Delson, Amy

Importance Although adding immune checkpoint inhibitors to neoadjuvant chemotherapy improves outcomes in high-risk early-stage breast cancer, opportunities remain to further enhance response. Dual checkpoint blockade offers a potential strategy to further enhance efficacy. Objective To evaluate the combination of anti−programmed cell death 1 protein (PD-1) cemiplimab and anti−lymphocyte activation gene 3 (LAG-3) added to neoadjuvant therapy in ERBB2 -negative early-stage, high-risk breast cancer. Design, Setting, and Participants The I-SPY2 (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis 2) is an ongoing randomized clinical platform trial being conducted at multiple US clinical sites including patients with early-stage (II or III) ERBB2 -negative, high-risk breast cancer. Participants, continuously enrolled since 2010, were adaptively randomized from February 2, 2020, to December 9, 2021, to one of several experimental neoadjuvant therapies or control groups based on receptor subtypes defined by hormone receptor (HR), ERBB2 status, and MammaPrint (Agendia Inc) molecular risk, categorized as high (MP1) or ultrahigh (MP2). Data were analyzed from January 1, 2022, to August 5, 2025. Interventions Both groups received weekly paclitaxel for 12 weeks, then doxorubicin and cyclophosphamide followed by surgery; concomitant with paclitaxel, the intervention group also received 4 doses of cemiplimab and fianlimab (PCF) every 3 weeks. Main Outcomes and Measures Pathologic complete response (pCR). Treatments graduated when they achieved 85% bayesian probability of success in a subtype-specific phase 3 trial. Pathway-specific biomarkers were assessed for response prediction. Results A total of 78 participants (mean [SD] age, 47 [39-54] years) were randomized to the intervention group, with 350 participants (mean [SD] age, 48 [39-57] years) randomized to the historical control population. PCF graduated in all clinical signatures, with pCR rates vs control of 44% (95% CI, 34%-53%) vs 21% (95% CI, 17%-25%) in all ERBB2 , 53% (95% CI, 39%-67%) vs 29% (95% CI, 22%-36%) in triple-negative, and 36% (95% CI, 23%-49%) vs 14% (95% CI, 9%-19%) in HR-positive and ERBB2 -negative disease. Among the total participants, 16 (21%) experienced adrenal insufficiency, including hypophysitis (11% grade 3 or 4), mostly occurring after immunotherapy completion. PCF was found to be highly effective in the subset of patients with immune signature positive status (ImPrint positive). Conclusions and Relevance In this randomized clinical trial, the combination of PD-1 and anti−LAG-3 inhibition with standard NAC was effective in early-stage ERBB2 -negative breast cancer, particularly in patients displaying a positive ImPrint immune signature. These results warrant further definitive trials. Trial Registration ClinicalTrials.gov Identifier: NCT01042379

PURPOSE Neoadjuvant immunotherapy (IO) has become the standard of care for early-stage triple-negative breast cancer (TNBC), but not yet for other subtypes. We previously developed a clinical-grade mRNA-based immune classifier (ImPrint) predicting response to IO that is now being used in I-SPY2.2 as part of the response predictive subtypes. We report the performance of ImPrint in hormone receptor–positive and human epidermal growth factor receptor 2–negative (HR+HER2–) patients from five IO arms. METHODS A total of 204 HR+HER2– (MammaPrint high-risk) patients from five IO arms (anti–PD-1, anti–PD-L1/poly [ADP-ribose] polymerase inhibitor combination, anti–PD-1/toll-like receptor 9 dual-IO combination, and anti–PD-1 ± lymphocyte activation gene 3 dual-IO combination) and 191 patients from the chemotherapy-only control arm were included in this analysis. Patients were classified as ImPrint+ (likely sensitive) versus ImPrint– (likely resistant), using pretreatment mRNA. Performance of ImPrint for predicting pathologic complete response (pCR) to IO-containing arms was characterized and compared with tumor grade (III), MammaPrint (ultra) High2 risk (MP2), and estrogen receptor (ER)-low (ER ≤ 10%). RESULTS Overall, the pCR rate across the five IO arms was 33%. 26% of HR+HER2– patients were ImPrint+, and pCR rates with IO were 75% in ImPrint+ versus 17% in ImPrint–, with the highest pCR rate >90% in a dual-IO arm. In the control arm, pCR rates were 33% in ImPrint+ and 8% in ImPrint–. Tumor grade (III), MP2, and ER-low showed pCR rates in IO of 45%, 56%, and 63%, respectively, with lower pCR odds ratios (OR < 7.5) compared with ImPrint (OR = 14.5). CONCLUSION Using an accurate selection strategy, HR+HER2– patients could achieve pCR rates similar to what is seen with best neoadjuvant therapies in TNBC and HER2+ (ie, pCR rate >65%-70%). ImPrint, an Food and Drug Administration IDE-enabled assay, may represent a way to identify HR+HER2– patients for IO that best balances likely benefit versus risk of serious immune-related adverse events.

