Meredith Buxton

Abstract S5-02: Veliparib/carboplatin plus standard neoadjuvant therapy for high-risk breast cancer: First efficacy results from the I-SPY 2 TRIAL

Background: I-SPY 2 is a multicenter, phase 2 screening trial using adaptive randomization within biomarker subtypes to evaluate a series of novel agents/combinations when added to standard neoadjuvant therapy (paclitaxel q wk x 12, doxorubicin & cyclophosphamide q 2-3 wk x 4, T/AC) vs. T/AC (control arm) for women with high-risk stage II/III breast cancer. The primary endpoint is pathologic complete response (pCR) at surgery. Our goal is to identify/graduate regimens that have ≥85% Bayesian predictive probability of success (statistical significance) in a 300-patient biomarker-linked Phase 3 neoadjuvant trial. Experimental regimens can “graduate” in at least 1 of 10 possible signatures defined by hormone-receptor (HR) & HER2 status & MammaPrint (MP), with a maximum number of 120 total patients enrolled. We report final efficacy results of the oral PARP inhibitor veliparib (V, ABT-888) in combination with carboplatin (carbo), 1 of 7 experimental regimens evaluated in the trial to date. Methods: Women with tumors ≥2.5 cm by clinical exam and ≥2 cm by imaging are eligible for screening. Tumors that are MP low/HR+/HER2- are ineligible for randomization. MRI scans (baseline, 3 weeks after start of therapy, at completion of weekly T, and prior to surgery) were used in a longitudinal statistical model to improve the efficiency of adaptive randomization. V+carbo was assigned to HER2- tumors only, which limits its possible signatures to: all HER2-, HR+/HER2-, HR-/HER2-. For these 3 signatures we provide estimated pCR rates with associated 95% Bayesian probability intervals for V+carbo and concurrently randomized controls. Analysis is intent to treat with patients who switched to non-protocol therapy regarded as non-pCRs. For each signature we provide probabilities of superiority for V+carbo over control and Bayesian predictive probabilities of success in a neoadjuvant Phase 3 trial equally randomized between V+carbo and control. Results: When V+carbo met the 85% predictive probability criterion in HR-/HER2- and all HER2-, this regimen graduated and accrual to V+carbo was stopped. V+carbo was assigned to 72 patients, and there were 62 concurrently randomized controls (44 HER2- controls). The following table shows final results based on available pCR information. Two patients assigned to V+carbo withdrew consent during treatment and are not included in the table. Conclusion: Adaptive randomization successfully identified a biomarker signature for V+carbo on the basis of a modest number of patients. V+carbo has graduated with a triple-negative (TN) breast cancer signature, and is the subset recommended for this regimen9s subsequent development. There is a suggestion that HR+/HER2- tumors benefit little from this regimen and inclusion of tumors in this subset would therefore dilute its effect in a subsequent trial. Analyses are currently underway to define additional biomarkers that may be predictive of response. The I-SPY 2 standing trial mechanism efficiently evaluates agents/combinations in biomarker-defined patient subsets, with future agents/combinations reported as available. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr S5-02.

Abstract S2-06: DNA repair deficiency biomarkers and MammaPrint high1/(ultra)high2 risk as predictors of veliparib/carboplatin response: Results from the neoadjuvant I-SPY 2 trial for high risk breast cancer

