Comprehensive analysis of the aberrantly expressed lncRNA‑associated ceRNA network in breast cancer

Abstract

Previous studies have suggested that long non-coding RNAs (lncRNAs) are closely associated with human diseases, particularly cancer, including cancer of the lung, breast and stomach. A variety of lncRNAs are abnormally expressed in cancer and participate in several pathways including cell proliferation and apoptosis; these elements are closely associated with the development of cancer. The Cancer Genome Atlas (TCGA) is an important cancer database. It consists of clinical data, genomic variation, mRNA, microRNA (miRNA) and lncRNAs expression, methylation and other data for various types of human cancer. In the present study, differential expression of RNA was identified using the edgeR package. A total 1,222 RNA sequencing profiles from patients with breast cancer were downloaded from TCGA. A competing endogenous RNA (ceRNA) network was constructed for breast cancer based on miRcode and miRTarBase. The top 10 lncRNAs were selected using Cox regression analysis. Survival analysis was performed using Kaplan-Meier analysis. A total of 1,028 breast cancer-associated lncRNAs and 89 miRNAs (fold change >2; P<0.05) were identified; among these, 93 lncRNAs and 19 miRNAs were included in the ceRNA network. Subsequently, 10 basic lncRNAs were selected and their associations with overall survival were identified. In addition, 5 lncRNAs (ADAM metallopeptidase with thrombospondin type 1 motif 9-antisense RNA 1, AL513123.1, chromosome 10 open reading frame 126, long intergenic non-protein coding RNA 536 and Wilms tumor 1 antisense RNA) were identified to be significantly associated with overall survival (P<0.05, log rank test). These results suggested that mRNAs, lncRNAs and miRNAs were involved in pathological mechanisms of breast cancer. The newly-identified ceRNA network included 93 breast cancer-specific lncRNAs, 19 miRNAs and 27 mRNAs. The results of the present study highlight the potential of lncRNAs in understanding the development and pathogenesis of breast cancer, and suggest novel concepts and an experimental basis for the identification of prognostic biomarkers and therapeutic targets for breast cancer.

An in-silico method leads to recognition of hub genes and crucial pathways in survival of patients with breast cancer

“…Among the recently appreciated genes in this regard are long non-coding RNAs (lncRNAs) 6 . These transcripts are involved in the regulation of fundamental cell survival pathways and have functional interactions with proteins and other non-coding RNAs that participate in the pathogenesis of breast cancer 7 . Identification of such networks is an important step towards design of targeted therapies in breast cancer.…”

Exploring specific prognostic biomarkers in triple-negative breast cancer

“…This publicly available database provides over 20,000 primary tumor and matched normal samples spanning 33 cancer types. Researches based on this database have already led to improvements of diagnosis, prevention and treatment for cancers [20][21][22] .…”

3′-UTR Shortening Contributes to Subtype-Specific Cancer Growth by Breaking Stable ceRNA Crosstalk of Housekeeping Genes

“…Furthermore, we revealed a role of 3 ′ US-ceRNA effect on HK genes. In the cancer context, the potential for being ceRNA was identified for mRNAs [e.g., (Tay et al, 2011)] as well as long non-coding RNAs [e.g., (Tuersong et al, 2019)] and pseudogenes [e.g., (Wei et al, 2017)]. Among mRNAs, it has been shown that TA genes and TF genes heavily contribute to ceRNA regulation (Sumazin et al, 2011).…”