22 research outputs found

    EXPANSION AND CHARACTERIZATION OF HUMAN BREAST CIRCULATING CANCER CELLS

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    Ph.DPH.D. IN MECHANOBIOLOGY (NGS

    Clinical Validation of an Ultra High-Throughput Spiral Microfluidics for the Detection and Enrichment of Viable Circulating Tumor Cells

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    Background: Circulating tumor cells (CTCs) are cancer cells that can be isolated via liquid biopsy from blood and can be phenotypically and genetically characterized to provide critical information for guiding cancer treatment. Current analysis of CTCs is hindered by the throughput, selectivity and specificity of devices or assays used in CTC detection and isolation. Methodology/Principal Findings: Here, we enriched and characterized putative CTCs from blood samples of patients with both advanced stage metastatic breast and lung cancers using a novel multiplexed spiral microfluidic chip. This system detected putative CTCs under high sensitivity (100%, n = 56) (Breast cancer samples: 12–1275 CTCs/ml; Lung cancer samples: 10–1535 CTCs/ml) rapidly from clinically relevant blood volumes (7.5 ml under 5 min). Blood samples were completely separated into plasma, CTCs and PBMCs components and each fraction were characterized with immunophenotyping (Pan-cytokeratin/CD45, CD44/CD24, EpCAM), fluorescence in-situ hybridization (FISH) (EML4-ALK) or targeted somatic mutation analysis. We used an ultra-sensitive mass spectrometry based system to highlight the presence of an EGFR-activating mutation in both isolated CTCs and plasma cell-free DNA (cf-DNA), and demonstrate concordance with the original tumor-biopsy samples. Conclusions/Significance: We have clinically validated our multiplexed microfluidic chip for the ultra high-throughput, low-cost and label-free enrichment of CTCs. Retrieved cells were unlabeled and viable, enabling potential propagation and real-time downstream analysis using next generation sequencing (NGS) or proteomic analysis.Singapore-MIT Alliance for Research and Technolog

    Label-free enrichment of human blast cells from whole blood for leukemia monitoring

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    Summary: Liquid biopsy is an alternative to invasive bone marrow biopsy for leukemia detection and management. However, no robust technology is available for enriching leukemic blast cells from the blood. Here, we present a simple and effective protocol for vigorous enrichment of blast cells from whole blood using a one-step microfluidic blast cell biochip (BCB) that exploits distinct cell mechanical properties between diseased and healthy leukocytes. The BCB system achieves higher sensitivity than flow cytometry in detecting blasts.For complete details on the use and execution of this protocol, please refer to Khoo et al. (2019). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics

    Early Predictor Tool of Disease Using Label-Free Liquid Biopsy-Based Platforms for Patient-Centric Healthcare

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    Cancer cells undergo phenotypic changes or mutations during treatment, making detecting protein-based or gene-based biomarkers challenging. Here, we used algorithmic analysis combined with patient-derived tumor models to derive an early prediction tool using patient-derived cell clusters from liquid biopsy (LIQBP) for cancer prognosis in a label-free manner. The LIQBP platform incorporated a customized microfluidic biochip that mimicked the tumor microenvironment to establish patient clusters, and extracted physical parameters from images of each sample, including size, thickness, roughness, and thickness per area (n = 31). Samples from healthy volunteers (n = 5) and cancer patients (pretreatment; n = 4) could be easily distinguished with high sensitivity (91.16 ± 1.56%) and specificity (71.01 ± 9.95%). Furthermore, we demonstrated that the multiple unique quantitative parameters reflected patient responses. Among these, the ratio of normalized gray value to cluster size (RGVS) was the most significant parameter correlated with cancer stage and treatment duration. Overall, our work presented a novel and less invasive approach for the label-free prediction of disease prognosis to identify patients who require adjustments to their treatment regime. We envisioned that such efforts would promote the management of personalized patient care conveniently and cost effectively

    Microfluidic modelling of the tumor microenvironment for anti-cancer drug development

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    Microfluidic tumor model has the unique advantage of recapitulating tumor microenvironment in a comparatively easier and representative fashion. In this review, we aim to focus more on the possibility of generating clinically actionable information from these microfluidic systems, not just scientific insight

    Oxidative stress induced by Etoposide anti-cancer chemotherapy drives the emergence of tumor-associated bacteria resistance to fluoroquinolones

