Evidence map›Paper›PMID 36449634›Full record

ArticleSmall (Weinheim an der Bergstrasse, Germany)2023

High-Throughput Cellular Heterogeneity Analysis in Cell Migration at the Single-Cell Level.

Mengli Zhou, Yushu Ma, Chun-Cheng Chiang, Edwin C Rock, Kathryn E Luker, Gary D Luker, Yu-Chih Chen

Open access · bronzeAbstract read
In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.0field-weighted citation impact, top 14% of its field
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

16 citing papers in PubMed, 24 citations in OpenAlex.

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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

7 authors at 3 institutions in 2 countries.

Mengli ZhouUPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA, 15232, USA.
Yushu MaUPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA, 15232, USA.
Chun-Cheng ChiangUPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA, 15232, USA.
Edwin C RockDepartment of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 3700 O'Hara Street, Pittsburgh, PA, 15260, USA.
Kathryn E LukerCenter for Molecular Imaging, Department of Radiology, University of Michigan, 109 Zina Pitcher Place, Ann Arbor, MI, 48109-2200, USA.
Gary D LukerCenter for Molecular Imaging, Department of Radiology, University of Michigan, 109 Zina Pitcher Place, Ann Arbor, MI, 48109-2200, USA.ORCID 0000-0001-6832-2581
Yu-Chih ChenUPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA, 15232, USA.ORCID 0000-0002-3875-4671
University of Pittsburgh · USUniversity of Michigan · USCentral South University · CN

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR001857 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2016 to 2025
$129.3M
Interstitial Fluid Flow Regulates Glioma Cell InvasionR37CA222563 · NCI · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI MUNSON, JENNIFER M · 2018 to 2024
$4.0M
Environmental Regulation of Cancer Stem Cell Plasticity in MetastasisU01CA210152 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LAHANN, JOERG, LUKER, GARY D · 2017 to 2021
$3.6M
University of Michigan Quantitative Co-Clinical Imaging Research ResourceU24CA237683 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHENEVERT, THOMAS L, LUKER, GARY D · 2019 to 2023
$3.1M
Imaging Disease Heterogeneity and Response to Therapy in MyelofibrosisR01CA238023 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LUKER, GARY D, ROSS, BRIAN D. · 2019 to 2023
$3.1M
Integrators of Metastatic PotentialR01CA238042 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GHOSH, PRADIPTA, LUKER, GARY D · 2019 to 2023
$2.3M
Specialist in Multi-Scale Molecular Imaging of Tumor EnvironmentsR50CA221807 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Kathryn Luker · 2018 to 2026
$1.6M
A High Throughput Human Tumor Modeling Technology for Cancer Drug DiscoveryR33CA225549 · NCI · UNIVERSITY OF AKRON · PI LUKER, GARY D, TAVANA, HOSSEIN · 2019 to 2021
$1.4M
NCATS NIH HHS UL1 TR001857NCI NIH HHS R01 CA238023NCI NIH HHS R01 CA238042NCI NIH HHS R33 CA225549NCI NIH HHS R37 CA222563NCI NIH HHS R50 CA221807NCI NIH HHS U01 CA210152NCI NIH HHS U24 CA237683NIH HHS R37 CA222563NIH HHS UL1TR001857
6 · The paper itself

Abstract

Cancer cell migration represents an essential step toward metastasis and cancer deaths. However, conventional drug discovery focuses on cytotoxic and growth-inhibiting compounds rather than inhibitors of migration. Drug screening assays generally measure the average response of many cells, masking distinct cell populations that drive metastasis and resist treatments. Here, this work presents a high-throughput microfluidic cell migration platform that coordinates robotic liquid handling and computer vision for rapidly quantifying individual cellular motility. Using this innovative technology, 172 compounds were tested and a surprisingly low correlation between migration and growth inhibition was found. Notably, many compounds were found to inhibit migration of most cells while leaving fast-moving subpopulations unaffected. This work further pinpoints synergistic drug combinations, including Bortezomib and Danirixin, to stop fast-moving cells. To explain the observed cell behaviors, single-cell morphological and molecular analysis were performed. These studies establish a novel technology to identify promising migration inhibitors for cancer treatment and relevant applications.

Indexed as

Drug DiscoveryMicrofluidicsCell Line, TumorCell MovementHigh-Throughput Screening AssaysSingle-Cell Analysisbreast cancercell migrationimage processingmetastasismicrofluidicssingle-cell analysis

Identifiers

PMID36449634
PMCPMC9908848
OpenAlexW4310433573

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.