Evidence map›Paper›PMID 35077462›Full record

ArticlePloS one2022

CKMT1A is a novel potential prognostic biomarker in patients with endometrial cancer.

Yaping Wang, Shujun Zhao, Qiaohong Qin, Xiang Gao, Xinlu Zhang, Min Zhang, Yi Jiang, Xiaorong Ji, Hai Zhu, Xin Zhao and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 57% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 1 institution in 1 country.

Yaping WangGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.ORCID 0000-0002-8058-0353
Shujun ZhaoGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Qiaohong QinGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Xiang GaoGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Xinlu ZhangGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Min ZhangGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Yi JiangGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Xiaorong JiGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Hai ZhuGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Xin ZhaoThe Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Hongyu LiGynecologic Oncology, the Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Third Affiliated Hospital of Zhengzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe International Federation of Gynecology and Obstetrics (FIGO) stage remains the standard staging system for the assessment of endometrial cancer (EC) prognosis. Thus, we aim to identify the significant genes or biomarkers associated with the stage of endometrial cancer, which may also help reveal the mechanism of EC progression and assess the prognosis of patients with EC. MATERIALS AND

methodsWe compared the mRNA expression levels of EC patients with stages I and II as well as stages III and IV in the Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) of EC patients at different stages were selected by volcano plot and Venn analysis. Gene Ontology (GO) and Pathways were applied to analyze the identified genes. Protein protein interaction (PPI) network was employed to identify the correlation. The survival analyses based on TCGA database were conducted for further screening. The Human Protein Atlas, quantitative PCR and immunohistochemistry were utilized to confirm the differences in expression of DEGs in endometrial cancer samples at different FIGO stages.

resultsCKMT1A was identified as a candidate gene. Through survival analyses, we found that CKMT1A may be a poor prognostic factor in the overall survival of endometrial cancer patients. GO and Pathways revealed that CKMT1A is closely associated with the metabolic process. More importantly, Human Protein Atlas and quantitative PCR confirmed the differences in expression of CKMT1A in endometrial cancer samples at different FIGO stages.

conclusionIn summary, this study shows that CKMT1A is a newly identified essential tumor progression regulator of endometrial cancer, which may give rise to novel therapeutic strategies in the management of endometrial cancer patients to prolong its prognosis and prevent tumor progression.

Indexed as

Biomarkers, TumorCreatine KinaseDatabases, Nucleic AcidEndometrial NeoplasmsGene Expression Regulation, EnzymologicGene Expression Regulation, NeoplasticNeoplasm ProteinsDisease-Free SurvivalFemaleHumansMiddle AgedNeoplasm StagingSurvival RateBiomarkers, TumorCKMT1A protein, humanCreatine KinaseNeoplasm Proteins

Identifiers

PMID35077462
PMCPMC8789190
OpenAlexW4206917663

What Socratic holds

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LicenceCC BY
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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 Socratic graph.