Veer, Laura J. van’t

Abstract Background: In the I-SPY 2 TRIAL, the addition of P to standard NAC resulted in more than doubling of the pathologic complete response (pCR) rates for both hormone receptor-positive (HR+)/HER2- and triple-negative (TN) early breast cancer (EBC) patients (pts) compared to NAC only (Nanda et al, JAMA Oncol, 2020). At 3 years, distant recurrence-free survival (DRFS) rates in pts with pCR following NAC+P was >95%. We hypothesized that ctDNA can serve as a predictive biomarker of response and survival in pts treated with NAC. Methods: A personalized ctDNA test (Signatera) was performed on 511 serial plasma samples from 138 pts with high-risk HR+/HER2- (n=77) or TN (n=61) stage II/III EBC. Pts received P with paclitaxel (Tx) followed by AC (P arm, n=42) or standard NAC only (n=96), an exploratory subset of pts evaluated for P efficacy. Plasma was collected; pretreatment (T0), 3 weeks after treatment initiation (T1), between Tx+/-P and AC regimens (T2), and prior to surgery (T3). ctDNA was deemed positive with a minimum of 2 of the pt specific tumor mutation fragments detected in cfDNA. Association of ctDNA with response and survival was analyzed using logistic and Cox regressions with pCR and DRFS as endpoints. Median follow-up was 2.8 years. Results: Detection of ctDNA decreased over time (P arm: T0-81%, T1-50%, T2-19%, T3-3%) and NAC only: T0-82%, T1-65%, T2-26%, T3-10%). ctDNA data at T0 and T1 was available for 96% (132/138) of pts in P arm or NAC only (Table). Among ctDNA+ patients at baseline, clearance at T1 was significantly associated with pCR (OR=1.92, ctDNA+/-; OR=0.27, ctDNA+/+; LR p<0.001). This association remained significant after adjustment for HR status and treatment (LR p<0.001) and P arm or NAC only (P: LR p=0.03; NAC: LR p=0.01). ctDNA data at T0, T1, and T2 was available for 86% (118/138) pts. (Table). Among all ctDNA+ pts at baseline, dynamics through T2 was associated with pCR (OR=1.44, ctDNA+/-/-; OR=0.33, ctDNA+/+/-, OR=0.12, ctDNA+/+/+; LR p=0.0011). This association remained significant when adjusted for HR status and treatment (LR p<0.001). Analysis within individual treatments showed significant association for NAC (LR p=0.040) and a non-significant trend in NAC+P (LR p=0.063), likely due to smaller sample size. All pts who achieved pCR were ctDNA- at T3 (n=34). Among those who failed to achieve pCR (n=81), DRFS was significantly better in ctDNA- (n=72/81; 20 in P and 52 in NAC) versus ctDNA+ pts (n=9/81; 1 in P and 8 in NAC) (adjusted HR 0.13; 95% CI 0.05-0.37). Conclusions: These exploratory results align with our previous findings that early clearance of ctDNA during NAC treatment was significantly associated with increased likelihood of achieving pCR. Additionally, we show that ctDNA clearance can be an early surrogate marker for therapy response assessment. Residual ctDNA after neoadjuvant treatment was a significant predictor of metastatic recurrence and death. Personalized monitoring of ctDNA during the course of NAC is feasible and provides information that can be combined with imaging and pathology, and may help to optimize decision making for de-escalation or escalation of therapy. Larger studies are ongoing. ctDNA dynamics and pCRctDNA status at T0 and T1 (n=132)ctDNA status at T0, T1, and T2 (n=118)ctDNA-/-ctDNA+/-ctDNA+/+ctDNA-/-/-ctDNA+/-/-ctDNA+/+/-ctDNA+/+/+Total, n (%)24 (18)28 (21)80 (61)22 (19)24 (20)43 (36)27 (23)pCR, n (%)9 (38)15 (54)11 (14)9 (41)12 (50)8 (19)2 (7)No pCR, n (%)15 (63)13 (46)69 (86)13 (59)12 (50)35 (81)25 (93) Citation Format: Mark Jesus M Magbanua, Denise Wolf, Derrick Renner, Svetlana Shchegrova, Lamorna Brown Swigart, Christina Yau, Gillian Hirst, Hsin-Ta Wu, Ekaterina Kalashnikova, Antony Tin, Amy Delson, Douglas Yee, Angela DeMichele, Raheleh Salari, Angel Rodriguez, Bernhard Zimmermann, Himanshu Sethi, Alexey Aleshin, Paul Billings, Laura Esserman, Minetta Liu, Rita Nanda, Laura van ‘t Veer, I-SPY 2 Investigators. Personalized ctDNA as a predictive biomarker in high-risk early stage breast cancer (EBC) treated with neoadjuvant chemotherapy (NAC) with or without pembrolizumab (P) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD9-02.

