Mutational Landscape Assessed in Tumor Tissue and Circulating Tumor DNA During Treatment of Patients with HER2/ERBB2-Mutated Solid Tumors - Kristian Egebjerg; Iben Spanggaard; Lise Barlebo Ahlborn; Kristoffer Staal Rohrberg; Laurine Harsloef; Martin Hoejgaard; Ane Yde Schmidt; Ulrik Lassen; Ida Viller Tuxen; Jane Preuss Hasselby; Maria Rossing; Eric Santoni-Rugiu; et al. (BMC Cancer)
Abstract Background Human epidermal growth factor receptor 2 (HER2) aberrations, such as protein overexpression and amplification of the HER2 gene (ERBB2), are well-established in breast and gastroesophageal adenocarcinomas. However, ERBB2 oncogenic variants occur in 3.5% of all solid tumors with possible therapeutic implications. This study investigates the treatment efficacy and mutational landscape of patients with ERBB2-mutated cancers receiving HER2-targeted therapy. Methods Nineteen patients with refractory solid tumors harboring ERBB2 oncogenic variants were enrolled in the Copenhagen Prospective Personalized Oncology trial and received HER2-targeted treatment. Whole-exome sequencing, ctDNA analysis, and imaging were conducted at baseline, during treatment, and upon progression. Descriptive statistics were employed due to the exploratory nature of the study. Results HER2-targeted treatment yielded a 37% overall response rate, a 68% disease control rate, and a median progression-free survival of 4.4 months. A tendency was observed toward higher overall response rate (60%) in patients harboring ERBB2 oncogenic variants located in the tyrosine kinase domain. Clonality of ERBB2 oncogenic variants was linked with treatment efficacy, underscoring the reduced effect when targeting subclonal mutations. Sequential ctDNA analysis of ERBB2 oncogenic variants demonstrated correlation with treatment response. Conclusion In this heterogeneous cohort of patients harboring ERBB2 oncogenic variants, HER2-targeted therapy demonstrated clinical efficacy. Mutational analysis revealed the importance of clonal ERBB2 oncogenic variants and identified factors influencing treatment outcomes. Limitations include a small sample size as well as heterogeneity in treatment regimens and cancer types.