Pseudogenes transcribed in breast invasive carcinoma show subtype-specific expression and ceRNA potential

Area of Science:

• Genomics
• Cancer Biology
• Bioinformatics

Background:

• Pseudogenes are increasingly recognized for their roles in cancer when dysregulated.
• Pseudogene transcripts can function as competing endogenous RNAs (ceRNAs), but their study is limited by sequence similarity and lack of integrated miRNA data.
• Previous research on pseudogenes in breast cancer has not performed large-scale analysis of ceRNA potential by integrating miRNA expression data.

Purpose of the Study:

• To investigate the pervasive regulatory role of transcribed pseudogenes in cancer.
• To develop a novel bioinformatic method for measuring pseudogene transcription from RNA-seq data.
• To analyze the ceRNA potential of pseudogenes in breast cancer using integrated expression data.

Main Methods:

• Developed a novel bioinformatic method to quantify pseudogene transcription from RNA-seq data.
• Applied the method to 819 breast cancer samples from The Cancer Genome Atlas (TCGA).
• Integrated pseudogene, gene, and miRNA expression data with miRNA target prediction for ceRNA analysis.

Main Results:

• Identified 440 transcribed pseudogenes in breast cancer tissue, with 309 showing differential expression across subtypes.
• Pseudogene expression levels accurately separated tumor from normal samples and distinguished Basal from Luminal and Her2 subtypes.
• Found more significant pseudogene-parent gene correlations and pseudogene-miRNA anti-correlations than expected by chance, with 177 pseudogenes predicted to act as ceRNAs.

Conclusions:

• Pseudogene transcription is widespread in breast cancer and plays a significant regulatory role.
• The developed method enables large-scale analysis of pseudogene transcription and ceRNA potential.
• Results expand the catalog of putative pseudogene ceRNAs and highlight their underappreciated role in breast cancer.