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HER2-targeted therapy dramatically improves outcomes in early breast cancer. Here we report the results of two HER2-targeted combinations in the neoadjuvant I-SPY2 phase 2 adaptive platform trial for early breast cancer at high risk of recurrence: ado-trastuzumab emtansine plus pertuzumab (T-DM1/P) and paclitaxel, trastuzumab and pertuzumab (THP). Eligible women have >2.5 cm clinical stage II/III HER2+ breast cancer, adaptively randomized to T-DM1/P, THP, or a common control arm of paclitaxel/trastuzumab (TH), followed by doxorubicin/cyclophosphamide, then surgery. Both T-DM1/P and THP arms ‘graduate’ in all subtypes: predicted pCR rates are 63%, 72% and 33% for T-DM1/P (n = 52), THP (n = 45) and TH (n = 31) respectively. Toxicity burden is similar between arms. Degree of HER2 pathway signaling and phosphorylation in pretreatment biopsy specimens are associated with response to both T-DM1/P and THP and can further identify highly responsive HER2+ tumors to HER2-directed therapy. This may help identify patients who can safely de-escalate cytotoxic chemotherapy without compromising excellent outcome., HER2-targeted therapy improves patient’s outcome in early breast cancer. Here, the authors present the efficacy and biomarker analysis of two HER2-targeted combinations (ado-trastuzumab emtansine plus pertuzumab and paclitaxel, trastuzumab and pertuzumab) in the context of the neoadjuvant I-SPY2 phase 2 adaptive platform trial for early breast cancer at high risk of recurrence.

Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.

Advances in tissue analysis methods, image analysis, high-throughput molecular profiling, and computational tools increasingly allow us to capture and quantify patient-to-patient variations that impact cancer risk, prognosis, and treatment response. Statistical models that integrate patient-specific information from multiple sources (e.g., family history, demographics, germline variants, imaging features) can provide individualized cancer risk predictions that can guide screening and prevention strategies. The precision, quality, and standardization of diagnostic imaging are improving through computer-aided solutions, and multigene prognostic and predictive tests improved predictions of prognosis and treatment response in various cancer types. A common theme across many of these advances is that individually moderately informative variables are combined into more accurate multivariable prediction models. Advances in machine learning and the availability of large data sets fuel rapid progress in this field. Molecular dissection of the cancer genome has become a reality in the clinic, and molecular target profiling is now routinely used to select patients for various targeted therapies. These technology-driven increasingly more precise and quantitative estimates of benefit versus risk from a given intervention empower patients and physicians to tailor treatment strategies that match patient values and expectations.

BACKGROUND We proposed that a test for sensitivity to the adjuvant endocrine therapy component of treatment for patients with stage II-III breast cancer (SET2,3) should measure transcription related to estrogen and progesterone receptors (SETER/PR index) adjusted for a baseline prognostic index (BPI) combining clinical tumor and nodal stage with molecular subtype by RNA4 (ESR1, PGR, ERBB2, and AURKA). PATIENTS AND METHODS Patients with clinically high-risk, hormone receptor-positive (HR+), human epidermal growth factor receptor 2 (HER2)-negative (HR+/HER2-) breast cancer received neoadjuvant taxane-anthracycline chemotherapy, surgery with measurement of residual cancer burden (RCB), and then adjuvant endocrine therapy. SET2,3 was measured from pre-treatment tumor biopsies, evaluated first in an MD Anderson Cancer Center (MDACC) cohort (n = 307, 11 years' follow-up, U133A microarrays), cut point was determined, and then independent, blinded evaluation was carried out in the I-SPY2 trial (n = 268, high-risk MammaPrint result, 3.8 years' follow-up, Agilent-44K microarrays, NCI Clinical Trials ID: NCT01042379). Primary outcome measure was distant relapse-free survival. Multivariate Cox regression models tested prognostic independence of SET2,3 relative to RCB and other molecular prognostic signatures, and whether other prognostic signatures could substitute for SETER/PR or RNA4 components of SET2,3. RESULTS SET2,3 added independent prognostic information to RCB in the MDACC cohort: SET2,3 [hazard ratio (HR) 0.23, P = 0.004] and RCB (HR 1.77, P < 0.001); and the I-SPY2 trial: SET2,3 (HR 0.27, P = 0.031) and RCB (HR 1.68, P = 0.008). SET2,3 provided similar prognostic information irrespective of whether RCB-II or RCB-III after chemotherapy, and in both luminal subtypes. Conversely, RCB was most strongly prognostic in cancers with low SET2,3 status (MDACC P < 0.001, I-SPY2 P < 0.001). Other molecular signatures were not independently prognostic; they could effectively substitute for RNA4 subtype within the BPI component of SET2,3, but they could not effectively substitute for SETER/PR index. CONCLUSIONS SET2,3 added independent prognostic information to chemotherapy response (RCB) and baseline prognostic score or subtype. Approximately 40% of patients with clinically high-risk HR+/HER2- disease had high SET2,3 and could be considered for clinical trials of neoadjuvant endocrine-based treatment.

Neoadjuvant therapy in breast cancer can downstage axillary lymph nodes and reduce extent of axillary surgery. As such, accurate determination of nodal status after neoadjuvant therapy and before surgery impacts surgical management. There are scarce data on the diagnostic accuracy of breast magnetic resonance imaging (MRI) for nodal evaluation after neoadjuvant therapy in patients with invasive lobular carcinoma (ILC), a diffusely growing tumor type. We retrospectively analyzed patients with stage 1–3 ILC who underwent pre-operative breast MRI after either neoadjuvant chemotherapy or endocrine therapy at our institution between 2006 and 2019. Two breast radiologists reviewed MRIs and evaluated axillary nodes for suspicious features. All patients underwent either sentinel node biopsy or axillary dissection. We evaluated sensitivity, specificity, negative and positive predictive values, and overall accuracy of the post-treatment breast MRI in predicting pathologic nodal status. Of 79 patients, 58.2% received neoadjuvant chemotherapy and 41.8% neoadjuvant endocrine therapy. The sensitivity and negative predictive value of MRI were significantly higher in the neoadjuvant endocrine therapy cohort than in the neoadjuvant chemotherapy cohort (66.7 vs. 37.9%, p = 0.012 and 70.6 vs. 40%, p = 0.007, respectively), while overall accuracy was similar. Upstaging from clinically node negative to pathologically node positive occurred in 28.0 and 41.7%, respectively. In clinically node positive patients, those with an abnormal post-treatment MRI had a significantly higher proportion of patients with ≥4 positive nodes on pathology compared to those with a normal MRI (61.1 versus 16.7%, p = 0.034). Overall, accuracy of breast MRI for predicting nodal status after neoadjuvant therapy in ILC was low in both chemotherapy and endocrine therapy cohorts. However, post-treatment breast MRI may help identify patients with a high burden of nodal disease (≥4 positive nodes), which could impact pre-operative systemic therapy decisions. Further studies are needed to assess other imaging modalities to evaluate for nodal disease following neoadjuvant therapy and to improve clinical staging in patients with ILC.

