Identifying putative breast cancer-associated long intergenic non-coding RNA loci by high density SNP array analysis.

Area of Science:

• Genomics
• Cancer Biology
• Molecular Genetics

Background:

• Long intergenic non-coding RNAs (lincRNAs) are recognized for their roles in cancer.
• Differential gene dosage of lincRNA genes in cancer genomes remains understudied.
• Understanding lincRNA copy number variations (CNVs) is crucial for cancer research.

Purpose of the Study:

• To investigate genomic copy number aberrations in lincRNA genes in breast cancer.
• To identify lincRNAs affected by somatic CNVs.
• To explore the susceptibility of lincRNA genes to CNVs compared to other genomic regions.

Main Methods:

• Utilized high-density Human Omni5-Quad BeadChips for SNP analysis.
• Analyzed seven tumor-normal paired primary human mammary epithelial cells (HMECs).
• Mapped lincRNA genes to SNP loci to identify lincRNA-associated CNVs.

Main Results:

• Identified 122 lincRNAs affected by somatic CNVs.
• Detected predominantly copy number losses, clustering to chromosome ends.
• Found lincRNA genes are less susceptible to CNVs (1.8%) compared to protein-coding (37.5%) and intergenic regions (60.6%).

Conclusions:

• Established a novel SNP array approach to identify lincRNA candidates linked to tumorigenesis.
• Provided new strategies for breast cancer diagnosis and treatment.
• Highlighted the distinct CNV susceptibility of lincRNA genes in cancer.