Evidence map›Paper›PMID 32681052›Full record

ArticleScientific reports2020

Ascites-induced compression alters the peritoneal microenvironment and promotes metastatic success in ovarian cancer.

Marwa Asem, Allison Young, Carlysa Oyama, Alejandro ClaureDeLaZerda, Yueying Liu, Matthew J Ravosa, Vijayalaxmi Gupta, Andrea Jewell, Dineo Khabele, M Sharon Stack

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

28 citing papers in PubMed, 45 citations in OpenAlex.

  1. Niches in cancer: from primary tumors to metastatic disease.Journal of hematology & oncology · 2026
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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

10 authors at 2 institutions in 1 country.

Marwa AsemDepartment of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, IN, USA.
Allison YoungHarper Cancer Research Institute, University of Notre Dame, 1234 N. Notre Dame Ave., A200 Harper Hall, South Bend, IN, 46617, USA.
Carlysa OyamaHarper Cancer Research Institute, University of Notre Dame, 1234 N. Notre Dame Ave., A200 Harper Hall, South Bend, IN, 46617, USA.
Alejandro ClaureDeLaZerdaHarper Cancer Research Institute, University of Notre Dame, 1234 N. Notre Dame Ave., A200 Harper Hall, South Bend, IN, 46617, USA.
Yueying LiuDepartment of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, IN, USA.
Matthew J RavosaHarper Cancer Research Institute, University of Notre Dame, 1234 N. Notre Dame Ave., A200 Harper Hall, South Bend, IN, 46617, USA.
Vijayalaxmi GuptaDepartment of Obstetrics & Gynecology, Medical Center, University of Kansas, Kansas City, USA.
Andrea JewellDepartment of Obstetrics & Gynecology, Medical Center, University of Kansas, Kansas City, USA.
Dineo KhabeleDepartment of Obstetrics & Gynecology, Medical Center, University of Kansas, Kansas City, USA.
M Sharon StackDepartment of Chemistry & Biochemistry, University of Notre Dame, Notre Dame, IN, USA. sstack@nd.edu.
University of Notre Dame · USUniversity of Kansas Medical Center · US

Funding

Transgenic & Gene-Targeting Shared ResourceP30CA168524 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI NICOLE L NOLLEN · 2012 to 2026
$40.1M
Receptor Cross-Talk in Early Metastatic DisseminationR01CA109545 · NCI · UNIVERSITY OF NOTRE DAME · PI STACK, MARY SHARON · 2006 to 2022
$4.3M
Macrophage-based ovarian cancer immunotherapyR01CA214043 · NCI · VANDERBILT UNIVERSITY · PI GIORGIO, TODD D, KHABELE, DINEO · 2017 to 2021
$1.9M
Targeting Cyclin E in Ovarian Cancer with Histone Deacetylase InhibitorsR21CA210210 · NCI · UNIVERSITY OF KANSAS MEDICAL CENTER · PI KHABELE, DINEO · 2017 to 2018
$384k
Aging and the Ovarian Tumor MicroenvironmentU01CA236979 · NCI · UNIVERSITY OF NOTRE DAME · PI STACK, MARY SHARON · 2019 to 2020
$232k
NCI NIH HHS P30 CA168524NCI NIH HHS R01 CA109545NCI NIH HHS R01 CA214043NCI NIH HHS R21 CA210210NCI NIH HHS U01 CA236979
6 · The paper itself

Abstract

The majority of women with recurrent ovarian cancer (OvCa) develop malignant ascites with volumes that can reach > 2 L. The resulting elevation in intraperitoneal pressure (IPP), from normal values of 5 mmHg to as high as 22 mmHg, causes striking changes in the loading environment in the peritoneal cavity. The effect of ascites-induced changes in IPP on OvCa progression is largely unknown. Herein we model the functional consequences of ascites-induced compression on ovarian tumor cells and components of the peritoneal microenvironment using a panel of in vitro, ex vivo and in vivo assays. Results show that OvCa cell adhesion to the peritoneum was increased under compression. Moreover, compressive loads stimulated remodeling of peritoneal mesothelial cell surface ultrastructure via induction of tunneling nanotubes (TNT). TNT-mediated interaction between peritoneal mesothelial cells and OvCa cells was enhanced under compression and was accompanied by transport of mitochondria from mesothelial cells to OvCa cells. Additionally, peritoneal collagen fibers adopted a more linear anisotropic alignment under compression, a collagen signature commonly correlated with enhanced invasion in solid tumors. Collectively, these findings elucidate a new role for ascites-induced compression in promoting metastatic OvCa progression.

Indexed as

Tumor MicroenvironmentAnimalsAnisotropyAscitesCell AdhesionCell Line, TumorCollagenEpitheliumFemaleHumansMice, Inbred C57BLMitochondriaModels, BiologicalNanotubesNeoplasm MetastasisOvarian NeoplasmsCollagen

Identifiers

PMID32681052
PMCPMC7367827
OpenAlexW3043325281

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.