Evidence map›Paper›PMID 29484528›Full record

ArticleAnnals of biomedical engineering2018

Variable Cell Line Pharmacokinetics Contribute to Non-Linear Treatment Response in Heterogeneous Cell Populations.

Matthew T McKenna, Jared A Weis, Vito Quaranta, Thomas E Yankeelov

Abstract read
In one paragraph

Article in Annals of biomedical engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. 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 3 institutions in 1 country.

Matthew T McKennaInstitute of Imaging Science, Vanderbilt University, Nashville, USA.
Jared A WeisDepartment of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, USA.
Vito QuarantaDepartment of Biochemistry, Vanderbilt University School of Medicine, Nashville, USA.
Thomas E YankeelovDepartment of Biomedical Engineering, The University of Texas at Austin, Austin, USA. thomas.yankeelov@utexas.edu.
Vanderbilt University · USThe University of Texas at Austin · USWake Forest University · US

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007347 · NIGMS · VANDERBILT UNIVERSITY · PI WILLIAMS, CHRISTOPHER S. · 1985 to 2023
$26.3M
Quantitative MRI for Predicting Response of Breast Cancer to Neoadjuvant TherapyU01CA142565 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KARCZMAR, GREGORY S., NANDA, RITA · 2010 to 2019
$4.5M
Quantitative Multiscale Imaging to Optimize Cancer Treatment StrategiesR01CA186193 · NCI · VANDERBILT UNIVERSITY · PI QUARANTA, VITO, RERICHA, ERIN C · 2014 to 2019
$3.1M
Image Driven Multi-Scale Modeling to Predict Treatment Response in Breast CancerU01CA174706 · NCI · VANDERBILT UNIVERSITY · PI QUARANTA, VITO, YANKEELOV, THOMAS E · 2013 to 2018
$2.5M
Evaluation and Validation of Imaging Biomarkers of Tumor Response to TreatmentR01CA138599 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MCINTYRE, JAMES OLIVER · 2010 to 2015
$2.2M
Multi-Scale Biomechanical Modeling of Tumor Growth and Response in Breast CancerK25CA204599 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI WEIS, JARED ANTHONY · 2016 to 2020
$747k
Development and Validation of a Predictive Model of Chemotherapy in Breast CancerF30CA203220 · NCI · VANDERBILT UNIVERSITY · PI MCKENNA, MATTHEW T. · 2016 to 2019
$134k
Cancer Prevention and Research Institute of Texas RR160005National Cancer Institute F30 CA203220National Cancer Institute K25 CA204599National Cancer Institute R01 CA138599National Cancer Institute R01 CA186193National Cancer Institute U01 CA174706National Institute of General Medical Sciences T32 GM007347NCI NIH HHS F30 CA203220NCI NIH HHS K25 CA204599NCI NIH HHS R01 CA138599NCI NIH HHS R01 CA186193NCI NIH HHS U01 CA142565NCI NIH HHS U01 CA174706NIGMS NIH HHS T32 GM007347
6 · The paper itself

Abstract

We develop a combined experimental-mathematical framework to investigate heterogeneity in the context of breast cancer treated with doxorubicin. We engineer a cell line to over-express the multi-drug resistance 1 protein (MDR1), an ATP-dependent pump that effluxes intracellular drug. Co-culture experiments mixing the MDR1-overexpressing line with its parental line are evaluated via fluorescence microscopy. To quantify the impact of population heterogeneity on therapy response, these data are analyzed with a coupled pharmacokinetics/pharmacodynamics model. The proliferation and death rates of each line vary with co-culture condition (the relative fraction of each cell line at the time of seeding). For example, the death rate in the parental line under low-dose doxorubicin treatment is increased from 0.64 (± 0.22) × 10

Indexed as

Antineoplastic AgentsModels, BiologicalATP Binding Cassette Transporter, Subfamily BCell Line, TumorFemaleHumansMicroscopy, FluorescenceNeoplasm ProteinsTriple Negative Breast NeoplasmsABCB1 protein, humanAntineoplastic AgentsATP Binding Cassette Transporter, Subfamily BNeoplasm ProteinsMathematical modelingOncologyPharmacology

Identifiers

PMID29484528
PMCPMC5935587
OpenAlexW2788449139

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.