Literature DB >> 26456240

Phenotypic drug profiling in droplet microfluidics for better targeting of drug-resistant tumors.

S Sarkar1, N Cohen1, P Sabhachandani1, T Konry1.   

Abstract

Acquired drug resistance is a key factor in the failure of chemotherapy. Due to intratumoral heterogeneity, cancer cells depict variations in intracellular drug uptake and efflux at the single cell level, which may not be detectable in bulk assays. In this study we present a droplet microfluidics-based approach to assess the dynamics of drug uptake, efflux and cytotoxicity in drug-sensitive and drug-resistant breast cancer cells. An integrated droplet generation and docking microarray was utilized to encapsulate single cells as well as homotypic cell aggregates. Drug-sensitive cells showed greater death in the presence or absence of Doxorubicin (Dox) compared to the drug-resistant cells. We observed heterogeneous Dox uptake in individual drug-sensitive cells while the drug-resistant cells showed uniformly low uptake and retention. Dox-resistant cells were classified into distinct subsets based on their efflux properties. Cells that showed longer retention of extracellular reagents also demonstrated maximal death. We further observed homotypic fusion of both cell types in droplets, which resulted in increased cell survival in the presence of high doses of Dox. Our results establish the applicability of this microfluidic platform for quantitative drug screening in single cells and multicellular interactions.

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Year:  2015        PMID: 26456240      PMCID: PMC4666301          DOI: 10.1039/c5lc00923e

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  69 in total

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Review 2.  Cell fusion as a hidden force in tumor progression.

Authors:  Xin Lu; Yibin Kang
Journal:  Cancer Res       Date:  2009-11-03       Impact factor: 12.701

3.  Induction of tumor-specific cytotoxicity and apoptosis by doxorubicin.

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4.  The analysis of doxorubicin resistance in human breast cancer cells using antibody microarrays.

Authors:  Laura Smith; Mark B Watson; Sara L O'Kane; Philip J Drew; Michael J Lind; Lynn Cawkwell
Journal:  Mol Cancer Ther       Date:  2006-08       Impact factor: 6.261

5.  Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways.

Authors:  Mirjam C Boelens; Tony J Wu; Barzin Y Nabet; Bihui Xu; Yu Qiu; Taewon Yoon; Diana J Azzam; Christina Twyman-Saint Victor; Brianne Z Wiemann; Hemant Ishwaran; Petra J Ter Brugge; Jos Jonkers; Joyce Slingerland; Andy J Minn
Journal:  Cell       Date:  2014-10-23       Impact factor: 41.582

6.  MCF7 side population cells with characteristics of cancer stem/progenitor cells express the tumor antigen MUC1.

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Journal:  Cancer Res       Date:  2008-04-01       Impact factor: 12.701

7.  Interaction between circulating galectin-3 and cancer-associated MUC1 enhances tumour cell homotypic aggregation and prevents anoikis.

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8.  Laminar flow mediated continuous single-cell analysis on a novel poly(dimethylsiloxane) microfluidic chip.

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9.  Pgp and MRP activities using calcein-AM are prognostic factors in adult acute myeloid leukemia patients.

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10.  Temporally sequenced anticancer drugs overcome adaptive resistance by targeting a vulnerable chemotherapy-induced phenotypic transition.

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  13 in total

1.  Dynamic analysis of immune and cancer cell interactions at single cell level in microfluidic droplets.

Authors:  S Sarkar; P Sabhachandani; D Stroopinsky; K Palmer; N Cohen; J Rosenblatt; D Avigan; T Konry
Journal:  Biomicrofluidics       Date:  2016-10-12       Impact factor: 2.800

2.  Machine learning-aided quantification of antibody-based cancer immunotherapy by natural killer cells in microfluidic droplets.

Authors:  Saheli Sarkar; Wenjing Kang; Songyao Jiang; Kunpeng Li; Somak Ray; Ed Luther; Alexander R Ivanov; Yun Fu; Tania Konry
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3.  Acoustofluidic Droplet Sorter Based on Single Phase Focused Transducers.

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4.  Droplet microfluidics for functional temporal analysis and cell recovery on demand using microvalves: application in immunotherapies for cancer.

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Review 5.  Microengineered 3D Tumor Models for Anti-Cancer Drug Discovery in Female-Related Cancers.

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Journal:  Ann Biomed Eng       Date:  2021-01-05       Impact factor: 3.934

Review 6.  Application of microfluidic chips in anticancer drug screening.

Authors:  Xin-Yue Fan; Zhuo-Fen Deng; Yan-Yan Yan; Valerii E Orel; Andrii Shypko; Valerii B Orel; Donika Ivanova; Christian Pilarsky; Jing Tang; Zhe-Sheng Chen; Jian-Ye Zhang
Journal:  Bosn J Basic Med Sci       Date:  2022-06-01       Impact factor: 3.759

7.  Microfluidic cell isolation technology for drug testing of single tumor cells and their clusters.

Authors:  Swastika S Bithi; Siva A Vanapalli
Journal:  Sci Rep       Date:  2017-02-02       Impact factor: 4.379

8.  Dynamic Analysis of Human Natural Killer Cell Response at Single-Cell Resolution in B-Cell Non-Hodgkin Lymphoma.

Authors:  Saheli Sarkar; Pooja Sabhachandani; Dashnamoorthy Ravi; Sayalee Potdar; Sneha Purvey; Afshin Beheshti; Andrew M Evens; Tania Konry
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9.  Droplet-based microtumor model to assess cell-ECM interactions and drug resistance of gastric cancer cells.

Authors:  Minjeong Jang; Ilkyoo Koh; Seok Jae Lee; Jae-Ho Cheong; Pilnam Kim
Journal:  Sci Rep       Date:  2017-01-27       Impact factor: 4.379

Review 10.  Microfluidic Devices for Drug Delivery Systems and Drug Screening.

Authors:  Samar Damiati; Uday B Kompella; Safa A Damiati; Rimantas Kodzius
Journal:  Genes (Basel)       Date:  2018-02-16       Impact factor: 4.096

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