Evidence map›Paper›PMID 27217840›Full record

ArticleCancer nanotechnology

Nanotechnology and cancer: improving real-time monitoring and staging of bladder cancer with multimodal mesoporous silica nanoparticles.

Sean K Sweeney, Yi Luo, Michael A O'Donnell, Jose Assouline

Open access · goldAbstract read
In one paragraph

Article in Cancer nanotechnology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.1field-weighted citation impact, top 7% 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

15 citing papers in PubMed, 35 citations in OpenAlex.

  1. Review
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  4. Review
  5. Nanoparticle-Based Techniques for Bladder Cancer Imaging: A Review.International journal of molecular sciences · 2023
    Review
  6. Review
  7. Current applications of nanomaterials in urinary system tumors.Frontiers in bioengineering and biotechnology · 2023
    Review
  8. Article
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  15. A Murine Orthotopic Bladder Tumor Model and Tumor Detection System.Journal of visualized experiments : JoVE · 2017
    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 1 institution in 1 country.

Sean K SweeneyDepartment of Biomedical Engineering, University of Iowa, 1402 Seamans Center for the Engineering Arts and Sciences, Iowa City, IA 52242 USA ; NanoMedTrix, LLC, 2500 Crosspark Road, Suite E119, Coralville, IA 52241-4710 USA.
Yi LuoDepartment of Urology, University of Iowa, Roy J. and Lucille A. Carver College of Medicine, 3204 Medical Education Research Facility, 375 Newton Road, Iowa City, IA 52242 USA.
Michael A O'DonnellDepartment of Urology, University of Iowa, Roy J. and Lucille A. Carver College of Medicine, 200 Hawkins Dr., Iowa City, IA 52242 USA.
Jose AssoulineDepartment of Biomedical Engineering, University of Iowa, 1402 Seamans Center for the Engineering Arts and Sciences, Iowa City, IA 52242 USA ; NanoMedTrix, LLC, 2500 Crosspark Road, Suite E119, Coralville, IA 52241-4710 USA.
University of Iowa · US

Funding

Viral VectorP30CA086862 · NCI · UNIVERSITY OF IOWA · PI Douglas Robert Spitz · 2000 to 2026
$70.0M
6 · The paper itself

Abstract

backgroundDespite being one of the most common cancers, bladder cancer is largely inefficiently and inaccurately staged and monitored. Current imaging methods detect cancer only when it has reached "visible" size and has significantly disrupted the structure of the organ. By that time, thousands of cells will have proliferated and perhaps metastasized. Repeated biopsies and scans are necessary to determine the effect of therapy on cancer growth. In this report, we describe a novel approach based on multimodal nanoparticle contrast agent technology and its application to a preclinical animal model of bladder cancer. The innovation relies on the engineering core of mesoporous silica with specific scanning contrast properties and surface modification that include fluorescence and magnetic resonance imaging (MRI) contrast. The overall dimensions of the nano-device are preset at 80-180 nm, depending on composition with a pore size of 2 nm.

methodsTo facilitate and expedite discoveries, we combined a well-known model of bladder cancer and our novel technology. We exposed nanoparticles to MB49 murine bladder cancer cells in vitro and found that 70 % of the cells were labeled by nanoparticles as measured by flow cytometry. The in vivo mouse model for bladder cancer is particularly well suited for T1- and T2-weighted MRI.

resultsUnder our experimental conditions, we demonstrate that the nanoparticles considerably improve tumor definition in terms of volumetric, intensity and structural characteristics. Important bladder tumor parameters can be ascertained, non-invasively, repetitively, and with great accuracy. Furthermore, since the particles are not biodegradable, repetitive injection is not required. This feature allows follow-up diagnostic evaluations during cancer treatment. Changes in MRI signals show that in situ uptake of free particles has predilection to tumor cells relative to normal bladder epithelium. The particle distribution within the tumors was corroborated by fluorescent microscopy of sections of excised bladders. In addition, MRI imaging revealed fibrous finger-like projections into the tumors where particles insinuated themselves deeply. This morphological characteristic was confirmed by fluorescence microscopy.

conclusionsThese findings may present new options for therapeutic intervention. Ultimately, the combination of real-time and repeated MRI evaluation of the tumors enhanced by nanoparticle contrast may have the potential for translation into human clinical studies for tumor staging, therapeutic monitoring, and drug delivery.

Indexed as

BladderCystoscopyMagnetic resonance imagingMesoporous silica nanoparticlesMouse orthotopic tumor modelTransitional cell carcinoma

Identifiers

PMID27217840
PMCPMC4846680
OpenAlexW2343683206

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.