Identification of a Circular RNA as a Potential Diagnostic and Prognostic Biomarker in Breast Cancer Through Integrated Bioinformatic and Experimental Analyses
TL;DR
This study presents a systematic framework for translating high‐throughput RNA data into quantifiable biomarker candidates with potential clinical relevance and revealed that hsa_circ_0000231 is significantly upregulated in BC tissues compared to adjacent non‐cancerous tissues.
Abstract
ABSTRACT Breast cancer (BC), which has complex molecular subgroups that contribute to a range of clinical outcomes, is still one of the top causes of morbidity and death among women globally. This challenge necessitates ongoing research to improve early detection, treatment strategies, and patient outcomes. Recent research has shown that circular RNAs (circRNAs) influence gene expression through various mechanisms, particularly by functioning as competing endogenous RNAs (ceRNAs). Moreover, numerous circRNAs have been implicated in the initiation and progression of various tumor types. Yet, the expression and functional roles of multiple circRNAs remain largely unexplored in specific cancers. In this study, circRNA expression data from three Gene Expression Omnibus datasets were analyzed to identify candidate circRNAs associated with BC. Reverse‐transcription quantitative polymerase chain reaction (RT‐qPCR) was performed to validate the candidate circRNAs in tissue samples from 24 BC patients. Using bioinformatic analyses, downstream target microRNAs and messenger RNAs of these circRNAs were probed for the construction of a ceRNA regulatory network. A combined number of 40 distinct circRNAs with differential expression were identified, among which hsa_circ_0000231 and hsa_circ_0011385 were selected based on their novelty and potential to function as ceRNAs, and a corresponding ceRNA network was built. RT‐qPCR revealed that hsa_circ_0000231 is significantly upregulated in BC tissues compared to adjacent non‐cancerous tissues. Additionally, based on bioinformatic investigations, hsa_circ_0000231/hsa‐miR‐5683/cyclin B1 regulatory axis was predicted. By combining cross‐dataset computational screening with targeted experimental validation and diagnostic accuracy assessment, this study presents a systematic framework for translating high‐throughput RNA data into quantifiable biomarker candidates with potential clinical relevance. These findings may contribute to the identification of a novel diagnostic and prognostic biomarker in BC.