Liquid biopsy offers unique opportunities for low invasive diagnosis, real-time patient monitoring and treatment selection. The phenotypic and molecular profile of circulating tumor cells (CTCs) can provide key information about the biology of tumor cells, contributing to personalized therapy. CTC isolation is still challenging, mainly due to their heterogeneity and rarity. To overcome this limitation, a microfluidic chip for label-free isolation of CTCs from peripheral blood was developed. This device, the CROSS chip, captures CTCs based on their size and deformability with an efficiency of 70%. Using 2 chips, 7.5 ml of whole blood are processed in 47 minutes with high purity, as compared to similar technologies and assessed by in situ immunofluorescence. The CROSS chip performance was compared to the CellSearch system in a set of metastatic colorectal cancer patients, resulting in higher capture of DAPI+/CK+/CD45− CTCs in all individuals tested. Importantly, CTC enumeration by CROSS chip enabled stratification of patients with different prognosis. Lastly, cells isolated in the CROSS chip were lysed and further subjected to molecular characterization by droplet digital PCR, which revealed a mutation in the APC gene for most patient samples analyzed, confirming their colorectal origin and the versatility of the technology for downstream applications.
In the last decade the field of liquid biopsies has evolved exponentially1. The ability to isolate, detect and analyze tumor-derived material in a minimally invasive way constitutes an exciting and unique opportunity in oncology to investigate tumor dynamics and progression with time1. Circulating tumor cells (CTCs) are shed from the primary tumor into peripheral blood and have the capacity to invade other organs, causing metastasis2. In fact, CTC enumeration has been correlated with disease progression-free and overall survival in various metastatic solid tumors3,4,5. However, the applicability of CTCs in the clinic has been limited by their scarcity (1–10 CTCs/billion of blood cells) and consequently, by their technically demanding isolation. To date, several different technologies have been developed to capture CTCs6, mainly based on either physical or biological properties7,8, such as size9 or antigen expression10. Nevertheless, only the CellSearch system is currently approved by the Food and Drug Administration (FDA) for the use of CTC enumeration in a clinical setting11,12. It has been validated as a companion diagnostic tool for prognostic evaluation and therapeutic-response monitoring in patients with metastatic colorectal3, breast12 and prostate cancer13. For metastatic colorectal cancer (CRC), a cut off of ≥3 CTCs in 7.5 mL of peripheral blood has been defined, correlating to an unfavourable prognosis14. Despite the clinical utility and validation of CellSearch, its CTC enrichment methodology causes some cell loss, associated to its sample preparation process. Moreover, CellSearch selects solely CTCs expressing the epithelial cell adhesion molecule (EpCAM), likely neglecting other clinically relevant CTC phenotypes. These include mesenchymal and stem cell-like tumor cells that display low levels or totally lack EpCAM expression15. In fact, the CTC plasticity has been well documented and attributed to a developmental program designated epithelial-to-mesenchymal transition (EMT), already linked to poorer prognosis and chemoresistance16,17,18. Consequently, by capturing exclusively EpCAM+ cells, the CellSearch system only detects CTCs in up to 60% of the metastatic cancer patients19.
Other techniques based on positive enrichment, using anti-EpCAM antibodies20,21,22,23 also suffer from this limitation, despite showing high capture efficiency of epithelial CTCs. On the other hand, negative-enrichment strategies targeting unwanted blood cells8 overcome this biological constrain, but tend to display lower purity yields, hindering downstream analyses24. Furthermore, immune-based isolation approaches (positive or negative) require relatively long incubation times (1–8 ml/h) to allow for antigen-antibody interaction20,25. Alternatively, label-free approaches based on size exclusion mechanisms have been suggested26,27, but sample loss, leukocyte contamination or clogging are frequently a problem28,29. The enrichment capacity of these systems is limited to CTCs that display a large diameter in comparison with white blood cells (WBCs), hence losing the smaller CTC population. Diverse 2D and 3D microfilters have been designed30,31,32,33,34 and even combined with blood pre-processing using Ficoll35 or beads36, with higher throughput than in positive immune-selection systems6. However, the purity of isolated cells remains the major obstacle of filtration-based methods.
Microfluidics has emerged as a low cost alternative to traditional cell isolation technologies, demonstrating superior sensitivity and enhanced cell recovery20,37. Furthermore, it reduces costs by requiring small sample and reagent volumes, and avoids sample-processing steps, lowering cell loss38,39. More importantly, all these features can be combined with high-throughput processing, portability and automation, greatly relevant in clinical settings. Microfluidic enrichment of CTCs can be implemented through positive20,23,40 or negative-immune selection25,41. Yet, as described using benchtop methodologies, the former depends on specific antigen expression and prior knowledge of CTC biomarkers, whereas the latter bypasses CTC heterogeneity but suffers from low throughput. Numerous positive selection microfluidic chips with various geometries and architectures, have been demonstrated to exhibit over 90% of capture efficiency, but only after tedious sample pre-processing steps6.
The distinct physical characteristics between CTCs and blood cells, such as size, deformability, density and electrical properties, have also been explored to successfully isolate and enrich CTCs using microfluidic chips. These label-free approaches offer faster processing of high volume samples and do not bias the cell selection, while reducing even further reagent-associated costs. Recent technology advancements include the use of hydrodynamic forces, inertial focusing, acoustic waves or dielectrophoresis to separate different cell populations based on their size6,42,43,44.
In this report, we present the development and pre-clinical validation of a high-throughput microfluidic cell filter, able to efficiently and rapidly isolate CTCs with high purity, directly from unprocessed whole blood of metastatic CRC patients, using a label-free approach. This system allows the isolation of CTCs based on their size and deformability, and also the in situ phenotypical characterization of trapped cells, together with their downstream molecular analysis. In addition, we compared the performance of our device against the gold standard CellSearch system, showing higher sensitivity and suggesting a new cut-off for patient stratification.
CROSS chip performance in spiked samples
Aiming at isolating all CTCs directly from unprocessed blood samples, a label-free microfluidic system for cell capture based on their size and deformability, the CROSS chip, was developed (Fig. 1A–D). The performance of the CROSS chip was investigated using SW480 colorectal cancer cells spiked in whole blood from healthy donors. To achieve the best isolation efficiency in whole blood samples, while maintaining the lowest level of false positives, the flow rate was optimized at 80 μl/min. Notably, the device is able to isolate in average 70% of spiked SW480 colorectal cancer cells, while depleting greatly the WBC population (99.99%), hence maintaining a very high purity (7.2%) (Fig. 1E). This strategy allows fast sample processing, i.e., 7.5 ml of whole blood are processed in 47 min using 2 CROSS chips simultaneously, avoiding potential sample loss and tedious sample preparation procedures.