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    Introduction: Antibiotic-resistant bacterial infections, such as Pseudomonas aeruginosa and Staphylococcus aureus, are prevalent in lung cancer patients, resulting in poor clinical outcomes and high mortality. Etoposide (ETO) is an FDA-approved chemotherapy drug that kills cancer cells by damaging DNA through oxidative stress. However, it is unclear if ETO can cause unintentional side effects on tumor-associated microbial pathogens, such as inducing antibiotic resistance. Objectives: We aimed to show that prolonged ETO treatment could unintendedly confer fluoroquinolone antibiotic resistance to P. aeruginosa, and evaluate the effect of tumor-associated P. aeruginosa on tumor progression. Methods: We employed experimental evolution assay to treat P. aeruginosa with prolonged ETO exposure, evaluated the ciprofloxacin resistance, and elucidated the gene mutations by DNA sequencing. We also established a lung tumor-P. aeruginosa bacterial model to study the role of ETO-evolved intra-tumoral bacteria in tumor progression using immunostaining and confocal microscopy. Results: ETO could generate oxidative stress and lead to gene mutations in P. aeruginosa, especially the gyrase (gyrA) gene, resulting in acquired fluoroquinolone resistance. We further demonstrated using a microfluidic-based lung tumor-P. aeruginosa coculture model that bacteria can evolve ciprofloxacin (CIP) resistance in a tumor microenvironment. Moreover, ETO-induced CIP-resistant (EICR) mutants could form multicellular biofilms which protected tumor cells from ETO killing and enabled tumor progression. Conclusion: Overall, our preclinical proof-of-concept provides insights into how anti-cancer chemotherapy could inadvertently allow tumor-associated bacteria to acquire antibiotic resistance mutations and shed new light on the development of novel anti-cancer treatments based on anti-bacterial strategies

    A deformability-based biochip for precise label-free stratification of metastatic subtypes using deep learning

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    Abstract Cellular deformability is a promising biomarker for evaluating the physiological state of cells in medical applications. Microfluidics has emerged as a powerful technique for measuring cellular deformability. However, existing microfluidic-based assays for measuring cellular deformability rely heavily on image analysis, which can limit their scalability for high-throughput applications. Here, we develop a parallel constriction-based microfluidic flow cytometry device and an integrated computational framework (ATMQcD). The ATMQcD framework includes automatic training set generation, multiple object tracking, segmentation, and cellular deformability quantification. The system was validated using cancer cell lines of varying metastatic potential, achieving a classification accuracy of 92.4% for invasiveness assessment and stratifying cancer cells before and after hypoxia treatment. The ATMQcD system also demonstrated excellent performance in distinguishing cancer cells from leukocytes (accuracy = 89.5%). We developed a mechanical model based on power-law rheology to quantify stiffness, which was fitted with measured data directly. The model evaluated metastatic potentials for multiple cancer types and mixed cell populations, even under real-world clinical conditions. Our study presents a highly robust and transferable computational framework for multiobject tracking and deformation measurement tasks in microfluidics. We believe that this platform has the potential to pave the way for high-throughput analysis in clinical applications, providing a powerful tool for evaluating cellular deformability and assessing the physiological state of cells

    Microdevices for Non-Invasive Detection of Bladder Cancer

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    Bladder cancer holds the record for the highest lifetime cost on a per-patient basis. This is due to high recurrence rates, which necessitate invasive and costly long-term evaluation methods such as cystoscopy and imaging. Microfluidics is emerging as an important approach to contribute to initial diagnosis and follow-up, by enabling the precise manipulation of biological samples. Specifically, microdevices have been used for the isolation of cells or genetic material from blood samples, sparking significant interest as a versatile platform for non-invasive bladder cancer detection with voided urine. In this review, we revisit the methods of bladder cancer detection and describe various types of markers currently used for evaluation. We detail cutting-edge technologies and evaluate their merits in the detection, screening, and diagnosis of bladder cancer. Advantages of microscale devices over standard methods of detection, as well as their limitations, are provided. We conclude with a discussion of criteria for guiding microdevice development that could deepen our understanding of prognoses at the level of individual patients and the underlying biology of bladder cancer development. Collectively, the development and widespread application of improved microfluidic devices for bladder cancer could drive treatment breakthroughs and establish widespread, tangible outcomes on patients’ long-term survival
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