Evidence map›Paper›PMID 28065783›Full record

ArticleJournal of theoretical biology2017

Mathematical modeling of mutant transferrin-CRM107 molecular conjugates for cancer therapy.

Dennis J Yoon, Kevin Y Chen, André M Lopes, April A Pan, Joseph Shiloach, Anne B Mason, Daniel T Kamei

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of theoretical biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

7 authors at 3 institutions in 1 country.

Dennis J YoonDepartment of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, 5121 Engineering V, Los Angeles, CA 90095, USA.
Kevin Y ChenDepartment of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, 5121 Engineering V, Los Angeles, CA 90095, USA.
André M LopesDepartment of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, 5121 Engineering V, Los Angeles, CA 90095, USA.
April A PanDepartment of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, 5121 Engineering V, Los Angeles, CA 90095, USA.
Joseph ShiloachBiotechnology Core Laboratory, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Health, Bethesda, MD 20892, USA.
Anne B MasonDepartment of Biochemistry, University of Vermont College of Medicine, Burlington, VT 05405, USA.
Daniel T KameiDepartment of Bioengineering, University of California, Los Angeles, 420 Westwood Plaza, 5121 Engineering V, Los Angeles, CA 90095, USA. Electronic address: kamei@seas.ucla.edu.
University of California, Los Angeles · USNational Institute of Diabetes and Digestive and Kidney Diseases · USUniversity of Vermont · US

Funding

Production and purification of biological compoundsZICDK015500 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI SHILOACH, JOSEPH · 2009 to 2022
$7.2M
Iron Delivery via Blood; Structure Role of TransferrinR01DK021739 · NIDDK · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI MASON, ANNE B. · 1987 to 2011
$3.4M
NIDDK NIH HHS R01 DK021739
6 · The paper itself

Abstract

The transferrin (Tf) trafficking pathway is a promising mechanism for use in targeted cancer therapy due to the overexpression of transferrin receptors (TfRs) on cancerous cells. We have previously developed a mathematical model of the Tf/TfR trafficking pathway to improve the efficiency of Tf as a drug carrier. By using diphtheria toxin (DT) as a model toxin, we found that mutating the Tf protein to change its iron release rate improves cellular association and efficacy of the drug. Though this is an improvement upon using wild-type Tf as the targeting ligand, conjugated toxins like DT are unfortunately still highly cytotoxic at off-target sites. In this work, we address this hurdle in cancer research by developing a mathematical model to predict the efficacy and selectivity of Tf conjugates that use an alternative toxin. For this purpose, we have chosen to study a mutant of DT, cross-reacting material 107 (CRM107). First, we developed a mathematical model of the Tf-DT trafficking pathway by extending our Tf/TfR model to include intracellular trafficking via DT and DT receptors. Using this mathematical model, we subsequently investigated the efficacy of several conjugates in cancer cells: DT and CRM107 conjugated to wild-type Tf, as well as to our engineered mutant Tf proteins (K206E/R632A Tf and K206E/R534A Tf). We also investigated the selectivity of mutant Tf-CRM107 against non-neoplastic cells. Through the use of our mathematical model, we predicted that (i) mutant Tf-CRM107 exhibits a greater cytotoxicity than wild-type Tf-CRM107 against cancerous cells, (ii) this improvement was more drastic with CRM107 conjugates than with DT conjugates, and (iii) mutant Tf-CRM107 conjugates were selective against non-neoplastic cells. These predictions were validated with in vitro cytotoxicity experiments, demonstrating that mutant Tf-CRM107 conjugates is indeed a more suitable therapeutic agent. Validation from in vitro experiments also confirmed that such whole-cell kinetic models can be useful in cancer therapeutic design.

Indexed as

Models, TheoreticalAntineoplastic AgentsBacterial ToxinsDiphtheria ToxinDrug Screening Assays, AntitumorHumansMutagenesis, Site-DirectedMutationNeoplasmsTransferrinAntineoplastic AgentsBacterial ToxinsDiphtheria ToxinTf-CRM107Transferrintransferrin-diphtheria toxin conjugateDiphtheria toxinDrug deliveryTargeted toxin

Identifiers

PMID28065783
PMCPMC5310938
OpenAlexW2567913608

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.