Abstract PD9-03: The genomic landscape of <i>de novo</i> metastatic breast cancer (MBC)
Authors: E Jain, D Kim, JB Buendia, O Cohen, RB Sousa, E Anastasio, M Dunphy, M McGillicuddy, R Stoddard, S Balch, B Thomas, S Di Lascio, BN Tomson, C Nguyen, C Painter, N Wagle
Journal: Cancer Research (2019)

Abstract Background: Approximately 5-10% of newly diagnosed breast cancers (BC) are de novo MBC, which means that metastatic disease was identified at the time of initial diagnosis. Patients with de novo MBC are underrepresented in currently available genomic studies. In The Cancer Genome Atlas (TCGA) dataset, only 15 out of ˜980 BC patients can be classified as having de novo MBC. The objective of this study is to analyze the genomic landscape of de novo MBC and to study the genomic differences of this cohort with early stage BC. To enhance our ability to study de novo MBC, we utilized data from the Metastatic Breast Cancer Project (MBCproject), a patient-partnered research project that aims to generate a large public database of clinical, genomic, and patient reported data (PRD) from patients with MBC. Methods: We defined de novo MBC as patients diagnosed with metastatic disease less than 4 months after their initial diagnosis with BC.Out of 127 patients in the MBCproject with publicly released whole exome sequencing (WES) data, we identified 33 patients with de novo MBC. We combined this data with 15 de novo MBC patients in TCGA. For patients with de novo MBC with multiple tumor biopsies available, we used WES from breast biopsies to enable appropriate comparison to the early stage biopsies. Somatic mutations were evaluated and significantly recurring genes were identified using MutSig2CV. We compared the mutations found in the de novo cohort with early stage tumors. 10 patients in the de novo MBC cohort had paired simultaneous primary and metastatic biopsies; genomic alterations in these samples were compared. Finally, we used RNA sequencing data to compare cytolytic signatures among the de novo and early stage biopsies. Results: Among the 48 patients analyzed the receptor subtype distribution was: HR+/HER2-(23), HR+/HER2+(13), HR-/HER2+(2), HR-/HER2-(3), HR+/HER2 unknown(5), and HR-/HER2 unknown(2). Histology subtype distribution was as follows: IDC(39), MDLC(6), ILC(2) and Other (1). Significantly recurrent genes in the de novo MBC cohort (q&amp;lt;0.1) included TP53(27%), PIK3CA(30%), CDH1(8%) and MAP3K1(11%). Mutations in PTEN, EGFR, and MDM4 were significantly enriched (p &amp;lt;0.05) in the de novo cohort when compared to early stage BC Evolutionary analysis of paired primary and metastatic biopsies for de novo MBC patients demonstrated the presence of shared clonal mutations, indicating that these were highly evolutionarily related. RNA-seq immune cytolytic signature was downregulated in de novo MBC as compared to early stage BC (p &amp;lt;0.2). Gene% Mutation Rate in De Novo MBC (N=48)% Mutation rate in Early Stage BC (N= 997)p-valuePTEN10.403.510.0324EGFR6.250.500.00435MDM44.170.300.0189 Conclusions: Our initial results highlight genomic differences between de novo MBC and early stage BC, including increased frequency of PTEN, EGFR, and MDM4 mutations. Enrichment of PTEN mutations (implicated in tumor immune surveillance), and downregulation of cytolytic signature potentially suggests that de novo MBC may have immunosuppressive tumor microenvironment. To date, ˜1200 patients with self-reported de novo MBC have registered for the MBCproject. We anticipate that additional study of genomic and clinical data from these patients will greatly improve our understanding of de novo MBC. Citation Format: Jain E, Kim D, Buendia JB, Cohen O, Sousa RB, Anastasio E, Dunphy M, McGillicuddy M, Stoddard R, Balch S, Thomas B, Di Lascio S, Tomson BN, Nguyen C, Painter C, Wagle N. The genomic landscape of de novo metastatic breast cancer (MBC) [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD9-03.