Evidence map›Paper›PMID 31719862›Full record

ArticleCellular and molecular bioengineering2017

Viscoelasticity Measurements Reveal Rheological Differences Between Stem-like and Non-stem-like Breast Cancer Cells.

A Mohammadalipour, M M Burdick, D F J Tees

Abstract read
In one paragraph

Article in Cellular and molecular bioengineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Micropipette-based biomechanical nanotools on living cells.European biophysics journal : EBJ · 2022
    Review
  5. Review
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

3 authors.

A Mohammadalipour1Department of Physics and Astronomy, Ohio University, Athens, OH 45701 USA.
M M Burdick2Department of Chemical and Biomolecular Engineering, Ohio University, Athens, OH 45701 USA.
D F J Tees1Department of Physics and Astronomy, Ohio University, Athens, OH 45701 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Defining the characteristics of cancer stem cells (CSC) has become an important subject in cancer research during the past decade. Although molecular surface expression levels have been used for CSC recognition, the clinical and prognostic impacts of these markers have remained a controversial issue. The finding that cancerous cells are considerably more deformable than normal ones provides the motivation for the hypothesis that the mechanical properties can be used as biomarkers to distinguish between stem-like and non-stem-like cancer cells. In this study, using micropipette aspiration (MA) and intracellular particle tracking (IPT) microrheology, measurements of the whole-cell and local viscoelasticity were made on four breast cancer cell lines with different CSC phenotypes based on their surface markers. Stem-like Hs578T and MDA-MB-231 cell lines were found to be the most deformable, while the non-stem-like MDA-MB-468 line was the least deformable. The non-stem-like BT-20 cell line showed an intermediate deformability. The enhanced deformability for stem-like cells was consistent with the observed lower and more dispersed F-actin content for the stem-like cells. Therefore, the cytoskeleton-related differences in the rheological properties of cancer cells can be a potential biomarker for CSC and eventually lead to novel cancer diagnostic and therapeutic methods.

Indexed as

Cancer stem cellsCytoskeletonIntracellular particle trackingMechanical biomarkerMechanical propertiesMicropipette aspirationMicrorheology

Identifiers

PMID31719862
PMCPMC6816627

What OpenQuestion holds

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Registered trials

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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.