Evidence map›Paper›PMID 36503580›Full record

ArticleJournal of translational medicine2022

Acidic ascites inhibits ovarian cancer cell proliferation and correlates with the metabolomic, lipidomic and inflammatory phenotype of human patients.

Qianlu Yang, Gyuntae Bae, Giorgi Nadiradze, Arianna Castagna, Georgy Berezhnoy, Laimdota Zizmare, Aditi Kulkarni, Yogesh Singh, Frank J Weinreich, Stefan Kommoss and 2 more

Open access · goldAbstract read
In one paragraph

Article in Journal of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

10 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

12 authors at 2 institutions in 1 country.

Qianlu YangNational Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany.
Gyuntae BaeDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany.
Giorgi NadiradzeNational Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany.
Arianna CastagnaNational Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany.
Georgy BerezhnoyDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany.
Laimdota ZizmareDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany.ORCID https://orcid.org/0000-0001-7208-3659
Aditi KulkarniDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany.
Yogesh SinghInstitute of Medical Genetics and Applied Genomics, University Hospital Tübingen, Tübingen, Germany.
Frank J WeinreichNational Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany.
Stefan KommossResearch Institute of Women's Health, Women's Hospital, University Hospital Tübingen, Tübingen, Germany.
Marc A ReymondNational Center for Pleura and Peritoneum, NCT South-West Germany, Tübingen, Germany.
Christoph TrautweinDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, Tübingen, Germany. christoph.trautwein@med.uni-tuebingen.de.ORCID http://orcid.org/0000-0003-4672-6395
Siemens (Germany) · DEUniversity Children's Hospital Tübingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe poor prognosis of ovarian cancer patients is strongly related to peritoneal metastasis with the production of malignant ascites. However, it remains largely unclear how ascites in the peritoneal cavity influences tumor metabolism and recurrence. This study is an explorative approach aimed at for a deeper molecular and physical-chemical characterization of malignant ascites and to investigate their effect on in vitro ovarian cancer cell proliferation.

methodsThis study included 10 malignant ascites specimens from patients undergoing ovarian cancer resection. Ascites samples were deeply phenotyped by

resultsThe overall extracellular (peritoneal) environment was alkaline, with pH of ascites at stage II-III = 7.51 ± 0.16, and stage IV = 7.78 ± 0.16. Ovarian cancer spheroids grew rapidly in a slightly alkaline environment. Decreasing pH of the cell culture medium suppressed tumor features, metabolic activity, adhesion, anti-apoptosis, and migratory ability. However, 10% ascites could prevent tumor cells from being affected by acidic pH. Metabolomics analysis identified stage IV patients had significantly higher concentrations of alanine, isoleucine, phenylalanine, and glutamine than stage II-III patients, while stage II-III patients had significantly higher concentrations of 3-hydroxybutyrate. pH was positively correlated with acetate, and acetate positively correlated with lipid compounds. IL-8 was positively correlated with lipid metabolites and acetate. Glutathione and carnitine were negatively correlated with cytokines IL-6 and chemokines (IL-8 & MCP-1).

conclusionAlkaline malignant ascites facilitated ovarian cancer progression. Additionally, deep ascites phenotyping by metabolomics and cytokine investigations allows for a refined stratification of ovarian cancer patients. These findings contribute to the understanding of ascites pathology in ovarian cancer.

Indexed as

Ovarian NeoplasmsPeritoneal NeoplasmsAscitesCell ProliferationCytokinesFemaleHumansInterleukin-8LipidsCytokinesInterleukin-8LipidsCell cultureCytokineIn vitroIn vivoMetabolic profilePeritoneal fluidpH

Identifiers

PMID36503580
PMCPMC9743551
OpenAlexW4311122984

What OpenQuestion holds

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LicenceCC BY
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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.