Blood-based monitoring identifies acquired and targetable driver HER2 mutations in endocrine-resistant metastatic breast cancer

通过血液监测可识别内分泌耐药转移性乳腺癌中的获得性和可靶向 HER2 驱动突变

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作者:Arielle J Medford #, Taronish D Dubash #, Dejan Juric, Laura Spring, Andrzej Niemierko, Neelima Vidula, Jeffrey Peppercorn, Steven Isakoff, Brittany A Reeves, Joseph A LiCausi, Benjamin Wesley, Giuliana Malvarosa, Megan Yuen, Ben S Wittner, Michael S Lawrence, A John Iafrate, Leif Ellisen, Beverly M

Abstract

Plasma genotyping identifies potentially actionable mutations at variable mutant allele frequencies, often admixed with multiple subclonal variants, highlighting the need for their clinical and functional validation. We prospectively monitored plasma genotypes in 143 women with endocrine-resistant metastatic breast cancer (MBC), identifying multiple novel mutations including HER2 mutations (8.4%), albeit at different frequencies highlighting clinical heterogeneity. To evaluate functional significance, we established ex vivo culture from circulating tumor cells (CTCs) from a patient with HER2-mutant MBC, which revealed resistance to multiple targeted therapies including endocrine and CDK 4/6 inhibitors, but high sensitivity to neratinib (IC50: 0.018 μM). Immunoblotting analysis of the HER2-mutant CTC culture line revealed high levels of HER2 expression at baseline were suppressed by neratinib, which also abrogated downstream signaling, highlighting oncogenic dependency with HER2 mutation. Furthermore, treatment of an index patient with HER2-mutant MBC with the irreversible HER2 inhibitor neratinib resulted in significant clinical response, with complete molecular resolution of two distinct clonal HER2 mutations, with persistence of other passenger subclones, confirming HER2 alteration as a driver mutation. Thus, driver HER2 mutant alleles that emerge during blood-based monitoring of endocrine-resistant MBC confer novel therapeutic vulnerability, and ex vivo expansion of viable CTCs from the blood circulation may broadly complement plasma-based mutational analysis in MBC.

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