Comparative analysis: Isolation of CTCs by CROSS chip versus CellSearch
Considering the good performance of the CROSS chip in spiking experiments, we next moved to its pre-clinical testing. 7.5 ml blood samples from metastatic CRC patients were collected, split in half, loaded in two syringes, and run simultaneously in two CROSS chips. In parallel, another set of 7.5 ml blood samples from the same individuals were collected simultaneously and subjected to CellSearch test. Immunofluorescence staining was used to identify captured CTCs in the CROSS chips, by detecting nucleated, morphologically intact DAPI+/CK+/CD45− cells. Importantly, cells positive for Vimentin and negative for CD45, as well as CK+/CD45− cell clusters were also observed retained in the CROSS device, but not considered for CTC enumeration (Fig. 2). Of note, 7 out of 9 patient samples analyzed showed ≥3 CTCs/7.5 ml of whole blood (mean value = 20.28 ± 14.3) by the CROSS chip. In contrast, none of the patients scored ≥3 CTCs/7.5 ml of whole blood by CellSearch (Fig. 3). No CTCs were detected in the blood of two healthy donors using the CROSS chip.
Detection of APC mutations in CTCs isolated with the CROSS chip, by ddPCR
In order to evaluate the origin of the cells isolated using the CROSS chip, CTCs were screened for the most common DNA mutation of the APC gene (c.4348C > T), which is highly frequent in CRC patients. Due to the limited amount of starting genetic material available, this analysis was performed by ddPCR. This APC mutation was found in 7 out of the 9 patients analyzed, which confirmed the tumor origin of the cells isolated by the CROSS chip (Fig. 4).
Clinical data correlation and overall survival
The number of CTCs enumerated by the CellSearch test was less than 3 CTCs/7.5 ml of whole blood for all samples analyzed (Fig. 3), i.e, below the established cut off for CRC using the CellSearch technology. Considering these data, patients could not be divided in different prognostic groups and all were classified as having good prognosis. However, with the CROSS chip, the CTC number obtained was higher in every patient and thus a possible correlation between CTC enumeration and disease prognosis was investigated. Patients were grouped in good or bad prognosis according to the number of isolated CTCs by the microfluidic device and using the cut-off value defined by CellSearch (<or ≥3 CTCs/7.5 ml of whole blood respectively). As illustrated in Fig. 5A, and according to a Kaplan Meier analysis with a 95% CI, a clear trend for shorter overall survival was observed for patients with ≥3 CTCs/7.5 ml of whole blood than those with <3 CTCs/7.5 mL blood, although not statistically significant (p = 0.3812). Remarkably, defining an alternative cut off of ≥7 CTCs/7.5 ml of whole blood, the CROSS chip is able to discriminate patients with good prognosis from those facing an unfavorable outcome (CTCs ≥ 7) (p = 0.0049), with a greater survival of 242 days (Fig. 5B).
The molecular characterization of a tumor, typically performed on a tissue biopsy, can help therapeutic reasoning and significantly impact the disease outcome. However, tumor heterogeneity and fast evolving dynamics can lead to genetic alterations, making clinical decisions based on historical biopsy data suboptimal45. Additionally, tissue biopsies are invasive and not always available, in contrast to CTC-based liquid biopsies. Unraveling the molecular profile of CTCs can provide key information into the biology of the tumor cells and thus improve personalized therapy2. However, the use of CTCs as a clinical biomarker is still on hold, given their extremely low frequency and great plasticity46,47, making CTC isolation technically challenging. Numerous approaches have been developed to capture these rare cells2,6,42, but with disparate results mostly due to ambiguous CTC classification criteria and lack of standard sample preparation protocols11. In this work, the CROSS microfluidic filter was developed aiming at rapid and unbiased isolation of unfixed CTCs with high efficiency and purity. This system was tested in a clinical setting and compared to CellSearch using a panel of metastatic CRC patients. Lastly, cells isolated using the CROSS device were screened for the presence of a specific mutation of the APC gene, highly frequent in CRC patients, to confirm their malignant origin.
To assess the performance of the CROSS chip, spiking experiments were carried out, demonstrating a high capture efficiency (70%) and purity (7.2%), when using whole blood, in contrast to several size-based technologies that display efficiencies of 40–60%48,49,50. Improved recoveries (up to 95%) have been reported by other label-free methodologies, but using pre-fixed cells51, long processing times52,53, RBC-depleted54,55 or diluted blood56 which favor sample loss. The Vortex chip, currently commercially available (Vortex Biosciences), demonstrated high purity (57–94%) but low capture efficiency (up to 37%) of spiked MCF7 breast cancer cells when using diluted blood57,58. On the other hand, the ApoStream (ApoCell) was reported to capture up to 75% of spiked renal tumor cells SKOV3 with only 1% purity in processed blood59. Warkiani and colleagues showed recoveries of spiked cells around 85% and high depletion of WBCs (99%) for lysed blood samples processed in a curvilinear microchannel chip60, now commercialized as the ClearCell FX system (Clearbridge Biomedics). Still, a wide variability in CTC purity was also observed (0.1–86%)54. Other commercial microfiltration systems have been reported, such as ScreenCell (ScreenCell)27 and CellSieveTM (Creatv MicroTech)34 which offer higher throughput (>5 ml/min)42 than the CROSS chip. Yet, cell damage, low CTC recoveries and filter clogging are major concerns of mechanical filtration devices given their high flow rate and filtration pressure28,30. Notably, all systems described above require sample pre-processing and struggle to discriminate CTCs from WBCs of larger size, often rendering poor isolation of small CTCs or large amount of WBC contamination61. To solve this issue, cell deformability can be further explored to discriminate CTCs from similarly sized leukocytes. In this context, capture efficiency rates of 62.5% or higher (>80%) together with minimal leukocyte contamination, have been shown with an optimization of the ParsortixTM (ANGLE) platform48 or the CellseeTM (Celsee Diagnostics) device51, using diluted or pre-fixed blood samples spiked with prostate or breast cancer cells, respectively. When using Parsortix and whole blood, capture efficiencies reached up to 70%, similar to that obtained in this work, but only for large size cells (>20 µm)62. Instead, with the T-24 bladder cancer cell line (average cell diameter of 18 µm) cell retention dropped to 42%62. Moreover, Parsortix, which has a size-restricted separation gap of 10 µm, was limited to running 4 ml of whole blood with a relatively slow sample processing speed62, in contrast to the 5 µm-gap of the CROSS chip that processes 7.5 ml in just 47 min. Further systems have shown good ability at isolating CTCs from whole blood, as reported using the Labyrinth chip, which in a double run isolates 91% of CTCs while retaining 663 WBCs per ml analyzed63.
