Ota, David M.

503 Background: To correlate clinical features of estrogen receptor positive breast cancer with somatic mutations, massively parallel sequencing (MPS) was applied to tumor and normal DNAs accrued from patients treated with neoadjuvant aromatase inhibitors (AI). Methods: MPS was applied to 77 baseline tumor biopsy samples from the preoperative letrozole trial (JACS 2009: 208, 906) and the Z1031 trial (JCO 2011: 29, 2342) followed by targeted sequencing in another 240 trial samples. Standard statistical approaches were used to compare mutation status and clinical parameters and pathway-based correlation was used to assess interactions between signaling perturbations induced by gene mutations and response to neoadjuvant AI. Results: Eighteen genes were significantly mutated above background. Aside from PIK3CA mutations, the list is dominated by loss-of-function mutations in tumor suppressor genes. Five (RUNX1, CBFP, MYH9, MLL3 and SF3B1) have been previously linked to benign and malignant hematopoietic disorders. Clinical correlation revealed that TP53 mutation was associated with PAM50 LumB status, high-grade histology and high proliferation rates whereas loss-of-function mutations in MAP3K1 associate with PAM50 lumA status, low proliferation rates, and low grade histology. Mutations in GATA3 were associated with greater suppression of proliferation upon AI treatment suggesting mutGATA3 may predict endocrine response. Notably, mutations in MAP3K1 were more common in PIK3CA mutant cases, suggesting cooperation. Pathway analysis demonstrated that rare MAP2K4 mutations produce similar pathway perturbations as MAP3K1 mutation, a logical finding since MAP2K4 is a substrate for MAP3K1. Signaling network patterns driven by lncRNA MALAT1 mutations were associated with multiple poor clinical outcome features. Rare mutations in druggable kinases included two in the kinase domain of HER2. Conclusions: Tumor heterogeneity in luminal-type breast cancer is driven by specific patterns of somatic mutations, however most druggable or potentially prognostic mutations are infrequent. Prospective clinical trials based on these findings will require comprehensive genome sequencing approaches and large scale investigations.

Purpose To determine the pathologic complete response (pCR) rate in estrogen receptor (ER) –positive primary breast cancer triaged to chemotherapy when the protein encoded by the MKI67 gene (Ki67) level was > 10% after 2 to 4 weeks of neoadjuvant aromatase inhibitor (AI) therapy. A second objective was to examine risk of relapse using the Ki67-based Preoperative Endocrine Prognostic Index (PEPI). Methods The American College of Surgeons Oncology Group (ACOSOG) Z1031A trial enrolled postmenopausal women with stage II or III ER-positive (Allred score, 6 to 8) breast cancer whose treatment was randomly assigned to neoadjuvant AI therapy with anastrozole, exemestane, or letrozole. For the trial ACOSOG Z1031B, the protocol was amended to include a tumor Ki67 determination after 2 to 4 weeks of AI. If the Ki67 was > 10%, patients were switched to neoadjuvant chemotherapy. A pCR rate of > 20% was the predefined efficacy threshold. In patients who completed neoadjuvant AI, stratified Cox modeling was used to assess whether time to recurrence differed by PEPI = 0 score (T1 or T2, N0, Ki67 < 2.7%, ER Allred > 2) versus PEPI > 0 disease. Results Only two of the 35 patients in ACOSOG Z1031B who were switched to neoadjuvant chemotherapy experienced a pCR (5.7%; 95% CI, 0.7% to 19.1%). After 5.5 years of median follow-up, four (3.7%) of the 109 patients with a PEPI = 0 score relapsed versus 49 (14.4%) of 341 of patients with PEPI > 0 (recurrence hazard ratio [PEPI = 0 v PEPI > 0], 0.27; P = .014; 95% CI, 0.092 to 0.764). Conclusion Chemotherapy efficacy was lower than expected in ER-positive tumors exhibiting AI-resistant proliferation. The optimal therapy for these patients should be further investigated. For patients with PEPI = 0 disease, the relapse risk over 5 years was only 3.6% without chemotherapy, supporting the study of adjuvant endocrine monotherapy in this group. These Ki67 and PEPI triage approaches are being definitively studied in the ALTERNATE trial (Alternate Approaches for Clinical Stage II or III Estrogen Receptor Positive Breast Cancer Neoadjuvant Treatment in Postmenopausal Women: A Phase III Study; clinical trial information: NCT01953588).

Abstract Background: Neoadjuvant aromatase inhibitor (AI) therapy would become a more acceptable alternative to chemotherapy if there was a way to identify AI-resistant cases early for triage to alternate systemic treatment. We therefore conducted a Phase 2 trial of post-menopausal patients with clinical stage 2 or 3 ER+ (Allred Score 6 to 8) breast cancer who were re-biopsied 2 to 4 weeks after initiating neoadjuvant AI therapy. If the tumor Ki67 level was &gt; 10% (AI resistant) the patient was triaged to either chemotherapy or immediate surgery and if &lt; 10% (AI sensitive) the patient completed 16 to 18 weeks of neoadjuvant AI treatment. Co-primary endpoints were: 1) to confirm that the pathological complete response (pCR) rate to standard NCCN chemotherapy in the AI resistant population is in the range of 20% (similar to ER− disease). This required the observation of least 4/35 pCRs; 2) whether patients were willing to accept a recommendation of no chemotherapy when the preoperative endocrine prognostic index score was zero (PEPI-0) (pStage 1 or 2A, Ki67&lt;2.7% and ER+) since, according to the PEPI model, these patients have such a low relapse risk that chemotherapy is unlikely to be of value (Ellis, M JNCI 100:1380–8, 2008). Feasible was defined as &lt;10% PEPI-0 cases receiving adjuvant chemotherapy. Secondary endpoints included a determination of the distribution of intrinsic subtypes in the AI sensitive and resistant groups (using a research use only assay). Results: 51 patients (21%) had 2 to 4 week Ki67&gt;10%, of these 36 received chemotherapy per protocol (27) anthracycline (A) and taxane (T)-based, 7 T-based, 1 A-only based and 1 other (non-NCCN) regimen but only 2 patients had a pCR (5.5%). 194 patients (79%) had a Ki67 &lt;10%, of these 176 had PEPI score information. 65 had a PEPI-0 (37%), of which 61 (94%) reported a treatment plan that did not include adjuvant chemotherapy. The AI resistant group had a significantly higher frequency of baseline high-risk intrinsic subtypes (LumB: 26, HER2-E: 2 versus LumA: 7) at baseline than the AI sensitive group (LumB: 40, HER2-E: 0 versus LumA: 66) Fishers exact test p = 7.16E−6. Additional molecular data will be presented at the meeting. Conclusion. A Ki67 value &gt;10% at 2 to 4 weeks strongly enriches for high-risk molecular subtypes (mainly LumB) however standard neoadjuvant chemotherapy did not meet pre-assigned criteria for adequate Phase 2 activity in this group. Novel neoadjuvant approaches for AI resistant-disease defined by high on treatment Ki67 are therefore a high priority. Management of patients with excellent response to neoadjuvant endocrine therapy (PEPI-0) without adjuvant chemotherapy is feasible. The ALTERNATE trial will enroll over 2000 patients to establish a new standard of care for neoadjuvant treatment of ER+ HER2− disease based on these principles. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr PD07-01.

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