Evidence map›Paper›PMID 31976020›Full record

ArticleDisease markers2019

Identification of miRNA-Based Signature as a Novel Potential Prognostic Biomarker in Patients with Breast Cancer.

Jia Tang, Wei Ma, Qinlong Zeng, Jieliang Tan, Keshen Cao, Liangping Luo

Abstract read
In one paragraph

Article in Disease markers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Mechanistic study on the inhibition of triple-negative breast cancer progression by LncRNA TFAP2A-AS1 through the regulation of miR-6892/PHGDH.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025
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  4. Delineating highly transcribed noncoding elements landscape in breast cancer.Computational and structural biotechnology journal · 2023
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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

6 authors.

Jia TangMedical Genetics Center, Jiangmen Maternity and Child Health Care Hospital, Jiangmen, Guangdong 529000, China.
Wei MaDepartment of Biology, School of Basic Medicine, Jiamusi University, Jiamusi, Heilongjiang 154007, China.
Qinlong ZengMedical Genetics Center, Jiangmen Maternity and Child Health Care Hospital, Jiangmen, Guangdong 529000, China.
Jieliang TanMedical Genetics Center, Jiangmen Maternity and Child Health Care Hospital, Jiangmen, Guangdong 529000, China.
Keshen CaoMedical Genetics Center, Jiangmen Maternity and Child Health Care Hospital, Jiangmen, Guangdong 529000, China.
Liangping LuoDepartment of Medical Imaging Center, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, Guangdong 510080, China.ORCID https://orcid.org/0000-0002-2359-9066

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To identify the novel, noninvasive biomarkers to assess the outcome and prognosis of breast cancer (BC), patients with high sensitivity and specificity are greatly desired. Herein, the miRNA expression profile and matched clinical features of BC patients were extracted from The Cancer Genome Atlas (TCGA) database. The preliminary candidates were screened out by the univariate Cox regression test. Then, with the help of LASSO Cox regression analysis, the hsa-let-7b, hsa-mir-101-2, hsa-mir-135a-2, hsa-mir-22, hsa-mir-30a, hsa-mir-31, hsa-mir-3130-1, hsa-mir-320b-1, hsa-mir-3678, hsa-mir-4662a, hsa-mir-4772, hsa-mir-493, hsa-mir-556, hsa-mir-652, hsa-mir-6733, hsa-mir-874, and hsa-mir-9-3 were selected to construct the overall survival (OS) predicting signature, while the hsa-mir-130a, hsa-mir-204, hsa-mir-217, hsa-mir-223, hsa-mir-24-2, hsa-mir-29b-1, hsa-mir-363, hsa-mir-5001, hsa-mir-514a-1, hsa-mir-624, hsa-mir-639, hsa-mir-659, and hsa-mir-6892 were adopted to establish the recurrence-free survival (RFS) predicting signature. Referring to the median risk scores generated by the OS and RFS formulas, respectively, subgroup patients with high risk were strongly related to a poor OS and RFS revealed by Kaplan-Meier (K-M) plots. Meanwhile, receiver operating curve (ROC) analysis validated the accuracy and stability of these two signatures. When stratified by clinical features, such as tumor stage, age, and molecular subtypes, we found that the miRNA-based OS and RFS classifiers were still significant in predicting OS/RFS and showed the best predictive values than any other features. Besides, functional prediction analyses showed that these targeted genes of the enrolled miRNAs were enriched in cancer-associated pathways, such as MAPK/RTK, Ras, and PI3K-Akt signaling pathways. In summary, our observations demonstrate that the novel miRNA-based OS and RFS signatures are independent prognostic indicators for BC patients and worthy to be validated by further prospective studies.

Indexed as

Biomarkers, TumorBreast NeoplasmsDisease-Free SurvivalFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansKaplan-Meier EstimateMicroRNAsPrognosisProspective StudiesROC CurveBiomarkers, TumorMicroRNAs

Identifiers

PMID31976020
PMCPMC6954483

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Registered trials

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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.