y.; Kim, S. T.; Han, H. S.; Kim, K.; Han, J. S. Optical Aptamer Probes of Fluorescent Imaging to Rapid Monitoring of Circulating Tumor Cell. Sensors (Switzerland) 2016, 16 (11), 1909. (97) Wang, C.; Ye, M.; Cheng, L.; Li, R.; Zhu, W.; Shi, Z.; Fan, C.; He, J.; Liu, J.; Liu, Z. Simultaneous Isolation and Detection of Circulating Tumor Cells with a Microfluidic Silicon-Nanowire-Array Integrated with Magnetic Upconversion Nanoprobes. Biomaterials 2015, 54, 55–62. (98) Alix-Panabières, C. EPISPOT Assay: Detection of Viable DTCs/CTCs in Solid Tumor Patients. Recent Results in Cancer Research. 2012, pp 69–76. (99) Yoon, H. J.; Kim, T. H.; Zhang, Z.; Azizi, E.; Pham, T. M.; Paoletti, C.; Lin, J.; Ramnath, N.; Wicha, M. S.; Hayes, D. F.; Simeone, D. M.; Nagrath, S. Sensitive Capture of Circulating Tumour Cells by Functionalized Graphene Oxide Nanosheets. Nat Nano 2013, 8 (10), 735–741. (100) Stott, S. L.; Hsu, C.-H.; Tsukrov, D. I.; Yu, M.; Miyamoto, D. T.; Waltman, B. A.; Rothenberg, S. M.; Shah, A. M.; Smas, M. E.; Korir, G. K.; Floyd, F. P. J.; Gilman, A. J.; Lord, J. B.; Winokur, D.; Springer, S.; Irimia, D.; Nagrath, S.; Sequist, L. V; Lee, R. J.; Isselbacher, K. J.; Maheswaran, S.; Haber, D. A.; Toner, M. Isolation of Circulating Tumor Cells Using a Microvortex-Generating Herringbone-Chip. Proc. Natl. Acad. Sci. U. S. A. 2010, 107 (43), 18392–18397. (101) Casavant, B. P.; Guckenberger, D. J.; Berry, S. M.; Tokar, J. T.; Lang, J. M.; Beebe, D. J. The VerIFAST: An Integrated Method for Cell Isolation and Extracellular/intracellular Staining. Lab Chip 2013, 13 (3), 391–396. (102) Saucedo-Zeni, N.; Mewes, S.; Niestroj, R.; Gasiorowski, L.; Murawa, D.; Nowaczyk, P.; Tomasi, T.; Weber, E.; Dworacki, G.; Morgenthaler, N. G.; Jansen, H.; Propping, C.; Sterzynska, K.; Dyszkiewicz, W.; Zabel, M.; Kiechle, M.; Reuning, U.; Schmitt, M.; Lucke, K. A Novel Method for the in Vivo Isolation of Circulating Tumor Cells from Peripheral Blood of Cancer Patients Using a Functionalized and Structured Medical Wire. Int. J. Oncol. 2012, 41 (4), 1241–1250. (90)