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 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.

Introduction: One of the principal limiting factors to achieving cures in patients with cancer is drug resistance. Drug repositioning is the application of FDA-approved drug compounds for novel indications beyond the scope of the drug’s original intended use. This approach offers advantages over traditional drug development by reducing development costs and providing shorter paths to approval, as drug safety has already been established during the drug’s original regulatory process. One approach for computational drug repositioning involves generating a disease gene expression signature and then identifying a drug that can reverse this disease signature. In this study, we extracted drug resistance signatures from the I-SPY 2 TRIAL by comparing gene expression profiles of responder and non-responder patients stratified by treatment and molecular subtype. We then applied our drug repositioning pipeline to predict compounds that can reverse the gene expression profiles of these drug resistance signatures. We hypothesize that reversing these drug resistance signatures will resensitize tumors to treatment and improve patient outcome. Methods: We first generated the drug resistance signatures by performing differential expression between responders (RCB 0/I) and non-responders (RCB III) within treatment arms and molecular subtypes. An optimal log fold-change cutoff was selected for each signature by identifying the cutoff that best separates the responder and non-responder samples using k-means clustering. We then applied our drug repositioning pipeline to identify compounds that significantly reverse these signatures using the drug perturbation profiles generated in a breast cancer cell line in the Connectivity Map v2 dataset. Briefly, the pipeline uses a non- parametric, rank-based pattern-matching strategy based on the Kolmogorov-Smirnov (KS) statistic to assess the enrichment of resistance genes in a ranked drug gene expression list. Significance of each prediction is estimated from a null distribution of scores generated from random gene signatures. Results: We found that few individual genes are shared among the resistance signatures across the treatment arms and molecular subtypes, with the most common genes present in only 5/17 of the treatment arm and molecular subtype groups. At the pathway-level, however, we found that immune-related pathways are generally enriched among the responders and estrogen-response pathways are generally enriched among the non-responders. Although most of our drug predictions are unique to treatment arms and molecular subtypes, our drug repositioning pipeline identified the selective estrogen receptor degrader (SERD) fulvestrant as a compound that can potentially reverse resistance across a majority of the treatment arms and molecular subtypes. Conclusion: We applied our drug repositioning pipeline to identify novel agents to sensitize drug-resistant tumors in the I-SPY 2+ clinical trial and identified a SERD, fulvestrant, as a potential candidate for multiple molecular subtypes and treatment arms. Citation Format: Katharine Yu, Amrita Basu, Christina Yau, Denise Wolf, Gillian Hirst, Laura Sit, Nicholas O’Grady, Thelma Brown, I-SPY 2 TRIAL Investigators, Angela DeMichele, Don Berry, Nola Hylton, Doug Yee, Laura Esserman, Laura van 't Veer, Marina Sirota. Computational drug repositioning for the identification of new agents to sensitize drug-resistant breast tumors across treatment arms and molecular subtypes [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 PS11-04.

Introduction: Dedicated breast positron emission tomography (dbPET) is an emerging imaging technique with the spatial resolution needed to assess functionality and intra-tumor heterogeneity in primary breast lesions. Breast cancer patients may benefit from dbPET imaging combined with molecularly targeted agents to non-invasively assess and predict response to targeted therapy in the neoadjuvant treatment setting. We have previously observed that [18F]-fluorodeoxyglucose (FDG) PET provides tumor metabolic information complementary to the angiogenic properties reflected by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for characterizing triple-negative breast cancers (TNBC) (1). In this study, we examined the relationship between FDG-dbPET and MRI features in a cohort of breast cancer patients receiving neoadjuvant chemotherapy (NAC). Methods: With institutional review board approval, patients with biopsy-proven locally-advanced breast cancer were imaged with breast MRI and dbPET before (T0) and after three weeks (T1) of NAC. Standard DCE-MRI was obtained using a dedicated breast coil. Patients also underwent dbPET with 5 mCi of FDG at 45 minutes post-injection. Functional tumor volumes (FTV) were calculated from DCE-MRI by summing all voxels with an early percent enhancement (PE) exceeding 70% within a manually defined volume of interest (VOI). Maximum and mean PE (PEMax, PEMean) values within the VOI were also computed for analyses. Tumors were segmented in dbPET images using semi-automated threshold-driven methods. Body weight-corrected maximum and mean standardized uptake values (SUVMax, SUVMean), total lesion glycolysis (TLG), and metabolic tumor volume (MTV) were calculated for FDG-dbPET. Percent change relative to T0 (Δ = 100*(T1 - T0)/T0) was calculated for each feature. Spearman’s correlation coefficient was used to evaluate the relationship between MRI and dbPET features. Results: Of the 16 patients enrolled in this study, 13 patients (N = 15 unique tumors) with MRI and dbPET at T0 and T1 were included in the analysis. 46% (6/13) of the patients had TNBC. Our initial findings indicated that ΔPEMax and ΔSUVMax had the highest correlation (ρ = 0.59, p = 0.022). FTV and TLG at T1 were also correlated (ρ = 0.56, p = 0.032). Among all imaging features, ΔMTV showed the largest post-treatment difference between TNBC (-54.5%) and non-TNBC (-6.06%) groups. Among MRI features, ΔFTV exhibited the largest difference between the groups: -70.4% in TNBC and -43.1% in non-TNBC. ΔSUVMax and ΔTLG were additional dbPET features with large differences between TNBC and non-TNBC patients (Table 1). Conclusion: This exploratory study suggests that post-treatment ΔSUVMax and TLG provide complementary metabolic information to angiogenic properties (ΔPEMax and FTV, respectively) reflected by MRI. Other dbPET features may provide independent information adjunct to MRI for describing primary breast tumors. Patients with TNBC exhibited larger reductions in FDG uptake values and metabolic volume than non-TNBC patients. These observed reductions may improve early treatment response in patients with TNBC, enabling more precise treatment guidance. Further studies in larger cohorts are needed to validate these initial observations. 1. Bolouri MS, et al. Triple-Negative and Non-Triple-Negative Invasive Breast Cancer: Association between MR and Fluorine 18 Fluorodeoxyglucose PET Imaging. Radiology 2013;269:354-61 Comparison of ΔMRI and ΔFDG-dbPET in TNBC vs non-TNBC patientsAll Tumors (N = 15 tumors) Median(IQR)TNBC (N = 6 tumors) Median(IQR)non-TNBC (N = 9 tumors) Median(IQR)DCE-MRIΔFTV (%)-66.1 (-77.6, -19.1)-70.4 (-79.0, -62.1)-43.1 (-72.5, -2.95)ΔPEMax (%)-9.91 (-31.5, 19.5)-10.3 (-26.3, 24.2)-9.91 (-31.8, 8.42)ΔPEMean (%)-10.7 (-22.4, 2.77)-9.57 (-12.8, 0.29)-17.0 (-26.0, 2.33)FDG-dbPETΔSUVMax (%)-31.6 (-53.9, -20.6)-47.3 (-55.7, -41.1)-23.1 (-31.6, 1.13)ΔSUVMean (%)-34.1 (-65.4, -14.2)-48.5 (-74.6, -9.74)-34.1 (-44.5, -14.8)ΔMTV (%)-6.18 (-57.0, 38.5)-54.5 (-75.4, 15.3)-6.06 (-47.2, 38.9)ΔTLG (%)-64.9 (-75.2, 23.3)-75.2 (-84.0, -60.0)-47.9 (-65.2, 31.1) Citation Format: Deep K Hathi, Ella F Jones, Wen Li, David C Newitt, Ruby Guo, Youngho Seo, Robert R Flavell, Bonnie N Joe, Diane Heditsian, Susie Brain, ISPY-2 Imaging Working Group, ISPY-2 Consortium, Laura J Esserman, Nola M Hylton. Relationship of dedicated breast PET and MRI features in breast cancer patients receiving neoadjuvant chemotherapy [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 PS13-50.

