scholarly journals Multiparametric quantitative phase imaging for real-time, single cell, drug screening in breast cancer

2021 ◽  
Author(s):  
Edward R Polanco ◽  
Tarek E Moustafa ◽  
Andrew Butterfield ◽  
Sandra D Scherer ◽  
Emilio Cortes-Sanchez ◽  
...  

Quantitative phase imaging (QPI) measures the growth rate of individual cells by quantifying changes in mass versus time. Here, we use the breast cancer cell lines MCF-7, BT-474, and MDA-MB-231 to validate QPI as a multiparametric approach for determining response to single-agent therapies. Our method allows for rapid determination of drug sensitivity, cytotoxicity, heterogeneity, and time of response for up to 100,000 individual cells or small clusters in a single experiment. We find that QPI EC50 values are concordant with CellTiter-Glo (CTG), a gold standard metabolic endpoint assay. In addition, we apply multiparametric QPI to characterize cytostatic/cytotoxic and rapid/slow responses and track the emergence of resistant subpopulations. Thus, QPI reveals dynamic changes in response heterogeneity in addition to average population responses, a key advantage over endpoint viability or metabolic assays. Overall, multiparametric QPI reveals a rich picture of cell growth by capturing the dynamics of single-cell responses to candidate therapies.

2017 ◽  
Vol 22 (4) ◽  
pp. 046004 ◽  
Author(s):  
Hassaan Majeed ◽  
Chukwuemeka Okoro ◽  
André Kajdacsy-Balla ◽  
Kimani C. Toussaint ◽  
Gabriel Popescu

2019 ◽  
Author(s):  
Kelvin C. M. Lee ◽  
Andy K. S. Lau ◽  
Anson H. L. Tang ◽  
Maolin Wang ◽  
Aaron T. Y. Mok ◽  
...  

AbstractA growing body of evidence has substantiated the significance of quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assay, which provides useful insights into understanding biophysical properties of cells and their roles in cellular functions. However, available QPI modalities are limited by the loss of imaging resolution at high throughput and thus run short of sufficient statistical power at the single cell precision to define cell identities in a large and heterogeneous population of cells – hindering their utility in mainstream biomedicine and biology. Here we present a new QPI modality, coined multi-ATOM that captures and processes quantitative label-free single-cell images at ultra-high throughput without compromising sub-cellular resolution. We show that multi-ATOM, based upon ultrafast phase-gradient encoding, outperforms state-of-the-art QPI in permitting robust phase retrieval at a QPI throughput of >10,000 cell/sec, bypassing the need for interferometry which inevitably compromises QPI quality under ultrafast operation. We employ multi-ATOM for large-scale, label-free, multi-variate, cell-type classification (e.g. breast cancer sub-types, and leukemic cells versus peripheral blood mononuclear cells) at high accuracy (>94%). Our results suggest that multi-ATOM could empower new strategies in large-scale biophysical single-cell analysis with applications in biology and enriching disease diagnostics.


Author(s):  
Ziqi Zhang ◽  
Queenie T. K. Lai ◽  
Kelvin C. M. Lee ◽  
Kenneth K. Y. Wong ◽  
Kevin K. Tsia

2019 ◽  
Vol 12 (7) ◽  
Author(s):  
Kelvin C. M. Lee ◽  
Andy K. S. Lau ◽  
Anson H. L. Tang ◽  
Maolin Wang ◽  
Aaron T. Y. Mok ◽  
...  

2019 ◽  
Vol 95 (5) ◽  
pp. 510-520 ◽  
Author(s):  
Kelvin C.M. Lee ◽  
Maolin Wang ◽  
Kathryn S.E. Cheah ◽  
Godfrey C.F. Chan ◽  
Hayden K.H. So ◽  
...  

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