High-Throughput, Time-Resolved Mechanical Phenotyping of Prostate Cancer Cells

Yuri Belotti (Lead / Corresponding author), Serenella Tolomeo, Michael Conneely, Tianjun Huang, Stephen McKenna, Ghulam Nabi, David McGloin (Lead / Corresponding author)

Research output: Contribution to journalArticle

21 Downloads (Pure)

Abstract

Worldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, timeresolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.
Original languageEnglish
Article number5742
Pages (from-to)1-9
Number of pages9
JournalScientific Reports
Volume9
DOIs
Publication statusPublished - 5 Apr 2019

Fingerprint

Prostatic Neoplasms
Hydrodynamics
Stretchers
Equipment and Supplies
Decision Trees
Microfluidics
Prostate
Lung Neoplasms
Suspensions
Cell Line

Cite this

@article{6a42ee773df2422cb8384b9c9e4071d5,
title = "High-Throughput, Time-Resolved Mechanical Phenotyping of Prostate Cancer Cells",
abstract = "Worldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, timeresolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.",
author = "Yuri Belotti and Serenella Tolomeo and Michael Conneely and Tianjun Huang and Stephen McKenna and Ghulam Nabi and David McGloin",
note = "We acknowledge the Scottish Universities Physics Alliance (SUPA) for support, as well as Tenovus Scotland and the Hugh Fraser Trust. Y.B. thanks EPSRC for support through a DTP studentship (EP/K503010/1).",
year = "2019",
month = "4",
day = "5",
doi = "10.1038/s41598-019-42008-0",
language = "English",
volume = "9",
pages = "1--9",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",

}

High-Throughput, Time-Resolved Mechanical Phenotyping of Prostate Cancer Cells. / Belotti, Yuri (Lead / Corresponding author); Tolomeo, Serenella; Conneely, Michael; Huang, Tianjun; McKenna, Stephen; Nabi, Ghulam; McGloin, David (Lead / Corresponding author).

In: Scientific Reports, Vol. 9, 5742, 05.04.2019, p. 1-9.

Research output: Contribution to journalArticle

TY - JOUR

T1 - High-Throughput, Time-Resolved Mechanical Phenotyping of Prostate Cancer Cells

AU - Belotti, Yuri

AU - Tolomeo, Serenella

AU - Conneely, Michael

AU - Huang, Tianjun

AU - McKenna, Stephen

AU - Nabi, Ghulam

AU - McGloin, David

N1 - We acknowledge the Scottish Universities Physics Alliance (SUPA) for support, as well as Tenovus Scotland and the Hugh Fraser Trust. Y.B. thanks EPSRC for support through a DTP studentship (EP/K503010/1).

PY - 2019/4/5

Y1 - 2019/4/5

N2 - Worldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, timeresolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.

AB - Worldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, timeresolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.

U2 - 10.1038/s41598-019-42008-0

DO - 10.1038/s41598-019-42008-0

M3 - Article

VL - 9

SP - 1

EP - 9

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 5742

ER -