I-SPY2 is a neoadjuvant trial evaluating experimental therapies in combination with cytotoxic chemotherapy compared to chemotherapy alone with the primary endpoint of pathologic complete response (pCR). Abundant preclinical evidence suggested the type I insulin-like growth factor receptor (IGF-1R) regulated breast cancer growth, although multiple clinical trials did not show benefit. We were the first to report the results of a monoclonal IGF-1R antibody ganitumab (G) in combination with chemotherapy. PGM followed by doxorubicin/cyclophosphamide (AC) did not result in substantial increases in pCR when compared to P followed by AC. In this report, we examined several potential predictive biomarkers. IGF-1R inhibitors induce hyperglycemia and we examined hemoglobin A1C (HgbA1c) as a measure of glucose control in patients before and after PGM therapy. 106 patients received PGM and 104 patients had baseline HgbA1c with a median of 5.4%. However, 27% (28/104) had levels greater than 5.7% the upper limit of normal as defined by the NIDDK. 4 of 104 had HgbA1c greater than 6.5%, a level associated with type 2 diabetes. pCR rates are similar between patients with baseline HgbA1c ≤5.7% (21%) vs. >5.7% (25%) (Fisher test p=0.79). 72 of these patients had an additional HgbA1c during the course of PGM therapy. For patients with HgbA1c ≤5.7%, 27% (14/52) had subsequent elevation above 5.7% after PGM. For patients with a baseline HgbA1C >5.7%, all 20 patients continued to have elevated levels through PGM. We also examined pre-treatment tumor gene expression profiles derived from custom Agilent 44K full-genome microarrays. We studied 11 genes associated with the IGF-1R signaling (IGF1, IGF2, IGF1R, INSR, IGFBP2, IRS1, IRS2, IGFBP3, IGFBP4, IGFBP5, CDH1), the IGFBP5/IGFBP4 ratio, and two IGFR expression signatures (Creighton, et al. J Clin Oncol 26:4078 2008 PMID: 18757322; Mu, et al. Breast Cancer Res Treat 133:321 2012 PMID: 22297468). The 2 signatures evaluated: the IGF1 ligand score and the IGF1-R signature are anti-correlated (Rp= - 0.79). In the population as a whole, lower levels of IRS1 and IGFBP5 significantly associated with response to PGM (likelihood ratio test (LR) p< 0.05), as do lower levels of the IGF1 ligand score and higher levels of the IGF-1R signature. However, levels of IRS1 and the two expression signatures also trend toward or are significantly associated with response in the control arm; and treatment interactions for all four biomarkers are non-significant (LR p>0.05). Therefore, none of these biomarkers qualify as specific predictors of response to PGM. Similarly, high MammaPrint scores (MP2) were associated with higher pCR scores in both PGM and Control arms. Previous gene expression profiles were divided into tertiles (low, intermediate, high). Similar to the continuous case, IGF1Rsig-class associates with pCR in both the PGM and control arms (Fisher test p=0.033 and 0.044, respectively), and thus also fails as a specific predictor of response to PGM. We conclude that PGM therapy results in worsening of glucose control and likely increases serum insulin levels. While IGF gene expression profiling associated with treatment response, they were not specific for PGM. Further, biomarker analysis and strategies to control glucose will be needed to optimize anti-IGF-1R therapies. Citation Format: Douglas Yee, Paul Haluska, Denise M Wolf, Christina Yau, Amy Wilson, I-SPY2 TRIAL Consortium, Angela DeMichele, Claudine Isaacs, Jane Perlmutter, Joan Venticinque, Hope S Rugo, Richard Schwab, Nola M Hylton, W Fraser Symmans, Michelle E Melisko, Teresa L Helsten, Laura J van't Veer, Donald A Berry, Laura J Esserman. Biomarker analysis of paclitaxel, ganitumab, and metformin (PGM) therapy in the I-SPY2 neoadjuvant clinical 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 PS4-08.