Our geometry, combined with our surface treatment, makes for large aspect ratio slippery filters that favor CTC entrapment, while even large white blood cells can be eliminated, reaching a compromise between efficiency, speed and purity. This is due to our anisotropic 5 μm wide/20 μm high filters that, while having smaller width than other filtration-based systems, allow the cells to deform in the vertical axis and squeeze through, retaining only cells which nucleus cannot deform, favoring the trapping of larger cells with high nucleus to cytoplasm ratio. Having just one filtering row prevents air bubble formation inside the device and pre-filters layout avoids clogging that usually takes place when processing whole blood. Although cytomorphological differences in cultured cancer cells and patient derived-CTCs have been acknowledged for prostate cancer64, with CTCs being considerably smaller, others have shown that the SW480 cells used in this study are appropriate models to investigate size-based CTCs enrichment systems, as their median diameter (11–13 μm) is very similar to that of colorectal CTCs (11 μm, as found by CellSearch)65. Additionally, the filter size of the CROSS chip is smaller (5 μm) than most systems previously reported33, including the commercially available ISET (Rarecells; 8 μm)26, ScreenCell (ScreenCell; 6.5 or 7.5 μm)27 and SmartBiopsyTM (CytoGen; 6.5 × 6.5 μm2 square pore)66. Hence, it has the potential to retain even smaller/more deformable CTCs, as is the case of mesenchymal and stem-cell-like CTCs67. This is in agreement with a recent report that uses a similar architecture for selective CTC isolation and reports on the presence of circulating cancer stem cells68.
Preclinical validation of our system was next pursued through a comparative blind study between the CROSS chip and CellSearch test, the gold standard for CTCs enumeration in clinical settings. Importantly, whole blood samples were introduced and filtered directly in the CROSS chip, avoiding sample pre-processing steps performed by numerous CTC isolation techniques including CellSearch6,51,69. Notably, using 2 CROSS chips we were able to rapidly (in 47 minutes) process whole blood samples from a set of metastatic CRC patients, and capture a higher number of CTCs than CellSearch in all individuals analyzed, which further reinforces the clinical potential of this system. Immunofluorescence staining of trapped cells corroborated a high capture efficiency and purity of CTCs. The total number of CTCs identified in the CROSS chips was further verified and validated by a technical expert routinely involved in the analysis of CellSearch data. Of the nine patient samples analyzed using CellSearch, all patients were classified as having good prognosis, since the CTC count was below the cut off. Nonetheless, four of the nine samples (44%) had CTCs only detectable by the CROSS chip. As for the other five samples, a great discrepancy was observed in CTC enumeration, with CellSearch reporting 1–2 CTCs and the CROSS chip ranging from 2–40 CTCs (average 19.8 CTCs). These results suggest that the isolation of epithelial CTCs using the CROSS chip is more efficient (p = 0.0039) and sensitive than CellSearch. Interestingly, Vimentin+/CD45− cells were also found retained in the CROSS device, indicating entrapment of not just epithelial-like CTCs but also cells with different phenotypes. When accounted for, this will increase even further the number of isolated CTCs and provide additional information of the disease. In fact, a recent study using Parsortix described the isolation of mesenchymal-like prostate CTCs, whose number correlated with worse prognosis70. Other microfluidic systems, such as the Vortex HT chip49, Parsortix48 and Labyrinth63 have also reported the capture of heterogeneous CTC subpopulations expressing epithelial, mesenchymal, EMT and/or cancer stem cell markers. The capacity of the CROSS device to isolate not only single CTCs but also CTC clusters, similarly to other systems such as Parsortix48 and ClearCell FX60, holds great potential as the later have been correlated with higher invasive capacity71.
In the scope of the comparative study herein presented, considering the established cut off for bad prognosis in CRC used by the CellSearch technology – i.e. ≥3 CTCs/7.5 ml of whole blood –, the results obtained by CellSearch were negative for all the patients analyzed. In contrast, due to the higher sensitivity, the results obtained with the CROSS chip suggest a new cut off (≥7 CTCs/7.5 ml of whole blood) that stratifies the patients in 2 very well defined populations with overall survival differences higher than 200 days. Yet, further studies on larger cohorts of patients are required to clarify the clinical relevance of this method for CRC monitoring and characterization.
Following CTC isolation, it is of outmost importance to characterize the isolated cells and confirm their tumor origin. Furthermore, this molecular and phenotypic characterization would provide clinically relevant information and be of great utility for therapeutic reasoning. Importantly, the CROSS chip allows downstream molecular analysis of the trapped cells (ddPCR, qPCR, etc), with increased sensitivity given the sample purity, as compared to other technologies6. To confirm the malignant origin of the cells isolated by the CROSS chip, the mutational status of APC, a tumor suppressor gene that regulates cell cycle and WNT signaling, was evaluated. This is the first time that APC status is described in CTCs isolated by a microfluidic system. For that, we selected a somatic non-sense mutation with high frequency of mutation among patients population. APC is the most frequently mutated gene in sporadic CRC, affecting up to 60% of CRC patients72,73,74,75. Moreover, a strong association between mutations in APC and other genes such as KRAS or BRAF and colon cancer initiation has in fact been established69,76,77,78,79. In addition, the APC gene has been linked to tumor initiation and the frequency of mutation is maintained by the passage of benign to malignant tumors80. Some authors suggested that the APC mutation has a relevant role in providing a selective advantage, through the activation of the Wnt signal transduction pathway and the chromosomal instability in the tumor cell81. Notably, APC mutations were detected in CROSS chip-isolated CTCs from 7 out of 9 patients, by ddPCR, even using DNA amounts as low as 0,065 ng/µl. Indeed, ddPCR technique has demonstrated superior sensitivity to detect clinically relevant mutations at very low concentration in liquid biopsies from patients with different malignancies82,83. Thus, our findings are in agreement with the overall frequency of APC mutation in CRC84. Nevertheless, false-negative results cannot be ruled out due to the low amount of starting DNA. A recent work confirmed that in all CRC patients analyzed, the mutational status of APC in both CTCs and the primary tumor matched, with 60% concordance85. However, to the best of our knowledge this is the first study reporting the analysis of APC alterations by ddPCR in CTCs isolated from CRC patients. In a similar study, APC mutations were investigated in circulating DNA using the BEAMing technology and were detected in >60% of CRC patients86. On an additional note, CRC-derived CTCs isolated by the ScreenCell size-based device have also been screened for mutations in the KRAS gene using ddPCR, which were observed in 57% of the cases87. In fact, ddPCR is commonly used for ctDNA analysis in oncology and, for example, KRAS is analyzed in the clinical routine as it conditions treatment selection for the patients who present KRAS mutation.
In summary, although several CTC isolation systems have been described and a fraction even reached commercialization as automated platforms42, it should be considered that validation with clinical samples has not always been performed88,89. The blood of a cancer patient shows different features compared to that of a healthy donor regarding density or clotting, influencing cell isolation performance of the technologies under investigation. Furthermore, of those studies including patient samples, not all performed a comparison with the only FDA-approved technology CellSearch66, crucial to provide an estimated number of captured CTC for each sample, as a positive control. The CROSS chip described herein displayed higher sensitivity than the gold standard, without the need of any sample pre-processing, while allowing downstream molecular analysis, key in a clinical setting. The versatility of this low cost device is further demonstrated by its ability to process blood straight after drawing or more than 24 h post collection.