Page 34 of 39

Page 35 of 39 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(103) Kirby, B. J.; Jodari, M.; Loftus, M. S.; Gakhar, G.; Pratt, E. D.; Chanel-Vos, C.; Gleghorn, J. P.; Santana, S. M.; Liu, H.; Smith, J. P.; Navarro, V. N.; Tagawa, S. T.; Bander, N. H.; Nanus, D. M.; Giannakakou, P. Functional Characterization of Circulating Tumor Cells with a Prostate-Cancer-Specific Microfluidic Device. PLoS One 2012, 7 (4), 1–10. (104) Yang, M.-H.; Imrali, A.; Heeschen, C. Circulating Cancer Stem Cells: The Importance to Select. Chin. J. Cancer Res. 2015, 27 (5), 437–449. (105) Jamal-Hanjani, M.; Thanopoulou, E.; Peggs, K. S.; Quezada, S. A.; Swanton, C. Tumour Heterogeneity and Immune-Modulation. Curr. Opin. Pharmacol. 2013, 13 (4), 497–503. (106) Hofman, V.; Ilie, M. I.; Long, E.; Selva, E.; Bonnetaud, C.; Molina, T.; Venissac, N.; Mouroux, J.; Vielh, P.; Hofman, P. Detection of Circulating Tumor Cells as a Prognostic Factor in Patients Undergoing Radical Surgery for Non-Small-Cell Lung Carcinoma: Comparison of the Efficacy of the CellSearch Assay and the Isolation by Size of Epithelial Tumor Cell Method. Int. J. cancer 2011, 129 (7), 1651–1660. (107) Hyun, K.-A.; Lee, T. Y.; Lee, S. H.; Jung, H.-I. Two-Stage Microfluidic Chip for Selective Isolation of Circulating Tumor Cells (CTCs). Biosens. Bioelectron. 2015, 67, 86–92. (108) Vona, G.; Sabile, A.; Louha, M.; Sitruk, V.; Romana, S.; Schutze, K.; Capron, F.; Franco, D.; Pazzagli, M.; Vekemans, M.; Lacour, B.; Brechot, C.; Paterlini-Brechot, P. Isolation by Size of Epithelial Tumor Cells : A New Method for the Immunomorphological and Molecular Characterization of Circulatingtumor Cells. Am. J. Pathol. 2000, 156 (1), 57–63. (109) Coumans, F. A. W.; van Dalum, G.; Beck, M.; Terstappen, L. W. M. M. Filter Characteristics Influencing Circulating Tumor Cell Enrichment from Whole Blood. PLoS One 2013, 8 (4), 1–12. (110) Park, S.; Ang, R. R.; Duffy, S. P.; Bazov, J.; Chi, K. N.; Black, P. C.; Ma, H. Morphological Differences between Circulating Tumor Cells from Prostate Cancer Patients and Cultured Prostate Cancer Cells. PLoS One 2014, 9 (1), 1–7. (111) Rejniak, K. A. Investigating Dynamical Deformations of Tumor Cells in Circulation: Predictions from a Theoretical Model. Frontiers in Oncology. 2012. (112) Cross, S. E.; Jin, Y.-S.; Rao, J.; Gimzewski, J. K. Nanomechanical Analysis of Cells from Cancer Patients. Nat Nano 2007, 2 (12), 780–783. (113) Chen, C.-L.; Mahalingam, D.; Osmulski, P.; Jadhav, R. R.; Wang, C.-M.; Leach, R. J.; Chang, T.-C.; Weitman, S. D.; Kumar, A. P.; Sun, L.; Gaczynska, M. E.; Thompson, I. M.; Huang, T. H.-M. Single-Cell Analysis of Circulating Tumor Cells Identifies Cumulative Expression Patterns of EMT-Related Genes in Metastatic Prostate Cancer. The Prostate. June 2013, pp 813–826. (114) Mak, M.; Erickson, D. A Serial Micropipette Microfluidic Device with Applications to Cancer Cell Repeated Deformation Studies. Integr. Biol. (Camb). 2013, 5 (11), 1374– 1384. (115) Fan, X.; Jia, C.; Yang, J.; Li, G.; Mao, H.; Jin, Q.; Zhao, J. A Microfluidic Chip Integrated with a High-Density PDMS-Based Microfiltration Membrane for Rapid Isolation and Detection of Circulating Tumor Cells. Biosens. Bioelectron. 2015, 71, 380–386. (116) Babahosseini, H.; Strobl, J. S.; Agah, M. Microfluidic Iterative Mechanical Characteristics (iMECH) Analyzer for Single-Cell Metastatic Identification. Anal. Methods 2017, 9 (5), 847–855. (117) Park, E. S.; Jin, C.; Guo, Q.; Ang, R. R.; Duffy, S. P.; Matthews, K.; Azad, A.; Abdi, H.; Todenhöfer, T.; Bazov, J.; Chi, K. N.; Black, P. C.; Ma, H. Continuous Flow



(118)

(119)

(120)

(121)

(122)

(123)

(124) (125) (126) (127)

(128) (129)

