Multi-omic profiling to identify RNA-protein concordance and post-transcriptional dysregulation in HER2+ breast cancer.

573 Background: Standard HER2 testing relies on single-modality assays, such as immunohistochemistry (IHC) for protein overexpression and in situ hybridization (ISH) for gene amplification. These tests may fail to capture the regulatory complexity underlying HER2 biology, including post-transcriptional modulation, which may result in RNA-protein discordance and potentially drive therapeutic resistance. We performed a multi-omic analysis to characterize functional HER2 biology and uncover regulatory mechanisms not captured by standard diagnostic testing. Methods: We utilized Panakeia’s multi-omics platform to analyze a set of 475 breast cancer samples with a complete set of ERBB2 RNA and protein expression values from the Cancer Genome Atlas (TCGA). HER2+ (n=79) and HER2− (n=396) cohorts were defined using clinical HER2 status assessed via IHC/ISH. Transcriptomic and proteomic over-expression states were binarized by thresholding RNA/protein expression values. RNA-protein concordance was assessed to define four molecular states of the tumor: coordinated activation (RNA+/Protein+), coordinated inactivation (RNA−/Protein−), translation blocks (RNA+/Protein−), or post-transcriptional upregulation (RNA−/Protein+). Results: A strong correlation was measured between RNA and protein over-expression (Pearson's correlation r=0.752, p<0.001) with 93.7% concordance (445/475). Molecular patterns with respect to HER2 clinical status were observed as follows: (1) coordinated activation (n=48, 10.1%) with 95.8% HER2+ concordance (46/48), validating HER2 over-expression; (2) coordinated inactivation (n=397, 83.6%) with 95.2% HER2− concordance (378/397), confirming HER2 inactivity; (3) RNA+/Protein− translation blocks (n=29, 6.1%) where ERBB2 RNA was over-expressed but not translated; (4) RNA−/Protein+ (n=1, 0.2%). Among 79 HER2+ patients, only 46 (58.2%) showed functional translation (RNA+/Protein+), while 19 (24.1%) had complete molecular negativity (both inactive) and 14 (17.7%) exhibited translation blocks. Multi-omics profiling identified actionable changes in 35/475 cases (7.4%): 19 potential over-treatment candidates, 14 potential treatment resistance cases, and 2 potential under-treatment cases that are clinically HER2− but exhibit coordinated molecular activity. Conclusions: Integrative multi-omic analysis of the HER2 molecular landscape enabled assessment beyond standard-of-care assays, identifying non-responders to HER2-targeted therapy by capturing post-transcriptional dysregulation not detected by single-modality testing. Overall, multi-omic profiling can support precision stratification by confirming active HER2 signalling, identifying potential over-treatment, refining patient selection and guiding treatment decisions.