Griffith, Malachi

Abstract Purpose: Cyclin-dependent kinase (CDK) 4/6 drives cell proliferation in estrogen receptor–positive (ER+) breast cancer. This single-arm phase II neoadjuvant trial (NeoPalAna) assessed the antiproliferative activity of the CDK4/6 inhibitor palbociclib in primary breast cancer as a prelude to adjuvant studies. Experimental Design: Eligible patients with clinical stage II/III ER+/HER2− breast cancer received anastrozole 1 mg daily for 4 weeks (cycle 0; with goserelin if premenopausal), followed by adding palbociclib (125 mg daily on days 1–21) on cycle 1 day 1 (C1D1) for four 28-day cycles unless C1D15 Ki67 > 10%, in which case patients went off study due to inadequate response. Anastrozole was continued until surgery, which occurred 3 to 5 weeks after palbociclib exposure. Later patients received additional 10 to 12 days of palbociclib (Cycle 5) immediately before surgery. Serial biopsies at baseline, C1D1, C1D15, and surgery were analyzed for Ki67, gene expression, and mutation profiles. The primary endpoint was complete cell cycle arrest (CCCA: central Ki67 ≤ 2.7%). Results: Fifty patients enrolled. The CCCA rate was significantly higher after adding palbociclib to anastrozole (C1D15 87% vs. C1D1 26%, P < 0.001). Palbociclib enhanced cell-cycle control over anastrozole monotherapy regardless of luminal subtype (A vs. B) and PIK3CA status with activity observed across a broad range of clinicopathologic and mutation profiles. Ki67 recovery at surgery following palbociclib washout was suppressed by cycle 5 palbociclib. Resistance was associated with nonluminal subtypes and persistent E2F-target gene expression. Conclusions: Palbociclib is an active antiproliferative agent for early-stage breast cancer resistant to anastrozole; however, prolonged administration may be necessary to maintain its effect. Clin Cancer Res; 23(15); 4055–65. ©2017 AACR.

Abstract 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