Background: The PARP inhibitor veliparib in combination with carboplatin (VC) was one of the experimental regimens evaluated in the phase 2 neoadjuvant I-SPY 2 standing trial for high risk breast cancer patients. VC graduated in the triple negative (TN) signature. However, not all TN patients achieved pathologic complete response (pCR) and some HR+HER2- patients responded. The I-SPY 2 biomarker component provides a platform for rigorous evaluation of mechanism-of-action-based markers in the context of established biomarkers (HR, HER2, MammaPrint) within the trial. Here, we report results from 5 investigator-submitted biomarker proposals and the MammaPrint High1/High 2 (MP1/2) classification as specific predictors of VC response. Methods: Data from 116 HER2- patients (VC: 72 and concurrent controls: 44) were available. BRCA1/2 germline mutation was assessed by Myriad Genetics. 3 expression signatures relating to DNA damage repair deficiency (PARPi-7, BRCAness and CIN70) and MP1/2 classification were evaluated on Agilent 44K arrays. PARP1 levels were measured using reverse phase protein arrays. We used logistic modeling to assess biomarker performance. A biomarker is considered a specific predictor of VC response if it associates with response in the V/C arm but not the control arm, and if the biomarker x treatment interaction is significant (likelihood ratio test, p Results: BRCA1/2 germline mutation status associates with VC response, but its low prevalence in the control arm precludes further evaluation. Of the biomarkers evaluated, three (PARPi-7, BRCAness, and MP1/2) associate with response in the VC arm but not the control arm, and have biomarker x treatment interactions with p Conclusion: If verified in a larger trial, PARPi7, BRCAness and MP1/2 signatures may help refine predictions of VC response, thereby improving patient care. Evaluation of the combined signature for patients treated with platinum-based chemotherapy is ongoing. Citation Format: Wolf DM, Yau C, Sanil A, Glas A, Petricoin C, Wulfkuhle J, Brown-Swigart L, Hirst G, I-SPY 2 TRIAL Investigators, Buxton M, DeMichele A, Hylton N, Symmans F, Yee D, Paoloni M, Esserman L, Berry D, Rugo H, Olapade O, van 9t Veer L. DNA repair deficiency biomarkers and MammaPrint high1/(ultra)high2 risk as predictors of veliparib/carboplatin response: Results from the neoadjuvant I-SPY 2 trial for high risk breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr S2-06.

Abstract P6-11-02: Efficacy of Hsp90 inhibitor ganetespib plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 trial

Background: Pathologic complete response(pCR) after neoadjuvant therapy is an established prognostic biomarker for high-risk breast cancer(BC). Improving pCR rates may identify new therapies that improve survival. I-SPY 2 uses response-adaptive randomization within biomarker subtypes to evaluate novel agents when added to standard neoadjuvant therapy for women with high-risk stage II/III breast cancer; the goal is to identify regimens that have ≥85% Bayesian predictive probability of success (statistical significance) in a 300-patient phase 3 neoadjuvant trial defined by hormone-receptor (HR), HER2 status and MammaPrint (MP). We report the results for Ganetespib, a selective inhibitor of Hsp90 that induces the degradation/deactivation of key drivers of tumor initiation, progression, angiogenesis, and metastasis.Ganetespib + taxanes previously have resulted in a superior therapeutic response compared to monotherapy in multiple solid tumor models including BC. Methods: Women with tumors ≥2.5cm were eligible for screening and participation. MP low/HR+ tumors were ineligible for randomization. QTcF >470msec and HbA1C >8.0% were ineligible. MRI scans (baseline, +3 cycles, following weekly paclitaxel, T, and pre-surgery) were used in a longitudinal statistical model to improve the efficiency of adaptive randomization. Ganetespib was given with weekly T at 150 mg/m 2 IV weekly (3 weeks on, 1 off). Patients were premedicated (dexamethasone 10mg and diphenhydramine HCl 25-50 mg, or therapeutic equivalents). Analysis was intention to treat with patients who switched to non-protocol therapy counted as non-pCRs. The Ganetespib regimen was open only to HER2- patients, and eligible for graduation in 3 of 10 pre-defined signatures: HER2-, HR+/HER2- and HR-/HER2-. Results: Ganetespib did not meet the criteria for graduation in the 3 signatures tested. When the maximum sample size was reached, accrual stopped. Ganetespib was assigned to 93 patients; there were 140 controls. We report probabilities of superiority for Ganetespib over control and Bayesian predictive probabilities of success in a neoadjuvant phase 3 trial equally randomized between Ganetespib and control, for the 3 biomarker signatures, using the final pCR data from all patients. Safety data will be presented. Conclusion: The I-SPY 2 adaptive randomization model efficiently evaluates investigational agents in the setting of neoadjuvant BC. The value of I-SPY 2 is that it provides insight as to the regimen9s likelihood of success in a phase 3 neoadjuvant study. Although no signature reached the efficacy threshold of 85% likelihood of success in phase 3, we observed the most impact in HR-/HER2- patients, with a 16% improvement in pCR rate. While our data do not support the continued development of Ganetespib alone for neoadjuvant BC, combinations with Ganetespib, which could potentiate its effect, may be worth pursuing in I-SPY 2 or similar trials. Citation Format: Forero A, Yee D, Buxton MB, Symmans WF, Chien AJ, Boughey JC, Elias AD, DeMichele A, Moulder S, Minton S, Kaplan HG, Albain KS, Wallace AM, Haley BB, Isaacs C, Korde LA, Nanda R, Lang JE, Kemmer KA, Hylton NM, Paoloni M, van9t Veer L, Lyandres J, Perlmutter J, Hogarth M, Yau C, Sanil A, Berry DA, Esserman LJ. Efficacy of Hsp90 inhibitor ganetespib plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 trial [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-11-02.

