Evidence map›Paper›PMID 23212313›Full record

ArticleLab on a chip2013

Elucidating mechanical transition effects of invading cancer cells with a subnucleus-scaled microfluidic serial dimensional modulation device.

Michael Mak, Cynthia A Reinhart-King, David Erickson

Abstract read
In one paragraph

Article in Lab on a chip, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing 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

57 citing papers in PubMed.

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  17. Collective metastasis: coordinating the multicellular voyage.Clinical & experimental metastasis · 2021
    Review
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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

3 authors.

Michael MakBiomedical Engineering Department, Cornell University, Ithaca, NY, United States.
Cynthia A Reinhart-King
David Erickson

Funding

TRANS-NETWORK PROJECTSU54CA143876 · NCI · CORNELL UNIVERSITY · PI SHULER, MICHAEL L · 2009 to 2014
$12.6M
NCI NIH HHS U54 CA143876NCI NIH HHS U54CA143876
6 · The paper itself

Abstract

Mechanical boundaries that define and regulate biological processes, such as cell-cell junctions and dense extracellular matrix networks, exist throughout the physiological landscape. During metastasis, cancer cells are able to invade across these barriers and spread to distant tissues. While transgressing boundaries is a necessary step for distal colonies to form, little is known about interface effects on cell behavior during invasion. Here we introduce a device and metric to assess cell transition effects across mechanical barriers. Using MDA-MB-231 cells, a highly metastatic breast adenocarcinoma cell line, our results demonstrate that dimensional modulation in confined spaces with mechanical barriers smaller than the cell nucleus can induce distinct invasion phases and elongated morphological states. Further investigations on the impact of microtubule stabilization and drug resistance reveal that taxol-treated cells have reduced ability in invading across tight spaces and lose their super-diffusive migratory state and taxol-resistant cells exhibit asymmetric cell division at barrier interfaces. These results illustrate that subnucleus-scaled confinement modulation can play a distinctive role in inducing behavioral responses in invading cells and can help reveal the mechanical elements of non-proteolytic invasion.

Indexed as

Cell MovementNeoplasm InvasivenessAntineoplastic Agents, PhytogenicBreast NeoplasmsCell DifferentiationCell Line, TumorCell SurvivalEpithelial CellsFemaleHumansMicrofluidic Analytical TechniquesMicrofluidicsMicrotubulesNeoplasm MetastasisNeoplasmsPaclitaxelAntineoplastic Agents, PhytogenicPaclitaxel

Identifiers

PMID23212313
PMCPMC3750734

What OpenQuestion holds

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Registered trials

None linked

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.