Automated Classification of Breast Cancer Across the Spectrum of <i>ERBB2</i> Expression Focusing on Heterogeneous Tumors With Low Human Epidermal Growth Factor Receptor 2 Expression.

Abstract

Although pharmaceutical companies conduct clinical trials of novel human epidermal growth factor receptor 2 (HER2)-low-directed drugs, diagnosing HER2-low cancer by immunohistochemistry (IHC) and in situ hybridization (ISH) remains challenging. This study investigates the performance of first-in-kind computerized intelligence to classify samples across gene expression levels and differentiate HER2-low tumors. We classified 251 samples: 142 primary invasive breast cancers (IBCs), 75 ductal carcinomas in situ (DCIS), and 34 mammaplasties (reference) using mRNA expression data from the QuantiGene Plex 2.0 assay. We used <i>g3mclass</i> probabilistic software to assess the number of classes in the assay data, the mean and the variance in each class, diagnostic cutoffs, and the prevalence of each class in the study population. HER2-low (IHC score of 1+ or 2+/ISH-) accounted for 31% of IBC. First, we discovered that HER2-low tumors were represented by cases with normal <i>ERBB2</i> transcript levels that were expected to produce physiologic levels of HER2 (70%) and cases with abnormally upregulated unamplified <i>ERBB2</i> (30%). We termed the latter cancers <i>ERBB2</i>-up as they do not meet the standard definitions for <i>ERBB2</i> overexpression and amplification. Second, HER2-low IBC classified as <i>ERBB2</i>-up had not only abnormally increased luminal growth and adhesion markers (<i>ERBB2</i>, <i>ESR1</i>, <i>PGR</i>, <i>IGF1R</i>, <i>VAV2</i>, <i>VAV3</i>, <i>KRT8</i>, <i>CDH1</i>) but also downregulated myoepithelial marker (<i>KRT5</i>). The vascularization (<i>RAP1</i> and <i>C3G</i>), immune cell infiltration (<i>VAV1</i>), and mesenchymal transition (<i>CDH2</i>) markers were dysregulated. Finally, in the independent cohort of DCIS, 40% of HER2-low DCIS shared similar traits with HER2-low IBC except for rare downregulation of <i>KRT5</i> and no change in <i>C3G</i>, <i>VAV1</i>, and <i>CDH2.</i> We demonstrated how innovative bioinformatic tools could help diagnose cancer across the spectrum of <i>ERBB2</i> expression to aid decision making for HER2-low.