Abstract P5-11-18: Trajectory of patient (Pt) reported physical function (PF) during and after neoadjuvant chemotherapy in the I-SPY 2 trial

Background Patients (pts) receiving chemotherapy for breast cancer experience toxicities impacting short and long-term quality of life (QOL). Within I-SPY 2, a trial adaptively randomizing stage II/III breast cancer pts to neoadjuvant chemotherapy +/- an investigational agent, we are collecting pt reported outcome (PRO) data to understand the impact of investigational agents on QOL. This PRO sub-study provides a unique opportunity to study QOL longitudinally and explore how pt and tumor characteristics, exposure to investigational therapies, and surgical outcome impact QOL. Methods Pts enrolled in this trial receive paclitaxel (T) +/- an investigational agent for 12 weeks followed by 4 cycles of doxorubicin and cyclophosphamide (AC). Surveys include the EORTC QLQ-C30 and BR-23, and PROMIS measures for QOL metrics including but not limited to physical function (PF), anxiety, and depression. Surveys are administered pre-chemotherapy to 2 years post-surgery. PF data from the EORTC and PROMIS instruments was analyzed for 238 pts at 5 sites (UCSF, UCSD, U of Pennsylvania, U of Minnesota, and Swedish Cancer Center). 48 pts completed baseline, inter-regimen (between T and AC), pre-operative and post-surgery surveys. Of the 48 pts 32 completed a 6-month follow up (FUP) and 31 completed a 1-year FUP survey. A linear mixed effect model, adjusting for HER2 status and treatment type was used to evaluate changes in PF over time. Sample size is small and statistics are descriptive rather than inferential. Results Median age of pts in this analysis was 50 (range 27-72). At baseline, mean PROMIS PF scores were higher than the US average (mean = 50) but declined as expected throughout treatment. HER2+ patients experienced a similar degree of recovery as HER2- pts post-surgery despite adjuvant treatment with Herceptin. Analysis of post-operative PROMIS PF indicated an average score within the U.S. general population (mean =50) but did not return to higher functioning seen at baseline levels (mean 52.5, p-value Conclusions: Among a subset of pts who completed all surveys in the I-SPY 2 QOL substudy, PF did not return to baseline at 6-12 months post-operatively. Through transition to an electronic platform of data collection we hope to improve compliance with survey completion. We continue to analyze other QOL measures and plan to correlate QOL data with treatment arm, adverse events, comorbidities, and response to neoadjuvant treatment. Citation Format: Shah M, Jensen R, Yau C, Straehley I, Berry DA, DeMichele A, Buxton MB, Hylton NM, Perlmutter J, Symmans WF, Tripathy D, Yee D, Wallace A, Kaplan HG, Clark A, Chien AJ, I-SPY 2 Investigators, Esserman LJ, Melisko ME. Trajectory of patient (Pt) reported physical function (PF) during and after neoadjuvant chemotherapy in the I-SPY 2 trial [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-11-18.

