Evidence map›Paper›PMID 32158223›Full record

ArticleOncoTargets and therapy2020

KNDC1 Is a Predictive Marker of Malignant Transformation in Borderline Ovarian Tumors.

Shuqian Yu, Jiayu Shen, Jing Fei, Xiaoqing Zhu, Meichen Yin, Jianwei Zhou

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 6 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

6 authors at 2 institutions in 1 country.

Shuqian Yu *Department of Gynecology, Tongde Hospital of Zhejiang Province, Hangzhou, Zhejiang 310012, People's Republic of China.
Jiayu Shen *Department of Gynecology, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310051, People's Republic of China.
Jing FeiDepartment of Gynecology, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310051, People's Republic of China.
Xiaoqing ZhuDepartment of Gynecology, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310051, People's Republic of China.
Meichen YinDepartment of Gynecology, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310051, People's Republic of China.
Jianwei ZhouDepartment of Gynecology, The Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang 310051, People's Republic of China.
Second Affiliated Hospital of Zhejiang University · CNTongde Hospital of Zhejiang Province · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFew screening markers for malignant transformation in borderline ovarian tumors (BOT) have been clearly established. The kinase noncatalytic C-lobe domain containing 1 (KNDC1), a brain-specific Ras guanine nucleotide exchange factor, negatively regulates dendrite growth. However, the biological role and underlying mechanism of KNDC1 in human cancers, including ovarian cancer (OC), remain unknown.

methodsGene chip screening was used to detect the expression of

resultsWe observed that the expression of

conclusionCollectively, we conclude that KNDC1 might function as a tumor suppressor in ovarian tumors, inhibiting the proliferation of ovarian cells by suppressing ERK1/2 activity and hindering the malignant transformation of BOT.

Indexed as

borderline ovarian tumorKNDC1malignant transformationovarian cancertumor marker

Identifiers

PMID32158223
PMCPMC6986543
OpenAlexW3002443391

What OpenQuestion holds

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LicenceCC BY-NC
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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.