Abstract P1-05-01: Landscape of somatic mutations in inflammatory breast cancer whole-genome sequences
Authors: X Li, S Krishnamurthy, S Kumar, S Reddy, W Woodward, J Reuben, C Hatzis, NT Ueno, M Gerstein, L Pusztai
Journal: Cancer Research (2017)

Abstract Goal: Inflammatory breast cancer (IBC) is a rare, aggressive form of breast cancer that is characterized by a highly metastatic phenotype. Numerous previous attempts failed to identify, recurrent, IBC-specific gene expression or DNA copy number alterations. We performed whole genome sequencing (WGS) of IBC biopsies obtained before any therapy to define a comprehensive genomic landscape of this disease. Methods: Illumina paired-end whole genome sequencing (WGS) of 20 IBC (n=9 ER+, n=11 ER-) and matched normal samples were performed with median coverage of 60X and 40X for cancer and normal, the percentages of mapped reads were 99.3% and 99.2%, respectively. We identified germ-line and somatic variants, indels as well as large scale structural variants, using GATK Haplotype Caller, MuTect and CREST, respectively. We performed the same analysis on WGS data from 23, age, race and ER and HER2 matched, non-IBC (n=12 ER+, n=11 ER-) from the TCGA for comparison. Variants in both coding and noncoding sequences were categorized by FunSeq to identify potential drivers. Mutation clustering in each gene, as well as significantly mutated non-coding regulatory modules, were identified using LARVA. DeconstructSigs were used to decompose the mutational spectrum of each cancer into 30 validated, mutational signatures provided by COSMIC. Contributions of each validated signature to mutations in IBC vs. non-IBC were compared using Welch's t-test. Results: We identified 118,818 somatic variants in the IBC samples (median: 3,856; minimum: 1,109; maximum: 24,815) including 1,060 variants (~0.9%) in coding regions. 5,287 somatic indels and 5,959 large scale structural variants were detected including 1,028 insertions and 1,857 deletions. Recurrent, non-synonymous mutations were detected in the coding region of GRIN2A gene in 3/20 IBC samples (15%), (previously reported as a potential driver mutation in 1.7% of breast cancers). Other significant mutations in coding regions included GRHL1, PIK3R2, ESR1, FLG2 and etc. Three DNase I hypersensitive sites (DHSs) in non-coding regions were altered in 20% (4/20) IBC samples vs. fewer than 8.7% (2/23) in non-IBC. Mutational frequency of GATA3 is 80.0% vs. 47.8% (p=0.03), and PTEN is 45.0% vs. 73.9% (p=0.05), in IBC vs. non-IBC samples when including both coding and non-coding variants. Contributions of mutational signature 9, that is associated with polymerase η , were significantly higher in IBC cohort than non-IBC cohort (p-value=0.056). Conclusion: This is the first whole genome sequencing analysis of IBC and comparison with the results from non-IBC. We identified promising candidate drivers in the coding sequence and in non-coding regulatory modules of expressed genes. We also identified mutational signature 9, and mutations in several DHS as significantly more frequent alterations in IBC compared to non-IBC. Citation Format: Li X, Krishnamurthy S, Kumar S, Reddy S, Woodward W, Reuben J, Hatzis C, Ueno NT, Gerstein M, Pusztai L. Landscape of somatic mutations in inflammatory breast cancer whole-genome sequences [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-05-01.