(130)

(131)

(132)

(133)

Deformability-Based Separation of Circulating Tumor Cells Using Microfluidic Ratchets. Small 2016, 12 (14), 1909–1919. Tan, S. J.; Yobas, L.; Lee, G. Y. H.; Ong, C. N.; Lim, C. T. Microdevice for the Isolation and Enumeration of Cancer Cells from Blood. Biomed. Microdevices 2009, 11 (4), 883–892. Hosokawa, M.; Hayata, T.; Fukuda, Y.; Arakaki, A.; Yoshino, T.; Tanaka, T.; Matsunaga, T. Size-Selective Microcavity Array for Rapid and Efficient Detection of Circulating Tumor Cells. Anal. Chem. 2010, 82 (15), 6629–6635. Zheng, S.; Lin, H. K.; Lu, B.; Williams, A.; Datar, R.; Cote, R. J.; Tai, Y.-C. 3D Microfilter Device for Viable Circulating Tumor Cell (CTC) Enrichment from Blood. Biomed. Microdevices 2011, 13 (1), 203–213. Huang, T.; Jia, C.-P.; Jun-Yang; Sun, W.-J.; Wang, W.-T.; Zhang, H.-L.; Cong, H.; Jing, F.-X.; Mao, H.-J.; Jin, Q.-H.; Zhang, Z.; Chen, Y.-J.; Li, G.; Mao, G.-X.; Zhao, J.-L. Highly Sensitive Enumeration of Circulating Tumor Cells in Lung Cancer Patients Using a Size-Based Filtration Microfluidic Chip. Biosens. Bioelectron. 2014, 51, 213–218. Lin, H. K.; Zheng, S.; Williams, A. J.; Balic, M.; Groshen, S.; Scher, H. I.; Fleisher, M.; Stadler, W.; Datar, R. H.; Tai, Y.-C.; Cote, R. J. Portable Filter-Based Microdevice for Detection and Characterization of Circulating Tumor Cells. Clin. Cancer Res. 2010, 16 (20), 5011–5018. Harouaka, R. A.; Zhou, M.-D.; Yeh, Y.-T.; Khan, W. J.; Das, A.; Liu, X.; Christ, C. C.; Dicker, D. T.; Baney, T. S.; Kaifi, J. T.; Belani, C. P.; Truica, C. I.; El-Deiry, W. S.; Allerton, J. P.; Zheng, S.-Y. Flexible Micro Spring Array Device for HighThroughput Enrichment of Viable Circulating Tumor Cells. Clin. Chem. 2014, 60 (2), 323–333. Di Carlo, D. Inertial Microfluidics. Lab Chip 2009, 9 (21), 3038–3046. Zhou, R.; Chang, H.-C. Capillary Penetration Failure of Blood Suspensions. J. Colloid Interface Sci. 2005, 287 (2), 647–656. Zhou, R.; Gordon, J.; Palmer, A. F.; Chang, H.-C. Role of Erythrocyte Deformability during Capillary Wetting. Biotechnol. Bioeng. 2006, 93 (2), 201–211. Wei Hou, H.; Gan, H. Y.; Bhagat, A. A. S.; Li, L. D.; Lim, C. T.; Han, J. A Microfluidics Approach towards High-Throughput Pathogen Removal from Blood Using Margination. Biomicrofluidics. June 2012, pp 24113–24115. Hjort, Z. W. and K. Microfluidic Hydrodynamic Cell Separation: A Review. Micro and Nanosystems. 2009, pp 181–192. Sun, J.; Liu, C.; Li, M.; Wang, J.; Xianyu, Y.; Hu, G.; Jiang, X. Size-Based Hydrodynamic Rare Tumor Cell Separation in Curved Microfluidic Channels. Biomicrofluidics. January 2013. Kim, T. H.; Yoon, H. J.; Stella, P.; Nagrath, S. Cascaded Spiral Microfluidic Device for Deterministic and High Purity Continuous Separation of Circulating Tumor Cells. Biomicrofluidics 2014, 8 (6), 64117. Moon, H.-S.; Kwon, K.; Hyun, K.-A.; Sim, T. S.; Park, J. C.; Lee, J.-G.; Jung, H.-I. Continual Collection and Re-Separation of Circulating Tumor Cells from Blood Using Multi-Stage Multi-Orifice Flow Fractionation. Biomicrofluidics 2013, 7 (1), 14105. Sollier, E.; Go, D. E.; Che, J.; Gossett, D. R.; O’Byrne, S.; Weaver, W. M.; Kummer, N.; Rettig, M.; Goldman, J.; Nickols, N.; McCloskey, S.; Kulkarni, R. P.; Di Carlo, D. Size-Selective Collection of Circulating Tumor Cells Using Vortex Technology. Lab Chip 2014, 14 (1), 63–77. Dhar, M.; Wong, J.; Karimi, A.; Che, J.; Renier, C.; Matsumoto, M.; Triboulet, M.; Garon, E. B.; Goldman, J. W.; Rettig, M. B.; Jeffrey, S. S.; Kulkarni, R. P.; Sollier, E.;