Abstract P1-14-03: The evaluation of trebananib plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 TRIAL

Background: I-SPY 2 is a multicenter phase 2 trial using response-adaptive randomization within biomarker subtypes to evaluate a series of novel agents when added to standard neoadjuvant therapy for women with high-risk stage II/III breast cancer. The primary endpoint is pathologic complete response (pCR). The goal is to identify/graduate regimens with ≥85% Bayesian predictive probability of success (statistical significance) in a 300-patient phase 3 neoadjuvant trial defined by hormone-receptor (HR), HER2 status & MammaPrint (MP). Regimens may also leave the trial for futility ( Methods: Women with tumors ≥2.5cm were eligible for screening. MP low/HR+/HER2- tumors were ineligible for randomization. Serial MRI scans (baseline, 2 during treatment and pre-surgery) were used in a longitudinal model to improve the efficiency of adaptive randomization. Participants are categorized into 8 subtypes based on: HR status, HER2 status and MP High 1 (MP1) or High 2 (MP2). MP1 and MP2 are determined by a predefined median cut-point of I-SPY 1 participants who fit the eligibility criteria for I-SPY 2. Trebananib was initially assigned to HER2- patients only; once safety data with trastuzumab (H) were obtained, it was also assigned to HER2+ patients. Analysis was intent to treat -- patients who switched to non-protocol therapy were designated non-pCRs. Results: Trebananib +/-H did not meet the criteria for graduation in any of the 10 signatures tested. When the maximum sample size was reached, accrual ceased. We report probabilities of trebananib +/-H being superior to control and Bayesian predictive probabilities of success in a 1:1 randomized neoadjuvant phase 3 trial for the 10 biomarker signatures, using the final pCR data from all patients. Citation Format: Albain KS, Leyland-Jones B, Symmans F, Paoloni M, van 9t Veer L, DeMichele A, Buxton M, Hylton N, Yee D, Lyandres Clennell J, Yau C, Sanil A, I-SPY 2 Trial Investigators, Berry D, Esserman L. The evaluation of trebananib plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 TRIAL. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P1-14-03.

Abstract P3-06-37: I-SPY 2 qualifying biomarker evaluation (QBE): The challenge and opportunity for interrogating predicted pathways in an adaptive design biomarker rich trial

I-SPY 2, a multicenter phase 2 neoadjuvant trial in high-risk breast cancer, uses adaptive randomization within biomarker subtypes to evaluate novel agents added to standard chemotherapy. In addition to efficiently evaluating agent/signature pairs, I-SPY 2 is a biomarker rich trial, where samples are profiled for gene expression, protein levels, and mutation status. Biomarkers are classified as established, qualifying, or exploratory. Established biomarkers are those used clinically (HR/HER2 status) or FDA cleared (MammaPrint), and,used for adaptive randomization to generate the 10 signatures from which a drug can graduate. Qualifying biomarkers (QB) represent evidence-based, biologic pathway markers (e.g.cell line predictors, known drug targets). QB analyses must be pre-specified and performed under CLIA. Exploratory markers are for discovery and may allow integration of data from different technologies. The QBE goal is to (1) evaluate biomarkers related to an agent’s mechanism of action to identify promising candidates for testing/patient selection in future trials, and (2) create a resource to elucidate biological mechanisms of response. The wealth of biomarker data is both a boon and a challenge. Our small size limits the generalizability of our findings. There are multiple genes in each pathway measured on multiple platforms, creating the problem of multiplicity, which is compounded by the evaluation of multiple proposals. Biomarkers may correlate with HR/HER2/MP subtypes. The adaptive randomization may increase the prevalence of biomarker positive subsets and bias our findings. These challenges limit definitive conclusions, so our statistics are descriptive rather than inferential, and are intended to avoid adding to the false positive biomarker literature. Methods: Three filters are applied: 1-The difference in biomarker performance in the experimental vs control arm (biomarker x treatment interaction) is evaluated using a logistic model under a pre-specified analysis plan 2-Biomarkers with a treatment interaction are dichotomized. The QB-High group is added to the graduating subtype to define a novel signature and the treatment effect in this group is evaluated 3-If the treatment effect is comparable to the graduating signature, and the prevalence is increased, the I-SPY 2 Bayesian model is modified to include the QB to assess the novel signature. QBE to date: Veliparib in combination with carboplatin (V/C) and neratinib (N) are the first two agents to graduate from I-SPY 2. For V/C, we have completed initial evaluation for 5 biomarker proposals, including BRCA1/2 germline mutations and expression signatures associated with DNA repair deficiencies. For N, 6 biomarker proposals, including HER family protein signaling markers, have been assessed. Evaluation of the best candidates from these initial analyses in the I-SPY 2 Bayesian framework is ongoing. Mutational analyses are pending. Conclusions: We have developed a rigorous approach for QB analysis. A small number of QB warrant further assessment. However, I-SPY 2 QB require validation, and should be considered preliminary efforts to effectively screen QB candidates for evaluation in ongoing and future trials. Citation Format: Christina Yau, Denise Wolf, Ashish Sanil, Laura van 9t Veer, Emanuel F Petricoin, Meredith Buxton, Joe Gray, Angela DeMichele, Mike Hogarth, Nola Hylton, Jane Perlmutter, Melissa Paoloni, Fraser Symmans, Doug Yee, Don Berry, Laura Esserman. I-SPY 2 qualifying biomarker evaluation (QBE): The challenge and opportunity for interrogating predicted pathways in an adaptive design biomarker rich trial [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-37.

