Dataset Information

Stratification of lncRNA modulation networks in breast cancer.

ABSTRACT:

Background

Recently, non-coding RNAs are of growing interest, and more scientists attach importance to research on their functions. Long non-coding RNAs (lncRNAs) are defined as non-protein coding transcripts longer than 200 nucleotides. We already knew that lncRNAs are related to cancers and will be dysregulated in them. But most of their functions are still left to further study. A mechanism of RNA regulation, known as competing endogenous RNAs (ceRNAs), has been proposed to explain the complex relationships among mRNAs and lncRNAs by competing for binding with shared microRNAs (miRNAs).

Methods

We proposed an analysis framework to construct the association networks among lncRNA, mRNA, and miRNAs based on their expression patterns and decipher their network modules.

Results

We collected a large-scale gene expression dataset of 1,061 samples from breast invasive carcinoma (BRCA) patients, each consisted of the expression profiles of 4,359 lncRNAs, 16,517 mRNAs, and 534 miRNAs, and applied the proposed analysis approach to interrogate them. We have uncovered the underlying ceRNA modules and the key modulatory lncRNAs for different subtypes of breast cancer.

Conclusions

We proposed a modulatory analysis to infer the ceRNA effects among mRNAs and lncRNAs and performed functional analysis to reveal the plausible mechanisms of lncRNA modulation in the four breast cancer subtypes. Our results might provide new directions for breast cancer therapeutics and the proposed method could be readily applied to other diseases.

SUBMITTER: Yu WH

PROVIDER: S-EPMC9059351 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Publications

Stratification of lncRNA modulation networks in breast cancer.

Yu Wen-Hsuan WH Hsu Chia-Lang CL Lin Chen-Ching CC Oyang Yen-Jen YJ Juan Hsueh-Fen HF Huang Hsuan-Cheng HC

BMC medical genomics 20220502 Suppl 3

<h4>Background</h4>Recently, non-coding RNAs are of growing interest, and more scientists attach importance to research on their functions. Long non-coding RNAs (lncRNAs) are defined as non-protein coding transcripts longer than 200 nucleotides. We already knew that lncRNAs are related to cancers and will be dysregulated in them. But most of their functions are still left to further study. A mechanism of RNA regulation, known as competing endogenous RNAs (ceRNAs), has been proposed to explain th ...[more]

PMID: 35501896

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Project description:Recently, rapid advances in bioinformatics analysis have expanded our understanding of the transcriptome to a genome-wide level. miRNA-mRNA-lncRNA interactions have been shown to play critical regulatory role in cancer biology. In this study, we discussed the use of an integrated systematic approach to explore new facets of the oestrogen receptor (ER)-regulated transcriptome. The identification of RNAs that are related to the expression status of the ER may be useful in clinical therapy and prognosis. We used a network modelling strategy. First, microarray expression profiling of mRNA, lncRNA and miRNA was performed in MCF-7 (ER-positive) and MDA-MB-231 cells (ER- negative). A co-expression network was then built using co-expression relationships of the differentially expressed mRNAs and lncRNAs. Finally, the selected miRNA-mRNA network was added to the network. The key miRNA-mRNA-lncRNA interaction can be inferred from the network. The mRNA and non-coding RNA expression profiles of the cells with different ER phenotypes were distinct. Among the aberrantly expressed miRNAs, the expression levels of miR-19a-3p, miR-19b-3p and miR-130a-3p were much lower in the MCF-7 cells, whereas that of miR-148b-3p was much higher. In a cluster of miR-17-92, the expression levels of six of seven miRNAs were lower in the MCF-7 cells, in addition to miR-20b in the miR-106a-363 cluster. However, the levels of all the miRNAs in the miR-106a-25 cluster were higher in the MCF-7 cells. In the co-expression networking, CD74 and FMNL2 gene which is involved in the immune response and metastasis, respectively, had a stronger correlation with ER. Among the aberrantly expressed lncRNAs, lncRNA-DLEU1 was highly expressed in the MCF-7 cells. A statistical analysis revealed that there was a co-expression relationship between ESR1 and lncRNA-DLEU1. In addition, miR-19a and lncRNA-DLEU1 are both located on the human chromosome 13q. We speculate that miR-19a might be co-expressed with lncRNA-DLEU1 to co-regulate the expression of ESR1, which influences the occurrence and development of breast cancer cells with different levels of ER expression. Our findings reveal that the status of ER is mainly due to the differences in the mRNA and ncRNA profile between the breast cancer cell lines, and highlight the importance of studying the miRNA-mRNA-lncRNA interactions to completely illustrate the intricate transcriptome.

Dataset Information

Stratification of lncRNA modulation networks in breast cancer.

Background

Methods

Results

Conclusions

Publications

Stratification of lncRNA modulation networks in breast cancer.

Similar Datasets

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