Background: The I-SPY 2 TRIAL, open to patients with locally advanced, molecular high-risk breast cancer, aims to bring each patient to pathologic complete response (pCR) with a minimum of toxicity. Here we test the hypothesis that imaging (MR volume predictors) combined with core biopsy may be used to accurately select candidates who show early response and provide an option of treatment de-escalation at mid-therapy (12 weeks). Methods: Of 100 I-SPY 2 patients with pathologist-assessed core biopsies at the inter-regimen time point (~12 weeks through treatment) and pCR data, 87 also had serial MR images and were considered in this study. Eleven I-SPY 2 TRIAL pathologists independently provided a digital assessment of the presence or absence of residual invasive cancer from H&E stained, and any requested ancillary IHC, images from imaging-guided core biopsies. Pathology predicts pCR if there is a consensus of no invasive residual disease. We generated predictions for all (55) unique pairs over the 11 pathologists, where pCR is predicted if both pathologists find no invasive cells. MRI pCR prediction models were previously developed on an independent dataset of ~990 I-SPY 2 patients, and applied to this cohort. Volume-based prediction models were previously optimized within each subtype and predicted probability thresholds were selected over a range of positive predictive value (PPV). In this study, MR predicts pCR (positive test) if the predicted probability is above a threshold that yields a given PPV value. For each pathologist pair, we combined pathology-based and MR-based predictors into a predictive-RCB (pre-RCB); and pre-RCB predicts a patient as pCR (RCB0) if both MR and pathology predicts pCR. Predictive performance is assessed by calculating the mean and range of PPV and sensitivity.Results: 39% (34/87) of the patients in this study achieved pCR. Over all pairs of pathologists, on average 80% of pathology-only predicted pCRs were true pCRs (mean PPV = 80% [range: 69-92%]), and 74% of patients who achieved pCR were predicted pCR by pathology alone (mean sensitivity = 74% [65-82%]). We assessed combinations with MR probability thresholds at PPV levels 50%-70%; and observed the best balance of PPV and sensitivity for the pre-RCB when MR thresholds were set at 50% PPV level. At this threshold setting, the pre-RCB achieved a PPV = 92% [83-100%], meaning on average 92% of predicted pCRs were true pCRs, and this improvement in positive predictive performance over pathology alone is achieved with a lower but still-reasonable 53% sensitivity [33-62%]. Conclusion: Pre-RCB, which predicts a patient as pCR if both MR and inter-regimen pathology predicts pCR, provides clinically actionable accuracy for treatment de-escalation for early responders (PPV>90%). Adding a final MR review at the time of early surgery may further improve performance. Resulting from data presented in this abstract, the pre-RCB algorithm, including the final MR review, has been operationalized and will be used prospectively to identify patients who are highly likely to have already achieved pCR by the inter-regimen timepoint. Citation Format: Sara J Venters, Wen Li, Denise M Wolf, Jodi M Carter, Molly E Klein, Kamaljeet Singh, Kimmie Rabe, I Tolgay Ocal, David Newitt, Christina Yau, Natsuko Onishi, Jessica Gibbs, Sunati Sahoo, Shuko Harada, Laila Khazai, Malini Harigopal, Alexander D Borowsky, Gregor Krings, Ronald Balassanian, Yunn-Yi Chen, Kimberley Cole, Sonal Shad, Barbara LeStage, Amy Delson, Sandra Finestone, Lamorna Brown-Swigart, I-SPY 2 Imaging Working Group, I-SPY 2 TRIAL Consortium, Laura Esserman, Laura van ‘t Veer, W Fraser Symmans, Nola M Hylton. Serial MRI and pathology combined to select candidates for therapy de-escalation in 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 PS4-10.

Background: The I-SPY 2 TRIAL randomizes patients with breast cancer to neoadjuvant chemotherapy (NAC) with or without experimental agents followed by anthracycline-cyclophosphamide (AC). As part of a de-escalation strategy to avoid overtreatment in good responders, combined information from serial MRI and mid-treatment core biopsy will be used to identify patients who may be candidates to skip AC. Presented are results of a pilot study to assess the location of biopsy clip in relation to tumor enhancement in MRI before and during treatment. Methods: 40 patients enrolled in I-SPY 2 who underwent mid-treatment core biopsy were reviewed. Patients had MRIs at four time points: pre-treatment (T0), early treatment (T1, 3 weeks after the start of first regimen), inter-regimen (T2, 12 weeks after completing the first regimen), and pre-surgery (T3). Clip visibility and location were assessed by a trained researcher on T1 weighted, fat suppressed dynamic contrast enhanced MR images at three time points: T0, T1, and T2. If clip was visible, location was scored 1 (inside), 2 (edge), or 3 (outside) in relation to tumor enhancement seen on a signal enhancement ratio (SER) map. Clips inside (score 1) were fully embedded and surrounded by a clear margin of tumor enhancement. Clips on the edge (score 2) were not fully embedded, with a portion of the clip touching tumor enhancement. Clips outside (score 3) had no portion of clip touching tumor enhancement. For patients with a focal tumor but with multiple clips visible in MRI, the clip most embedded within tumor enhancement was designated as the primary clip for evaluation. In cases of multifocal disease, the clip visualized in the largest area of tumor enhancement was assessed. Clips touching tumor cavity edge and enhancement were scored as 3. Results: Among 40 patients, two patients had no clips visualized in MRI at all three time points. One patient had no clip visualized at T0, but a clip was observed at T1 and T2. In addition, one T1 MRI was rejected due to incomplete exam and one T2 MRI was rejected due to different scanner from baseline. At T0, 51% (19/37) of clips were inside tumor enhancement and no clips were assessed outside tumor enhancement. 59% (22/37) of clips at T1 were on the edge or outside. At T2, 73% (27/37) of clips were on the edge and 19% (7/37) of clips were outside. While no clips were identified outside of tumor at baseline, tumor shrinkage with treatment resulted in clips outside of tumor in approximately 20 percent of cases at inter-regimen, and higher rates of clips identified at tumor edge. Conclusions: Clips were visible and location could be assessed in MRI in a majority of cases. Clip evaluation can be challenging and attention to clip placement is essential for patients with multifocal disease or diffuse tumors. The results of this study may have implications for assisting the mid-treatment core biopsy and selecting candidates for de-escalation of neoadjuvant chemotherapy. Table 1: Clips observed at three MR time pointsT0T12T231 (inside)191532 (edge)1821273 (outside)01171 No clips were seen outside tumor enhancement 2 One T1 MR was rejected due to incomplete exam 3 One T2 MR was rejected due to different scanner from baseline Citation Format: Teffany Joy Bareng, Jessica Gibbs, Wen Li, Natsuko Onishi, Bonnie N Joe, Elissa Price, Barbara LeStage, Coleen Crespo, I-SPY 2 Imaging Working Group, I-SPY 2 Consortium, Nola M Hylton. Assessment of clip locations on breast MRI during NAC to guide tumor bed biopsy at mid-treatment [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 PS3-14.

