Allred, D. Craig

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.

LBA513 Background: Neoadjuvant aromatase inhibitor (AI) therapy is a rational and effective approach to improving the breast conservation surgery (BCS) rate for postmenopausal patients with large, estrogen receptor (ER) rich breast cancers. Barriers to adopting this strategy include lack of experience in this management approach in the US and uncertainty regarding the comparative effectiveness of the three approved aromatase inhibitors for this indication. Methods: ACOSOG Z1031 is a multicenter, open-label, neoadjuvant phase III screening study that randomized postmenopausal women with clinical stage II/III ER rich (Allred score 6-8) breast cancer to 16 weeks of either exemestane (EXE) 25 mg daily, letrozole (LET) 2.5 mg daily, or anastrozole (ANA) 1 mg daily. At baseline study participants were either marginal for BCS (MBCS), candidates for mastectomy only (MO), or inoperable (IO). Planned enrolment was 125 patients per arm in order that the likelihood of the treatment with the “best” 16-week clinical response rate (based on caliper measurements) by WHO criteria (cRR) was included among the subset of treatments with “similar” cRR (90% power). Secondary endpoints included: extent of surgery, radiologic and pathologic response rates. Results: From 4/1/2006 to 10/1/2009, 377 postmenopausal women with clinical stage II or III ER rich breast cancer were enrolled. 374 women began treatment and were included in an intent-to-treat analysis. Median age was 66 yrs (range: 43-90 yrs), Median tumor size was 4.0 cm (range: 2-13 cm). The 16-week cRR was 60.5% (95%CI: 51.3-69.1%) for EXE; 70.9% (95% CI: 62.2-78.6%) for LET, and 66.7% (95% CI: 57.6-74.9%) for ANA. Seventeen patients did not have surgery due to refusal (12 pts), progression (3 pts) or other medical conditions (2 pts). The BCS rate was 78% (163/207) in MBCS group; 42% (77/163) in MO group; and 75% in IO group (3/4). Surgeons made the decisions regarding procedure choice 75% of the time in both the MBCS and the MO categories. Conclusions: This large multicenter screening trial selected non-steroidal AIs for further development due to their higher observed cRR. The study demonstrates that high response and breast conservation rates and low rates of disease progression can be achieved through patient selection based on high ER expression. We are currently refining our approach for early detection of poor response to AIs through an assessment of the tumor Ki67 proliferation index at 2 to 4 weeks (Z1031 Cohort B). [Table: see text]

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 Ki-67 proliferation marker-based response monitoring will be prospectively tested in the ALternate Treatment for ER positive NeoAdjuvant TrEatment (ALTERNATE) trial. Tumor Ki-67 will be analyzed after one month of neoadjuvant anastrozole, fulvestrant or the combination to detect early resistance (Ki-67 &gt;10%) for triage to alternate treatment (chemotherapy/investigational agent). Ki-67 will be repeated on the surgical specimen after 24 weeks to detect PEPI-0 cases (path Stage 0/1/2A and Ki-67 ≤2.7%), which will be managed without adjuvant chemotherapy. A CLIA-approved Ki-67 assay was required by CTEP/FDA. FDA reviewed-components included the CONFIRM anti-Ki-67 (30-9) Rabbit Monoclonal Primary Antibody, the Benchmark XT platform and the VENTANA iScan Coreo scanner. The validation process was as follows: Step 1 was a TMA-based bridging study between a SP6-based research assay to the 30-9 CLIA assay using visual point counting (VPC); Step 2 trained a scoring SOP using Companion Algorithm Ki-67 (30-9) image analysis software with triage to VPC when certain observations were flagged; Step 3 was an independent test of the SOP using relevant patient outcome-associated samples from the P024 and POL neoadjuvant endocrine studies with two independent pathology analyses. STEP 1: Bridging Research to CLIA. Using a 28-case TMA, and VPC, the intra-class correlation (ICC) for agreement measure of Ki-67 10% cut-point (CP) between research Ki-67 and CLIA Ki-67 was 0.96 (CI 0.92-0.98). The Cohen's simple kappa for agreement measure was 0.78 (CI 0.55-1.0). STEP 2: Scanner-based Algorithm training. An SOP for the image analysis was developed by reviewing discordant cases in two independent reads at the 10% and 2.7% CP in a training set (N+ disease from P024 N = 61). Histology features that led to inaccurate scoring from the image analysis included: streaming /fascicular tumor cells, a large amount of intervening stromal cells, heavy immune cell infiltration, sparse scattered tumor cells, faint staining, and plump stromal cells. These cases were flagged for VPC. The final Ki-67 scoring SOP used image analysis with triage to VPC when necessary (required in 16% of cases). STEP 3: Scoring Algorithm Validation. The Ki-67 SOP was run on T1/2 N0 cases from the P024 trial N = 58. The% positive agreement for the combined scanner and VPC approach using the Ki-67 2.7% CP was 87.5% (95% CI 61.7- 98.5%); percent negative agreement 88.9% (95% CI: 65.3-98.6%). Minor discordance did not affect the ability to predict very similar survival outcomes (Log Rank P = 0.044 and P = 0.055). The data for the 10% CP was similar (N = 66), the percentage positive agreement was 100%; percent negative agreement 93.55% (95% CI: 78.58-99.21%). The survival predictions were again similar (P = 0.0001 and P = 0.0002). The FDA ruled the use of Ki-67 in the ALTERNATE trial is “no significant risk” because previous clinical trial data indicated the majority of patients with Stage 0/1/2A disease post neoadjuvant endocrine therapy already do not receive chemotherapy. Thus the use of Ki-67 reduces the risk of under-treatment of patients with low stage disease but aggressive biology. CTEP accepted these data on assay concordance and performance and the ALTERNATE trial will proceed. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P3-05-10.

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

Purpose Preoperative aromatase inhibitor (AI) treatment promotes breast-conserving surgery (BCS) for estrogen receptor (ER) –positive breast cancer. To study this treatment option, responses to three AIs were compared in a randomized phase II neoadjuvant trial designed to select agents for phase III investigations. Patients and Methods Three hundred seventy-seven postmenopausal women with clinical stage II to III ER-positive (Allred score 6-8) breast cancer were randomly assigned to receive neoadjuvant exemestane, letrozole, or anastrozole. The primary end point was clinical response. Secondary end points included BCS, Ki67 proliferation marker changes, the Preoperative Endocrine Prognostic Index (PEPI), and PAM50-based intrinsic subtype analysis. Results On the basis of clinical response rates, letrozole and anastrozole were selected for further investigation; however, no other differences in surgical outcome, PEPI score, or Ki67 suppression were detected. The BCS rate for mastectomy-only patients at presentation was 51%. PAM50 analysis identified AI-unresponsive nonluminal subtypes (human epidermal growth factor receptor 2 enriched or basal-like) in 3.3% of patients. Clinical response and surgical outcomes were similar in luminal A (LumA) versus luminal B tumors; however, a PEPI of 0 (best prognostic group) was highest in the LumA subset (27.1% v 10.7%; P = .004). Conclusion Neoadjuvant AI treatment markedly improved surgical outcomes. Ki67 and PEPI data demonstrated that the three agents tested are biologically equivalent and therefore likely to have similar adjuvant activities. LumA tumors were more likely to have favorable biomarker characteristics after treatment; however, occasional paradoxical increases in Ki67 (12% of tumors with > 5% increase after therapy) suggest treatment-resistant cells, present in some LumA tumors, can be detected by post-treatment profiling.