Evidence map›Paper›PMID 34424503›Full record

ArticleAdvances in therapy2021

The High Expression of RRM2 Can Predict the Malignant Transformation of Endometriosis.

Binkai Yang, Tian Wang, Na Li, Wenwen Zhang, Yuanjing Hu

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Article in Advances in therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Binkai YangGraduate School of Tianjin Medical University, Tianjin Medical University, Tianjin, China.
Tian WangDepartment of Gynecological Oncology, Tianjin Central Hospital of Gynecology Obstetrics, No. 156 Nankai San Ma Road, Nankai District, Tianjin, China.
Na LiDepartment of Gynecological Oncology, Tianjin Central Hospital of Gynecology Obstetrics, No. 156 Nankai San Ma Road, Nankai District, Tianjin, China.
Wenwen ZhangDepartment of Gynecological Oncology, Tianjin Central Hospital of Gynecology Obstetrics, No. 156 Nankai San Ma Road, Nankai District, Tianjin, China.
Yuanjing HuDepartment of Gynecological Oncology, Tianjin Central Hospital of Gynecology Obstetrics, No. 156 Nankai San Ma Road, Nankai District, Tianjin, China. hyj_tdj@sina.com.ORCID http://orcid.org/0000-0002-4631-4115
Tianjin Central Hospital of Gynecology Obstetrics · CNTianjin Nankai Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionA large number of epidemiological studies have revealed that women with endometriosis (EMS) have a higher risk of developing endometriosis-associated ovarian cancer (EAOC). At present, there are few studies on predicting the malignant transformation of ovarian endometriosis (OE). The purpose of this study is to identify and verify the molecules that may be able to predict the malignant transformation of OE.

methodsThe gene expression profiles of ovarian cancer and OE were downloaded from Gene Expression Omnibus (GEO), and a common hub gene ribonucleotide reductase M2 (RRM2) was identified. A total of 44 patients with EAOC and 44 with OE were enrolled in this study. Immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction (RT-qPCR) were used to detect the expression of RRM2, while the relationship between RRM2 and Ki-67 was analyzed by IHC co-localization.

resultsBioinformatics analysis showed that the expression of RRM2 was low in EMS and high in ovarian cancer. RRM2 was obviously positively expressed in eutopic endometrium (EU), ectopic endometrium (EC), and cancer tissues of EAOC patients. The IHC signal and mRNA levels of RRM2 were higher in the EC of EAOC patients compared with OE patients (P < 0.01). In addition, there was a correlation between the expression of RRM2 and Ki-67 in EC of EAOC patients (P < 0.01).

conclusionThe upregulated expression of RRM2 in the EC of OE patients may indicate malignant transformation. High expression of RRM2 promotes abnormal proliferation of histiocytes. RRM2 can be used as a potential marker of malignant transformation of OE.

Indexed as

EndometriosisOvarian NeoplasmsCarcinoma, Ovarian EpithelialCell Transformation, NeoplasticFemaleHumansRibonucleoside Diphosphate ReductaseRibonucleoside Diphosphate Reductaseribonucleotide reductase M2Ectopic endometriumEndometriosis-associated ovarian cancerHub geneOvarian endometriosisrrm2

Identifiers

PMID34424503
OpenAlexW3193631208

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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.