Classification of HER2 status across multiple cancers using epigenomic profiles from a novel liquid biopsy assay.
Authors: Anthony D'Ippolito, Jonathan Beagan, Melissa E. Hughes, Matthew Strickland, Martin Samuel Taylor, Corrie Painter, Kalie Smith, Aditya Pandey, Ilexa A Schechter, Mosammat F Afreen, Jayne Stommel, Aparna Gorthi, Nancy U. Lin, Matthew Freedman, Heather Anne Parsons, Samuel J. Klempner, Gordon B. Mills, Sara M. Tolaney, Matthew Eaton, J. Carl Carl Barrett
Journal: Journal of Clinical Oncology (2024)

3047 Background: The efficacy of trastuzumab deruxtecan in multiple cancers led to a recent FDA granting of priority review for the treatment of adults with HER2-positive solid tumors. This underscores the critical need for reliable assessment of HER2 expression across cancers. The current standard using IHC/ISH for HER2 scoring is fraught with challenges including scoring discordance and tumor heterogeneity. Here we describe the ability to classify HER2 status from 1 ml of plasma, using epigenomic signatures from a novel multi-analyte liquid biopsy (LBx) platform, offering a minimally invasive approach for patient (pt) selection across cancers. Methods: We selected 179 samples from 172 pts with advanced breast (BC), gastro-esophageal (GEA) and ovarian (OV) cancers who had associated HER2 status scored from tissue-based IHC/ISH according to ASCO/CAP guidelines (table). Samples were taken at baseline or at progression and those with detectable cell free DNA, as assessed by iChorCNA, were profiled for genome-wide epigenomic signals across histone modifications associated with active enhancers, promoters and DNA methylation. A regularized regression model developed to classify HER2 status in BC cell lines and was refined and validated for HER2 status prediction for each pt cohort (HER2+ = 3+, 2+/ISH+; HER2- = 2+/ISH-, 1+, 0). The BC cell-line derived HER2 classifier was refined to incorporate GEA and OV cancer specific features before being applied to those samples. Performance was assessed via AUC in a leave-one-out cross-validation schema. We also evaluated HER2 status at progression in a subset of pts with benchmarked HER2 IHC to assess dynamic changes in receptor status by LBx. Results: The epigenomic HER2 classifier was applied to all samples with ctDNA detectable by ichorCNA (90 of 179; 50%). HER2 classification of BC pts by epigenomic liquid biopsy was concordant with standard tissue-based IHC for 64/72 (89%) BC samples (AUC 0.9, table). HER2 classifier predictions for all longitudinally collected samples were concordant with IHC-based HER2 status, including the one patient whose status switched from HER2+ to HER2- at progression. Accurate classification of 11/14 (79%, GEA) and 4/4 (100%, OV) pts was achieved using the indication-refined HER2 classifier. Conclusions: We demonstrate proof of concept for a HER2 classification approach using comprehensive epigenomic signals from 1 ml of plasma that could be applied across multiple cancers. With further development, our genome-wide profiling approach could alleviate clinical constraints associated with multiple tissue-based HER2 scoring assays (IHC/ISH) and enable longitudinal monitoring of HER2 status on therapy. [Table: see text]