Abstract Background: I-SPY 2 is a multicenter, phase 2 trial using response-adaptive randomization within molecular subtypes defined by receptor status and MammaPrint (MP) risk to evaluate novel agents as neoadjuvant therapy for women with high-risk stage II/III breast cancer. The primary endpoint is pathologic complete response (pCR, ypT0/Tis ypN0). SGN-LIV1A is an investigational antibody drug conjugate consisting of an antibody to LIV1A, a zinc transporter highly prevalent in breast cancer, and a highly potent microtubule inhibitor, monomethyl auristatin E. Retrospective IHC analysis of LIV1A expression levels amongst tumor samples from 100 previous ISPY-2 patients showed 88% of breast tumor samples with moderate to high expression of LIV1A (Yau, C. et al SABCS 2018).Methods: Women with tumors ≥ 2.5cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment, hormone-receptor positive (HR+) patients had to have MP high molecular profile. Treatment included SGN-LIV1A 2.5 mg/kg (max dose 250 mg) every 3 weeks x 4, followed by doxorubicin/cyclophosphamide (AC) every 2-3 weeks x 4. The control arm was weekly paclitaxel x 12 followed by AC every 2-3 weeks x 4. All patients undergo serial MR imaging where response at 3 & 12 weeks combined with accumulating pCR data are used to estimate, and continuously update, predicted pCR rate for the trial arm. Analysis set was modified intention to treat with patients who switched to non-protocol therapy counted as non-pCR and not as their pCR status at time of surgery. The goal is to identify/graduate regimens with ≥85% Bayesian predictive probability of success (i.e. demonstrating superiority to control) in a future 300-patient phase 3 neoadjuvant trial with a pCR endpoint within signatures defined by HR & HER2 status & MP result. This investigational arm was eligible for graduation in 3 of 10 pre-defined signatures: HER2-, HR+HER2- and HR-HER2-. Regimens may also leave the trial for futility (< 10% probability of success), maximum sample size accrual (10% < probability of success <85%), maximum time in trial (2 years) or for safety as recommended by the independent DSMB. Results: Sixty patients were randomized and evaluable to SGN-LIV1A. The study arm was stopped due to reaching the predetermined time limit for patient accrual of 2 yrs. Final estimated pCR rates are below. The estimated pCR rates were similar between the SGN-LIV1A and control arms for any tumor subtype. Preliminary safety events for SGN-LIV1A include increased rates of transaminitis and hyperglycemia and reduced rates of peripheral neuropathy compared to control. One patient was removed from the analysis as she was determined to have angiosarcoma of the breast. Notably, this patient had a dramatic early response and subsequent pCR to SGN-LIV1A treatment. Conclusion: The value of I-SPY 2 is to give insight about the performance of an investigational agent’s likelihood of achieving pCR. SGN-LIV1A delivered every 3 weeks was comparable to paclitaxel for the primary endpoint of pCR in I-SPY2 and may have a similar side effect profile, however, with less peripheral neuropathy. Clinical trials evaluating weekly dosing of SGN-LIV1A are ongoing. A trial of SGN-LIV1A in the treatment of angiosarcoma is under consideration at this time. Final Estimated pCR Rates and Predictive ProbabilitiesEstimated pCR rate(95% prob interval)SignatureSGN-LIV1AControlProbability SGNLIV1A Superior to ControlPredictive Probability of Success in Phase 3HER2-0.16 (0.08-0.24) N= 600.20 (0.16-0.25) N= 3270.180.02HR-/HER2-0.25 (0.12-0.37) N=360.28 (0.21-0.35) N=1460.310.06HR+/HER2-0.09 (0-0.18) N=240.14 (0.09-0.19) N=1810.150.03 Citation Format: Heather Beckwith, Richard Schwab, Christina Yau, Erica Stringer-Reasor, Shi Wei, A. Jo Chien, Kathy S Albain, Kevin Kalinsky, Anne Wallace, Anthony Elias, Douglas Yee, Amy S Clark, Judy C Boughey, Heather Han, Rita Nanda, Claudine Isaacs, Zahi Mitri, Julie E Lang, Alexandra Thomas, Tara Sanft, Angela DeMichele, Jane Perlmutter, Hope S Rugo, Nola M Hylton, W. Fraser Symmans, Michelle E Melisko, Laura J van't Veer, I-SPY 2 Consortium, Amy Wilson, Smita M Asare, Ashish Sanil, Donald A Berry, Laura J Esserman. Evaluation of SGN-LIV1a followed by AC in high-risk HER2 negative stage II/III breast cancer: Results from the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD1-10.

