Integrated landscape of copy number variation and RNA expression associated with nodal metastasis in invasive ductal breast carcinoma

// Michael Behring 1, 2 , Sadeep Shrestha 1 , Upender Manne 2, 3 , Xiangqin Cui 4 , Agustin Gonzalez-Reymundez 5, 6 , Alexander Grueneberg 6 and Ana I. Vazquez 5, 6 1 Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA 2 Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL 35294, USA 3 Department of Pathology and Surgery, University of Alabama at Birmingham, Birmingham, AL 35294, USA 4 Biostatistics Department, University of Alabama at Birmingham, Birmingham, AL 35294, USA 5 Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI 48824, USA 6 Institute for Quantitative Health Science and Engineering, Michigan State University, East Lansing, MI 48824, USA Correspondence to: Michael Behring, email: behringm@uab.edu Ana I. Vazquez, email: avazquez@msu.edu Keywords: breast cancer; lymph node metastasis; integrated genomics; copy number variation; differential expression Received: February 14, 2018      Accepted: October 31, 2018      Published: December 07, 2018 ABSTRACT Background: Lymph node metastasis (NM) in breast cancer is a clinical predictor of patient outcomes, but how its genetic underpinnings contribute to aggressive phenotypes is unclear. Our objective was to create the first landscape analysis of CNV-associated NM in ductal breast cancer. To assess the role of copy number variations (CNVs) in NM, we compared CNVs and/or associated mRNA expression in primary tumors of patients with NM to those without metastasis. Results: We found CNV loss in chromosomes 1, 3, 9, 18, and 19 and gains in chromosomes 5, 8, 12, 14, 16-17, and 20 that were associated with NM and replicated in both databases. In primary tumors, per-gene CNVs associated with NM were ten times more frequent than mRNA expression; however, there were few CNV-driven changes in mRNA expression that differed by nodal status. Overlapping regions of CNV changes and mRNA expression were evident for the CTAGE5 gene. In 8q12, 11q13-14, 20q1, and 17q14-24 regions, there were gene-specific gains in CNV-driven mRNA expression associated with NM. Methods: Data on CNV and mRNA expression from the TCGA and the METABRIC consortium of breast ductal carcinoma were utilized to identify CNV-based features associated with NM. Within each dataset, associations were compared across omic platforms to identify CNV-driven variations in gene expression. Only replications across both datasets were considered as determinants of NM. Conclusions: Gains in CTAGE5 , NDUFC2 , EIF4EBP1 , and PSCA genes and their expression may aid in early diagnosis of metastatic breast carcinoma and have potential as therapeutic targets.