Page 36 of 39

Page 37 of 39 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(134) (135)

(136)

(137)

(138)

(139)

(140)

(141)

(142)

(143)

(144)

(145)

(146)

(147)

Di Carlo, D. High Efficiency Vortex Trapping of Circulating Tumor Cells. Biomicrofluidics. November 2015. Pohl, H. A. The Motion and Precipitation of Suspensoids in Divergent Electric Fields. J. Appl. Phys. 1951, 22 (7), 869–871. Shim, S.; Stemke-Hale, K.; Tsimberidou, A. M.; Noshari, J.; Anderson, T. E.; Gascoyne, P. R. C. Antibody-Independent Isolation of Circulating Tumor Cells by Continuous-Flow Dielectrophoresis. Biomicrofluidics 2013, 7 (1), 11807. Qiao, G.; Duan, W.; Chatwin, C.; Sinclair, A.; Wang, W. Electrical Properties of Breast Cancer Cells from Impedance Measurement of Cell Suspensions. J. Phys. Conf. Ser. 2010, 224 (1), 12081. Avram, A.; Marculescu, C.; Balan, C. M.; Voitincu, C.; Pirvulescu, C.; Volmer, M.; Popescu, A.; Mihailescu, M.; Avram, M. Microbiosensor for Electrical Impedance Spectroscopic Study of Melanoma Cells. CAS 2012 (International Semiconductor Conference). 2012, pp 165–168. Han, A.; Yang, L.; Frazier, A. B. Quantification of the Heterogeneity in Breast Cancer Cell Lines Using Whole-Cell Impedance Spectroscopy. Clin. Cancer Res. 2007, 13 (1), 139–143. Shim, S.; Stemke-Hale, K.; Noshari, J.; Becker, F. F.; Gascoyne, P. R. C. Dielectrophoresis Has Broad Applicability to Marker-Free Isolation of Tumor Cells from Blood by Microfluidic Systems. Biomicrofluidics 2013, 7 (1), 11808. Avram, M.; B\ualan, C. M.; Petrescu, I.; Schiopu, V.; M\uarculescu, C.; Avram, A. Gold Nanoparticle Uptake by Tumour Cells of B16 Mouse Melanoma. Plasmonics 2012, 7 (4), 717–724. Huang, S.-B.; Chen, J.; Wang, J.; Yang, C.-L.; Wu, M.-H. A New Optically-Induced Dielectrophoretic (ODEP) Force-Based Scheme for Effective Cell Sorting; 2011; Vol. 7. Chiu, T.-K.; Chou, W.-P.; Huang, S.-B.; Wang, H.-M.; Lin, Y.-C.; Hsieh, C.-H.; Wu, M.-H. Application of Optically-Induced-Dielectrophoresis in Microfluidic System for Purification of Circulating Tumour Cells for Gene Expression Analysis- Cancer Cell Line Model. Sci. Rep. 2016, 6, 32851. Park, J. W.; Lee, N. R.; Cho, S. M.; Jung, M. Y.; Ihm, C.; Lee, D. S. Microdevice for Separation of Circulating Tumor Cells Using Embedded Magnetophoresis with vShaped Ni-Co Nanowires and Immuno-Nanomagnetic Beads. ETRI J. 2015, 37 (2), 233–240. Karabacak, N. M.; Spuhler, P. S.; Fachin, F.; Lim, E. J.; Pai, V.; Ozkumur, E.; Martel, J. M.; Kojic, N.; Smith, K.; Chen, P.; Yang, J.; Hwang, H.; Morgan, B.; Trautwein, J.; Barber, T. A.; Stott, S. L.; Maheswaran, S.; Kapur, R.; Haber, D. A.; Toner, M. Microfluidic, Marker-Free Isolation of Circulating Tumor Cells from Blood Samples. Nat. Protoc. 2014, 9 (3), 694–710. Alshareef, M.; Metrakos, N.; Juarez Perez, E.; Azer, F.; Yang, F.; Yang, X.; Wang, G. Separation of Tumor Cells with Dielectrophoresis-Based Microfluidic Chip. Biomicrofluidics 2013, 7 (1), 11803. Marchalot, J.; Chateaux, J.-F.; Faivre, M.; Mertani, H. C.; Ferrigno, R.; Deman, A.-L. Dielectrophoretic Capture of Low Abundance Cell Population Using Thick Electrodes. Biomicrofluidics 2015, 9 (5), 54104. Gradilone, A.; Naso, G.; Raimondi, C.; Cortesi, E.; Gandini, O.; Vincenzi, B.; Saltarelli, R.; Chiapparino, E.; Spremberg, F.; Cristofanilli, M.; Frati, L.; Agliano, A. M.; Gazzaniga, P. Circulating Tumor Cells (CTCs) in Metastatic Breast Cancer (MBC): Prognosis, Drug Resistance and Phenotypic Characterization. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 2011, 22 (1), 86–92.