Abstract Background: Pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in patients with breast cancer is associated with improved survival. Further assessment of the extent of residual disease, using the pathological anatomic American Joint Committee on Cancer staging method (ypStage) or the Residual Cancer Burden (RCB) method, have been shown to add prognostic information for patients with residual disease. Neo-Bioscore, an alternate system to classify response to NAC, includes clinical stage at diagnosis and biology and defines eight prognostic groups. The goal of this study was to compared three scoring systems (anatomic ypStage (7th ed), RCB Class and Neo-Bioscore) and assess whether RCB Class and Neo-Bioscore provide additional prognostic value in the context above anatomic ypStage, the most commonly used method for post-neoadjuvant residual disease assessment. Methods: Data from 5161 patients treated with NAC was pooled from 12 sites. Patients without clinical and pathological staging were excluded, as were patients with HER2+ breast cancer who did not receive neoadjuvant HER2-targeted therapy, leaving 3730 for analysis. PCR was defined as no residual invasive tumor in breast and nodes, i.e. RCB-0 or ypT0/Tis and ypN0. Patients with discordant pCR status by RCB Class vs ypStage (n=9) were excluded. Associations between each scoring system and event-free survival (EFS) were evaluated using the log rank test. EFS at 5 years was estimated using the Kaplan Meier method. Associations between Neo-Bioscore and EFS were assessed in the pCR group. For patients with residual disease, we assessed RCB and Neo-Bioscore within each ypStage. Analysis was performed overall and within subtype. Subgroups with <5 patients were excluded from the survival analyses. Results: ypAJCC staging, RCB class and Neo-Bioscore were all associated with EFS in the overall population and within each subtype (log rank p<0.0001). Of note, 13 patients with a Neo-Bioscore of 7 all recurred or died within 19 months of follow-up. Overall, 34% (1264/3721) of patients achieved a pCR. Their Neo-Bioscore ranges from 0-5, where 3% (37/1264) has a Neo-Bioscore of 5 despite achieving pCR. The Neo-Bioscore was not associated with EFS in case of a pCR, with EFS estimates at 5 years of 95%, 94%, 92%, 93%, 90% and 92% for Neo-Bioscores 0-5 respectively. As HR and HER2 status are components of the score, the range of Neo-Bioscore in the pCR group differs by subtype. However, similar to the overall analysis, the Neo-Bioscore was not prognostic within subtypes in case of pCR. Overall, among the patients who did not achieve pCR, both RCB class and Neo-Bioscore were associated with EFS within ypStages I, II and III. However, the ypStage within which RCB and Neo-Bioscore are prognostic is different for each subtype. RCB class was prognostic in ypStage I in both HR+ subtypes: patients with ypStage-I/RCB-I had significantly improved survival compared to patients with ypStage-I/RCB-II (5-year EFS: 100% vs 83% in HR+HER2- and 95% vs 77% in HR+HER2+). In contrast, for patients with triple negative breast cancer, RCB class was prognostic within ypStage II and III. Analysis by clinical stage and the components of the three systems that contribute most to prognosis will be presented. Conclusions: The degree of response to NAC adds important information to pCR versus residual disease. The Neo-Bioscore was not prognostic among patients with pCR, suggesting that clinical stage (including subtype and grade) adds little information in the setting of a pCR. In contrast, both RCB and Neo-Bioscore provide additional prognostic information to the conventional ypAJCC staging among non-pCR patients, suggesting that clinical stage, tumor biology as well as extent of residual disease all contribute to prognosis in the setting of residual disease after NAC. Citation Format: Marieke EM van der Noordaa, Christina Yau, Sonal Shad, Marie Osdoit, Tessa G Steenbruggen, Diane de Croze, Anne-Sophie Hamy, Marick Lae, Fabien Reyal, Maria Del Monte-Millán, Miguel Martin, Sara Lopez Tarruella, I-SPY 2 TRIAL Consortium, Judy C Boughey, Matthew Goetz, Tanya Hoskin, Rebecca Gould, Vincent Valero, Gabe Sonke, Maartje van Seijen, Jelle Wesseling, John Bartlett, Stephan Edge, Mi-Ok Kim, Jean Abraham, Carlos Caldas, Helena Earl, Elena Provenzano, Stephen-John Sammut, David Cameron, Ashley Graham, Peter Hall, Lorna MacKintosh, Fang Fan, Andrew K Godwin, Kelsey Schwensen, Priyanka Sharma, Angela DeMichele, Janet Dunn, Louise Hiller, Larry Hayward, Jeremy Thomas, Kimberley Cole, Lajos Pusztai, Laura van 't Veer, Fraser Symmans, Laura Esserman. Assessing prognosis after neoadjuvant therapy: A comparison between anatomic ypAJCC staging, residual cancer burden class and neo-bioscore [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr GS4-07.

