Evidence map›Paper›PMID 34209281›Full record

ArticleToxins2021

Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer.

Eiji Hishinuma, Muneaki Shimada, Naomi Matsukawa, Daisuke Saigusa, Bin Li, Kei Kudo, Keita Tsuji, Shogo Shigeta, Hideki Tokunaga, Kazuki Kumada and 9 more

Open access · goldAbstract read
In one paragraph

Article in Toxins, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 18% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  10. Dietary habits and plasma lipid concentrations in a general Japanese population.Metabolomics : Official journal of the Metabolomic Society · 2024
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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

19 authors at 3 institutions in 1 country.

Eiji HishinumaAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Muneaki ShimadaAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Naomi MatsukawaTohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan.
Daisuke SaigusaTohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan.
Bin LiAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Kei KudoDepartment of Obstetrics and Gynecology, Graduate School of Medicine, Tohoku University, Sendai 980-8574, Japan.
Keita TsujiDepartment of Obstetrics and Gynecology, Graduate School of Medicine, Tohoku University, Sendai 980-8574, Japan.
Shogo ShigetaDepartment of Obstetrics and Gynecology, Graduate School of Medicine, Tohoku University, Sendai 980-8574, Japan.
Hideki TokunagaDepartment of Obstetrics and Gynecology, Graduate School of Medicine, Tohoku University, Sendai 980-8574, Japan.
Kazuki KumadaAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Keigo KomineAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Hidekazu ShirotaAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Yuichi AokiTohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan.
Ikuko N MotoikeTohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan.
Jun YasudaTohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan.
Kengo KinoshitaAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Masayuki YamamotoAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Seizo KoshibaAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Nobuo YaegashiAdvanced Research Center for Innovations in Next Generation Medicine, Tohoku University, Sendai 980-8573, Japan.
Tohoku Medical Megabank Organization · JPTohoku University · JPTohoku University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual's current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.

Indexed as

MetabolomeAdultAgedBiomarkers, TumorCarcinoma, Ovarian EpithelialFemaleHumansMetabolomicsMiddle AgedOvarian NeoplasmsPrognosisToxins, BiologicalUremiaBiomarkers, TumorToxins, Biologicalbiomarkerepithelial ovarian cancermetabolomicsratio of kynurenine and tryptophanuremic toxins

Identifiers

PMID34209281
PMCPMC8309959
OpenAlexW3176057307

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.