Dysregulated ceRNA network modulated by copy number variation‐driven lncRNAs in breast cancer: A comprehensive analysis

Abstract

Breast cancer is a malignancy harmful to physical and mental health in women, with quite high mortality. Copy number variations (CNVs) are vital factors affecting the progression of breast cancer. Detecting CNVs in breast cancer to predict the prognosis of patients has become a promising approach to accurate treatment in recent years. The differential analysis was performed on CNVs of long noncoding RNAs (lncRNAs) as well as the expression of lncRNAs, microRNAs (miRNAs) and mRNAs in normal tissue and breast tumor tissue based on The Cancer Genome Atlas (TCGA) database. The CNV-driven lncRNAs were identified by the Kruskal-Wallis test.Meanwhile, a competitive endogenous RNA (ceRNA) network regulated by CNVdriven lncRNA was constructed. As the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed, the mRNAs in the dysregulated ceRNA network were mainly enriched in the biological functions and signaling pathways, including the Focal Adhesion-PI3K-Akt-mTOR-signaling pathway, the neuronal system, metapathway biotransformation Phase I and II and blood circulation, etc. The relationship between the CNVs of five lncRNAs and their gene expression in the ceRNA network was analyzed via a chi-square test, which confirmed that except for LINC00243, the expression of four lncRNAs was notably correlated with the CNVs.The survival analysis revealed that only the copy number gain of LINC00536 was evidently related to the poor prognosis of patients. The CIBERSORT algorithm showed that five lncRNAs were correlated with the abundance of immune cell infiltration and immune checkpoints. In a word, by analyzing CNV-driven lncRNAs and the ceRNA network regulated by these lncRNAs, this study explored the mechanism of breast cancer and provided novel insights into new biomarkers.

Genomic Alterations Affecting Competitive Endogenous RNAs (ceRNAs) and Regulatory Networks (ceRNETs) with Clinical Implications in Triple-Negative Breast Cancer (TNBC)

“…CNV is a substantial factor in the progression of cancers, including breast cancer [ 14 ], and has been associated with lymph node metastasis in TNBC [ 35 ]. While CNV of lncRNAs is less common than that of coding genes, CNV in intergenic regions is quite common, accounting for over 60% of CNV in breast cancer [ 5 ].…”

“…Specific examples of CNV-altered ceRNA species have been identified in breast cancer and TNBC. CNV-altered ceRNET-associated mRNAs in breast cancer were shown to have a biological function and pathway enrichment for Focal Adhesion Kinase FAK-PI3K-Akt–mTOR-signaling [ 14 ]. Gain in copy number of one of the lncRNAs in the ceRNA network (LINC00536) was found to correlate with poor prognosis.…”

“…Within these networks, predicted regulatory ceRNAs for cancer driver genes were tested, with 68% of the driver genes being downregulated upon silencing of their respective inferred ceRNA regulators. Zhu et al showed that ceRNA networks are modulated by CNV in lncRNAs in breast cancer [ 14 ]. These networks were enriched in focal Adhesion FAK-PI3K-Akt–mTOR signaling.…”

“…Further, alteration in non-coding genes is an important but previously overlooked mechanism of post-transcriptional regulation in cancer. Specific CNV-altered lncRNAs with corresponding expression alterations have been identified in breast cancer [ 14 ]. Some of these lncRNAs regulate functions that are key to cancer pathogenesis and therapy, such as growth signaling, immune infiltration and immune checkpoints [ 14 ].…”

“…Specific CNV-altered lncRNAs with corresponding expression alterations have been identified in breast cancer [ 14 ]. Some of these lncRNAs regulate functions that are key to cancer pathogenesis and therapy, such as growth signaling, immune infiltration and immune checkpoints [ 14 ]. In addition to transcriptional regulating functions, including binding to RNA-binding proteins and RNA polymerase II, circRNAs that may be affected by genomic alteration can influence ceRNA networks by acting as miRNA sponges [ 4 ].…”