Endocrine-Therapy-Resistant ESR1 Variants Revealed by Genomic Characterization of Breast-Cancer-Derived Xenografts
Jin Zhang, Rama Suresh, Shuying Liu, Loren S. Michel, Richard K. Wilson, Austin Lin, Christopher G. Maher, Donna McEachern, Chanpheng Phommaly, Michelle Harrison, Sherri R. Davies, Yi Dong, Tom Mooney, Jeffrey Hiken, Jieya Shao, Robert T. Kitchens, Charles M. Perou, Christopher A. Miller, Michael Naughton, Joshua F. McMichael, Obi L. Griffith, Dave Larson, R. McDowell, Wenbin Liu, Robert S. Fulton, Megha Shyam Kavuri, Rebecca Aft, Xiaping He, Ron Bose, Dong Shen, Shunqiang Li, X. Cynthia, Timothy Pluard, Crystal Cooper, Matthew J. Ellis, William E. Gillanders, Christopher Schlosberg, Aleix Prat, Ana M. González-Angulo, Therese Giuntoli, César Sánchez, Katherine DeSchryver, Elaine R. Mardis, Charles Lu, Shaomeng Wang, Robert G. Crowder, Jingqin Luo, Jeremy Hoog, Gordon B. Mills, Li Ding, Rodrigo Gonçalves, John R. Edwards, Yu Tao, Laila Saied, Caroline Bumb
Abstract
To characterize patient-derived xenografts (PDXs) for functional studies, we made whole-genome comparisons with originating breast cancers representative of the major intrinsic subtypes. Structural and copy number aberrations were found to be retained with high fidelity. However, at the single-nucleotide level, variable numbers of PDX-specific somatic events were documented, although they were only rarely functionally significant. Variant allele frequencies were often preserved in the PDXs, demonstrating that clonal representation can be transplantable. Estrogen-receptor-positive PDXs were associated with ESR1 ligand-binding-domain mutations, gene amplification, or an ESR1/YAP1 translocation. These events produced different endocrine-therapy-response phenotypes in human, cell line, and PDX endocrine-response studies. Hence, deeply sequenced PDX models are an important resource for the search for genome-forward treatment options and capture endocrine-drug-resistance etiologies that are not observed in standard cell lines. The originating tumor genome provides a benchmark for assessing genetic drift and clonal representation after transplantation.