Evidence map›Paper›PMID 33335254›Full record

ArticleScientific reports2020

Identification and validation of a miRNA-based prognostic signature for cervical cancer through an integrated bioinformatics approach.

Yumei Qi, Yo-Liang Lai, Pei-Chun Shen, Fang-Hsin Chen, Li-Jie Lin, Heng-Hsiung Wu, Pei-Hua Peng, Kai-Wen Hsu, Wei-Chung Cheng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Review
  2. [Prediction of immunotherapy targets for chronic cerebral hypoperfusion by bioinformatics method].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
    Article
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  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
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  11. Article
  12. Review
  13. Review
  14. Cervical Cancer, Papillomavirus, and miRNA Dysfunction.Frontiers in molecular biosciences · 2021
    Review
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

9 authors.

Yumei QiDepartment of Obstetrics and Gynecology, Suzhou BenQ Medical Center, The Affiliated BenQ Hospital, Nanjing Medical Medical University, Suzhou, 215010, Jiangsu, China.
Yo-Liang LaiGraduate Institute of Biomedical Science, China Medical University, Taichung, 40403, Taiwan, ROC.
Pei-Chun ShenResearch Center for Cancer Biology, China Medical University, Taichung, 40403, Taiwan, ROC.
Fang-Hsin ChenDepartment of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, 33302, Taiwan, ROC.
Li-Jie LinThe Ph.D. Program for Cancer Biology and Drug Discovery, China Medical University and Academia Sinica, Taichung, 40403, Taiwan, ROC.
Heng-Hsiung WuGraduate Institute of Biomedical Science, China Medical University, Taichung, 40403, Taiwan, ROC.
Pei-Hua PengCancer Genome Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan, 33302, Taiwan, ROC.
Kai-Wen HsuResearch Center for Cancer Biology, China Medical University, Taichung, 40403, Taiwan, ROC. kevin01182002@yahoo.com.tw.
Wei-Chung ChengGraduate Institute of Biomedical Science, China Medical University, Taichung, 40403, Taiwan, ROC. cwc0702@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical cancer is the fourth most common cancer in women worldwide. Increasing evidence has shown that miRNAs are related to the progression of cervical cancer. However, the mechanisms that affect the prognosis of cancer are still largely unknown. In the present study, we sought to identify miRNAs associated with poor prognosis of patient with cervical cancer, as well as the possible mechanisms regulated by them. The miRNA expression profiles and relevant clinical information of patients with cervical cancer were obtained from The Cancer Genome Atlas (TCGA). The selection of prognostic miRNAs was carried out through an integrated bioinformatics approach. The most effective miRNAs with synergistic and additive effects were selected for validation through in vitro experiments. Three miRNAs (miR-216b-5p, miR-585-5p, and miR-7641) were identified as exhibiting good performance in predicting poor prognosis through additive effects analysis. The functional enrichment analysis suggested that not only pathways traditionally involved in cancer but also immune system pathways might be important in regulating the outcome of the disease. Our findings demonstrated that a synergistic combination of three miRNAs may be associated, through their regulation of specific pathways, with very poor survival rates for patients with cervical cancer.

Indexed as

Computational BiologyFemaleGene Expression Regulation, NeoplasticHumansMicroRNAsPrognosisTranscriptomeUterine Cervical NeoplasmsMicroRNAsMIRN216 microRNA, humanMIRN585 microRNA, humanMIRN7641 microRNA, human

Identifiers

PMID33335254
PMCPMC7747620

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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.