Evidence map›Paper›PMID 29795392›Full record

ArticleScientific reports2018

Understanding the Connection between Nanoparticle Uptake and Cancer Treatment Efficacy using Mathematical Modeling.

Terisse A Brocato, Eric N Coker, Paul N Durfee, Yu-Shen Lin, Jason Townson, Edward F Wyckoff, Vittorio Cristini, C Jeffrey Brinker, Zhihui Wang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
4.1field-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

27 citing papers in PubMed, 57 citations in OpenAlex.

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  8. A Multiscale Model to Identify Limiting Factors in Nanoparticle-Based miRNA Delivery for Tumor InhibitionAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021
    Article
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  17. Image-guided mathematical modeling for pharmacological evaluation of nanomaterials and monoclonal antibodies.Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology · 2020
    Review
  18. A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery.Computational and structural biotechnology journal · 2020
    Article
  19. Review
  20. Mathematical Modeling to Address Challenges in Pancreatic Cancer.Current topics in medicinal chemistry · 2020
    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

9 authors at 3 institutions in 1 country.

Terisse A BrocatoDepartment of Chemical and Biological Engineering and Center for Biomedical Engineering, University of New Mexico, Albuquerque, NM, 87131, USA.
Eric N CokerAdvanced Materials Lab, Sandia National Laboratories, Albuquerque, NM, 87106, USA.
Paul N DurfeeDepartment of Chemical and Biological Engineering and Center for Biomedical Engineering, University of New Mexico, Albuquerque, NM, 87131, USA.
Yu-Shen LinDepartment of Internal Medicine, Division of Molecular Medicine, the University of New Mexico, Albuquerque, NM, 87131, USA.
Jason TownsonDepartment of Internal Medicine, Division of Molecular Medicine, the University of New Mexico, Albuquerque, NM, 87131, USA.
Edward F WyckoffCenter for Micro-Engineered Materials, the University of New Mexico, Albuquerque, NM, 87131, USA.
Vittorio CristiniCenter for Precision Biomedicine, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center (UTHealth) McGovern Medical School at Houston, Houston, TX, 77030, USA.
C Jeffrey BrinkerDepartment of Chemical and Biological Engineering and Center for Biomedical Engineering, University of New Mexico, Albuquerque, NM, 87131, USA. cjbrink@sandia.gov.
Zhihui WangCenter for Precision Biomedicine, Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center (UTHealth) McGovern Medical School at Houston, Houston, TX, 77030, USA. Zhihui.Wang@uth.tmc.edu.
University of New Mexico · USThe University of Texas MD Anderson Cancer Center · USSandia National Laboratories · US

Funding

Imaging and Molecular Correlates of Progression in Cystic Neoplasms of the PancreasU01CA196403 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI MAITRA, ANIRBAN · 2015 to 2020
$5.8M
Targeted therapeutics for ovarian cancer and its microenvironment - treatment and theoretical modelingU01CA213759 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LOPEZ-BERESTEIN, GABRIEL · 2017 to 2021
$2.5M
NCI NIH HHS U01 CA196403NCI NIH HHS U01 CA213759
6 · The paper itself

Abstract

Nanoparticles have shown great promise in improving cancer treatment efficacy while reducing toxicity and treatment side effects. Predicting the treatment outcome for nanoparticle systems by measuring nanoparticle biodistribution has been challenging due to the commonly unmatched, heterogeneous distribution of nanoparticles relative to free drug distribution. We here present a proof-of-concept study that uses mathematical modeling together with experimentation to address this challenge. Individual mice with 4T1 breast cancer were treated with either nanoparticle-delivered or free doxorubicin, with results demonstrating improved cancer kill efficacy of doxorubicin loaded nanoparticles in comparison to free doxorubicin. We then developed a mathematical theory to render model predictions from measured nanoparticle biodistribution, as determined using graphite furnace atomic absorption. Model analysis finds that treatment efficacy increased exponentially with increased nanoparticle accumulation within the tumor, emphasizing the significance of developing new ways to optimize the delivery efficiency of nanoparticles to the tumor microenvironment.

Indexed as

Models, TheoreticalNanoparticlesPharmacokineticsAnimalsBiological AvailabilityBreast NeoplasmsCell Line, TumorDoxorubicinDrug Delivery SystemsFemaleHumansMiceMice, Inbred BALB CNeoplasmsTissue DistributionTumor BurdenDoxorubicin

Identifiers

PMID29795392
PMCPMC5967303
OpenAlexW2803964020

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.