Evidence map›Paper›PMID 33374439›Full record

ArticleInternational journal of molecular sciences2020

miR-497-5p Decreased Expression Associated with High-Risk Endometrial Cancer.

Ivana Fridrichova, Lenka Kalinkova, Miloslav Karhanek, Bozena Smolkova, Katarina Machalekova, Lenka Wachsmannova, Nataliia Nikolaieva, Karol Kajo

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 11% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 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

8 authors at 4 institutions in 1 country.

Ivana FridrichovaDepartment of Genetics, Cancer Research Institute, Biomedical Research Center of Slovak Academy of Sciences, 84505 Bratislava, Slovakia.ORCID 0000-0001-7581-1770
Lenka KalinkovaDepartment of Genetics, Cancer Research Institute, Biomedical Research Center of Slovak Academy of Sciences, 84505 Bratislava, Slovakia.
Miloslav KarhanekLaboratory of Bioinformatics, Biomedical Research Center of Slovak Academy of Sciences, 84505 Bratislava, Slovakia.
Bozena SmolkovaDepartment of Molecular Oncology, Cancer Research Institute, Biomedical Research Center of Slovak Academy of Sciences, 84505 Bratislava, Slovakia.ORCID 0000-0002-4906-5652
Katarina MachalekovaDepartment of Pathology, St. Elisabeth Cancer Institute, 81250 Bratislava, Slovakia.
Lenka WachsmannovaDepartment of Genetics, Cancer Research Institute, Biomedical Research Center of Slovak Academy of Sciences, 84505 Bratislava, Slovakia.ORCID 0000-0002-3000-6644
Nataliia NikolaievaDepartment of Genetics, Cancer Research Institute, Biomedical Research Center of Slovak Academy of Sciences, 84505 Bratislava, Slovakia.
Karol KajoDepartment of Pathology, St. Elisabeth Cancer Institute, 81250 Bratislava, Slovakia.
Cancer Research Institute of the Slovak Academy of Sciences · SKVysoká Škola Zdravotníctva a Sociálnej Práce sv. Alžbety · SKBiomedical Research Center of the Slovak Academy of Sciences · SKSlovak Academy of Sciences · SK

Funding

Ministry of Health of the Slovak Republic 2018/45-SAV-4Scientific Grant Agency of the Ministry of Education, Science, Research and Sport o fthe Slovak Republic and the Slovak Academy of Sciences 2/0036/19 and 2/0102/17
6 · The paper itself

Abstract

The current guidelines for diagnosis, prognosis, and treatment of endometrial cancer (EC), based on clinicopathological factors, are insufficient for numerous reasons; therefore, we investigated the relevance of miRNA expression profiles for the discrimination of different EC subtypes. Among the miRNAs previously predicted to allow distinguishing of endometrioid ECs (EECs) according to different grades (G) and from serous subtypes (SECs), we verified the utility of miR-497-5p. In ECs, we observed downregulated miR-497-5p levels that were significantly decreased in SECs, clear cell carcinomas (CCCs), and carcinosarcomas (CaSas) compared to EECs, thereby distinguishing EEC from SEC and rare EC subtypes. Significantly reduced miR-497-5p expression was found in high-grade ECs (EEC G3, SEC, CaSa, and CCC) compared to low-grade carcinomas (EEC G1 and mucinous carcinoma) and ECs classified as being in advanced FIGO (International Federation of Gynecology and Obstetrics) stages, that is, with loco-regional and distant spread compared to cancers located only in the uterus. Based on immunohistochemical features, lower miR-497-5p levels were observed in hormone-receptor-negative, p53-positive, and highly Ki-67-expressing ECs. Using a machine learning method, we showed that consideration of miR-497-5p expression, in addition to the traditional clinical and histopathologic parameters, slightly improves the prediction accuracy of EC diagnosis. Our results demonstrate that changes in miR-497-5p expression influence endometrial tumorigenesis and its evaluation may contribute to more precise diagnoses.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticAdenocarcinoma, Clear CellAdenocarcinoma, MucinousAdultAgedAged, 80 and overCarcinomaCarcinoma, EndometrioidCystadenocarcinoma, SerousEndometrial NeoplasmsEndometriumFemaleHumansMachine LearningMicroRNAsMicroRNAsMIRN497 microRNA, humanendometrioid endometrial carcinomamachine learning evaluationmiR-497-5p expressionrare subtypes of endometrial carcinomaserous endometrial carcinoma

Identifiers

PMID33374439
PMCPMC7795869
OpenAlexW3116115096

What Socratic 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 Socratic graph.