Abstract Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within molecular subtypes defined by receptor status and MammaPrint risk to evaluate novel agents as neoadjuvant therapy for breast cancer. The primary endpoint is pathologic complete response (pCR, ypT0/is ypN0)). DNA repair deficiency in cancer cells can lead to immunogenic neoantigens, activation of the STING pathway, and PARP inhibition can also upregulate PD-L1 expression. Based on these rationales we tested the combination of durvalumab (anti-PDL1), olaparib (PARP inhibitor) and paclitaxel in I-SPY2. Methods: Women with tumors ≥ 2.5 cm were eligible for screening. Only HER2 negative (HER2-) patients were eligible for this treatment, hormone receptor positive (HR+) patients had to have MammaPrint high molecular profile. Treatment included durvalumab 1500 mg every 4 weeks x 3, olaparib 100 mg twice daily through weeks 1-11 concurrent with paclitaxel 80 mg/m2 weekly x 12 (DOP) followed by doxorubicin/cyclophosphamide (AC) x 4. The control arm was weekly paclitaxel x 12 followed by AC x 4. All patients undergo serial MRI imaging and imaging response at 3 & 12 weeks combined with accumulating pCR data are used to estimate, and continuously update, predicted pCR rate for the trial arm. Regimens “graduation with success” when the Bayesian predictive probability of success in a 300-patient phase 3 neoadjuvant trial in the appropriate biomarker groups reaches > 85%. Results: A total of 73 patients received DOP treatment including 21 HR- tumors (i.e. triple-negative breast cancer, TNBC) and 52 HR+ tumors between May 2018 - June 2019. The control group included 299 patients with HER2- tumors. The DOP arm graduated in June 2019, 13 months after enrollment had started, for all HER2- negative and the HR+/HER2- cohorts with > 0.85% predictive probabilities of success. 72 patient completed surgery and evaluable for pCR, the final predicted probabilities of success in a future phase III trial to demonstrate higher pCR rate with DOP compared to control are 81% for all HER2- cancers (estimated pCR rate 37%), 80% for TNBC (estimated pCR rate 47%) and 74.5% for HR+/HER2- patients (estimated pCR rate 28%). Association between pCR and germline BRCA status and immune gene expression including PDL1 will be presented at the meeting. No unexpected toxicities were seen, but 10 patients (14%) had possibly immune or olaparib related grade 2/3 AEs (3 pneumonitis, 2 adrenal insufficiency, 1 colitis, 1 pancreatitis, 2 elevated LFT, 1 skin toxicity, 2 hypothyroidism, 1 hyperthyroidism, 1 esophagitis). Conclusion: I-SPY2 demonstrated a significant improvement in pCR with durvalumab and olaparib included with paclitaxel compared to chemotherapy alone in women with stage II/III high-risk, HER2-negative breast cancer, improvement was seen in both the HR+ and TNBC subsets. Citation Format: Lajos Pusztai, Hyo S. Han, Christina Yau, Denise Wolf, Anne M. Wallace, Rebecca Shatsky, Teresa Helsten, Judy C. Boughey, Tufia Haddad, Erica Stringer-Reasor, Carla Falkson, A. Jo Chien, Rita Mukhtar, Anthony Elias, Borges Virginia, Rita Nanda, Douglas Yee, Kevin Kalinsky, Kathy S. Albain, Aixa Soyano Muller, Kathleen Kemmer, Amy S. Clark, Claudine Isaacs, Alexandra Thomas, Nola Hylton, W. Fraser Symmans, Jane Perlmutter, Michelle Melisko, Hope S. Rugo, Richard Schwab, Amy Wilson, Amy Wilson, Ruby Singhrao, Smita Asare, Laura J. van't Veer, Angela M. DeMichele, Ashish Sanil, Donald A. Berry, Laura J. Esserman, Trial Consortium I-SPY 2. Evaluation of durvalumab in combination with olaparib and paclitaxel in high-risk HER2 negative stage II/III breast cancer: Results from the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr CT011.

Abstract Purpose In breast MRI, contrast enhancement of normal fibroglandular tissue is referred to as background parenchymal enhancement (BPE). Hormonal status significantly affects the degree of BPE, potentially due to the association with mammary vascularity and activity1-5. Studies have shown that BPE may be associated with breast cancer survival6, treatment response to neoadjuvant chemotherapy (NAC)7,8 and future breast cancer risk9. In most patients undergoing NAC, BPE is suppressed by the nonspecific anti-proliferative effects of chemotherapy on normal breast and/or ovary5,10. However, some patients exhibit equivalent or even stronger BPE post-NAC compared to pre-NAC. We hypothesized that non-suppressed BPE in post-NAC MRI may be associated with inferior treatment response. This study aimed to investigate the association between BPE suppression and treatment response as defined by pathologic complete response (pCR). Methods This study included patients with stage II/III breast cancer enrolled in the I-SPY 2 TRIAL being treated with standard NAC with or without investigational agents. The whole cohort was split into two subgroups based on hormone receptor status (HR+, n= 536; HR-, n=452). Patients underwent dynamic contrast enhanced MRIs at four time points during NAC: baseline (T0), after 3 weeks of the first regimen (T1), inter-regimen (T2), and pre-surgery (T3). Using in-house software, the contralateral breast parenchyma was automatically segmented for the entire breast volume. Quantitative BPE (qBPE) was calculated as the mean early (~150s post-contrast injection) percent enhancement of the central 50% of the axial slices. A breast radiologist reviewed all exams and excluded those where automated segmentation failed to accurately define tissue. For T1, T2 and T3, BPE was categorized based on the change from T0 as suppressed (qBPE < qBPE[T0]) or non-suppressed (qBPE ≥ qBPE[T0]). Chi-squared test was used to examine the association between BPE suppression and pCR, with p<0.05 considered statistically significant. Results HR+ cohort: pCR rates were lower for patients with non-suppressed BPE than those with suppressed BPE at every visit (T1-T3) (Table 1). The difference was statistically significant at T2 (p=0.04) and T3 (p=0.01). Table 1: HR+ cohortpCR rate (%)No. of pCR patientsNo. of non-pCR patientsTotal number of patientsP valueOverall22.8122414536BPE at T1suppressed23.6822663480.45non-suppressed20.532124156BPE at T2suppressed25.7972803770.04*non-suppressed16.01789106BPE at T3suppressed25.7982833810.01*non-suppressed12.5128496 HR- cohort: pCR rates were slightly lower for the non-suppressed BPE group, but no statistically significant association was found (Table 2). Table 2: HR- cohortpCR rate (%)No. of pCR patientsNo. of non-pCR patientsTotal number of patientsP valueOverall44.7202250452BPE at T1suppressed46.81411603010.66non-suppressed44.45265117BPE at T2suppressed48.81441512950.79non-suppressed47.3434891BPE at T3suppressed49.31461502960.94non-suppressed48.9434588 Conclusion In HR+ breast cancer, lack of BPE suppression may indicate inferior treatment response. The contrasting results in HR+ and HR- cohorts are noteworthy in terms of the possible relationship between suppression of normal mammary and ovarian activity and treatment response in HR+ cancer. Reference Radiographics 2014; 34: 234-47. Radiology 1997; 203: 137-44. Radiology 1997; 203: 145-9. Breast J 2005; 11: 236-41. AJR Am J Roentgenol 2015; 204: 669-73. Eur Radiol 2018; 28: 4705-16. Eur Radiol 2016; 26: 1590-6. Transl Oncol 2015; 8: 204-9. J Clin Oncol 2019; : JCO1800378. Radiology 2015; 277: 687-96. Citation Format: Natsuko Onishi, Wen Li, David C. Newitt, Roy Harnish, Jessica Gibbs, Ella F. Jones, Alex Nguyen, Lisa Wilmes, Bonnie N. Joe, Michael J. Campbell, Amrita Basu, Laura J. van’t Veer, Angela DiMichele, Douglas Yee, Donald A. Berry, Kathy S. Albain, Judy C. Boughey, A. Jo Chien, Amy S. Clark, Kirsten K. Edmiston, Anthony D. Elias, Erin D. Ellis, David M. Euhus, Heather S. Han, Claudine Isaacs, Qamar J. Khan, Julie E. Lang, Janice Lu, Jane L. Meisel, Zaha Mitri, Rita Nanda, Donald W. Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K. Viscusi, Anne M. Wallace, Rachel Yung, Michelle E. Melisko, Jane Perlmutter, Hope S. Rugo, Richard Schwab, W. Fraser Symmans, Smita M. Asare, Julie E. Yau, Christina Yau, Laura J. Esserman, Nola M. Hylton. Lack of background parenchymal enhancement suppression in breast MRI during neoadjuvant chemotherapy may be associated with inferior treatment response in hormone receptor positive breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-05.

Abstract Background: In an adaptive randomized trial, when new treatment combinations are being tested, it is important to be able to identify patients who are progressing on treatment so that they can be changed to a different therapeutic regimen. We know that even within the molecularly high risk patients in I-SPY 2, there is considerable variation in biology. In this study, we will present results of using MRI-calculated functional tumor volume (FTV) to identify tumor progression for each breast cancer subtype. Methods: Patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Four MRI exams were performed for each patient: pre-NAC (T0), after 3 weeks of NAC (T1), between regimens (T2), and post-NAC (T3). Functional tumor volume (FTV) was calculated at each exam by summing voxels meeting enhancement thresholds. Tumor progression at T1, T2 or T3 was identified by a positive FTV change relative to T0. Visual inspection was used to exclude false progression due to strong background parenchymal enhancement post-contrast, prominent vessels, motion, or insufficient image quality. pCR was defined as no invasive disease in the breast and lymph nodes. Negative predictive value for pCR was defined as:NPV=number of true non-pCRs / number of patients with MRI assessed tumor progressions, where “true non-pCRs” referred to patients who were non-pCRs at surgery and were assessed as progressors by MRI. The analysis was performed in the full cohort and in sub-cohorts defined by HR and HER2 statuses. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Total and non-pCR numbers for each subtype, number of patients with tumor progression assessed by MRI at T1, T2, and T3, and NPVs, are shown in Table 1. In the full cohort, the NPV increased consistently over treatment, from T1 (NPV=83%) to T2 (93%), and to T3 (100%). The HER2+ cancer subtypes showed fewer MRI-assessed tumor progressions than HER2- subtypes: e.g. 10/209 (5%) vs. 108/669 (16%) at T1. NPV was 100% for HER2+ subtypes at T1 and T2 except for a single misclassification of a HR- tumor at T1. Only 6 tumor progressors, all HER2- were identified at T3, and all were confirmed at surgery as non-pCRs (NPV=100%). For HR+/HER2-, the NPV increased slightly from 89% at T1 to 91% at T2, while triple negative subtype had a more substantial increase, from 78% to 92%. Conclusions: Our study showed strong association between tumor progressors assessed by MRI with true non-pCRs after NAC. For HER2+ tumors, although MRI progressors are rare, they strongly indicate non-pCR at all treatment time points, while HER2- subtypes show more accurate results later in treatment. We are evaluating MRI change at 6 weeks to determine if that time point is sufficient to predict progressors. Table 1 MRI assessed tumor progression at different treatment time pointN/non-pCRs/%non-pCRMRI assessed tumor progressionT1 (after 3 