Evidence map›Paper›PMID 28120873›Full record

ArticleScientific reports2017

Novel approach for the detection of intraperitoneal micrometastasis using an ovarian cancer mouse model.

Ayesha B Alvero, Dongin Kim, Eydis Lima, Natalia J Sumi, Jung Seok Lee, Carlos Cardenas, Mary Pitruzzello, Dan-Arin Silasi, Natalia Buza, Tarek Fahmy and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

11 authors.

Ayesha B AlveroDivision of Reproductive Sciences, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven CT, USA.
Dongin KimDepartment of Biomedical Engineering, Yale University, New Haven, CT, USA.
Eydis LimaDivision of Reproductive Sciences, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven CT, USA.
Natalia J SumiDivision of Reproductive Sciences, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven CT, USA.
Jung Seok LeeDepartment of Biomedical Engineering, Yale University, New Haven, CT, USA.
Carlos CardenasDivision of Reproductive Sciences, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven CT, USA.
Mary PitruzzelloDivision of Reproductive Sciences, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven CT, USA.
Dan-Arin SilasiDivision of Reproductive Sciences, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven CT, USA.
Natalia BuzaDepartment of Pathology, Yale University School of Medicine, New Haven CT, USA.
Tarek FahmyDepartment of Biomedical Engineering, Yale University, New Haven, CT, USA.
Gil MorDivision of Reproductive Sciences, Department of Obstetrics, Gynecology and Reproductive Sciences, Yale University School of Medicine, New Haven CT, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Targeting the vascularity for delivery of inhibitors of metastasis in ovarian cancer.R01CA199004 · NCI · YALE UNIVERSITY · PI LIU, HAIPENG, MOR, GIL G · 2015 to 2019
$2.5M
NCATS NIH HHS UL1 TR001863NCI NIH HHS R01 CA199004
6 · The paper itself

Abstract

Patients with epithelial ovarian cancer have the best overall survival when maximal surgical effort is accomplished. However, despite numerous technological advances, surgery still relies primarily on white-light reflectance and the surgeon's vision. As such, micrometastases are usually missed and most patients clinically classified as a complete responder eventually recur and succumb to the disease. Our objective is to develop optical enhancers which can aid in the visualization of ovarian cancer micrometastasis. To this end we developed a nanoparticle (NP) platform, which is specifically targeted to the tumor microenvironment. Targeting is achieved by coating FDA-approved PLGA-PEG NP with the peptide sequence RGD, which binds with high affinity to αVβ3 integrins present in both the tumor-associated neovasculature and on the surface of ovarian cancer cells. Administration of the NP platform carrying fluorescent dyes to mice bearing intraperitoneal ovarian cancer allowed visualization of tumor-associated vasculature and its contrast against normal blood vessels. More importantly, we demonstrate the visualization of intraperitoneal ovarian cancer micrometastasis as small as 100 μm with optimal resolution. Finally, we demonstrate that the fluorescent dye cargo was able to penetrate intra-tumorally. Such modality could be used to allow microscopic surgical debulking to assure maximal surgical effort.

Indexed as

AnimalsDisease Models, AnimalFemaleMiceNeoplasm MicrometastasisOptical ImagingOvarian NeoplasmsPeritoneal NeoplasmsStaining and Labeling

Identifiers

PMID28120873
PMCPMC5264387

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Registered trials

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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.