Evidence map›Paper›PMID 30607157›Full record

ArticleJournal of breast cancer2018

Identification and Validation of Circulating MicroRNA Signatures for Breast Cancer Early Detection Based on Large Scale Tissue-Derived Data.

Xiaokang Yu, Jinsheng Liang, Jiarui Xu, Xingsong Li, Shan Xing, Huilan Li, Wanli Liu, Dongdong Liu, Jianhua Xu, Lizhen Huang and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of breast cancer, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Exploring research progress in studying serum exosomal miRNA-21 as a molecular diagnostic marker for breast cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2024
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  14. The Role of MiRNA in Cancer: Pathogenesis, Diagnosis, and Treatment.Methods in molecular biology (Clifton, N.J.) · 2022
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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

11 authors.

Xiaokang YuSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Jinsheng LiangSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Jiarui XuDepartment of Laboratory Science, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Xingsong LiSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Shan XingDepartment of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Huilan LiDepartment of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Wanli LiuDepartment of Laboratory Medicine, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.
Dongdong LiuDepartment of Laboratory Science, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Jianhua XuDepartment of Laboratory Science, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Lizhen HuangSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.
Hongli DuSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou, China.ORCID https://orcid.org/0000-0002-6419-0160

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeBreast cancer is the most commonly occurring cancer among women worldwide, and therefore, improved approaches for its early detection are urgently needed. As microRNAs (miRNAs) are increasingly recognized as critical regulators in tumorigenesis and possess excellent stability in plasma, this study focused on using miRNAs to develop a method for identifying noninvasive biomarkers.

methodsTo discover critical candidates, differential expression analysis was performed on tissue-originated miRNA profiles of 409 early breast cancer patients and 87 healthy controls from The Cancer Genome Atlas database. We selected candidates from the differentially expressed miRNAs and then evaluated every possible molecular signature formed by the candidates. The best signature was validated in independent serum samples from 113 early breast cancer patients and 47 healthy controls using reverse transcription quantitative real-time polymerase chain reaction.

resultsThe miRNA candidates in our method were revealed to be associated with breast cancer according to previous studies and showed potential as useful biomarkers. When validated in independent serum samples, the area under curve of the final miRNA signature (miR-21-3p, miR-21-5p, and miR-99a-5p) was 0.895. Diagnostic sensitivity and specificity were 97.9% and 73.5%, respectively.

conclusionThe present study established a novel and effective method to identify biomarkers for early breast cancer. And the method, is also suitable for other cancer types. Furthermore, a combination of three miRNAs was identified as a prospective biomarker for breast cancer early detection.

Indexed as

Breast neoplasmsData miningEarly detection of cancerMicroRNAsTumor biomarkers

Identifiers

PMID30607157
PMCPMC6310725

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