Abstract
Background
The discovery of cancer biomarkers is pivotal for early diagnosis, therapeutic planning, and patient monitoring, offering a molecular insight into tumor characteristics. This study aimed to identify novel diagnostic and prognostic biomarkers for breast cancer (BC), gastric cancer (GC), and colorectal cancer (CRC) using a systems biology approach.
Methods
High-throughput gene expression analysis was conducted using the limma package in R Studio on datasets GSE134359, GSE54129, and GSE81558. Potential non-coding regulatory factors were identified through RNA and protein interaction analyses. Interaction networks were visualized with Cytoscape. Pathway enrichment analysis (Reactome) and survival analysis (GEPIA2) were utilized to elucidate the regulatory mechanisms of selected RNAs. The findings were validated using qRT-PCR experiments on GC, BC, and CRC samples.
Results
Bioinformatics analyses revealed significantly low expression of LCN6 in BC, CRC, and GC samples. Interaction analysis showed that lncRNAs MEG9 and MZF1-AS1 physically interact with LCN6 mRNA. Gene expression analysis using ENCORI indicated dysregulation of MEG9 and MZF1-AS1 in BC, CRC, and GC samples. Correlation analysis uncovered novel relationships between the expression of these lncRNAs and mRNA in the three cancer types. ROC analysis suggested that LCN6 and MZF1-AS1 are potential biomarkers for GC and CRC, while MEG9 could serve as a robust diagnostic biomarker for BC, CRC, and GC. Significant positive correlations were observed between MZF1-AS1 and MEG9 with LCN6 in BC samples and between LCN6 and MEG9 in GC samples, but no correlation was found in CRC samples.
Conclusion
LncRNAs MZF1-AS1 and MEG9 may regulate the expression of LCN6 in the "transport of fatty acid" signaling pathway, potentially influencing the risk of BC, GC, and CRC through this regulatory mechanism.