Evidence map›Paper›PMID 38222473›Full record

ArticleMicrosystems & nanoengineering2024

Experimental measurement and numerical modeling of deformation behavior of breast cancer cells passing through constricted microfluidic channels.

Pouyan Keshavarz Motamed, Hesam Abouali, Mahla Poudineh, Nima Maftoon

Abstract read
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Article in Microsystems & nanoengineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Pouyan Keshavarz MotamedDepartment of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1 Canada.
Hesam AboualiCenter for Bioengineering and Biotechnology, University of Waterloo, Waterloo, ON N2L 3G1 Canada.
Mahla PoudinehCenter for Bioengineering and Biotechnology, University of Waterloo, Waterloo, ON N2L 3G1 Canada.ORCID 0000-0001-8684-3102
Nima MaftoonDepartment of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1 Canada.ORCID 0000-0003-0853-996X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the multistep process of metastasis, cancer cells encounter various mechanical forces which make them deform drastically. Developing accurate in-silico models, capable of simulating the interactions between the mechanical forces and highly deformable cancer cells, can pave the way for the development of novel diagnostic and predictive methods for metastatic progression. Spring-network models of cancer cell, empowered by our recently proposed identification approach, promises a versatile numerical tool for developing experimentally validated models that can simulate complex interactions at cellular scale. Using this numerical tool, we presented spring-network models of breast cancer cells that can accurately replicate the experimental data of deformation behavior of the cells flowing in a fluidic domain and passing narrow constrictions comparable to microcapillary. First, using high-speed imaging, we experimentally studied the deformability of breast cancer cell lines with varying metastatic potential (MCF-7 (less invasive), SKBR-3 (medium-high invasive), and MDA-MB-231 (highly invasive)) in terms of their entry time to a constricted microfluidic channel. We observed that MDA-MB-231, that has the highest metastatic potential, is the most deformable cell among the three. Then, by focusing on this cell line, experimental measurements were expanded to two more constricted microchannel dimensions. The experimental deformability data in three constricted microchannel sizes for various cell sizes, enabled accurate identification of the unknown parameters of the spring-network model of the breast cancer cell line (MDA-MB-231). Our results show that the identified parameters depend on the cell size, suggesting the need for a systematic procedure for identifying the size-dependent parameters of spring-network models of cells. As the numerical results show, the presented cell models can simulate the entry process of the cell into constricted channels with very good agreements with the measured experimental data.

Indexed as

EngineeringPhysics

Identifiers

PMID38222473
PMCPMC10786721

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.