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The number of Circulating Tumor Cells (CTCs) in blood indicates the tumor response to chemotherapeutic agents and disease progression. In early cancer diagnosis and treatment monitoring routine, detection and enumeration of CTCs in clinical blood samples have significant applications. In this paper, we design a Deep Convolutional Neural Network (DCNN) with automatically learned features for image-based CTC detection. We also present an effective training methodology which finds the most representative training samples to define the classification boundary between positive and negative samples. In the experiment, we compare the performance of auto-learned feature from DCNN and hand-crafted features, in which the DCNN outperforms hand-crafted feature. We also prove that the proposed training methodology is effective in improving the performance of DCNN classifiers.
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Chemo-specific designs for the enumeration of circulating tumor cells: advances in liquid biopsy
Advanced materials and chemo-specific designs at the nano/micrometer-scale have ensured revolutionary progress in next-generation clinically relevant technologies. For example, isolating a rare population of cells, like circulating tumor cells (CTCs) from the blood amongst billions of other blood cells, is one of the most complex scientific challenges in cancer diagnostics. The chemical tunability for achieving this degree of exceptional specificity for extra-cellular biomarker interactions demands the utility of advanced entities and multistep reactions both in solution and in the insoluble state. Thus, this review delineates the chemo-specific substrates, chemical methods, and structure–activity relationships (SARs) of chemical platforms used for isolation and enumeration of CTCs in advancing the relevance of liquid biopsy in cancer diagnostics and disease management. We highlight the synthesis of cell-specific, tumor biomarker-based, chemo-specific substrates utilizing functionalized linkers through chemistry-based conjugation strategies. The capacity of these nano/micro substrates to enhance the cell interaction specificity and efficiency with the targeted tumor cells is detailed. Furthermore, this review accounts for the importance of CTC capture and other downstream processes involving genotypic and phenotypic CTC analysis in real-time for the detection of the early onset of metastases progression and chemotherapy treatment response, and for monitoring progression free-survival (PFS), disease-free survival (DFS), and eventually overall survival (OS) in cancer patients.
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- Award ID(s):
- 1946202
- PAR ID:
- 10216693
- Date Published:
- Journal Name:
- Journal of Materials Chemistry B
- ISSN:
- 2050-750X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Circulating Tumor Cells (CTCs), which migrate from original sites in a body to distant organs through blood, are a key factor in cancer detection. Emerging Label-free techniques owing to their inherent advantage to preserve characteristics of sorted cells and low consumption of samples can be promising to the prediction of cancer progression and metastasis research. Deterministic Lateral Displacement (DLD) is one of the label-free separation techniques employing a specific arrangement of micro-posts for continuous separation of suspended cells in a buffer based on the size of cells. Separation based solely on size is challenging since the size distributions of CTCs might overlap with those of normal blood cells. To address this problem, DLD can be combined with dielectrophoresis (DEP) technique which is the phenomenon of particle movement in a non-uniform electric field owing to the polarization effect. Although, DLD devices employ the laminar flow in low Reynolds number (Re) fluid flow due to predictability of such flow regimes, they should be improved to work in higher Re flow regime so as to attain high throughput devices. In this paper, a particle tracing simulation is developed to study the effects of different post shapes, shift fraction of micropost arrays, and dielectrophoresis forces on separation of CTCs from peripheral blood cells. Our numerical model and results provide a groundwork for design and fabrication of high-throughput DLD-DEP devices for improvement of CTC separation.more » « less
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Profiling circulating tumour cells (CTCs) in cancer patients' blood samples is critical to understand the complex and dynamic nature of metastasis. This task is challenged by the fact that CTCs are not only extremely rare in circulation but also highly heterogeneous in their molecular programs and cellular functions. Here we report a combinational approach for the simultaneous biochemical and functional phenotyping of patient-derived CTCs, using an integrated inertial ferrohydrodynamic cell separation (i 2 FCS) method and a single-cell microfluidic migration assay. This combinatorial approach offers unique capability to profile CTCs on the basis of their surface expression and migratory characteristics. We achieve this using the i 2 FCS method that successfully processes whole blood samples in a tumor cell marker and size agnostic manner. The i 2 FCS method enables an ultrahigh blood sample processing throughput of up to 2 × 10 5 cells s −1 with a blood sample flow rate of 60 mL h −1 . Its short processing time (10 minutes for a 10 mL sample), together with a close-to-complete CTC recovery (99.70% recovery rate) and a low WBC contamination (4.07-log depletion rate by removing 99.992% of leukocytes), results in adequate and functional CTCs for subsequent studies in the single-cell migration device. For the first time, we employ this new approach to query CTCs with single-cell resolution in accordance with their expression of phenotypic surface markers and migration properties, revealing the dynamic phenotypes and the existence of a high-motility subpopulation of CTCs in blood samples from metastatic lung cancer patients. This method could be adopted to study the biological and clinical value of invasive CTC phenotypes.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/d0tb02574g
