Evidence map›Paper›PMID 29344897›Full record

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

Modeling of Interactions between Cancer Stem Cells and their Microenvironment: Predicting Clinical Response.

Mary E Sehl, Max S Wicha

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Cancer Stem Cell Plasticity - A Deadly Deal.Frontiers in molecular biosciences · 2020
    Review
  5. Review
  6. 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

2 authors.

Mary E SehlDivision of Hematology-Oncology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA.
Max S WichaDepartment of Internal Medicine, University of Michigan, 1500 East Medical Center Drive, Ann Arbor, MI, 48109, USA. mwicha@umich.edu.

Funding

Targeting breast cancer stem cellsR35CA197585 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WICHA, MAX S. · 2016 to 2022
$6.4M
UCLA Clinical and Translational Science InstituteKL2TR000122 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2012 to 2015
$4.5M
Regulation of Breast Stem Cells by the MicroenvironmentR01CA101860 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WICHA, MAX S. · 2004 to 2013
$2.4M
Stem Cell Self-Renewal mammary CarcinogenesisR01CA129765 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI WICHA, MAX S. · 2008 to 2015
$2.4M
NCATS NIH HHS KL2 TR000122NCI NIH HHS R01 CA101860NCI NIH HHS R01 CA129765NCI NIH HHS R35 CA197585
6 · The paper itself

Abstract

Mathematical models of cancer stem cells are useful in translational cancer research for facilitating the understanding of tumor growth dynamics and for predicting treatment response and resistance to combined targeted therapies. In this chapter, we describe appealing aspects of different methods used in mathematical oncology and discuss compelling questions in oncology that can be addressed with these modeling techniques. We describe a simplified version of a model of the breast cancer stem cell niche, illustrate the visualization of the model, and apply stochastic simulation to generate full distributions and average trajectories of cell type populations over time. We further discuss the advent of single-cell data in studying cancer stem cell heterogeneity and how these data can be integrated with modeling to advance understanding of the dynamics of invasive and proliferative populations during cancer progression and response to therapy.

Indexed as

Models, BiologicalNeoplasmsNeoplastic Stem CellsTumor MicroenvironmentAnimalsHumansTranslational Research, BiomedicalBreast cancerCancer stem cellMathematical modelOptimal therapy design

Identifiers

PMID29344897
PMCPMC6322404

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.