Background: The I-SPY 2 TRIAL is a multi-site response adaptive clinical trial evaluating novel drug combinations for neoadjuvant treatment of breast cancer. Patients receive four or more MRI studies during treatment, and serial measurement of functional tumor volume (FTV) is used to assess response. Under FDA IDE approval, FTV plays an integral role in adjusting patient randomization and evaluating treatment efficacy. FTV is a quantitative measure that requires stringent standards for image quality and protocol adherence. The I-SPY 2 TRIAL consistently reports a high level of data quality and data acceptance for FTV measurements. We present an overview of MRI operational performance and share lessons learned about maintaining high quality MRI data in a multi-site clinical trial. Methods: Over the 10-year course of the I-SPY 2 TRIAL, workflow has been improved to optimize communication between the Imaging Core Lab (ICL) and sites and to collect details about the MRI that are needed for accurate FTV measurement. A standardized imaging acquisition protocol is distributed to all sites, and new sites submit two test cases for review at site initiation. A scan verification form is required for each MRI study completed at sites to document critical information. Sites submit studies using TRIAD image transfer and de-identification software (American College of Radiology), and data is archived and processed at the ICL. All MRI studies are reviewed by the ICL for protocol adherence as soon as they are submitted, and feedback is provided to sites. Image quality factors including motion, fat suppression, and signal-to-noise ratio are qualitatively assessed. The ICL communicates with sites through a centralized email account, regular Coordinator Calls, and Imaging Working Group meetings to discuss emerging issues and offer ongoing training. The ICL contributes to revisions of study protocols and standard operating procedures. Results: As of June 2020, 3020 patients had been registered in I-SPY 2, 1741 patients randomized to treatment with one of 18 experimental drugs or standard therapy (controls), and a total of 7527 MRI studies were performed. FTV could be calculated for 97% (7317/7527) of MRI studies. Of the 7317 studies where FTV could be calculated, relatively minor issues with image quality or imaging protocol adherence were documented for 28% (2030/7317). These issues included motion artifacts (32%, 659/2030), off-protocol scan duration (21%, 433/2030), off-protocol contrast injection rate (14%, 281/2030), and off-protocol imaging field of view (9%, 191/2030). Conclusion: Breast MRI studies using a variety of scan protocols are well-suited for diagnostic evaluation, including BIRADS categorization, measurement of longest diameter, and assessment of lesion washout. The quantitative measures used in the I-SPY 2 trial require adherence to a specific imaging protocol that is kept consistent for all MRI studies for a single patient. Operational standardization, clear communication with sites, and streamlined workflow yield high quality MRI data across multiple sites and scanners. As a result, FTV is a robust biomarker of response to treatment, and is being used to predict patient response and guide treatment planning. We are actively investigating strategies that will improve FTV accuracy for predicting response and informing guidelines for treatment de-escalation. This will allow the ICL to further standardize and improve image quality and will provide the foundation for testing a variety of imaging biomarkers in the I-SPY 2 TRIAL. Citation Format: Jessica Gibbs, David C Newitt, Margarita Watkins, Wen Li, Lisa Cimino, Clifton Li, Natsuko Onishi, Lisa J Wilmes, Teffany Joy Bareng, Evelyn Proctor, Barbara LeStage, Bev Parker, the I-SPY 2 Coodinators, the I-SPY 2 Imaging Working Group, Nola M Hylton. Operational standardization and quality assurance yield high acceptance rate for breast MRI in 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 PS11-08.

Objective The A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance. Methods The A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b-value, echo-planar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping. Results Thirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability (P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p Conclusion Image quality remains a technical challenge in breast DWI, particularly for smaller lesions. Protocol optimization and advanced acquisition and post-processing techniques would help to improve clinical utility.

This retrospective study examined magnetic resonance imaging (MRI)–derived tumor sphericity (SPH) as a quantitative measure of breast tumor morphology, and investigated the association between SPH and reader-assessed morphological pattern (MP). In addition, association of SPH with pathologic complete response was evaluated in patients enrolled in an adaptively randomized clinical trial designed to rapidly identify new agents for breast cancer. All patients underwent MRI examinations at multiple time points during the treatment. SPH values from pretreatment (T0) and early-treatment (T1) were investigated in this study. MP on T0 dynamic contrast-enhanced MRI was ranked from 1 to 5 in 220 patients. Mean SPH values decreased with the increased order of MP. SPH was higher in patients with pathologic complete response than in patients without (difference at T0: 0.04, 95% confidence interval [CI]: 0.02–0.05, P &lt, 001, difference at T1: 0.03, 95% CI: 0.02–0.04, P &lt, 001). The area under the receiver operating characteristic curve was estimated as 0.61 (95% CI, 0.57–0.65) at T0 and 0.58 (95% CI, 0.55–0.62) at T1. When the analysis was performed by cancer subtype defined by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status, highest area under the receiver operating characteristic curve were observed in HR−/HER2+: 0.67 (95% CI, 0.54–0.80) at T0, and 0.63 (95% CI, 0.51–0.76) at T1. Tumor SPH showed promise to quantify MRI MPs and as a biomarker for predicting treatment outcome at pre- or early-treatment time points.

Background: Achieving a pathologic complete response (pCR) has been shown on the patient level to predict excellent long-term event-free survival outcomes. Residual cancer burden (RCB) quantifies the extent of residual disease for patients who did not achieve pCR. A high proportion of metastatic events to the central nervous system (CNS), a known chemotherapy sanctuary site, was previously observed among the small number of relapses in patients achieving a pCR (Symmans et al 2017), raising the possibility that these CNS events may be independent of response in the breast. I-SPY2 is an adaptively randomized, phase II, platform trial that evaluates new drugs and combinations in the neoadjuvant setting for women with high-risk primary breast cancer. In this study, we evaluated the type and sites of recurrences by RCB classes in the I-SPY 2 TRIAL. Methods: I-SPY 2 patients enrolled prior to 11/2016 across 9 experimental and control arms, with available RCB and event-free survival (EFS) data were included in this analysis. The median follow-up is 3.8 years. We summarized the EFS event type, further sub-dividing the distant recurrence events by their site of relapse (CNS-only, CNS and other sites, Non-CNS). We estimated the overall and site-specific distant recurrence incidence in each RCB class at 3 years using a competing risk (Fine-Gray) model. In addition, we assessed the association between RCB and distant recurrence free survival including all distant recurrences (DRFS), as well as excluding the CNS-only recurrences (non-CNS DRFS) using a Cox model. Our statistics do not adjust for multiplicities beyond variables evaluated in this study. Results: Among 938 subjects, there were 180 EFS events, including 28 (16%) local recurrences (without distant recurrence and/or death) and 152 DRFS events. Among the DRFS events, 25 patients died without a distant recurrence. 127 experienced distant recurrences, including 22 (17.3%) with CNS-only, 16 (12.6%) with CNS and other sites, 87 (68.5%) with non-CNS distant recurrence; 2 (1.6%) patients had missing recurrence site information. Incidence of CNS-only recurrences are low and are similar across RCB classes (pCR/RCB-0 (n=338): 1%, RCB-I (n=129): 3%, RCB-II (n=328): 2%, RCB-III (n=143): 2% at 3 years). In contrast, the incidence of non-CNS recurrences increase with increasing RCB (RCB-0: 2%, RCB-I: 4%, RCB-II: 11%, RCB-III: 19% at 3 years). DRFS of RCB-I patients do not significantly differ from those achieving a pCR/RCB-0 (DRFS at 3 years: 92% vs. 95%, hazard ratio: 1.77 (0.87-3.63)); the small numerical difference is further reduced when the CNS-only recurrences are excluded (non-CNS DRFS at 3 years: 95% vs. 96%, hazard ratio: 1.48 (0.61-3.58)). CNS recurrences among DRFS events are proportionally higher within the pCR (5/16 (31%)) and RCB-I (5/12 (42%)) than in the RCB-II (8/57 (14%)) and RCB-III (4/42 (9%)) groups largely because of the relative low frequency of non-CNS recurrence events. Conclusions: In our high-risk I-SPY 2 cohort, CNS-only recurrences are uncommon but appear similar across RCB groups, independent of response, suggesting that the CNS is a treatment sanctuary site. In contrast, non-CNS recurrence rates increase as RCB increases. These findings, if confirmed, support the use of RCB to identify patients with excellent outcomes beyond those achieving a pCR; and suggest that inclusion of CNS only recurrences as an outcome event may impact the association between neoadjuvant therapy response and long-term outcome. Citation Format: Christina Yau, Angela DeMichele, W. Fraser Symmans, Lajos Pusztai, Douglas Yee, Amy S. Clark, Christos Hatzis, Jeffrey B. Matthews, Jodi Carter, Yunn-Yi Chen, Kimberly Cole, Laila Khazai, Molly Klein, Dina Kokh, Gregor Krings, Sunati Sahoo, Kathy S. Albain, A. Jo Chien, 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, Nola M. Hylton, Judy C. Boughey, Michelle E. Melisko, Jane Perlmutter, Hope S. Rugo, Richard Schwab, Laura J. van' t Veer, Donald A. Berry, Laura J. Esserman. Site of recurrence after neoadjuvant therapy: Clues to biology and impact on endpoints [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 P2-20-02.