Besides allowing phenotypic and molecular characterization of captured cells, further advantages of the CROSS chip include easy cell recovery in a very small volume (the internal volume of the system is below 100 μl), by simply inverting the flow and without inducing significant cell damage, particularly important for cell culturing and further downstream applications. This particularity, can enhance the possibilities to establish CTC cultures, which has been to date challenging due mainly to low cell density90. Also, the CROSS chip can be used for the study of other cancer types, particularly in diseases where the scarcity of epithelial-like CTCs hinders the applicability of CellSearch. Moreover, the simple setup and protocol used, allows for the deployment of this system in any research or pathology laboratory without the need of any special equipment, and only requiring a syringe pump for CTC isolation.
The CROSS chip has shown limitations in volume capacity but, due to the inner multiplex capacity of the microfluidic systems, it is possible to redesign the system and increase the surface area of the device to analyze higher volumes of whole blood in the same or even less time, having undeniable potential for early cancer diagnosis. Also, further developments will integrate the design in an all-in-one system just comprising a single outlet in a smaller glass slide to facilitate image acquisition. Even though recent studies have shown microfluidic chips able to isolate CTCs with outstanding efficiency and purity from unprocessed blood samples63, our latest tests have indicated that the analysis of fresh samples renders higher isolation yields and better quality of the samples, as expected91.
From this work we can conclude that the CROSS chip is able to rapidly isolate unfixed CTCs from whole blood with high efficiency and purity, while enabling CTC recovery. Importantly, it shows higher sensitivity than CellSearch when isolating CTCs from metastatic CRC patients, capturing a higher number of cells, even in samples considered negative by the gold standard. The findings obtained suggest that the CROSS chip may allow a better discrimination of patients with poorer prognosis, highlighting its potential as a powerful tool for liquid biopsy studies in CRC and other types of cancer. Moreover, ddPCR confirmed the tumor origin of the isolated cells, and paves the way for further molecular downstream analysis.
Microfluidic device design and fabrication
The CROSS microdevice was designed to split the blood equally in 4 different modules (Fig. 1A). Each module is able to process a maximum of 1 ml of whole blood and contains a set of pre-filters and cell isolation filters (Fig. 1B). Across the middle section of each module, a single row of 700 anisotropic micropillars with diameter 25 μm and spaced 5 μm constitutes the cell filtering area (Fig. 1C). The gap size, geometry and aspect ratio was carefully chosen to allow blood cells to deform and gently flow through, while retaining larger or more rigid cells in the filter. The pre-filters present 120 μm gaps to prevent large clumps or debris from clogging the setup (Fig. 1D). Each microdevice holds an approximate volume of 100 μl. Cells can be retrieved from the system by simply inverting the flow. Surface coating is decisive in both cell isolation and retrieval, as it is crucial to prevent cell attachment to maximize cell purity and recovery.
The microfluidic masters were designed in 2D AutoCAD software (Autodesk, USA) and fabricated on a 200 mm silicon wafer using photolithography and deep reactive ion etching. Briefly, the silicon wafer (P/Boron, <100>, Siegert Wafer, Germany) was rinsed with deionized water, dehydrated at 150 °C and exposed to hexamethyldisilazane (HDMS, Sigma Aldrich, USA) vapour prime to improve the adhesion of the photoresist to the sample. Later, the wafer was spun coated with 2.2 μm of AZP4110 (Microchemicals GmbH, Germany), using a SÜSS MicroTec optical track (SÜSS MicroTec AG, Germany). The pattern was transferred onto the coated wafer using a Direct Write Laser system (DWL 2.0 Heidelberg, Germany) with an Hg laser energy of 95% and focus −50. Following the post bake, the exposed photoresist was developed with AZ400K (Microchemicals GmbH, Germany), and the wafer was rinsed with deionized water and dried. The pattern was then etched with sulfur hexafluoride (SF6, Sigma Aldrich, USA) by Silicon Deep Reactive Ion Etching (STPS Pegasus, United Kingdom), and exposed areas passivated with octafluorocyclobutane (C4F8, Sigma Aldrich, USA). Trench depth was measured in between steps using an optical profilometer (OPM profilometer, Oceon Optics NanoCalc XR) until the desired depth of 20 μm was reached. Residues were stripped using oxygen plasma and the master was characterized by means of Scanning Electron Microscopy (Quanta SEM, FEI, USA). Finally, the wafer was diced into the individual masters using a DAD 3350 Dicing Saw (Disco, Japan) and cleaned with Isopropyl alcohol (IPA, Sigma Aldrich, USA), rinsed with deionized water and dried at 150 °C on a hot plate.
Prior to master replication, the wafer was hydrophobized with a vapor-phase treatment in trichloro(1H,1H,2H,2H-perfluorooctyl)silane (Sigma Aldrich, USA) for 1 h in a desiccator, and cured for another hour at 65 °C. Polydimethylsiloxane (PDMS, Ellsworth Adhesives Iberica, Spain) was mixed at 1:10 ratio, degassed, poured over the master, degassed again and cured at 70 °C for 2 h. After curing, the PDMS was unmolded and inlet and outlets were punched. Finally, clean glass slides and PDMS replicas were treated with oxygen plasma at low power for 15 s and subsequently brought in contact to produce irreversible bonding.
Upon activation with oxygen plasma, the microfluidic devices were connected to a syringe pump and filled with ethanol at 100 μl/min to enhance the wettability; then rinsed with 10 mM Phosphate Buffer Saline (PBS, Sigma Aldrich, USA), and later treated with 1% Pluronic F-127 (Sigma Aldrich, USA) overnight to avoid unspecific attachment of cells onto the channel surface. Considering its cross-shaped design, this CTC isolation device has been designated CROSS chip.
Cell culture and spiking experiments
The human colorectal cancer cell line SW480 was obtained from ECACC in 2014 and cultured in DMEM (Lonza, Switzerland), supplemented with 10% fetal bovine serum (Invitrogen, USA) and 1% Penicillin/Streptomycin (Invitrogen, USA) at 37 °C with 5% CO2. Cells were authenticated and tested for mycoplasma by ECACC and passaged 2–3 times before being aliquoted and stored in liquid nitrogen. No new cell line authentication or mycoplasma testing were performed for thawed cells, passaged for <6 months. When reaching confluence, cells were harvested by incubation in 0.25% Trypsin-EDTA (Invitrogen, USA), washed with PBS and labeled with 12.5 μM Calcein-AM (Sigma Aldrich, USA) according to the manufacturer’s protocol. 100 cells were then spiked in 3.75 mL of whole blood collected from healthy donors and injected at 80 μl/min in the CROSS chip with a syringe pump (New Era Pump Systems, Inc., USA). Trapped cells were rinsed with PBS-2% Bovine Serum Albumin (BSA, Sigma Aldrich, USA), fixed with 4% paraformaldehyde (PFA, Sigma Aldrich, USA) for 15 min at room temperature (RT), stained with 1:10000 DAPI (Sigma Aldrich, USA) for 10 min, and washed again with PBS. Following spiked sample processing, a fluorescence microscopy analysis of the trapped cells was performed using a plan fluor 20x objective (Nikon, Spain) coupled to a fluorescence-adapted inverted Nikon-MA 200 microscope (Nikon, Spain) equipped with a sCMOS camera (Andor Neo scc-01633, Andor Technology Ltd, Ireland). To assess the isolation efficiency of the CROSS chip, the number of Calcein+/DAPI+ cells trapped in the device was compared with the total number of SW480 cells spiked, according to Eq. (1). At the same time, the capacity of the system to deplete the WBC population was calculated by comparing the total number Calcein−/DAPI+ events against the theoretical amount of WBCs in the total volume of blood analyzed (7.5 × 106 WBCs/ml), according to Eq. (2). Finally, the purity of the cell population isolated in the system was determined using Eq. (3). Experiments were done in triplicate.