weeks)T2 (inter-regimen)T3 (post-NAC)NNPV (%)NNPV (%)NNPV (%)Full cohort878/572/65%11883.14192.76100%HR+/HER2-344/280/81%4588.91190.93100%HR+/HER2+134/85/63%610021000N/AHR-/HER2+75/23/31%47521000N/Atriple negative325/184/57%6377.82692.33100% Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Jessica Gibbs, Lisa J Wilmes, Ella F Jones, Bonnie N Joe, Laura S Sit, Christina Yau, A. Jo Chien, Elissa Price, Kathy S Albain, Theresa Kuritza, Kevin Morley, Judy C Boughey, Kathy Brandt, Sadia Choudhery, Amy S Clark, Mark Rosen, Elizabeth S McDonald, Anthony D Elias, Dulcy Wolverton, Kelly Fountain, David M Euhus, Heather S Han, Bethany Niell, Jennifer Drukteinis, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Smita M Asare, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Donald A Berry, Angela DeMichele, Hiroyuki Abe, Deepa Sheth, Kirsten K Edmiston, Erin D Ellis, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Michael Nelson, An Church, Claudine Isaacs, Qamar J Khan, Karen Y Oh, Neda Jafarian, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Pulin Sheth, Linda Hovanessian-Larsen, Mohammad Eghtedari, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Sally Goudreau, Thelma Brown, Laura J Esserman, Nola M Hylton. Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-04.

Abstract Background: The I-SPY 2 TRIAL enrolls women with locally advanced, molecular high-risk breast cancer. An integrated Residual Cancer Burden (iRCB), based on MRI volume change through treatment, is used to predict pathologic complete response (pCR) in the randomization/evaluation Bayesian engine. With the goal of effective de-escalation of treatment for patients exhibiting an early response, biomarkers are being assessed for their ability to predict pCR, alone or with MR data, during treatment. Here, we present the results of a pilot study to examine if invasive tumor cellularity in mid-treatment tissue core biopsies predicts pCR in a 40-patient cohort of I-SPY 2 patients. Other pathologic variables evaluated include Ki67, tumoral histologic features, and stromal tumor-infiltrating lymphocytes (sTILs). Methods: I-SPY 2 TRIAL pathologists (N=4) were provided images of H&E-stained and Ki67 IHC- labelled (DAKO/Agilent, clone MIB-1) core biopsy sections from 40 patients at the inter-regimen time point, ~12-weeks into treatment. Of the 40 patients, 35 had 4 cores, 3 had 3 cores, and 2 had 2 cores assessed. In total, images from 153 cores were evaluated. For each core, pathologists were asked to score the % area occupied by tumor bed (treatment changes and/or residual cancer), % of viable invasive tumor (0-100%) within tumor bed (with Nottingham grading, % Ki67 labelled, and % sTILs, using standardized guidelines). As decided by the pathologist group, only cores with identified tumor bed were included in the initial analysis. Concordance between pathologists was assessed for all scored criteria, using % agreement for dichotomous variables, and Pearson correlation (r)/standard deviation (sd) for continuous variables. The maximum and average cellularity recorded over all cores/patient, averaged over all pathologists, were analyzed for association with pCR using t- tests (significance threshold: p<0.05). Fisher’s Exact test was used for dichotomous variables, and Pearson’s correlation for association of continuous variables with the residual cancer burden (RCB) index. Results: Pathologist were in general agreement about the presence or absence of tumor bed, with greater than 82% agreement between any two (83-96%), and an overall agreement of 77%. For scoring the % of the tumor bed involved by invasive cancer, correlations between pairs of pathologists ranged from 0.79-0.95 (mean(r)=0.87, sd=5%), and agreement on a binary presence/absence of invasive cancer was 78%. Both the mean (t-test: p=7.59E-05) and maximum (t-test: p=0.0012) %invasive tumor at 12 weeks, scored as an average over all pathologists, were significantly higher in patients who did not achieve pCR than in responders. We also treated %invasive cellularity as a dichotomous variable (present/absent). 90% (9/10) of patients scored by all pathologists as 0% invasive tumor cells (absent) achieved a pCR, vs only 20% (6/30) of patients scored as >0% invasive cellularity by one or more pathologists (present) (OR=32, Fisher p=0.0005); yielding a positive predictive value for pCR of 0.9. Ki67 and sTILS at 12 weeks were fairly concordant across pathologists ((r,sd)=(0.92, 8.45%) and (0.82,5.5%), respectively), but did not associate with response (p>0.05 for pCR, RCB01, or RCB index). Tumor histologic grade at 12 weeks, assessed in 29/30 patients with non-zero cellularity, trended toward association (Fisher p=0.078): 44% (4/9) with Grade 3 went on to have a pCR, vs. 15% (2/13) with Grade 2 and 0 with Grade 1. These data demonstrate the utility of invasive tumor cellularity as a predictor of pCR in a clinical setting. Conclusion: In this pilot study we demonstrate that the absence of invasive cancer cells within identified tumor bed in mid-treatment core biopsy samples is highly predictive of pCR. Citation Format: Sara J Venters, Denise M Wolf, Lamorna Brown-Swigart, Christina Yau, Amy L Delson, Bev Parker, Ron Balassanian, Jodi Carter, Yunn-Yi Chen, Kimberly Cole, Laila Khazai, Molly Klein, Dina Kokh, Gregor Krings, Sunati Sahoo, Jane Wei, I-SPY 2 TRIAL Consortium, Laura J Esserman, Laura J van't Veer, W Fraser Symmans. Assessing biomarkers to inform treatment de-escalation: Mid-treatment biopsy cellularity predicts pCR in the I-SPY 2 Trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-10-02.