Abstract P3-06-15: Evaluation of HER family protein signaling network as a predictive biomarker for pCR for breast cancer patients treated with neratinib in the I-SPY 2 trial

Background: We hypothesize that response to the pan-ERBB inhibitor, neratinib (N), may be predicted by pre-treatment HER2-EGFR signaling. In the I-SPY 2 TRIAL, N graduated in the HR-/HER2+ signature. All patients received at least standard chemotherapy. For HER2+ patients, N was administered in place of trastuzumab. We evaluated 18 HER family signaling proteins as biomarkers of N response using reverse phase protein microarray (RPMA) data from pre-treatment LCM purified tumor epithelium. Methods: 168 patients (N: 106, concurrent controls: 62) had RPMA and pCR data. 18 biomarkers relating to HER family signaling were evaluated: AKT S473, AKT T308, EGFR, EGFR Y1068, EGFR Y1148, EGFR Y1173, EGFR Y992, ERBB2, ERBB2 Y1248, ERBB3 total, ERBB3 Y1289, ERK1/2 T202/Y204, Heregulin, mTOR, mTOR S2448, PI3K p85 Y458/p55 Y199, PTEN S380, and SHC Y317. We assessed association between biomarker and response in the N and control arms alone (likelihood ratio test), and relative performance between arms (biomarker x treatment interaction) using a logistic model. Analysis was also performed adjusting for HR/HER2 status. In an exploratory analysis, we selected the marker with the greatest interaction (phosphorylated EGFR (Y1173)) to dichotomize patients optimally based on the data and assessed it in the context of the graduating signature by adding the EGFR Y1173-High patients to the HR-/HER2+ subtype and evaluating the treatment effect in this ‘biomarker-positive’ group. Our study is exploratory with no claims for generalizability of the data and does not account for multiplicities. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). Results: 7 HER pathway markers (EGFR Y1068, EGFR Y1173, EGFR Y992, ERBB2 total, ERBB2 Y1248, ERBB3 Y1289, SHC Y317) are associated with response in the N but not the control arm. However, the difference in performance between arms did not reach significance by permutation testing. Adjusting for HR/HER2 status, EGFR Y1173 shows a significant biomarker x treatment interaction (p = 0.049). In an exploratory analysis, we dichotomized patients by their EGFR Y1173 levels and evaluated the distribution of pCR rates (Table 1). OR between EGFR Y1173 groups in the N relative to control arm is 10.1. When EGFR Y1173 High patients are added to the graduating HR-/HER2+ subset, the OR associated with treatment is 3.2 and is comparable to that in the HR-/HER2+ signature (OR: 2.1), while increasing the prevalence of biomarker-positive patients by ∼50%. Evaluation of EGFR Y1173 under the I-SPY 2 Bayesian model is pending. Conclusion: Our sample size is too small to draw definitive conclusions. Our exploratory analysis reveals that HER family phosphoproteins associate with response to N, but only phosphorylated EGFR Y1173 appears to add value to the graduating signature. Given that this biomarker would expand the patient population that may benefit, it merits evaluation in other ongoing trials of neratinib. Citation Format: Julia D Wulfkuhle, Christina Yau, Denise M Wolf, Rosa I Gallagher, Ashish Sanil, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, I-SPY 2 TRIAL Investigators, Meredith Buxton, Angela DeMichele, Nola Hylton, William F Symmans, Laura van9t Veer, Douglas Yee, Melissa Paoloni, Laura Esserman, Donald Berry, Minetta C Liu, John W Park, Emanuel F Petricoin III. Evaluation of HER family protein signaling network as a predictive biomarker for pCR for breast cancer patients treated with neratinib in the I-SPY 2 trial [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-15.