Abstract Background: Neoadjuvant immunotherapy (IO) has become standard of care for early-stage triple negative breast cancer (TNBC). I-SPY2 was the first randomized trial to examine the efficacy of IO therapy in high-risk HR+HER2- breast cancer, where most IO arms showed improved efficacy relative to control. We also previously showed immune-gene expression signatures associate with pathologic complete response (pCR) in HR+HER2- treated with IO; and developed a clinically applicable Immune classifier (ImPrint) predicting response to IO that is now being used in I-SPY2.2 as part of the Response Predictive Subtypes. Here we report the performance of ImPrint in HR+HER2- patients from 5 IO arms. Methods: 204 HR+HER2- (MammaPrint high risk) patients from 5 IO arms (anti-PD1, anti-PDL1/PARPi, anti-PD1/TLR9 dual-IO, and anti-PD1 +/- LAG3 dual-IO) and 191 patients from the control arm were included in this analysis. Patients were classified ImPrint+ (likely sensitive) vs. ImPrint- (likely resistant), by Agendia, Inc, using pre-treatment mRNA. Performance of ImPrint for predicting pCR to IO was characterized and compared to that of MammaPrint (ultra) High2 risk (MP2) and tumor grade (III). Based on the DRFS of pCR vs. non-pCR HR+HER2-/ImPrint+ patients (median follow up ~4.5yr), we predicted the DRFS in the IO vs. control arms using an exponential model as a function of the pCR rates. Results: Overall, the pCR rate over the 5 IO arms was 33%. 28% of HR+HER2- patients were ImPrint+; and pCR rates with IO were 76% in ImPrint+ vs. 16% in ImPrint-, with the highest pCR rate &gt;90% in a dual-IO arm. In the control arm, pCR rates were 33% in ImPrint+ and 8% in ImPrint-. Based on the pCR rates in the IO vs. control (76% vs. 33%), the predicted DRFS of HR+HER2-/ImPrint+ patients are 91% vs 80% at 5 years, respectively. This translates to a risk reduction of 52% for the IO arm relative to standard chemotherapy in HR+HER2-/ImPrint+ patients. We also compared MP2 and tumor grade (III) to ImPrint+ as pCR predictors, as these markers have been used or proposed as selection markers for neoadjuvant IO trials in HR+HER2-. The pCR rates for MP2, Grade III, at 56%, 45%, respectively, are much smaller than that for ImPrint+ at 75% pCR; thus ImPrint appears to be a more precise predictive biomarker for neoadjuvant IO therapy in the HR+HER2- breast cancers. Conclusion: These results suggest that a subset of high risk HR+HER2- breast cancers is highly sensitive to immunotherapy, and by using a specific and sensitive selection strategy patients could achieve pCR rates similar to what is seen with best neoadjuvant therapies in TNBC and HER2+ (i.e., pCR rate &gt; 65-70%). ImPrint, an FDA IDE-enabled assay currently being further evaluated in I-SPY2, may represent the way to identify patients for IO that best balances likely benefit vs risk of serious immune-related adverse events. Citation Format: Denise M. Wolf, Christina Yau, Lajos Pusztai, Rita Nanda, Jo Chien, Erica Stringer-Reasor, Rebecca Shatsky, Claudine Isaacs, MInetta Liu, Hyo Han, Hatem Soliman, Michael Campbell, Annuska Glas, Andrei Barcaru, Lorenza Mittempergher, Midas Kuilman, Lamorna Brown Swigart, Gillian Hirst, Hongmei Yu, Philip Beineke, Amrita Basu, I-SPY2 Investigators, Douglas Yee, W. Fraser Symmans, Angela DeMichele, Jane Perlmutter, Amy Delson, Laura Huppert, Hope Rugo, Amy Clark, Nola Hylton, Paula Pohlmann, Laura Esserman, Laura van 't Veer. Immune subtyping identifies a subset of HR+HER2- early-stage breast cancer patients with a very high likelihood of response to neoadjuvant immunotherapy (IO): Results from 5 IO arms of the I-SPY2 TRIAL [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1207.