Patient sample collection
Metastatic CRC patients, median age 72.44 years, were recruited at the Medical Oncology Department from the University Hospital Complex of Santiago de Compostela, Spain. Clinicopathological characteristics of the patients are summarized in Table 1. Two 7.5 mL samples of peripheral blood were collected in a CellSave preservative tube (CellSearch, Janssen Diagnosis, USA –now owned by Menarini-Silicon Biosystems, Italy-) and in an EDTA-coated tube, respectively, after informed consent and following the approval and recommendations of the Ethics Committee of Galicia (CAEI2014/126). For control purposes, peripheral blood from healthy donors was collected in EDTA-coated tubes after informed consent. All samples were anonymized and encoded before the analysis.
Patient sample analysis
CellSearch results analysis was performed by the Liquid Biopsy Analysis Unit of the University Hospital Complex of Santiago de Compostela, Spain, as previously described92. Whole blood samples to be analyzed in the CROSS chip were collected in EDTA-coated tubes before or after treatment onset, shipped at RT and processed the day after collection. Each EDTA tube containing 7.5 ml of whole blood was divided in half and 3.75 ml processed in each of two CROSS chips, as in the spiking experiments.
Immunofluorescence and CTC enumeration in the CROSS chip
Isolated cells from patient samples were permeabilized with 0.25% Triton X-100 solution (Sigma Aldrich, USA) and fluorescently labeled inside the microfluidic device with anti-pan CK-FITC (clone C-11, recognizes human cytokeratins 4,5,6,8,10,13, and 18, Sigma; 1:100 in PBS-2% BSA), anti-Vimentin eFluor 570 (eBioscience, 1:50 in PBS-2%BSA) and anti-CD45-Cy5 (Abcam; 1:25 in PBS-2%BSA) antibodies for 1 h. DAPI (Sigma Aldrich, 1:1000 in PBS-2%BSA) was used as a nuclear marker. Fluorescence microscopy analysis was performed using the same setup as described in the cell culture and spiking experiments sub-section. Only DAPI+/CK+/CD45− cells were considered for CTCs enumeration, whereas DAPI+/CK−/CD45+ represented leukocytes. CTC quantification was performed adding the number of cells isolated in the 2 CROSS chips used for each analysis, with blind scoring and by 3 different experienced examiners. The ability of the CROSS device to isolate epithelial-mesenchymal (EMT) or mesenchymal-epithelial (MET) transitioning CTCs was evaluated by confirming the presence of DAPI+/Vim+/CD45− cells.
DNA extraction and ddPCR analysis
Extraction of genomic DNA from cells retained in the microfluidic devices was performed using AllPrep DNA/RNA Mini Kit (Qiagen, USA). Firstly, cells were lysed upon injection of a lysis buffer (Buffer RLT) at 80 µl/min followed by 5 min incubation and a second injection of the same buffer at 250 µL/min to collect all cell content. Subsequent steps were performed according to the manufacturer’s recommendations. Quantification of the extracted genomic DNA was performed with the Quantifluor ONE dsDNA System using Quantus Fluorometer (Promega, USA).
Absolute quantification of APC transcript was performed by ddPCR analysis (QX200™ Droplet Digital™ PCR System, Bio-Rad, USA) at the Universitat Autònoma de Barcelona (UAB) Scientific Technical Services (Barcelona, Spain). Prior to quantification, samples were digested (HaeIII, Sigma-Aldrich, USA) and preamplified (Sso Advanced Preamp Supermix, Bio-Rad, USA). ddPCR experiments were performed using probes dHsaCP2500509 and dHsaCP2500508 for APC. The droplets were quantified using the Bio-Rad Quantisoft software. Two replicates per sample were performed.
Statistical analysis was performed using GraphPad Prism software, version 6.01 (GraphPad Software, USA). The Wilcoxon signed rank test (95% confidence intervals) was used to compare CTC enumeration using CellSearch test versus the CROSS filter from the same metastatic patient, whereas Kaplan Meier method was used for survival analysis from time of sample collection. Findings of p < 0.05 were considered statistically significant.
The datasets generated during and/or analysed during the current study are not publicly available, being now exclusively licenced to a for-profit company, but are available from the corresponding author on reasonable request.
Siravegna, G., Marsoni, S., Siena, S. & Bardelli, A. Integrating liquid biopsies into the management of cancer. Nature Reviews Clinical Oncology 14, 531, https://doi.org/10.1038/nrclinonc.2017.14 (2017).
Alix-Panabieres, C. & Pantel, K. Challenges in circulating tumour cell research. Nat Rev Cancer 14, 623–631, https://doi.org/10.1038/nrc3686 (2014).
Cohen, S. J. et al. Relationship of Circulating Tumor Cells to Tumor Response, Progression-Free Survival, and Overall Survival in Patients With Metastatic Colorectal Cancer. Journal of Clinical Oncology 26, 3213–3221, https://doi.org/10.1200/jco.2007.15.8923 (2008).
Liu, M. C. et al. Circulating Tumor Cells: A Useful Predictor of Treatment Efficacy in Metastatic Breast Cancer. Journal of Clinical Oncology 27, 5153–5159, https://doi.org/10.1200/JCO.2008.20.6664 (2009).
Wallwiener, M. et al. Serial enumeration of circulating tumor cells predicts treatment response and prognosis in metastatic breast cancer: a prospective study in 393 patients. BMC Cancer 14, 512, https://doi.org/10.1186/1471-2407-14-512 (2014).
Jackson, J. M., Witek, M. A., Kamande, J. W. & Soper, S. A. Materials and microfluidics: enabling the efficient isolation and analysis of circulating tumour cells. Chemical Society Reviews 46, 4245–4280, https://doi.org/10.1039/C7CS00016B (2017).
Tadimety, A. et al. Liquid biopsy on chip: a paradigm shift towards the understanding of cancer metastasis. Integrative Biology 9, 22–49, https://doi.org/10.1039/C6IB00202A (2017).
Ferreira, M. M., Ramani, V. C. & Jeffrey, S. S. Circulating tumor cell technologies. Molecular Oncology 10, 374–394, https://doi.org/10.1016/j.molonc.2016.01.007 (2016).
Low, W. S. & Wan Abas, W. A. B. Benchtop Technologies for Circulating Tumor Cells Separation Based on Biophysical Properties. BioMed Research International 2015, 22, https://doi.org/10.1155/2015/239362 (2015).
