BC Cancer Agency, Vancouver, BC, Canada
Nathalie LeVasseur , Veronika Csizmok , Melika Bonakdar , Yaoqing Shen , Lindsay Zibrik , Eric Yang Zhao , Sophie Sun , Karen A. Gelmon , Janessa J. Laskin , Marco A. Marra , Stephen K. L. Chia
Background: The genomic profiling of breast cancers has led to a greater understanding of the mutational landscape of metastatic breast cancer (MBC) with potential therapeutic implications. Despite these advances, there is a paucity of data regarding the additive value and relevance of gene expression across histological and molecular subtypes, which represents the majority of informative and actionable findings identified in the BC Cancer personalized oncogenomics program (POG). Methods: Informative findings with potential clinical application from whole genome sequencing (WGS) and whole transcriptome sequencing (WTS) in MBC patients between 2012-2018 were reviewed. Variants observed in pathway genes of potential clinical relevance, as defined by a curated list of genes, were examined across histological subtypes. High and low expression outliers relative to TCGA breast cases, defined as expression greater than 98th percentile and FC > 2 compared to Illumina breast dataset and lower than 25th percentile and FC < -2 compared to Illumina breast dataset, respectively, were then analyzed to establish how many outliers were observed in pathways of potential clinical relevance. Results: A total of 113 cases were included. WGS revealed that TP53 was the most frequent single nucleotide variant (SNV) in triple negative breast cancer (23/30, 77%), whereas PIK3CA (37/78, 47%), PTEN (11/78, 14%) and ESR1 (19/78, 24%) were most frequent in ER positive cases and CDKN2A (2/18, 11%) in HER2 positive cases. Across all subtypes, the mTOR and cell cycle pathways were found to have the highest frequency of SNVs, with the identification of 86 and 71 variants, respectively. Expression data for 113 RNA-sequenced patients revealed a high frequency of expression outliers in the mTOR pathway (26 high expression and 424 low expression outlier genes) and cell cycle pathways (35 high expression and 331 low expression outlier genes), but also in the WNT pathway (96 high expression and 490 lower expression outlier genes) and NOTCH pathway (84 high expression and 564 low expression outlier genes). Conclusions: Frequently identified SNVs across histological subtypes were correlated with expression outliers in pathways of clinical relevance in breast cancer. Additional informative findings, in pathways of potential clinical relevance not historically targeted in breast cancer, were identified with WTS. The clinical utility of these findings warrants further study.
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