ArticleDisease markers2019
Identification of miRNA-Based Signature as a Novel Potential Prognostic Biomarker in Patients with Breast Cancer.
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.
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Who cites it
21 citing papers in PubMed.
- 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.] · 2025Article
- Identification of potential crucial genes and mechanisms associated with metabolically unhealthy obesity based on the gene expression profile.Frontiers in genetics · 2025Article
- Analysis and Validation of the Prognosis ability of the M7GRelated miRNAs in Lung Adenocarcinoma.Asian Pacific journal of cancer prevention : APJCP · 2023Article
- Delineating highly transcribed noncoding elements landscape in breast cancer.Computational and structural biotechnology journal · 2023Article
- Interpretable Machine Learning Models to Predict the Resistance of Breast Cancer Patients to Doxorubicin from Their microRNA Profiles.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- An Eleven-microRNA Signature Related to Tumor-Associated Macrophages Predicts Prognosis of Breast Cancer.International journal of molecular sciences · 2022Article
- Review
- Identification and validation of a novel prognostic signature based on transcription factors in breast cancer by bioinformatics analysis.Gland surgery · 2022Article
- Epigenetic Regulation in Exposome-Induced Tumorigenesis: Emerging Roles of ncRNAs.Biomolecules · 2022Review
- Identification of novel biomarkers in breast cancer via integrated bioinformatics analysis and experimental validation.Bioengineered · 2021Article
- Article
- Review
- The Role of MicroRNA as Clinical Biomarkers for Breast Cancer Surgery and Treatment.International journal of molecular sciences · 2021Review
- Article
- Article
- A novel miRNA-based classification model of risks and stages for clear cell renal cell carcinoma patients.BMC bioinformatics · 2021Article
- Systematic Understanding of the Mechanism of Baicalin against Gastric Cancer Using Transcriptome Analysis.BioMed research international · 2021Article
- Network analysis of miRNA targeting m6A-related genes in patients with esophageal cancer.PeerJ · 2021Article
- A Novel TCGA-Validated, MiRNA-Based Signature for Prediction of Breast Cancer Prognosis and Survival.Frontiers in cell and developmental biology · 2021Article
- MicroRNA-Dependent Targeting of RSU1 and the IPP Adhesion Complex Regulates the PTEN/PI3K/AKT Signaling Pathway in Breast Cancer Cell Lines.International journal of molecular sciences · 2020Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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