Abstract Background: We compared the predictive and prognostic value of ctDNA dynamics in high-risk hormone receptor-positive/HER2-negative (HR+/HER2-) and triple negative breast cancer (TNBC) receiving neoadjuvant chemotherapy (NAC) enrolled in the I-SPY 2 trial (NCT01042379). To our knowledge, this is the largest ctDNA study in breast cancer in the neoadjuvant setting. Methods: Blood samples were collected at pre-treatment (T0), during treatment (T1 at 3 weeks, and T2 at 12 weeks) and after NAC (T3 at 24 weeks) from 106 HR+/HER2- and 97 TNBC patients. Plasma samples (n=734) were analyzed using a personalized and tumor-informed mPCR NGS-based ctDNA test (SignateraTM). Patients, all high risk for recurrence by MammaPrint, received paclitaxel-based treatment +/- experimental therapy followed by anthracycline. The median follow-up was 3.0 years (0.5 to 6.5). The predictive and prognostic value of ctDNA dynamics and status at different timepoints were examined. Our analysis is exploratory and does not adjust for other biomarkers. Results: Pretreatment ctDNA positivity (Fisher p&lt;0.0001) and levels (mean tumor molecules/mL, MTM/mL, t test p=0.0062) were significantly higher in TNBC (90.7%, 14.7 MTM/mL) than in high risk HR+/HER2- (66.0%, 5.5 MTM/mL). Early and late ctDNA clearance during treatment (3 and 12 weeks of NAC) was predictive of pathologic complete response (pCR) and residual cancer burden (RCB), class 0-III, in TNBC but not HR+/HER2- (Table). In both subtypes: (1) ctDNA was a significant negative prognostic factor for distant recurrence-free survival (DRFS) at all timepoints (p&lt;0.05) except at pretreatment; (2) all patients who achieved pCR were ctDNA-negative after NAC; (3) among non-responding patients, ctDNA-negativity after NAC was associated with improved DRFS (Table). Conclusions: The predictive value of ctDNA for prediction of pCR and RCB differed between subtypes (HR+/HER2- vs. TNBC), while similar prognostic value was observed. In TNBC, early clearance of ctDNA at 3 weeks was a significant predictor of favorable response to NAC. Compared to patients who were ctDNA-positive after NAC, ctDNA-negative status in both subtypes was associated with improved DRFS even in patients with residual cancer (no pCR or RCB-II/III). These findings could inform on the design of future studies that seek to demonstrate the utility of ctDNA in the curative setting. Predictive and prognostic significance of ctDNA in early breast cancer in the neoadjuvant setting HR+HER2- (n=106) TNBC (n=97) Predictive value for prediction of pCR and RCB Fisher p-value Fisher p-value Early ctDNA clearance (between T0 and T1) and pCR 0.4521 &lt;0.0001 Late ctDNA clearance (between T0 and T2) and pCR 0.8071 0.0004 Early ctDNA clearance (between T0 and T1) and RCB (0-III) 0.1360 &lt;0.0001 Late ctDNA clearance (between T0 and T2) and RCB (0-III) 0.4869 0.0004 Early ctDNA clearance at T1 and pCR rates pCR rate pCR rate ctDNA clearance (ctDNA+ at T0/ctDNA- at T1) 21% 67% Late ctDNA clearance (betweeNo early clearance (ctDNA+ at T0/ctDNA+ at T1) 13% 14% Prognostic value for prediction of DRFS Log rank p-value Log rank p-value ctDNA at T3 and pCR vs no PCR 0.0002 &lt;0.0001 ctDNA at T3 and RCB (0-I vs II-III) 0.0110 &lt;0.0001 Timepoints: T0 - pretreatment; T1 - three weeks after treatment initiation; T2 - at 12 weeks, between paclitaxel-based and anthracycline regimens; T3- after neoadjuvant chemotherapy prior to surgery Citation Format: Mark Jesus Mendoza Magbanua, Lamorna Brown Swigart, Derrick Renner, Svetlana Shchegrova, Gillian L. Hirst, Christina Yau, Denise M. Wolf, Hsin-Ta Wu, Ekaterina Kalashnikova, Amy L. Delson, A. Jo Chien, Debu Tripathy, Smita Asare, Raheleh Salari, Angel Rodriguez, Bernhard Zimmermann, Himanshu Sethi, Alexey Aleshin, Paul Billings, Rita Nanda, Hope S. Rugo, Laura J. Esserman, Minetta C. Liu, Angela DeMichele, Laura van 't Veer. Comparison of the predictive and prognostic significance of circulating tumor DNA in patients with high risk HER2-negative breast cancer receiving neoadjuvant chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB111.

