Identification of Breast Cancer Subtype-Specific Biomarkers by Integrating Copy Number Alterations and Gene Expression Profiles

• Main Authors: Claudia Cava, Mirko Pisati, Marco Frasca, Isabella Castiglioni
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: Medicina
• Subjects: copy number alteration; gene expression; breast cancer subtypes
• Online Access: https://www.mdpi.com/1648-9144/57/3/261

<i>Background and Objectives</i>: Breast cancer is a heterogeneous disease categorized into four subtypes. Previous studies have shown that copy number alterations of several genes are implicated with the development and progression of many cancers. This study evaluates the effects of DNA copy number alterations on gene expression levels in different breast cancer subtypes. <i>Materials and Methods</i>: We performed a computational analysis integrating copy number alterations and gene expression profiles in 1024 breast cancer samples grouped into four molecular subtypes: luminal A, luminal B, HER2, and basal. <i>Results</i>: Our analyses identified several genes correlated in all subtypes such as <i>KIAA1967</i> and <i>MCPH1</i>. In addition, several subtype-specific genes that showed a significant correlation between copy number and gene expression profiles were detected: <i>SMARCB1</i>, <i>AZIN1</i>, <i>MTDH</i> in luminal A, <i>PPP2R5E</i>, <i>APEX1</i>, <i>GCN5</i> in luminal B, <i>TNFAIP1</i>, <i>PCYT2</i>, <i>DIABLO</i> in HER2, and <i>FAM175B</i>, <i>SENP5</i>, <i>SCAF1</i> in basal subtype. <i>Conclusions</i>: This study showed that computational analyses integrating copy number and gene expression can contribute to unveil the molecular mechanisms of cancer and identify new subtype-specific biomarkers.