BackgroundThe targeted ERBB2 therapy, trastuzumab, has had a tremendous impact on management of patients with HER2+ breast cancer, leading to development and increased use of further HER2 targeted therapies. The major clinical side effect is cardiotoxicity but the mechanism is largely unknown. On the basis that gene expression is known to be altered in multiple models of heart failure, we examined differential gene expression of iPSC‐derived cardiomyocytes treated at day 11 with the ERBB2 targeted monoclonal antibody, trastuzumab for 48 h and the small molecule tyrosine kinase inhibitor of EGFR and ERBB2. ResultsTranscriptome sequencing was performed on four replicates from each group (48 h untreated, 48 h trastuzumab and 48 h lapatinib) and differential gene expression analyses were performed on each treatment group relative to untreated cardiomyocytes. 517 and 1358 genes were differentially expressed, p < 0.05, respectively in cardiomyocytes treated with trastuzumab and lapatinib. Gene ontology analyses revealed in cardiomyocytes treated with trastuzumab, significant down‐regulation of genes involved in small molecule metabolism (p = 3.22 × 10−9) and cholesterol (p = 0.01) and sterol (p = 0.03) processing. We next measured glucose uptake and lactate production in iPSC‐derived cardiomyocytes 13 days post‐plating, treated with trastuzumab up to 96 h. We observed significantly decreased glucose uptake from the media of iPSC‐derived cardiomyocytes treated with trastuzumab as early as 24 h (p = 0.001) and consistently up to 96 h (p = 0.03). ConclusionsOur study suggests dysregulation of cardiac gene expression and metabolism as key elements of ERBB2 signaling that could potentially be early biomarkers of cardiotoxicity.

BackgroundInvasive lobular carcinoma (ILC) comprises approximately ~10–20% of breast cancers. In general, multifocal/multicentric (MF/MC) breast cancer has been associated with an increased rate of regional lymph node metastases. Tumor heterogeneity between foci represents a largely unstudied source of genomic variation in those rare patients with MF/MC ILC.MethodsWe characterized gene expression and copy number in 2 or more foci from 11 patients with MF/MC ILC (all ER+, HER2-) and adjacent normal tissue. RNA and DNA were extracted from 3x1.5mm cores from all foci. Gene expression (730 genes) and copy number (80 genes) were measured using Nanostring PanCancer and Cancer CNV panels. Linear mixed models were employed to compare expression in tumor versus normal samples from the same patient, and to assess heterogeneity (variability) in expression among multiple ILC within an individual.Results35 and 34 genes were upregulated (FC>2) and down-regulated (FC<0.5) respectively in ILC tumor relative to adjacent normal tissue, q<0.05. 9/34 down-regulated genes (FIGF, RELN, PROM1, SFRP1, MMP7, NTRK2, LAMB3, SPRY2, KIT) had changes larger than CDH1, a hallmark of ILC. Copy number changes in these patients were relatively few but consistent across foci within each patient. Amplification of three genes (CCND1, FADD, ORAOV1) at 11q13.3 was present in 2/11 patients in both foci. We observed significant evidence of within-patient between-foci variability (heterogeneity) in gene expression for 466 genes (p<0.05 with FDR 8%), including CDH1, FIGF, RELN, SFRP1, MMP7, NTRK2, LAMB3, SPRY2 and KIT.ConclusionsThere was substantial variation in gene expression between ILC foci within patients, including known markers of ILC, suggesting an additional level of complexity that should be addressed.