Purpose Standard treatment for ductal carcinoma in situ (DCIS) involves surgical excision and radiation treatment, and often adjuvant endocrine therapy (ET). However, this may constitute overtreatment for some women. The purpose of this neoadjuvant ET study in patients with biopsy-proven DCIS was to evaluate the relationship between the primary outcome of upstaging at surgery (invasive disease) and changes in the pre- and post-ET MRI appearances of both (1) lesion and (2) background parenchymal enhancement (BPE), with the goal to better inform de-escalated therapy. Methods Outcomes of patients with DCIS who were prospectively enrolled in a neoadjuvant ET trial between 2002 and 2009 were retrospectively analyzed with IRB approval. All patients had dynamic contrast-enhanced breast MRI prior to and following an average of 3.1 months of ET (range 1.9 – 5 months), followed by surgical excision within one year of the second MRI. Pathology reports were used to confirm initial biopsy results and to determine the nature and extent of disease postoperatively. Surgeon and radiologist’s reports were used to assess improvement of lesion after ET based on 1) less prominently enhancing pattern or 2) reduction in size of DCIS lesion after treatment. BPE response to ET on imaging was assessed by two radiologists specialized in breast imaging who compared pre- and post-ET MRI’s, blinded to all imaging reports. The change in BPE of the ipsilateral breast with treatment was scored subjectively as increased, decreased, or unchanged. Readers reached a consensus on discordant classifications of the change in BPE. The correlation between imaging change (of lesion and BPE) and incidence of invasive ductal carcinoma (IDC) at surgery was determined using Fisher’s exact test. Results: Of 34 patients evaluated, six (18%) had IDC at surgery. The prevalence of IDC in each group is shown in Table 2. Those with improvement of lesion on MRI had a lower likelihood of IDC at surgery compared to patients with no imaging improvement (Table 2, p= 0.048). Addition of change in BPE to the evaluation of lesion improvement significantly increased the chance of identifying specific patients who were much more likely to have an underlying invasive cancer at surgery (Table 2, p= 0.032). The risk of having IDC at surgery was considerably higher in the group whose lesion was assessed as not improved and who had decreased BPE scores on MRI (Table 2, p= 0.018). Conclusion: In our unique population of patients with mostly ER+ DCIS receiving pre-operative endocrine therapy, the combination of lack of lesion improvement and reduction in BPE score in blinded reads was significantly associated with the finding of invasive disease at surgical excision. This result may reflect the unmasking of a more aggressive lesion in those with underlying IDC and help identify patients with a higher likelihood of the presence of IDC at surgery. Although this study is small, it suggests that risk-stratifying patients with DCIS based on lesion and parenchymal imaging features associated with treatment response may aid in tailoring therapy for DCIS. We are testing this prospectively in an active surveillance cohort. Table 1. Incidence of IDC at surgery depending on image features (n= 34)Improvement of lesion in MRINo Improvement of lesion in MRIP-value (Fisher’s Exact Test)& No Reduction in BPE& Reduction in BPE& No Reduction in BPE& Reduction in BPEIncidence of IDC at surgery (n)0204Incidence of Not IDC at surgery (n)121024%IDC at surgery when assessing lesion only (%)9.1%40%0.048*%IDC at surgery when assessing lesion AND BPE (%)0%16.7%0%50%0.032*%IDC at surgery when assessing lesion AND BPE (%)8.3%50%0.018* Citation Format: Paul Kim, Heather I. Greenwood, Rita I. Freimanis, Gillian L Hirst, Megan Fischer-Colbrie, Jessica Gibbs, Nola M Hylton, Christina Yau, Eun-Sil Shelley Hwang, Laura J. Esserman, Rita A Mukhtar. Improved early stratification of invasive cancer risk using MRI in a ductal carcinoma in-situ short-term active surveillance cohort treated with neoadjuvant endocrine therapy [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 P6-16-06.

Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR) at 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 1:1 randomized neoadjuvant trial with pCR endpoint within signatures defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status. Regimens may leave the trial for futility (< 10% probability of success), maximum sample size accrual (with probability of success ≥ 10% and < 85%), or safety concerns as recommended by the independent DSMB. For HER2+ patients, the I-SPY2 control arm was 12 weekly cycles of paclitaxel+trastuzumab (TH, control) followed by doxorubicin/cyclophosphamide (AC) q2-3 weeks x4 and surgery. Patritumab is a fully human monoclonal antibody that inhibits HER3. In this experimental arm for HER2+ patients, patritumab was given q3w x 4 cycles (18mg/kg loading dose followed by 9mg/kg/dose) concurrent with paclitaxel and trastuzumab q1w x 12 weeks (PTH, treatment), followed by AC q2-3w. Methods: Women with tumors ≥ 2.5cm were eligible for screening. MP low/HR+ tumors were ineligible. MRI scans (baseline, 3 weeks after start of therapy, prior to AC, and prior to surgery) were used in a longitudinal statistical model to predict pCR for individual patients. Analysis was intention to treat. Patients who switched to non-protocol therapy count as non-pCR. Patients on treatment arm therapy at the time of arm closure are non-evaluable. Graduation potential was in 3 of 10 pre-defined signatures: all HER2+, HR-/HER2+, and HR+/HER2+. Results: The PTH regimen was stopped at the recommendation of the Safety Working Group and DSMB based on a safety event (bilateral sensorineural hearing loss, Gr 3) observed in one patient. At the time of arm closure, N=31 patients had received PTH treatment; 4 patients receiving PTH were changed to non-protocol therapy and removed from the analysis. The final estimated pCR report will consider 27 PTH and 31 TH as evaluable patients. Accrual was insufficient to assess graduation, however, there appears to be good signal in the HER2+HR- but not HER2+HR+ signatures. I-SPY 2 TRIAL Est. pCR at time of arm closureSignaturesPTH (Treatment)N= 31TH (Control)N = 31All (HER2+)0.40 (0.22 - 0.59), n=310.23 (0.09 - 0.37), n=31HR-/HER2+0.64 (0.36 - 0.91), n=110.30 (0.12 - 0.47), n=12HR+/HER2+0.28 (0.08 - 0.48), n=200.20 (0.06 - 0.34), n=19 HR+/HER2+0.28 (0.08 - 0.48), n=200.20 (0.06 - 0.34), n=19The patient who developed Gr3 sensorineural hearing loss 6 days after the 2nd patritumab (and 4th paclitaxel/trastuzumab) treatment, did not recover her hearing after patritumab was stopped, and also reported Gr3 vulvovaginal pain, vulvitis, and vaginal inflammation. Other gynecological symptoms in the PTH arm include: 1 pt with Gr1 vaginal hemorrhage, and 1 pt with Gr2 dyspareunia. There was a higher frequency of Gr3 hypokalaemia (12.5% vs. 3.2%). One pt in the PTH arm reported Gr3 small intestinal obstruction which resolved with conservative management. Conclusion: The I-SPY 2 study aims to assess the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial; PTH was stopped due to safety concerns, although there was activity in the HER2+ HR- signature. This is the first report of Gr3 hearing loss associated with patritumab/paclitaxel/trastuzumab, and thus attribution is uncertain. Citation Format: Teresa L Helsten, Shelly S Lo, Christina Yau, Kevin Kalinsky, Anthony D Elias, Anne M Wallace, A. Jo Chien, Janice Lu, Julie E Lang, Kathy S Albain, Erica Stringer-Reasor, Amy S Clark, Judy C Boughey, Erin D Ellis, Douglas Yee, Angela DeMichele, Claudine Isaacs, Jane Perlmutter, Hope S Rugo, Richard Schwab, Nola M. Hylton, W. Fraser Symmans, Michelle E Melisko, Laura J van't Veer, Amy Wilson, Ruby Singhrao, Smita M Asare, Ashish Sanil, Donald A Berry, Laura J Esserman. Evaluation of patritumab/paclitaxel/trastuzumab over standard paclitaxel/trastuzumab in early stage, high-risk HER2 positive breast cancer: Results from the neoadjuvant 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 P3-11-02.

Background: I-SPY2 is a multicenter, response-adaptive randomization phase 2 trial to evaluate novel agents when added to standard neoadjuvant therapy for women with high-risk stage II/III breast cancer - weekly paclitaxel + investigational treatment x 12 wks followed by doxorubicin & cyclophosphamide(AC) q3 wks x 4 vs. weekly paclitaxel/AC (control). The primary endpoint is pathologic complete response (pCR). The goal for all investigational arms 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 1:1 randomized neoadjuvant trial with a pCR endpoint within signatures defined by hormone-receptor (HR) & HER2 status & MammaPrint (MP). Findings from the graduated, previously reported Pembro4 arm (Nanda et al, ASCO 2017) supported investigation of de-escalating therapy, and determining if pembrolizumab (an anti-PD-1 antibody) alone q3 wks x 4 after weekly paclitaxel x 12 wks + pembrolizumab q3 wks x 4 was sufficient to sustain response without AC. Methods: Women with tumors ≥2.5cm were eligible for screening. MP low/HR+ were ineligible. MRI scans (at baseline, 3 wks, 12 wks, and prior to surgery) were used in a longitudinal statistical model to predict pCR for individual patients (pts). Pts who receive non-protocol therapy (e.g., carboplatin or AC for the Pembro8-noAC arm) count as non-pCR. Pembro8-noAC was open to HER2- pts for evaluation in 3 of 10 pre-defined signatures: HER2-, HR+/HER2-, and HR-/HER2-. Regimens exit the trial for futility ( Results: Pembro8-noAC was randomized to 73 pts, 3 of whom progressed while receiving pembrolizumab alone on study. Randomization to this arm continued after the first report because the rate of progression during AC over the course of the trial was estimated to be 6.5% based on serial MRI studies. However, notification of the third case prompted the study team to ask the DSMB for the summary response for this arm. Although it did not meet formal stopping rules for either graduation or futility, Pembro8-noAC was not near the target threshold pCR rates of 60% for HR-/HER2- and 30% for HR+/HER2+. As a result of this information, combined with the on-treatment progressions, assignment to Pembro8-noAC was discontinued. Treatment with pembrolizumab alone was no longer allowed due to the potential concern for progression, and investigators were given the option to administer AC with pembrolizumab or proceed with definitive surgery following the 12 weeks of paclitaxel + pembrolizumab. 34 pts had surgery results at the time the study was closed. Of the remaining 39 pts, 34 pts have on-therapy MRI assessments. Estimated pCR rates were based on all pts with information at the time (see table). Immune-related adverse events included grade 3 colitis (n=2), grade 3 pneumonitis (n=1), grade 3 transaminitis (n=1), grade 3 hypothyroidism (n=1), and grade 1-2 adrenal insufficiency (n=5). Conclusion: Although Pembro8-noAC is performing at least as well as standard paclitaxel/AC, the likelihood is very low that the regimen would be successful in a phase 3 trial. Pembrolizumab alone following 12 weeks of paclitaxel + pembrolizumab was not sufficient to sustain a response. This was quickly assessed with a small number of patients. Estimated pCR rateSignature(95% prob interval)Pembro8-noACControlHER2-0.210.2(0.09-0.32)(0.15-0.25)HR-/HER2-0.270.27(0.09-0.45)(0.19-0.35)HR+/HER2-0.150.15(0.01-0.29)(0.09-0.20) Citation Format: Minetta C. Liu, Patricia A Robinson, Christina Yau, Anne M Wallace, A. Jo Chien, Erica Stringer-Reasor, Rita Nanda, Douglas Yee, Kathy S Albain, Judy C Boughey, Heather S Han, Anthony D Elias, Kevin Kalinsky, Amy S Clark, Kathleen Kemmer, Claudine Isaacs, Julie E Lang, Janice Lu, Tara Sanft, Angela DeMichele, Nola M Hylton, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Patricia K Haugen, Amy Wilson, Ruby Singhrao, Smita Asare, Ashish Sanil, Donald A Berry, Laura J Esserman. Evaluation of a novel agent plus standard neoadjuvant therapy in early stage, high-risk HER2 negative breast cancer: Results from 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 P3-09-02.