Chen, P., Huang, Y.-Y., Hoshino, K. & Zhang, X. Multiscale immunomagnetic enrichment of circulating tumor cells: from tubes to microchips. Lab on a Chip 14, 446–458, https://doi.org/10.1039/C3LC51107C (2014).
Andree, K. C., van Dalum, G. & Terstappen, L. W. M. M. Challenges in circulating tumor cell detection by the CellSearch system. Molecular Oncology 10, 395–407, https://doi.org/10.1016/j.molonc.2015.12.002 (2016).
Cristofanilli, M. et al. Circulating Tumor Cells, Disease Progression, and Survival in Metastatic Breast Cancer. New England Journal of Medicine 351, 781–791, https://doi.org/10.1056/NEJMoa040766 (2004).
de Bono, J. S. et al. Circulating Tumor Cells Predict Survival Benefit from Treatment in Metastatic Castration-Resistant Prostate Cancer. Clinical Cancer Research 14, 6302–6309, https://doi.org/10.1158/1078-0432.ccr-08-0872 (2008).
Cohen, S. J. et al. Prognostic significance of circulating tumor cells in patients with metastatic colorectal cancer. Annals of Oncology 20, 1223–1229, https://doi.org/10.1093/annonc/mdn786 (2009).
Yu, M. et al. Circulating Breast Tumor Cells Exhibit Dynamic Changes in Epithelial and Mesenchymal Composition. Science (New York, N.Y.) 339, 580–584, https://doi.org/10.1126/science.1228522 (2013).
Kalluri, R. & Weinberg, R. A. The basics of epithelial-mesenchymal transition. The Journal of Clinical Investigation 119, 1420–1428, https://doi.org/10.1172/JCI39104 (2009).
Fischer, K. R. et al. Epithelial-to-mesenchymal transition is not required for lung metastasis but contributes to chemoresistance. Nature 527, 472, https://doi.org/10.1038/nature15748 (2015).
Zheng, X. et al. Epithelial-to-mesenchymal transition is dispensable for metastasis but induces chemoresistance in pancreatic cancer. Nature 527, 525, https://doi.org/10.1038/nature16064 (2015).
Allard, W. J. et al. Tumor Cells Circulate in the Peripheral Blood of All Major Carcinomas but not in Healthy Subjects or Patients With Nonmalignant Diseases. Clinical Cancer Research 10, 6897–6904, https://doi.org/10.1158/1078-0432.ccr-04-0378 (2004).
Nagrath, S. et al. Isolation of rare circulating tumour cells in cancer patients by microchip technology. Nature 450, 1235–1239 (2007).
Pluim, D., Devriese, L. A., Beijnen, J. H. & Schellens, J. H. M. Validation of a multiparameter flow cytometry method for the determination of phosphorylated extracellular-signal-regulated kinase and DNA in circulating tumor cells. Cytometry Part A 81A, 664–671, https://doi.org/10.1002/cyto.a.22049 (2012).
Stott, S. L. et al. Isolation of circulating tumor cells using a microvortex-generating herringbone-chip. Proceedings of the National Academy of Sciences 107, 18392–18397, https://doi.org/10.1073/pnas.1012539107 (2010).
Harb, W. et al. Mutational Analysis of Circulating Tumor Cells Using a Novel Microfluidic Collection Device and qPCR Assay. Translational Oncology 6, 528-IN521, https://doi.org/10.1593/tlo.13367 (2013).
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. Experimental Hematology 32, 891–904, https://doi.org/10.1016/j.exphem.2004.07.007 (2004).
Ozkumur, E. et al. Inertial Focusing for Tumor Antigen–Dependent and –Independent Sorting of Rare Circulating Tumor Cells. Science Translational Medicine 5, 179ra147–179ra147, https://doi.org/10.1126/scitranslmed.3005616 (2013).
Vona, G. et al. Isolation by size of epithelial tumor cells: a new method for the immunomorphological and molecular characterization of circulating tumor cells. The American Journal of Pathology 156, 57–63, https://doi.org/10.1016/S0002-9440(10)64706-2 (2000).
Desitter, I. et al. A New Device for Rapid Isolation by Size and Characterization of Rare Circulating Tumor Cells. Anticancer Research 31, 427–441 (2011).
Zhou, M.-D. et al. Separable Bilayer Microfiltration Device for Viable Label-free Enrichment of Circulating Tumour Cells. Scientific Reports 4, 7392, https://doi.org/10.1038/srep07392 (2014).
Farace, F. et al. A direct comparison of CellSearch and ISET for circulating tumour-cell detection in patients with metastatic carcinomas. British Journal of Cancer 105, 847–853, https://doi.org/10.1038/bjc.2011.294 (2011).
Zheng, S. et al. 3D microfilter device for viable circulating tumor cell (CTC) enrichment from blood. Biomedical microdevices 13, https://doi.org/10.1007/s10544-10010-19485-10543, https://doi.org/10.1007/s10544-010-9485-3 (2011).
Tang, Y. et al. Microfluidic device with integrated microfilter of conical-shaped holes for high efficiency and high purity capture of circulating tumor cells. Scientific Reports 4, 6052, https://doi.org/10.1038/srep06052 (2014).
Lim, L. S. et al. Microsieve lab-chip device for rapid enumeration and fluorescence in situ hybridization of circulating tumor cells. Lab on a Chip 12, 4388–4396, https://doi.org/10.1039/C2LC20750H (2012).
Dolfus, C., Piton, N., Toure, E. & Sabourin, J.-C. Circulating tumor cell isolation: the assets of filtration methods with polycarbonate track-etched filters. Chinese Journal of Cancer Research 27, 479–487, https://doi.org/10.3978/j.issn.1000-9604.2015.09.01 (2015).
Adams, D. L. et al. The systematic study of circulating tumor cell isolation using lithographic microfilters. RSC advances 9, 4334–4342, https://doi.org/10.1039/C3RA46839A (2014).
Xu, T., Lu, B., Tai, Y.-C. & Goldkorn, A. A cancer detection platform which measures telomerase activity from live circulating tumor cells captured on microfilter. Cancer research 70, 6420–6426, https://doi.org/10.1158/0008-5472.CAN-10-0686 (2010).
Kim, M. S. et al. SSA-MOA: a novel CTC isolation platform using selective size amplification (SSA) and a multi-obstacle architecture (MOA) filter. Lab on a Chip 12, 2874–2880, https://doi.org/10.1039/C2LC40065K (2012).
Dong, Y. et al. Microfluidics and Circulating Tumor Cells. The Journal of Molecular Diagnostics 15, 149–157, https://doi.org/10.1016/j.jmoldx.2012.09.004 (2013).
Hyun, K.-A. & Jung, H.-I. Advances and critical concerns with the microfluidic enrichments of circulating tumor cells. Lab on a Chip 14, 45–56, https://doi.org/10.1039/C3LC50582K (2014).
Whitesides, G. M. The origins and the future of microfluidics. Nature 442, 368–373 (2006).
Gleghorn, J. P. et al. Capture of circulating tumor cells from whole blood of prostate cancer patients using geometrically-enhanced differential immunocapture (GEDI) and a prostate specific antibody. Lab on a chip 10, 27–29, https://doi.org/10.1039/b917959c (2010).
