Abstract PO5-13-06: Classifying HER2-low breast cancer using a combination of ERBB2 mRNA expression and altered genes

Abstract Background It has been recently demonstrated that some HER2-low, defined as immunohistochemistry (IHC) 1+ or 2+ with no gene amplification by FISH, breast cancer (BC) patients respond to trastuzumab deruxtecan (T-DXd). Results of the DAISY trial also suggested clinical activity with T-DXd in some of those classified as HER2-0 cancers by IHC, indicating an unmet need to better identify cancers that may truly respond to T-DXd. We compared ERBB2 (HER2) mRNA expression obtained from whole-transcriptome sequencing with IHC/FISH assignment of HER2 status. Furthermore, we constructed a classifier using ERBB2 expression and alterations in other genes as a proof of concept to illustrate classification of BC samples into HER2-0 versus HER2-low status. Methods We chose consecutive HR positive/HER2-negative BC samples that were submitted for OncoExTraTM testing between April 2020 and October 2022. The OncoExTra test uses tumor-normal whole exome and whole transcriptome sequencing to detect somatic single base substitutions, indels, copy number alterations, gene fusions and alternative transcripts. In addition, we investigated the expression profile of select genes for this analysis. We utilized OncoExTra data to examine the relationship between HER2 IHC status and gene expression, mutation and copy number profiles of selected genes, and built a classifier to predict HER2 status. Results A total of 279 BC samples were analyzed, including 106 HER2-IHC 0, 120 HER2-IHC 1+ and 53 HER2-IHC 2+. Of these, 273 were primary and 6 were metastatic samples. The distributions of patient age and tumor fraction were similar among these categories (p=0.54 and p=0.41, respectively; one-way ANOVA). ERBB2 expression differed among all three HER2-IHC categories and was lowest in HER2-0 and highest in HER2-2+ (HER2-0 vs HER2-1+, p 0.001; HER2-0 vs HER2-2+, p 0.0001; HER2-1+ vs HER2-2+, p=0.011; HER2-0 vs HER2-low, p 0.0001; Mann-Whitney U test in all comparisons). Five genes were mutated in more than 10% of samples: PIK3CA (45.5%), GATA3 (15.4%), CDH1 (12.5%), MAP3K1 (11.1%) and TP53 (10.8%). Mutations in two genes, GATA3 and PTEN, appeared to differ in frequency between the HER2-0 and HER2-low categories (Table 1). We selected 4 genes with mutations, 2 genes with copy number changes, and expression from ERBB2, ESR1, CD274, HLA-A, HLA-B and HLA-C to train a logistic regression classifier to predict HER2 IHC status. The classifier was trained on 163 samples, hyperparameter tuning was done using 55 samples, and testing was performed on 61 samples. Preliminary results indicated that of the 28 HER2-IHC 0 samples in the test set, 17 (65%) were classified as HER2-low. Further development and evaluation of the classifier using a blinded testing set is currently in progress. Conclusion In this cohort of BC samples, ERBB2 mRNA expression was positively associated with HER2 protein IHC status. Additional studies are required to determine whether a classifier including ERBB2 mRNA expression could be used to identify patients for T-DXd therapy. The relative enrichment of PTEN alterations in HER2-IHC 0 samples suggests that mTOR/AKT inhibitors may sometimes be appropriate in patients who are not eligible for T-DXd therapy, and further investigation should be considered. Table 1. Number (frequency) of altered genes by HER2 IHC status. Citation Format: Gargi Basu, Niru Chennagiri, Turgut Dogruluk, David Hall, Jess Hoag, Cynthia Flannery, Snehal Thakkar, Melanie Palomares, Frederick Baehner, Lajos Pusztai. Classifying HER2-low breast cancer using a combination of ERBB2 mRNA expression and altered genes abstract. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-13-06.