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 &gt;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&lt;0.001). This association remained significant after adjustment for HR status and treatment (LR p&lt;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&lt;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: 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&lt;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 &gt;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&gt;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: The detection of circulating tumor DNA (ctDNA) during neoadjuvant therapy (NAT) may serve as an early indicator of emerging resistance and disease progression. In this study, we analyzed ctDNA from high-risk early breast cancer patients who received NAT and definitive surgery in the I-SPY 2 TRIAL (NCT01042379). We hypothesized that ctDNA can serve as a biomarker of response and survival in this setting. Methods: ctDNA analysis was performed on 291 plasma samples from 84 high-risk stage II and III breast cancer patients randomized either to an investigational agent MK-2206, an AKT inhibitor, in combination with paclitaxel followed by doxorubicin and cyclophosphamide (AC) (n=52)—or standard-of-care (paclitaxel followed by AC) (n=32). HER2+ patients also received trastuzumab. Serial plasma was collected at pretreatment (T0), at 3 weeks after initiation of paclitaxel treatment (T1), between paclitaxel and AC regimens (T2), and after NAT prior to surgery (T3). A personalized ctDNA test was designed to detect a set of 16 patient-specific somatic variants, initially identified from whole exome sequencing of pretreatment tumor, then tested in plasma samples. Regions containing the somatic variants were amplified from cell-free DNA using specific polymerase chain reaction primers. Amplified products were subjected to ultra-deep sequencing (mean: 94,000x) to detect somatic variants. Association between ctDNA and clinicopathologic variables was assessed using Fisher’s exact test. Association of ctDNA with response and survival was analyzed using logistic and Cox regressions, respectively. The survival endpoint of the study was distant disease-free survival. The median follow-up was 4.8 years. Results: At pretreatment (T0), 61 of the 84 (73%) patients had detectable ctDNA. Pretreatment (T0) ctDNA positivity and levels (mean mutant molecules per mL of plasma) were significantly associated with increased tumor burden (clinical T stage T3/T4), more aggressive tumor biology (higher Mammaprint scores) and subtype (HER2+ and Triple negative). CtDNA detection during NAT decreased over time (T0- 73%; T1- 35%; T2- 14%; T3- 9%). Of the 84 patients, 23 (27%) achieved pCR and all were ctDNA-negative after NAT (T3), while all 6 patients who had detectable ctDNA at T3 did not achieve pCR. Patients who cleared ctDNA early at T1 (n=27, 48% pCR rate) had significantly increased probability of achieving a pathologic complete response (pCR) compared to those who remained ctDNA-positive (n=29, 17% pCR rate; Odds ratio=4.33, Likelihood ratio p=0.012). Patients who were ctDNA-positive at T3 (n=6) had significantly increased risk of metastatic recurrence (HR 14.7; 95% CI 1.6-131.5) compared to those who achieved pCR and were ctDNA-negative (n=17). The risk of metastatic recurrence in patients who cleared ctDNA during NAT was not significantly different from those who were negative at T0 and remained negative by T3 (hazard ratio, HR: 2.1, 95% CI: 0.22-20.2). Interestingly, patients who were ctDNA-negative (n=37) but failed to achieve pCR had similar risk of metastatic recurrence with those who achieved pCR (HR 1.4; 95% CI 0.15-13.5). Conclusions: Early clearance of ctDNA during NAT was significantly associated with increased likelihood of achieving pCR. Residual ctDNA after NAT was a significant predictor of metastatic recurrence, while clearance of ctDNA at any point during NAT was associated with improved outcomes. Taken together, personalized monitoring of ctDNA during NAT may aid in real-time assessment of treatment response and help fine-tune pCR as a surrogate endpoint of survival. Validation studies in a larger cohort are warranted. Citation Format: Mark Jesus M Magbanua, Lamorna Brown-Swigart, Gillian Hirst, Christina Yau, Denise Wolf, Hsin-Ta Wu, Antony Tin, Svetlana Shchegrova, Himanshu Sethi, Raheleh Salari, Alexey Aleshin, Maggie Louie, Bernhard Zimmermann, Angela DeMichele, Minetta Liu, Amy Delson, Amy Jo Chien, Smita Asare, Laura Esserman, I-SPY 2 TRIAL Consortium, Laura van't Veer. Personalized monitoring of circulating tumor DNA during neoadjuvant therapy in high-risk early stage breast cancer reflects response and risk of metastatic recurrence [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 P5-01-04.