Abstract P3-06-05: Evaluation of an in vitro derived signature of olaparib response (PARPi-7) as a predictive biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 TRIAL

Background: We developed a 7-gene DNA-repair deficiency signature (PARPi-7) that predicts breast cancer cell line sensitivity to the PARP inhibitor olaparib [PMID: 22875744]. We hypothesized that this signature would also predict response to other PARP inhibitors including veliparib. In the I-SPY 2 TRIAL, HER2- patients were randomized to receive standard chemotherapy or the oral PARP inhibitor veliparib in combination with carboplatin (V/C) and chemotherapy. V/C graduated in the triple-negative (TN) signature. Here we assess the PARPi-7 as a specific biomarker of V/C response. Methods: 115 HER2- patients (V/C: 71 and concurrent controls: 44) were considered in this analysis. The PARPi-7 signature score is computed from Agilent 44K array data as published using expression levels of BRCA1, CHEK2, MAPKAPK2, MRE11A, NBN, TDG, and XPA. We assess association between PARPi-7 and response in the V/C and control arms alone (Wald p Results: The PARPi-7 signature associates with patient response in the V/C arm (OR = 3.9, p=0.00056) but not in the control arm (OR = 0.87, p=0.68). There is a significant biomarker x treatment interaction (OR in V/C arm relative to control arm = 4.48, p=0.0028), which remains significant upon adjusting for HR status (p=0.0018). In an exploratory analysis, PARPi-7 dichotomized using the published in vitro derived cutpoint yields 62 PARPi-7 Low and 53 PARPi-7 High patients. 26% of PARPi-7 High patients are not TN. The distribution of pCR rates among PARPi-7 dichotomized groups are in Table 1. When the PARPi-7 High patients are added to the graduating TN subset, the OR associated with V/C is 5.12, which is comparable to that of the TN signature (OR: 4.29), while increasing the prevalence of biomarker-positive patients by ∼12%. Evaluation of PARPi-7 in the context of the graduating signature under the I-SPY 2 Bayesian model is pending. Conclusion: Our sample size is small. Our pre-specified analysis suggests the PARPi-7 signature shows promise for predicting response to veliparib/carboplatin combination therapy relative to control. If verified in a larger trial, this cell-line derived signature may contribute to the selection criteria of PARP inhibitor trials in the future. Citation Format: Denise M Wolf, Christina Yau, Ashish Sanil, Anneleen Daemen, Laura Heiser, Joe Gray, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, I-SPY 2 TRIAL Investigators, Meredith Buxton, Angela DeMichele, Nola Hylton, Fraser Symmans, Doug Yee, Melissa Paoloni, Laura Esserman, Don Berry, Hope Rugo, Olufunmilayo Olopade, Laura van 9t Veer. Evaluation of an in vitro derived signature of olaparib response (PARPi-7) as a predictive biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-05.

Abstract P3-06-25: MammaPrint High1/High2 risk class as a biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL

Background: Further stratification of the 70-gene MammaPrintTM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score Methods:115 HER2- patients (V/C: 71 and concurrent controls: 44) were considered in this analysis. We assess association between MP1/MP2 and response in the V/C and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p Results: In the V/C arm vs. concurrent controls, there were 66 MP1 (V/C: 32, Control: 34) and 49 MP2 patients (V/C: 39, Control: 10), 78% of which are TN. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. The OR between MP1/MP2 risk groups for predicting pCR is 9.71 in the V/C arm (p=6.63E-05), in comparison to an OR of 0.97 in the control arm (p=1). There is a significant biomarker x treatment interaction (p=0.023), which remains upon adjusting for HR status (p= 0.028). Based on the I-SPY 2 Bayesian model, a Phase III trial with 300 MP2 patients has a 95% predictive probability of success. When the MP2 patients are added to the graduating TN subset, the OR associated with V/C is 4.36, which is comparable to that of the TN signature (OR: 4.29), while increasing the prevalence of biomarker-positive patients by ∼10%. Conclusion: In our exploratory analysis, MP2 suggests higher sensitivity to V/C combination therapy relative to controls. This observation has prompted an investigation into the biological mechanisms distinguishing the MP1/MP2 subtype that may account for this specificity. Citation Format: Denise M Wolf, Christina Yau, Ashish Sanil, Jo Chien, Anne Wallace, Angela DeMichele, Hank Kaplan, Doug Yee, Claudine Isaacs, Kathy Albain, Rebecca Viscuzi, Judy Boughey, Stacey Moulder, Steven Chui, Qamar Khan, Toncred Styblo, Kirsten Edmiston, Donald Northfelt, Anthony Elias, Barbara Haley, Debu Tripathy, Lamorna Brown-Swigart, Susan Flynn, Gillian Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, Fraser Symmans, Laura Esserman, Don Berry, Hope Rugo, Olufunmilayo I. Olopade, Laura van 9t Veer. MammaPrint High1/High2 risk class as a biomarker of response to veliparib/carboplatin plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-25.

Abstract P3-06-29: MammaPrint High1/High2 risk class as a biomarker of response to neratinib plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL

Background: Further stratification of the 70-gene MammaPrint TM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score AC). HER2- patients were randomized to receive N+T- >AC vs. T->AC. For HER2+ patients, neratinib was administered in place of trastuzumab (N+T->AC vs. H+T->AC). Here, we assess the performance of MP1/MP2 class as a specific biomarker of neratinib response. Methods: 115 patients in the neratinib arm and 76 concurrently randomized controls had Agilent 44K microarrays and pCR data available for analysis. We assess association between MP1/MP2 and response in the neratinib and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p Results: There are 133 MP1 patients (neratinib: 74, Control: 59) and 58 MP2 patients (neratinib: 41, Control: 17), 84% (49) of which are Her2-. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. MP2, one of the 10 eligible signatures, did not meet the graduation threshold; and MP1/MP2 did not show a significant biomarker x treatment interaction (OR in neratinib relative to control arm = 1.25). The MP1/MP2 x treatment interaction remains non-significant after adjustment for HR and HER2 status (p=0.54). In HER2- patients receiving neratinib, 45% (15/33) of MP2 patients achieved a pCR, compared to 0% (0/17) of MP1 patients. In the HER2- controls, there is a 31% pCR rate in MP2 (5/16) vs. 18% in MP1 (7/39) patients (OR=2.14). This difference in performance between treatment arms appears significant (p=0.041). 90% of HER2+ patients are MP1, thus MP1/MP2 status x treatment interaction within the HER2+ subtype cannot be evaluated. Conclusion: Within the I-SPY 2 population as a whole, MP1/MP2 stratification does not appear to be a specific biomarker of response to neratinib relative to the control arm. The number of HER2- patients is small and precludes any definitive conclusion, but these data motivate further investigation of the biological mechanisms distinguishing MP1 from MP2 to better understand chemotherapy and/or neratanib responsiveness. Citation Format: Christina Yau, Denise M Wolf, Ashish Sanil, Jo Chien, Anne Wallace, Judy Boughey, Doug Yee, Debu Tripathy, Angela DeMichele, Rita Nanda, Steven Chiu, Claudine Isaacs, Kathy Albain, Hank Kaplan, Stacey Moulder, Rebecca Viscusi, Donald Northfelt, Kirsten Edmiston, Anthony Elias, Toncred Styblo, Barbara Haley, Lamorna Brown-Swigart, Susan Flynn, Gillian L Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, W Fraser Symmans, Laura Esserman, Don Berry, Minetta C Liu, John W Park, Laura van 9t Veer. MammaPrint High1/High2 risk class as a biomarker of response to neratinib plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-29.