Evidence map›Paper›PMID 35158887›Full record

ArticleCancers2022

PD-L1 near Infrared Photoimmunotherapy of Ovarian Cancer Model.

Jiefu Jin, Ishwarya Sivakumar, Yelena Mironchik, Balaji Krishnamachary, Flonné Wildes, James D Barnett, Chien-Fu Hung, Sridhar Nimmagadda, Hisataka Kobayashi, Zaver M Bhujwalla and 1 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. 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
1.6field-weighted citation impact, top 19% 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

13 citing papers in PubMed, 11 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Jiefu JinDivision of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.ORCID 0000-0002-5318-1111
Ishwarya SivakumarDivision of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.ORCID 0000-0002-3429-1315
Yelena MironchikDivision of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Balaji KrishnamacharyDivision of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Flonné WildesDivision of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
James D BarnettDivision of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.ORCID 0000-0002-4692-6656
Chien-Fu HungSidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Sridhar NimmagaddaSidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.ORCID 0000-0002-6413-7191
Hisataka KobayashiMolecular Imaging Program, Center for Cancer Research, National Cancer Institute, US National Institutes of Health, Bethesda, MD 20814, USA.ORCID 0000-0003-1019-4112
Zaver M BhujwallaDivision of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Marie-France PenetDivision of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Johns Hopkins University · USNational Institutes of Health · US

Funding

Cancer-cell specific therapy: photo-immunotherapyZIABC011513 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI KOBAYASHI, HISATAKA · 2013 to 2025
$15.5M
Molecular Imaging and Theranostics of CancerR35CA209960 · NCI · JOHNS HOPKINS UNIVERSITY · PI BHUJWALLA, ZAVER M. · 2017 to 2023
$6.5M
Non-invasive Quantification of Dose-Exposure-Response of PD-L1 Therapeutics at the TumorR01CA236616 · NCI · JOHNS HOPKINS UNIVERSITY · PI NIMMAGADDA, SRIDHAR · 2018 to 2022
$2.3M
Emerson Collective Cancer FundNCI NIH HHS R01 CA236616NCI NIH HHS R35 CA209960NIH HHS R35 CA209960
6 · The paper itself

Abstract

(1) Background: Despite advances in surgical approaches and drug development, ovarian cancer is still a leading cause of death from gynecological malignancies. Patients diagnosed with late-stage disease are treated with aggressive surgical resection and chemotherapy, but recurrence with resistant disease is often observed following treatment. There is a critical need for effective therapy for late-stage ovarian cancer. Photoimmunotherapy (PIT), using an antibody conjugated to a near infrared (NIR) dye, constitutes an effective theranostic strategy to detect and selectively eliminate targeted cell populations. (2) Methods: Here, we are targeting program death ligand 1 (PD-L1) using NIR-PIT in a syngeneic mouse model of ovarian cancer. PD-L1 PIT-mediated cytotoxicity was quantified in RAW264.7 macrophages and ID8-Defb29-VEGF cells in culture, and in vivo with orthotopic ID8-Defb29-VEGF tumors. (3) Results: Treatment efficacy was observed both in vitro and in vivo. (4) Conclusions: Our data highlight the need for further investigations to assess the potential of using NIR-PIT for ovarian cancer therapy to improve the treatment outcome of ovarian cancer.

Indexed as

ovarian cancerphotoimmunotherapytheranostics

Identifiers

PMID35158887
PMCPMC8833482
OpenAlexW4210761805

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.