Doxorubicin and the ERBB2 targeted therapy, trastuzumab, are routinely used in the treatment of HER2+ breast cancer. In mouse models, doxorubicin is known to cause cardiomyopathy and conditional cardiac knock out of Erbb2 results in dilated cardiomyopathy and increased sensitivity to doxorubicin-induced cell death. In humans, these drugs also result in cardiac phenotypes, but severity and reversibility is highly variable. We examined the association of decline in left ventricular ejection fraction (LVEF) at 15,204 single nucleotide polymorphisms (SNPs) spanning 72 cardiomyopathy genes, in 800 breast cancer patients who received doxorubicin and trastuzumab. For 7033 common SNPs (minor allele frequency (MAF) > 0.01) we performed single marker linear regression. For all SNPs, we performed gene-based testing with SNP-set (Sequence) Kernel Association Tests: SKAT, SKAT-O and SKAT-common/rare under rare variant non-burden; rare variant optimized burden and non-burden tests; and a combination of rare and common variants respectively. Single marker analyses identified seven missense variants in OBSCN (p = 0.0045–0.0009, MAF = 0.18–0.50) and two in TTN (both p = 0.04, MAF = 0.22). Gene-based rare variant analyses, SKAT and SKAT-O, performed very similarly (ILK, TCAP, DSC2, VCL, FXN, DSP and KCNQ1, p = 0.042–0.006). Gene-based tests of rare/common variants were significant at the nominal 5% level for OBSCN as well as TCAP, DSC2, VCL, NEXN, KCNJ2 and DMD (p = 0.044–0.008). Our results suggest that rare and common variants in OBSCN, as well as in other genes, could have modifying effects in cardiomyopathy.

Background: Understanding heterogeneity within individual breast tumors is key to the ability to predict therapeutic outcome. Molecular heterogeneity is commonly evaluated based on genomic features, including mRNA abundance, gene copy number events, and somatic mutations. The expression profile and activation state of key proteins is widely recognized as another key element in defining tumor heterogeneity. We have taken advantage of NanoString 3D Biology™ technology (for research use only) and curated nCounter Vantage 3DTM Solid Tumor Assay to interrogate a survey panel of HER2-positive breast tumors with the ultimate goal of determining key relationships between multiple genomic and proteomic profiles in individual tumors. Methods: We analyzed samples from 24 HER2+ breast cancer patients using NanoString technology to quantify the expression profile for over 25 total and phospho signaling proteins, including PI3K/MAPK/EGFR/HER2, 770 mRNA corresponding to 13 canonical cancer pathways, and 104 somatic mutations and small INDELS that are commonly associated with cancer, including 8 known PIK3CA mutations. These analyses were carried out in a matched fresh frozen and FFPE samples on the nCounter paltform. Data were analyzed by nSolver to identify genotype specific expression profiles across the 24 samples. Results: In our proof-of-concept data set, we successfully demonstrate that NanoString’s 3D biology Technology shows concordance across both FFPE and fresh frozen sample types for DNA, RNA, and protein. NanoString analysis also showed high concordance to gold-standard techniques used to assess genotype and RNA expression profiles. The combination of digital DNA, RNA, and protein data from our HER2+ breast cancer samples yielded potentially actionable data based on mapping of mutational status as the driver of key differences in protein expression and mRNA abundance of the signaling targets profiled. This work sheds new light on HER2+ breast cancer biology and the interplay between genomic and proteomic profiles while setting the stage for future studies that further probe the differences observed in this sample set. Conclusions: Simultaneous analysis of mutational status (SNV) and expression at the level of both mRNA and protein promises to enable a more detailed view of the relationship between genotype and the biological and clinical behavior of key tumor types. The NanoString Vantage 3DTM Solid Tumor platform provides a rapid, reliable, and economic means of assessing these analytes simultaneously. The application of these analytes to models that make clinically actionable predictions will require additional analyses of large sample cohorts, but such analysis is quite feasible using a variety of sample types. Acknowledgements: Supported in part by grants from the Breast Cancer Research Foundation and the 26.2 with Donna Foundation. Citation Format: Sarayna Chumsri, Daniel J. Serie, Brian M. Necela, Jennifer M. Kachergus, Bianca C. Axenfeld, Gokhan Demirkan, Gavin Meredith, P. Martin Ross, Anisha Kharkia, Erin Piazza, Afshin Mashadi-Hossein, Sarah Warren, Sarah A. McLaughlin, Joseph Beechem, Gary Geiss, E. Aubrey Thompson. Simultaneous analysis of the mutational landscape and RNA and protein expression profile of HER2-positive breast cancer using 3D BiologyTM [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3377. doi:10.1158/1538-7445.AM2017-3377