Skip to main content

Abstract LB-423: Whole genome comparisons of pre- and post- aromatase inhibitor treatment in estrogen receptor positive breast cancer

Publication ,  Conference
Ellis, MJ; Li, D; Shen, D; Luo, J; Suman, VJ; Wallis, JW; Van Tine, BA; Hoog, J; Crowder, RJ; Snider, JE; Ballman, K; Chen, K; Koboldt, DC ...
Published in: Cancer Research
April 15, 2012

Background: Estrogen receptors are over-expressed in around 70% of breast cancer cases. The genetic changes that occur during aromatase inhibitor (AI) treatment are not well understood and may differ depending upon the patient's response phenotype. Methods: We performed whole genome sequencing (WGS) of matched blood, pre-treatment, and post-treatment biopsy samples from 22 estrogen receptor positive breast cancer patients treated with neoadjuvant aromatase inhibitors. For 5 cases, we performed the whole genome sequencing (WGS) on patients’ matched normal, two pre AI-treatment, and two post AI-treatment DNA isolates from biopsy samples. We validated all putative coding and non-coding somatic mutations using deep sequencing. By comparing the validated somatic mutations from pre- and post- AI treatment biopsy samples, we were able to determine the alterations in the tumor genomes. In every case we defined the clonal architecture of each pair of pre-treatment and post-treatment biopsy samples by comparing the variant allele frequencies from thousands of validated somatic mutations. Results: Comparisons of the two pre AI-treatment biopsy samples from the same patient indicates that the variant allele frequencies of mutations showed high concordances in all 5 cases, 0.74 to 0.95 range of correlation coefficient. Only a small percentage of somatic mutations were detected in one pre-treatment sample and not the other (4.65% overall). In comparing the somatic variations between pre-treatment and matched post-treatment biopsy samples in 22 cases, we found that patients with good clinical response to AI treatment retained known driver mutations only in their pre-treatment tumors. Conversely, those patients with poor clinical response presented new driver mutations in their post-treatment samples. Furthermore, the variant allele frequency for most mutated genes decreased in post AI treatment samples for patients with good AI treatment response; on the contrary, the variant allele frequency increased for patients with poor clinical response. Conclusions: From WGS of matched normal, pre-treatment, and post-treatment biopsy samples, we identified new driver genes mutated in patients with poor clinical response, while patients with good clinical response had lost mutated driver genes in their post-treatment biopsy samples. The genetic landscape revealed by WGS of pre-treatment and post-treatment biopsy samples reveals mutational repertoires are remodeled by AI therapy. This finding suggests deep sequencing of AI treated samples will be necessary to reveal the complete complement of mutations present in a patient's tumor.Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-423. doi:1538-7445.AM2012-LB-423

Duke Scholars

Published In

Cancer Research

DOI

EISSN

1538-7445

ISSN

0008-5472

Publication Date

April 15, 2012

Volume

72

Issue

8_Supplement

Publisher

American Association for Cancer Research (AACR)

Related Subject Headings

  • Oncology & Carcinogenesis
  • 3211 Oncology and carcinogenesis
  • 3101 Biochemistry and cell biology
  • 1112 Oncology and Carcinogenesis
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Ellis, M. J., Li, D., Shen, D., Luo, J., Suman, V. J., Wallis, J. W., … Mardis, E. R. (2012). Abstract LB-423: Whole genome comparisons of pre- and post- aromatase inhibitor treatment in estrogen receptor positive breast cancer. In Cancer Research (Vol. 72). American Association for Cancer Research (AACR). https://doi.org/10.1158/1538-7445.am2012-lb-423
Ellis, Matthew J., Ding Li, Dong Shen, Jingqin Luo, Vera J. Suman, John W. Wallis, Brian A. Van Tine, et al. “Abstract LB-423: Whole genome comparisons of pre- and post- aromatase inhibitor treatment in estrogen receptor positive breast cancer.” In Cancer Research, Vol. 72. American Association for Cancer Research (AACR), 2012. https://doi.org/10.1158/1538-7445.am2012-lb-423.
Ellis MJ, Li D, Shen D, Luo J, Suman VJ, Wallis JW, et al. Abstract LB-423: Whole genome comparisons of pre- and post- aromatase inhibitor treatment in estrogen receptor positive breast cancer. In: Cancer Research. American Association for Cancer Research (AACR); 2012.
Ellis, Matthew J., et al. “Abstract LB-423: Whole genome comparisons of pre- and post- aromatase inhibitor treatment in estrogen receptor positive breast cancer.” Cancer Research, vol. 72, no. 8_Supplement, American Association for Cancer Research (AACR), 2012. Crossref, doi:10.1158/1538-7445.am2012-lb-423.
Ellis MJ, Li D, Shen D, Luo J, Suman VJ, Wallis JW, Van Tine BA, Hoog J, Crowder RJ, Snider JE, Ballman K, Chen K, Koboldt DC, Schierding WS, McMichael JF, Miller CA, Kandoth C, Lu C, Harris CC, McLellan MD, Wendl MC, DeSchryver K, Allred DC, Esserman L, Unzeitig G, Margenthaler J, Babiera GV, Marcom PK, Guenther JM, Leitch M, Hunt K, Olson J, Tao Y, Fulton LL, Fulton RS, Harrison M, Oberkfell B, Du F, Demeter R, Griffith M, Vickery TL, McDonald SA, Watson M, Dooling DJ, Ota D, Chang L-W, Bose R, Ley TJ, Wilson RK, Mardis ER. Abstract LB-423: Whole genome comparisons of pre- and post- aromatase inhibitor treatment in estrogen receptor positive breast cancer. Cancer Research. American Association for Cancer Research (AACR); 2012.

Published In

Cancer Research

DOI

EISSN

1538-7445

ISSN

0008-5472

Publication Date

April 15, 2012

Volume

72

Issue

8_Supplement

Publisher

American Association for Cancer Research (AACR)

Related Subject Headings

  • Oncology & Carcinogenesis
  • 3211 Oncology and carcinogenesis
  • 3101 Biochemistry and cell biology
  • 1112 Oncology and Carcinogenesis