Abstract Background: Strong background parenchymal enhancement (BPE) may cause overestimation in tumor volume measured from dynamic contrast-enhanced (DCE) MRI, which may adversely affect the ability of MR tumor volume to predict treatment outcome for patients undergoing neoadjuvant chemotherapy (NAC). Specifically, an overestimation of tumor volume can result in misclassification of patients with complete pathologic response (pCR) as non-responders, leading to less confidence in MRI prediction. As well, overestimation of extent of disease might lead to more aggressive surgical therapy than necessary. This study investigated whether high BPE in the contralateral breast influences the predictive performance of MRI-measured functional tumor volume (FTV) for patients with locally advanced breast cancer undergoing NAC. Methods: patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Each patient had 4 MRI exams: pre-NAC (T0), after 3 weeks of NAC (T1), between NAC regimens (T2), and post-NAC (T3). FTV was calculated at each MRI exam by summing voxels meeting enhancement thresholds. Background parenchymal enhancement (BPE) in the contralateral breast was calculated automatically as mean percentage enhancement on the early (nominal 150sec post-contrast) image in the fibroglandular tissue segmented from 5 continuous axial slices centered in the inferior-to-superior stack. For each treatment time point, patients having both FTV and BPE measurements were included in the analysis. The area under the ROC curve (AUC) was estimated as the association between FTV and pCR at T1, T2, and T3. The analysis was conducted in the full patient cohort and in sub-cohorts defined by hormone receptor (HR) and HER2 status. In each patient cohort, a cut-off BPE value was selected to classify patients with high vs. low BPE by testing AUCs estimated with low-BPE patients reached maximum when the cut-off value varied from median to maximum in steps of 10%. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Table 1 shows the number of patients, pCR rate, and AUC of FTV for predicting pCR using all patients available vs. a subset patients with low BPE (< BPE cut-off). In the full cohort, AUC increased slightly across all time points after patients with high BPE were removed. In the HR+/HER2- subtype, AUC increased at T1 after removal of cases with high BPE (0.65 vs. 0.71). For HR-/HER2+, AUC increased substantially after removal of high BPE cases (0.65 to 0.86 at T1, 0.71 to 0.87 at T2, and 0.71 to 0.89 at T3), with greater improvement at the early time point (T1) compared to later time points (T2 and T3). Only a slight improvement in the AUC was observed in the HR+/HER2+ and HR-/HER2- subtypes across all time points. Conclusions: High background parenchymal enhancement adversely affected the predictive performance of functional tumor volume measured by DCE-MRI, at early treatment time point for HR+/HER2- and across all time points for HR-/HER2+ cancer subtype. The adverse effect might be offset using subtype-optimized enhancement threshold in calculating functional tumor volume. Table 1 Effect of BPE on the prediction of pCR using FTV at various treatment time pointsT1T2T3npCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offFullAll64734%0.662762334%0.701761134%0.6925Subset45334%0.6831133%0.7230534%0.72HR+/HER2-All26218%0.651924918%0.718225518%0.7519Subset13118%0.7124818%0.7120419%0.76HR+/HER2+All10636%0.642110538%0.62269634%0.7120Subset5332%0.668438%0.665740%0.73HR-/HER2+All5175%0.65204774%0.71204973%0.7116Subset3073%0.862871%0.872475%0.89HR-/HER2-All22842%0.682822243%0.751821143%0.6916Subset15940%0.7111137%0.7810540%0.75 Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Roy Harnish, Ella F Jones, Lisa J Wilmes, Jessica Gibbs, Elissa Price, Bonnie N Joe, A. Jo Chien, Donald A Berry, Judy C Boughey, Kathy S Albain, Amy S Clark, Kirsten K Edmiston, Anthony D Elias, Erin D Ellis, David M Euhus, Heather S Han, Claudine Isaacs, Qamar J Khan, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Christina Yau, Smita M Asare, Angela DeMichele, Sally Goudreau, Hiroyuki Abe, Deepa Sheth, Dulcy Wolverton, Kelly Fountain, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Theresa Kuritza, Kevin Morley, Michael Nelson, An Church, Bethany Niell, Jennifer Drukteinis, Karen Y Oh, Neda Jafarian, Kathy Brandt, Sadia Choudhery, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Mohammad Eghedari, Pulin Sheth, Linda Hovanessian-Larsen, Mark Rosen, Elizabeth S McDonald, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Laura J Esserman, Nola M Hylton. The effect of background parenchymal enhancement on the predictive performance of functional tumor volume measured in MRI [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-02-01.

