Evidence map›Paper›PMID 34709744›Full record

ArticleClinical and translational medicine2021

Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model.

Simone Pisano, Stefania Lenna, Gareth D Healey, Fereshteh Izardi, Lucille Meeks, Yajaira S Jimenez, Oscar S Velazquez, Deyarina Gonzalez, Robert Steven Conlan, Bruna Corradetti

Open access · goldAbstract read
In one paragraph

Article in Clinical and translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.7field-weighted citation impact, top 31% 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

12 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. 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

10 authors at 3 institutions in 2 countries.

Simone PisanoDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, Texas.ORCID 0000-0002-5412-1241
Stefania LennaDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, Texas.
Gareth D HealeyCenter for NanoHealth, Swansea University Medical School, Swansea, UK.
Fereshteh IzardiCenter for NanoHealth, Swansea University Medical School, Swansea, UK.
Lucille MeeksDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, Texas.
Yajaira S JimenezDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, Texas.ORCID 0000-0003-4647-4546
Oscar S VelazquezDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, Texas.
Deyarina GonzalezCenter for NanoHealth, Swansea University Medical School, Swansea, UK.
Robert Steven ConlanDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, Texas.
Bruna CorradettiDepartment of Nanomedicine, Houston Methodist Research Institute, Houston, Texas.
Houston Methodist · USSwansea University · GBTexas A&M Health Science Center · US

Funding

HCRW_ HS-16-38
6 · The paper itself

Abstract

backgroundOvarian cancer (OC) is typically diagnosed late, associated with high rates of metastasis and the onset of ascites during late stage disease. Understanding the tumor microenvironment and how it impacts the efficacy of current treatments, including immunotherapies, needs effective in vivo models that are fully characterized. In particular, understanding the role of immune cells within the tumor and ascitic fluid could provide important insights into why OC fails to respond to immunotherapies. In this work, we comprehensively described the immune cell infiltrates in tumor nodules and the ascitic fluid within an optimized preclinical model of advanced ovarian cancer.

methodsGreen Fluorescent Protein (GFP)-ID8 OC cells were injected intraperitoneally into C57BL/6 mice and the development of advanced stage OC monitored. Nine weeks after tumor injection, mice were sacrificed and tumor nodules analyzed to identify specific immune infiltrates by immunohistochemistry. Ascites, developed in tumor bearing mice over a 10-week period, was characterized by mass cytometry (CyTOF) to qualitatively and quantitatively assess the distribution of the immune cell subsets, and their relationship to ascites from ovarian cancer patients.

resultsTumor nodules in the peritoneal cavity proved to be enriched in T cells, antigen presenting cells and macrophages, demonstrating an active immune environment and cell-mediated immunity. Assessment of the immune landscape in the ascites showed the predominance of CD8

conclusionsWe performed, for the first time, a multiparametric analysis of the ascitic fluid and specifically identify immune cell populations in the peritoneal cavity of mice with advanced OC. Data obtained highlights the impact of CytOF as a diagnostic tool for this malignancy, with the opportunity to concomitantly identify novel targets, and define personalized therapeutic options.

Indexed as

AnimalsAscitesDisease Models, AnimalFemaleMiceMice, Inbred C57BLOvarian NeoplasmsTumor MicroenvironmentascitesCyTOFimmunotherapymass cytometrymodelovarian cancerperitoneal cancers

Identifiers

PMID34709744
PMCPMC8506632
OpenAlexW3206402442

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.