Evidence map›Paper›PMID 29525998›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2018

Intravital Imaging of Tumor Cell Motility in the Tumor Microenvironment Context.

Battuya Bayarmagnai, Louisiane Perrin, Kamyar Esmaeili Pourfarhangi, Bojana Gligorijevic

Open access · greenAbstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
4.8field-weighted citation impact, top 5% 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

11 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Frontiers in Intravital Multiphoton Microscopy of Cancer.Cancer reports (Hoboken, N.J.) · 2020
    Review
  10. Review
  11. 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

4 authors at 2 institutions in 1 country.

Battuya BayarmagnaiDepartment of Bioengineering, Temple University, Philadelphia, PA, USA.
Louisiane PerrinDepartment of Bioengineering, Temple University, Philadelphia, PA, USA.
Kamyar Esmaeili PourfarhangiDepartment of Bioengineering, Temple University, Philadelphia, PA, USA.
Bojana GligorijevicDepartment of Bioengineering, Temple University, Philadelphia, PA, USA. bojana.gligorijevic@temple.edu.
Temple University · USFox Chase Cancer Center · US

Funding

Systems Microscopy Analysis of Tumor Cell Motility in Microenvironment ContextR00CA172360 · NCI · TEMPLE UNIV OF THE COMMONWEALTH · PI GLIGORIJEVIC, BOJANA · 2015 to 2017
$747k
Systems microscopy analysis of tumor cell motility in microenvironment contextK99CA172360 · NCI · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI GLIGORIJEVIC, BOJANA · 2013 to 2014
$279k
NCI NIH HHS K99 CA172360NCI NIH HHS R00 CA172360
6 · The paper itself

Abstract

Cancer cell motility and invasion are key features of metastatic tumors. Both are highly linked to tumor microenvironmental parameters, such as collagen architecture or macrophage density. However, due to the genetic, epigenetic and microenvironmental heterogeneities, only a small portion of tumor cells in the primary tumor are motile and furthermore, only a small portion of those will metastasize. This creates a challenge in predicting metastatic fate of single cells based on the phenotype they exhibit in the primary tumor. To overcome this challenge, tumor cell subpopulations need to be monitored at several timescales, mapping their phenotype in primary tumor as well as their potential homing to the secondary tumor site. Additionally, to address the spatial heterogeneity of the tumor microenvironment and how it relates to tumor cell phenotypes, large numbers of images need to be obtained from the same tumor. Finally, as the microenvironment complexity results in nonlinear relationships between tumor cell phenotype and its surroundings, advanced statistical models are required to interpret the imaging data. Toward improving our understanding of the relationship between cancer cell motility, the tumor microenvironment context and successful metastasis, we have developed several intravital approaches for continuous and longitudinal imaging, as well as data classification via support vector machine (SVM) algorithm. We also describe methods that extend the capabilities of intravital imaging by postsacrificial microscopy of the lung as well as correlative immunofluorescence in the primary tumor.

Indexed as

AnimalsCell MovementFluorescent Antibody TechniqueIntravital MicroscopyLung NeoplasmsMiceNeoplasm MetastasisPodosomesSupport Vector MachineTumor Microenvironment4D multiphoton fluorescent microscopyCorrelative immunofluorescenceIntravital imagingInvadopodiaInvasionMotilityPhotoconvertible proteinsSecond harmonic generationSupport vector machine classificationTumor microenvironment

Identifiers

PMID29525998
PMCPMC5996994
OpenAlexW2794012062

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.