Abstract Background: The explosion in new treatment options targeting immune checkpoints, HER signaling, DNA repair deficiency, AKT, and other pathways calls for updated breast cancer subtypes beyond HR and HER2 status to predict which patients will respond to which treatments. Here we leverage the I-SPY 2 TRIAL biomarker program over the past 8 years across 10 treatment arms to elucidate a minimal set of biomarkers that may improve response prediction in a modern treatment context, and to investigate which new patient phenotypes are identified by these response-predictive biomarkers. Methods: 986 patients were considered in this analysis. Treatments included paclitaxel alone (or with trastuzumab (H) in HER2+) or combined with investigational agents: veliparib/carboplatin (VC); neratinib; MK2206; ganitumab; ganetespib; AMG386; TDM1/pertuzumab (P); H/P; and pembrolizumab (Pembro). 24 prospectively defined, mechanism-of-action and pathway-based expression and phospho-protein signatures/biomarkers assayed from pre-treatment biopsies were previously found to be predictive in a particular agent/arm in pre-specified analysis. Here we evaluate these biomarkers in all patients. We assessed association between each biomarker and response in the population as a whole and within each arm and HR/HER2 subtype using a logistic model. To identify optimal dichotomizing thresholds for select biomarkers, 2-fold cross-validation was repeated 500 times. Our analysis is exploratory and does not adjust for multiplicities. Results: Our initial set of 24 predictive biomarkers reflects DNA repair deficiency (n=2), immune activation (n=7), ER signaling (n=2), HER2 signaling (n=4), proliferation (n=2), phospho-activation of AKT/mTOR (n=2), and ANG/TIE2 (n=1) pathways, among others. Biomarkers reflecting similar biology are correlated and cluster together. We make use of this correlation structure to reduce the dimensionality of the biomarker set to five predictive signals: proliferation, DNA repair deficiency (DRD), immune-engaged (Immune+), luminal/ER (lum), and HER2-activated. These biomarkers, when dichotomized, identify patient groups with differential predicted sensitivities to I-SPY 2 agents and are present at different proportions within receptor subtypes. For instance, in the HER2- subset, Immune+/DRD+ patients are predicted sensitive to both VC and Pembro, and account for 39% of TN, but only 12% of HR+HER2-. On the other end of the spectrum, only 17% of TN are Immune-/DRD-, compared to the majority (56%) of HR+HER2-. There are also subsets of patients positive for only one marker. For the HER2+ subset, 67% are HER2-activated+, and 25% lum+; of these HER2-activated+ patients are more likely to be Immune+ (44%), vs 23% in lum+. HER2-activated+/Immune+ patients have higher predicted sensitivity to HER2-targeted agents than lum+ or Immune- patients. In all, these molecular phenotypes predict sensitivity to one or more I-SPY 2 investigational agents for 75% of the ˜ 1000 patients. Conclusion: Molecular phenotypes reflecting proliferation, immune engagement, HER2-activation, luminal/ER-signaling, and DNA repair deficiency may provide a roadmap to guide treatment prioritization for emerging therapeutics. Citation Format: Wolf DM, Yau C, Wulfkuhle J, Petricoin E, Campbell M, Brown-Swigart L, Hirst G, Asare S, Zhu Z, Lee EP, Delson A, Pohlmann P, I-SPY 2 TRIAL Consortium, Hylton N, Liu MC, Symmans F, DeMichele A, Yee D, Berry D, Esserman L, van 't Veer L. Identifying breast cancer molecular phenotypes to predict response in a modern treatment landscape: Lessons from ˜1000 patients across 10 arms of the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-10-02.