In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. 2411-2411
Abstract:
Individual tumors, including the aggressive and difficult to treat triple-negative (ER-/PR-/HER2-) breast cancers (TNBCs) are heterogeneous collections of cells with multiple subclonal populations each contributing to the tumor. While subclonal heterogeneity is likely responsible for the development of drug resistance, identification of how tumor cell populations change over time has been difficult, largely because of the challenges in resampling tumor tissue at close time points. Here we quantify tumor evolution in human patient-derived xenografts implanted into NSG mice, which we use to test subclonal heterogeneity as a function of location within a tumor, propagation time, and drug treatment. We used high-depth (∼400x) sequencing of a targeted panel of 358 genes to quantify somatic mutation allele frequencies from 6 spatially-separated and 8 temporally-propagated xenograft samples derived from the same TNBC patient tumors. Samples ranged in age from 2-4 months post-engraftment. Although we observed a few low frequency mutations distinguishing samples, overall we found that allele frequencies of somatic mutations were well-preserved on this time scale. We then generated replicate xenografts from the same patient tumor and treated them respectively with cisplatin, doxorubicin, cyclophosphamide, docetaxel, or vehicle control for 25 days. Although again somatic mutations showed few differences in allele frequency across samples, substantial variations were seen when data were analyzed for copy number alterations. To confirm these effects we repeated the treatments for xenografts derived from two additional TNBC patients. Again we observed strong changes in tumor heterogeneity at the copy number level. This effect was particularly, but not exclusively, apparent in tumors with the greatest response to therapy. We further verified these measurements through Sanger and digital PCR sequencing on the treated mice and other mice in the same cohorts. Using a multi-sample xenograft propagation, dissection, sequencing, and computational analysis protocol, we have shown that tumor subpopulation changes in response to treatment can be quantified and distinguished from spatial or temporal effects, even for treatment time courses as short as 1 month. In triple negative breast cancer these variations are most apparent at the level of copy number variation. Our study demonstrates how patient-derived xenografts can provide detailed resolution of tumor population evolution during the manifestation of resistance. Citation Format: Hyunsoo Kim, Pooja Kumar, Francesca Menghi, Joshy George, Guru Ananda, Susan Mockus, Chengsheng Zhang, Nicholas Larson, Henry C. Chen, Yan Yang, James Keck, R. Krishnamurthy Karuturi, Charles Lee, Carol Bult, Edison Liu, Jeffrey H. Chuang. Evolution during propagation and treatment of patient-derived triple negative breast cancer xenografts. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2411.
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2016-2411
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2016
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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