AUTHOR=Bahramy Afshin , Zafari Narges , Rajabi Fatemeh , Aghakhani Amirhossein , Jayedi Ahmad , Khaboushan Alireza Soltani , Zolbin Masoumeh Majidi , Yekaninejad Mir Saeed 

TITLE=Prognostic and diagnostic values of non-coding RNAs as biomarkers for breast cancer: An umbrella review and pan-cancer analysis

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2023.1096524

DOI=10.3389/fmolb.2023.1096524

ISSN=2296-889X

ABSTRACT=Background: Although numerous studies have been conducted to assess the prognostic and diagnostic value of non-coding RNAs (ncRNAs) in breast cancer, their overall potential remains unclear. In this field of study, there are various systematic reviews and meta-analysis studies that report tons of data. In this study, we tried to collect all these systematic review and meta-analysis studies in order to re-analyze their data without any restriction to breast cancer or non-coding RNA type to make it as comprehensive as possible.
Methods: Three databases were searched to find any relevant meta-analysis studies. Finally, after the precise screening of titles, abstracts, and full-text, the quality of all included studies was assessed by the AMSTAR tool. All the required data including HRs, Sens, and Spec were extracted for further analysis and all analyses were done using STATA.
Results: In the prognostic part, our initial search of three databases resulted in 10,548 articles of which 57 studies were included in the current study. We assessed the correlation of ncRNAs expression with different survival outcomes in breast cancer patients: OS (HR=1.521), DFS (HR=1.33), RFS (HR=1.66), PFS (HR=1.71), MFS (HR=0.90), and DSS (HR=0.37). After eliminating poor-quality studies, the results did not change significantly. In the diagnostic part, 22 articles and 30 datasets were retrieved. The quality of all studies was determined. The bivariate and random-effect models were used to assess the diagnostic value of ncRNAs. The overall AUC of ncRNAs in distinguishing patients is 0.88 (SENS: 80% and SPEC: 82%). There was no difference in the potential of single and combined ncRNAs in differentiating BC patients. However, the overall potential of miRNAs is higher than that of LncRNAs. No publication bias was found in the current study. Nine miRNAs, four LncRNAs, and five gene targets showed significant OS and RFS between normal and cancer patients based on pan-cancer data analysis, demonstrating their potential prognostic value.
Conclusion: The present umbrella review showed that ncRNAs, including LncRNAs and miRNAs, can be used as prognostic and diagnostic biomarkers for breast cancer patients, regardless of the sample sources, ethnicity of patients, and the subtype of breast cancer.