Evidence map›Paper›PMID 30991758›Full record

ArticleBiosensors2019

Real-Time Measurement of Melanoma Cell-Mediated Human Brain Endothelial Barrier Disruption Using Electric Cell-Substrate Impedance Sensing Technology.

Akshata Anchan, Panagiota Kalogirou-Baldwin, Rebecca Johnson, Dan T Kho, Wayne Joseph, James Hucklesby, Graeme J Finlay, Simon J O'Carroll, Catherine E Angel, E Scott Graham

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

15 citing papers in PubMed, 21 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Melanoma in the Eyes of Mechanobiology.Frontiers in cell and developmental biology · 2020
    Review
  15. Article
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

10 authors at 1 institution in 1 country.

Akshata AnchanDepartment of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand. a.anchan@auckland.ac.nz.
Panagiota Kalogirou-BaldwinDepartment of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand. pkalogiroubaldwin@gmail.com.
Rebecca JohnsonDepartment of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand. rebecca.johnson@auckland.ac.nz.ORCID 0000-0001-9473-2621
Dan T KhoDepartment of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand. dkho024@aucklanduni.ac.nz.
Wayne JosephAuckland Cancer Society Research Centre, University of Auckland, Auckland 1023, New Zealand. w.joseph@auckland.ac.nz.
James HucklesbyDepartment of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand. james.hucklesby@auckland.ac.nz.ORCID 0000-0003-1591-6823
Graeme J FinlayDepartment of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand. g.finlay@auckland.ac.nz.
Simon J O'CarrollCentre for Brain Research, University of Auckland, Auckland 1023, New Zealand. s.ocarroll@auckland.ac.nz.
Catherine E AngelSchool of Biological Sciences, Faculty of Science, University of Auckland, Auckland 1010, New Zealand. c.angel@auckland.ac.nz.ORCID 0000-0003-1737-8539
E Scott GrahamDepartment of Molecular Medicine and Pathology, School of Medical Sciences, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand. s.graham@auckland.ac.nz.
University of Auckland · NZ

Funding

Neurological Foundation NA
6 · The paper itself

Abstract

Electric cell-substrate impedance sensing (ECIS) is an impedance-based method for monitoring changes in cell behaviour in real-time. In this paper, we highlight the importance of ECIS in measuring the kinetics of human melanoma cell invasion across human brain endothelium. ECIS data can be mathematically modelled to assess which component of the endothelial paracellular and basolateral barriers is being affected and when. Our results reveal that a range of human melanoma cells can mediate disruption of human brain endothelium, primarily involving the paracellular route, as demonstrated by ECIS. The sensitivity of ECIS also reveals that the paracellular barrier weakens within 30-60 min of the melanoma cells being added to the apical face of the endothelial cells. Imaging reveals pronounced localisation of the melanoma cells at the paracellular junctions consistent with paracellular migration. Time-lapse imaging further reveals junctional opening and disruption of the endothelial monolayer by the invasive melanoma cells all within several hours. We suggest that the ability of ECIS to resolve changes to barrier integrity in real time, and to determine the route of migration, provides a powerful tool for future studies investigating the key molecules involved in the invasive process of cancer cells.

Indexed as

Biosensing TechniquesBlood-Brain BarrierBrainCutaneous Malignant MelanomaElectric ImpedanceEndothelial CellsHumansMelanomaSkin NeoplasmsTime Factorsbarrier functionblood–brain barrierECISendotheliumimpedance

Identifiers

PMID30991758
PMCPMC6627833
OpenAlexW2938580250

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.