(148) Gradilone, A.; Raimondi, C.; Naso, G.; Silvestri, I.; Repetto, L.; Palazzo, A.; Gianni, W.; Frati, L.; Cortesi, E.; Gazzaniga, P. How Circulating Tumor Cells Escape from Multidrug Resistance: Translating Molecular Mechanisms in Metastatic Breast Cancer Treatment. Am. J. Clin. Oncol. 2011, 34 (6), 625–627. (149) Chou, W.-P.; Wang, H.-M.; Chang, J.-H.; Chiu, T.-K.; Hsieh, C.-H.; Liao, C.-J.; Wu, M.-H. The Utilization of Optically-Induced-Dielectrophoresis (ODEP)-Based Virtual Cell Filters in a Microfluidic System for Continuous Isolation and Purification of Circulating Tumour Cells (CTCs) Based on Their Size Characteristics. Sensors Actuators B Chem. 2017, 241 (Supplement C), 245–254. (150) Fischer, J. C.; Niederacher, D.; Topp, S. A.; Honisch, E.; Schumacher, S.; Schmitz, N.; Zacarias Fohrding, L.; Vay, C.; Hoffmann, I.; Kasprowicz, N. S.; Hepp, P. G.; Mohrmann, S.; Nitz, U.; Stresemann, A.; Krahn, T.; Henze, T.; Griebsch, E.; Raba, K.; Rox, J. M.; Wenzel, F.; Sproll, C.; Janni, W.; Fehm, T.; Klein, C. A.; Knoefel, W. T.; Stoecklein, N. H. Diagnostic Leukapheresis Enables Reliable Detection of Circulating Tumor Cells of Nonmetastatic Cancer Patients. Proc. Natl. Acad. Sci. U. S. A. 2013, 110 (41), 16580–16585.


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For Table of Contents Use Only Manuscript title:”Detction of circulating tumor cells using microfluidics” Authors: Tiberiu A. Burinaru*, Marioara Avram, Andrei Avram, Cătălin Mărculescu, Bianca Țîncu, Vasilica Țucureanu, Alina Matei, Manuella Militaru


Detection of Circulating Tumor Cells Using Microfluidics - ACS

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