Dieguez, L., Winter, M. A., Pocock, K. J., Bremmell, K. E. & Thierry, B. Efficient microfluidic negative enrichment of circulating tumor cells in blood using roughened PDMS. Analyst 140, 3565–3572, https://doi.org/10.1039/C4AN01768D (2015).
Cho, H. et al. Microfluidic technologies for circulating tumor cell isolation. Analyst 143, 2936–2970, https://doi.org/10.1039/C7AN01979C (2018).
Rana, A., Zhang, Y. & Esfandiari, L. Advancements in microfluidic technologies for isolation and early detection of circulating cancer-related biomarkers. Analyst 143, 2971–2991, https://doi.org/10.1039/C7AN01965C (2018).
Khamenehfar, A. et al. Label-free isolation of a prostate cancer cell among blood cells and the single-cell measurement of drug accumulation using an integrated microfluidic chip. Biomicrofluidics 9, 064104–064104, https://doi.org/10.1063/1.4934715 (2015).
Brock, G., Castellanos-Rizaldos, E., Hu, L., Coticchia, C. & Skog, J. Liquid biopsy for cancer screening, patient stratification and monitoring. Translational Cancer Research 4, 280–290 (2015).
Barbazán, J. et al. A logistic model for the detection of circulating tumour cells in human metastatic colorectal cancer. Journal of Cellular and Molecular Medicine 16, 2342–2349, https://doi.org/10.1111/j.1582-4934.2012.01544.x (2012).
Barbazán, J. et al. Molecular Characterization of Circulating Tumor Cells in Human Metastatic Colorectal Cancer. Plos One 7, e40476, https://doi.org/10.1371/journal.pone.0040476 (2012).
Xu, L. et al. Optimization and Evaluation of a Novel Size Based Circulating Tumor Cell Isolation System. Plos One 10, e0138032, https://doi.org/10.1371/journal.pone.0138032 (2015).
Renier, C. et al. Label-free isolation of prostate circulating tumor cells using Vortex microfluidic technology. npj Precision Oncology 1, 15, https://doi.org/10.1038/s41698-017-0015-0 (2017).
Lee, A. et al. All-in-One Centrifugal Microfluidic Device for Size-Selective Circulating Tumor Cell Isolation with High Purity. Analytical Chemistry 86, 11349–11356, https://doi.org/10.1021/ac5035049 (2014).
Riahi, R. et al. A novel microchannel-based device to capture and analyze circulating tumor cells (CTCs) of breast cancer. International Journal of Oncology 44, 1870–1878, https://doi.org/10.3892/ijo.2014.2353 (2014).
Park, E. S. et al. Continuous Flow Deformability-Based Separation of Circulating Tumor Cells Using Microfluidic Ratchets. Small 12, 1909–1919, https://doi.org/10.1002/smll.201503639 (2016).
Qin, X. et al. Size and deformability based separation of circulating tumor cells from castrate resistant prostate cancer patients using resettable cell traps. Lab on a Chip 15, 2278–2286, https://doi.org/10.1039/C5LC00226E (2015).
Warkiani, M. E. et al. Ultra-fast, label-free isolation of circulating tumor cells from blood using spiral microfluidics. Nature Protocols 11, 134, https://doi.org/10.1038/nprot.2016.003 (2015).
Hyun, K.-A., Kwon, K., Han, H., Kim, S.-I. & Jung, H.-I. Microfluidic flow fractionation device for label-free isolation of circulating tumor cells (CTCs) from breast cancer patients. Biosensors and Bioelectronics 40, 206–212, https://doi.org/10.1016/j.bios.2012.07.021 (2013).
Hou, H. W. et al. Isolation and retrieval of circulating tumor cells using centrifugal forces. Scientific Reports 3, 1259, https://doi.org/10.1038/srep01259 (2013).
Sollier, E. et al. Size-selective collection of circulating tumor cells using Vortex technology. Lab on a Chip 14, 63–77, https://doi.org/10.1039/C3LC50689D (2014).
Che, J. et al. Classification of large circulating tumor cells isolated with ultra-high throughput microfluidic Vortex technology. Oncotarget 7, 12748–12760, https://doi.org/10.18632/oncotarget.7220 (2016).
Gupta, V. et al. ApoStream(™), a new dielectrophoretic device for antibody independent isolation and recovery of viable cancer cells from blood. Biomicrofluidics 6, 024133, https://doi.org/10.1063/1.4731647 (2012).
Warkiani, M. E. et al. Slanted spiral microfluidics for the ultra-fast, label-free isolation of circulating tumor cells. Lab on a Chip 14, 128–137, https://doi.org/10.1039/C3LC50617G (2014).
Williams, A., Balic, M., Datar, R. & Cote, R. In Minimal Residual Disease and Circulating Tumor Cells in Breast Cancer (eds Ignatiadis, M., Sotiriou, C. & Pantel, K.) 87–95 (Springer Berlin Heidelberg, 2012).
Hvichia, G. E. et al. A novel microfluidic platform for size and deformability based separation and the subsequent molecular characterization of viable circulating tumor cells. International journal of cancer 138, 2894–2904, https://doi.org/10.1002/ijc.30007 (2016).
Lin, E. et al. High-Throughput Microfluidic Labyrinth for the Label-free Isolation of Circulating Tumor Cells. Cell Systems 5, 295–304.e294, https://doi.org/10.1016/j.cels.2017.08.012 (2017).
Park, S. et al. Morphological Differences between Circulating Tumor Cells from Prostate Cancer Patients and Cultured Prostate Cancer Cells. Plos One 9, e85264, https://doi.org/10.1371/journal.pone.0085264 (2014).
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 8, e61770, https://doi.org/10.1371/journal.pone.0061770 (2013).
Kim, T.-H. et al. FAST: Size-Selective, Clog-Free Isolation of Rare Cancer Cells from Whole Blood at a Liquid–Liquid Interface. Analytical Chemistry 89, 1155–1162, https://doi.org/10.1021/acs.analchem.6b03534 (2017).
Zhang, W. et al. Microfluidics separation reveals the stem-cell–like deformability of tumor-initiating cells. Proceedings of the National Academy of Sciences 109, 18707–18712, https://doi.org/10.1073/pnas.1209893109 (2012).
Cho, H.-Y. et al. Selective isolation and noninvasive analysis of circulating cancer stem cells through Raman imaging. Biosensors and Bioelectronics 102, 372–382, https://doi.org/10.1016/j.bios.2017.11.049 (2018).
Chan, T. L., Zhao, W., Leung, S. Y. & Yuen, S. T. BRAF and KRAS Mutations in Colorectal Hyperplastic Polyps and Serrated Adenomas. Cancer Research 63, 4878–4881 (2003).
Xu, L. et al. The novel association of circulating tumor cells and circulating megakaryocytes with prostate cancer prognosis. Clinical Cancer Research, https://doi.org/10.1158/1078-0432.ccr-16-3081 (2017).