Abstract Background: A variety of investigational HER2-inhibitor agents/combinations have been tested in I-SPY 2, including neratinib (N), TDM1 combined with pertuzumab (P) (TDM1/P), and trastuzumab (H) combined with pertuzumab (H/P; prior to this combination becoming standard of care), all with trastuzumab as control (Ctr). All three experimental arms graduated, showing improved efficacy over control in one or more receptor subsets (HR+HER2+, HR-HER2+, or/and HER2+). Here we assess 10 biomarkers in the HER2, ER/PR, and proliferation pathways on multiple levels of resolution (expression, protein, phospho-protein) as predictors of response in these four arms, hypothesizing that highly HER2-activated, proliferative tumors may be more sensitive to HER2-inhibition than those that are more luminal and quiescent. Methods: 192 HER2+ patients were considered in this analysis: (31 Ctr, 65 N, 52 TDM1/P, and 44 H/P). 10 biomarkers relating to HER2, ER, or proliferation were evaluated from pre-treatment biopsies: HER2 IHC (n=145), 3 expression signatures (n=192), BluePrint subtype (n=192), and 5 protein/phospho-protein analytes by RPPA (n=175). Each biomarker was tested for association with pCR in the whole population and within each arm using a logistic model. This analysis was adjusted for HR status and treatment arm as covariates, and performed within receptor subtypes. This analysis does not adjust for multiplicities of other biomarkers. Results: In the population as a whole, HER2 and HER2-signaling biomarkers, evaluated at multiple levels of resolution: IHC, total-/phospho-protein by RPPA, and mRNA (HER2 amplicon module) - are highly correlated (rho=0.8 [0.65-0.92]). Higher HER2 levels and activity are associated with response: HER2 IHC 3+ status (LR p=0.00032), total quantitative ERBB2 protein by RPPA (LR p=5.4E-09), ERBB2 activation levels (LR p=6.58E-06 (pERBB2 (Y1248)) and 9.95E-06 (pEGFR Y1173)), and the ERBB2 amplicon expression signature (LR p=2.38E-08). In contrast, higher average ER/PR expression associates with non-response to HER2-targeted therapy (LR p=4.28E-08). Both HER2 and ER/PR signaling phenotypes are captured by BluePrint subtyping; and consistent with the individual pathway markers, tumors classified Luminal-type had a lower pCR rate relative to those classified as Her2-type (or Basal-type) (LR p=4.84E-11). These associations all retain significance in a model adjusting for HR status and treatment arm, and in the HR+HER2+ subset. In addition, we quantitatively assessed proliferation markers at the total protein (RPPA: Ki67), phospho-protein (pAURKA) and mRNA (proliferation signature Module11_Prolif) levels. All three proliferation biomarkers predict response overall; but this association is strongest within the HR+HER2+ subset (LR p=0.0012 (Module11_prolif), 0.0036 (pAURK), and 0.045 (Ki67)). None of the biomarkers tested were associated with response in the HR-HER2+ subset. Numbers are small within individual arms. Within the HR+HER2+ subtype, higher HER2 and lower ER/PR is observed in responders in all experimental arms; but the proliferation markers Module11_Prolif (LR p=0.0031) and Ki67 total protein (LR p=0.0029) are associated with response to TDM1/P but not H/P or N. Conclusion: High HER2 signaling at the expression, protein, and phospho-protein levels, and low ER signaling, all predict response to HER2-inhibition across treatment arms. Proliferation markers may be useful for prioritizing therapies in the HR+HER2+ subset. Citation Format: Denise M Wolf, Christina Yau, Julia Wulfkuhle, Lamorna Brown-Swigart, Smita M. Asare, Gillian L. Hirst, Laura Sit, Jane Perlmutter, I-SPY 2 TRIAL Consortium, Minetta Liu, John Park, Angela DeMichele, Douglas Yee, Don Berry, Laura Esserman, Emanuel Petricoin, Laura van t' Veer. HER2 signaling, ER, and proliferation biomarkers predict response to multiple HER2-targeted agents/combinations plus standard neoadjuvant therapy in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-02.