Aceto, N. et al. Circulating Tumor Cell Clusters are Oligoclonal Precursors of Breast Cancer Metastasis. Cell 158, 1110–1122, https://doi.org/10.1016/j.cell.2014.07.013 (2014).
Zhang, B. et al. β-Catenin and ras Oncogenes Detect Most Human Colorectal Cancer. Clinical Cancer Research 9, 3073–3079 (2003).
Fransén, K. et al. Mutation analysis of the BRAF, ARAF and RAF-1 genes in human colorectal adenocarcinomas. Carcinogenesis 25, 527–533, https://doi.org/10.1093/carcin/bgh049 (2004).
Lüchtenborg, M. et al. Mutations in APC, CTNNB1 and K-ras genes and expression of hMLH1 in sporadic colorectal carcinomas from the Netherlands Cohort Study. BMC Cancer 5, 160, https://doi.org/10.1186/1471-2407-5-160 (2005).
Suraweera, N. et al. Mutations within Wnt pathway genes in sporadic colorectal cancers and cell lines. International Journal of Cancer 119, 1837–1842, https://doi.org/10.1002/ijc.22046 (2006).
Vogelstein, B. et al. Genetic Alterations during Colorectal-Tumor Development. New England Journal of Medicine 319, 525–532, https://doi.org/10.1056/nejm198809013190901 (1988).
Scholtka, B. et al. A gene marker panel covering the Wnt and the Ras-Raf-MEK-MAPK signalling pathways allows to detect gene mutations in 80% of early (UICC I) colon cancer stages in humans. Cancer Epidemiology 33, 123–129, https://doi.org/10.1016/j.canep.2009.05.001 (2009).
Schneider, M. et al. Detection of up to 65% of Precancerous Lesions of the Human Colon and Rectum by Mutation Analysis of APC, K-Ras, B-Raf and CTNNB1. Cancers 3, 91–105, https://doi.org/10.3390/cancers3010091 (2011).
Fearon, E. R. & Vogelstein, B. A genetic model for colorectal tumorigenesis. Cell 61, 759–767, https://doi.org/10.1016/0092-8674(90)90186-I (1990).
Powell, S. M. et al. APC mutations occur early during colorectal tumorigenesis. Nature 359, 235, https://doi.org/10.1038/359235a0 (1992).
Fodde, R. The APC gene in colorectal cancer. European Journal of Cancer 38, 867–871, https://doi.org/10.1016/S0959-8049(02)00040-0 (2002).
Hindson, B. J. et al. High-Throughput Droplet Digital PCR System for Absolute Quantitation of DNA Copy Number. Analytical Chemistry 83, 8604–8610, https://doi.org/10.1021/ac202028g (2011).
Bettegowda, C. et al. Detection of Circulating Tumor DNA in Early- and Late-Stage Human Malignancies. Science Translational Medicine 6, 224ra224–224ra224, https://doi.org/10.1126/scitranslmed.3007094 (2014).
Jass, J. R., Young, J. & Leggett, B. A. Evolution of colorectal cancer: Change of pace and change of direction. Journal of Gastroenterology and Hepatology 17, 17–26, https://doi.org/10.1046/j.1440-1746.2002.02635.x (2002).
Kong, S. L. et al. Molecular characterization of circulating colorectal tumor cells defines genetic signatures for individualized cancer care. Oncotarget 8, 68026–68037, https://doi.org/10.18632/oncotarget.19138 (2017).
Diehl, F. et al. Detection and quantification of mutations in the plasma of patients with colorectal tumors. Proceedings of the National Academy of Sciences of the United States of America 102, 16368–16373, https://doi.org/10.1073/pnas.0507904102 (2005).
Denis, J. A. et al. Droplet digital PCR of circulating tumor cells from colorectal cancer patients can predict KRAS mutations before surgery. Molecular Oncology 10, 1221–1231, https://doi.org/10.1016/j.molonc.2016.05.009 (2016).
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. Biomedical Microdevices 11, 883–892, https://doi.org/10.1007/s10544-009-9305-9 (2009).
Zheng, S. et al. Membrane microfilter device for selective capture, electrolysis and genomic analysis of human circulating tumor cells. Journal of Chromatography A 1162, 154–161, https://doi.org/10.1016/j.chroma.2007.05.064 (2007).
Cayrefourcq, L. et al. Establishment and Characterization of a Cell Line from Human Circulating Colon Cancer Cells. Cancer Research 75, 892–901, https://doi.org/10.1158/0008-5472.can-14-2613 (2015).
Lima, L. et al. Sialyl-Tn identifies muscle-invasive bladder cancer basal and luminal subtypes facing decreased survival, being expressed by circulating tumor cells and metastases. Urologic Oncology: Seminars and Original Investigations 35, 675.e671–675.e678, https://doi.org/10.1016/j.urolonc.2017.08.012 (2017).
Muinelo-Romay, L. et al. Evaluation of Circulating Tumor Cells and Related Events as Prognostic Factors and Surrogate Biomarkers in Advanced NSCLC Patients Receiving First-Line Systemic Treatment. Cancers 6, 153 (2014).
This work was supported by the InveNNta Project (Innovation in Nanomedicine), co-financed by the European Union through the Operational Programme for Cross-border Cooperation Spain-Portugal European Regional Development Fund (ERDF) (POCTEP 2007–2013), by the InveNNta2 project funded through the Nanocontest (Galician Agency of Innovation); by the CANCER project (NORTE-01-0145-FEDER-000029) co-funded through the NORTE-45-2015-02 program, and by Roche-Chus Joint Unit (financed by Galician Agency of Innovation and Ministry of Economy and Competitiveness (IN853A2015/10)). The authors would like to thank the patients participating in this study for providing blood samples. Alicia Abalo and Carmen Abuín for the clinical sample and data collection. Salvador Bartolomé Piñol for his help with the ddPCR. Mariam Debs and Helder Fonseca for their contributions regarding micro and nanofabrication.
Some of the authors have filed the following patent application: PCT/EP2016/078406, 22 November 2016, covering the geometry of the microfluidic system for CTC isolation. (Applicant: INL; name of inventors: Lorena Diéguez, Silvina Samy, Marta Oliveira, João Gaspar; status: pending). The exploitation rights have been licensed to the spin-off company RUBYnanomed, incorporated by the last author.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Ribeiro-Samy, S., Oliveira, M.I., Pereira-Veiga, T. et al. Fast and efficient microfluidic cell filter for isolation of circulating tumor cells from unprocessed whole blood of colorectal cancer patients. Sci Rep 9, 8032 (2019). https://doi.org/10.1038/s41598-019-44401-1
Potential theranostics of circulating tumor cells and tumor-derived exosomes application in colorectal cancer
Cancer Cell International (2020)
Direct comparison of size-dependent versus EpCAM-dependent CTC enrichment at the gene expression and DNA methylation level in head and neck squamous cell carcinoma
Scientific Reports (2020)
Scalable Signature-Based Molecular Diagnostics Through On-chip Biomarker Profiling Coupled with Machine Learning
Annals of Biomedical Engineering (2020)