Importance: It is essential to refine the populations most likely to benefit from targeted chemotherapy combinations. Background: MINDACT showed that molecularly low risk patients, as assessed by the Amsterdam 70-gene profile MammaPrint® (Agendia) (MP), did not benefit from chemotherapy. In the I-SPY2 trial, MP low risk Hormone Receptor (HR) positive/HER2 negative patients are not eligible; however, HR negative or HER2 positive patients were considered high risk and included for treatment with chemotherapy plus novel agents. The neoadjuvant setting provides an opportunity to evaluate whether molecularly low risk HER2 positive patients are good candidates for neoadjuvant chemo/anti-HER2 therapy, where pathologic complete response (pCR) and 3-year outcomes are measured. Objective: To evaluate and further characterize the fraction of and outcomes for patients molecular low-risk disease in the I-SPY2 trial. Methods: The I-SPY2 platform trial is an ongoing multicenter phase 2 multi-arm study utilizing adaptive design and evaluating efficacy and tolerability of investigational agents in combination with standard-of-care chemotherapy for patients with high-risk anatomic stage II/III breast cancer. Patients with HR+HER2- MP low-risk tumors are not eligible. All enrolled patients undergo pretreatment biopsy for genomic evaluation of early recurrence risk with MP for risk stratification and with the 80-gene BluePrint® (Agendia) test for intrinsic subtype classification. Primary endpoint of the study is pCR in breast and lymph nodes (ypT0/is, ypN0). Secondary outcomes included event-free survival (EFS) and distant-recurrence free survival (DRFS). Following standard neoadjuvant treatment with or without a concomitant investigational agent, patients are followed for long-term outcomes. EFS and DRFS at 3 and 5 years in the pCR vs non-pCR groups within histologic and molecular subtypes are determined using the Kaplan Meier method. Results: Of the 1038 enrolled patients by November 2016, 24 patients (3.2%) had molecular low-risk disease as determined by MP. Of these, 21 (87.5%) had HR+HER2+, 1 (4.2%) had HR-HER2+, and 2 (8.4%) had HR-HER2-. BluePrint expression subtyping classified 17 as luminal-type, 6 HER2 enriched-type and 1 basal type. One patient withdrew consent for follow-up. Of the 23 remaining, none achieved pCR and only one (HR+/HER2+) had an EFS event (with median follow-up of 4.3 years). Overall, EFS and DRFS data were available for 950 of the 1038 patients (as of February 2019), with median follow-up of 3.8 years. Of the 173 HR+HER2+ in this cohort, 20 (11.6%) had molecular low-risk tumors. The EFS and DRFS for the 173 HER2+HR+ pCR group is 97% and 98% (non-pCR group 89% and 94%), respectively at 3 years. Removing the molecular low-risk HER2+ patients from the denominator reveals the worse outcome for patients with non pCR: EFS 86% and DRFS 92% at 3 years. The difference is more apparent at 5 years, changing from 74% to 66% for EFS and from 81% to 75% for DRFS. Intrinsic subtypes vary and do not predict early risk. Conclusions: I-SPY2 focuses on women with high clinical risk with only 3.2% of enrolled patients having low molecular risk tumors. However, 12% of HER+ breast cancer enrolled patients had molecular low risk tumors of which 95% were also HR+. In this group, early recurrence is very low despite absence of pCR and irrespective of intrinsic subtype. Refining the population using molecular high-risk classification of patients reveals a greater difference between the pCR and non-pCR groups within the HR+HER2+ subtype in the EFS and DRFS analysis. Clinical trial designs could address the opportunity to find more targeted and less toxic treatments for the HER2+ low molecular risk patient population. Citation Format: Paula R Pohlmann, Christina Yau, Angela DeMichele, Claudine Isaacs, Judy C Boughey, Nola Hylton, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, W. Fraser Symmans, I-SPY 2 TRIAL Consortium, Donald A Berry, Laura Esserman. Amsterdam 70-gene profile (MammaPrint) low risk, even in the HER2 positive subset, identifies a population of women with lower early risk for recurrence despite low response rates to chemotherapy and to HER2 targeted therapy [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 P6-10-06.

Quantitative imaging (QI) plays a vital role in identifying biomarkers describing the genetic and phenotypic heterogeneity underpinning breast cancer through screening, diagnosis, and treatment assessment in patients receiving neoadjuvant chemotherapy. Changes to the structural biology of the breast tumor microenvironment are reflected in morphologic and functional imaging. They may serve as surrogate markers for identifying disease burden or therapeutic effect, which may provide valuable information on subsequent clinical decision making. In breast cancer, mammography is the primary tool for screening and initial evaluation, while magnetic resonance imaging (MRI) and positron emission tomography (PET) are used in diagnosis, staging, and treatment response assessment. In the past decade, advances in ultrafast sequence design in MRI, targeted PET tracers, and the adoption of new mammographic technology hold promise for rapid screening, more accurate diagnosis, and personalized treatment. In this chapter, the application of current QI technologies at each stage of breast cancer management is summarized, and advances in each modality for informing early diagnosis and therapy interventions to improve patient outcomes are highlighted.

I-SPY2 is an adaptively randomized phase 2 clinical trial evaluating novel agents in combination with standard-of-care paclitaxel followed by doxorubicin and cyclophosphamide in the neoadjuvant treatment of breast cancer. Ganitumab is a monoclonal antibody designed to bind and inhibit function of the type I insulin-like growth factor receptor (IGF-1R). Ganitumab was tested in combination with metformin and paclitaxel (PGM) followed by AC compared to standard-of-care alone. While pathologic complete response (pCR) rates were numerically higher in the PGM treatment arm for hormone receptor-negative, HER2-negative breast cancer (32% versus 21%), this small increase did not meet I-SPY’s prespecified threshold for graduation. PGM was associated with increased hyperglycemia and elevated hemoglobin A1c (HbA1c), despite the use of metformin in combination with ganitumab. We evaluated several putative predictive biomarkers of ganitumab response (e.g., IGF-1 ligand score, IGF-1R signature, IGFBP5 expression, baseline HbA1c). None were specific predictors of response to PGM, although several signatures were associated with pCR in both arms. Any further development of anti-IGF-1R therapy will require better control of anti-IGF-1R drug-induced hyperglycemia and the development of more predictive biomarkers.

Importance Residual cancer burden (RCB) distributions may improve the interpretation of efficacy in neoadjuvant breast cancer trials. Objective To compare RCB distributions between randomized control and investigational treatments within subtypes of breast cancer and explore the relationship with survival. Design, Setting, and Participants The I-SPY2 is a multicenter, platform adaptive, randomized clinical trial in the US that compares, by subtype, investigational agents in combination with chemotherapy vs chemotherapy alone in adult women with stage 2/3 breast cancer at high risk of early recurrence. Investigational treatments graduated in a prespecified subtype if there was 85% or greater predicted probability of higher rate of pathologic complete response (pCR) in a confirmatory, 300-patient, 1:1 randomized, neoadjuvant trial in that subtype. Evaluation of a secondary end point was reported from the 10 investigational agents tested in the I-SPY2 trial from March 200 through 2016, and analyzed as of September 9, 2020. The analysis plan included modeling of RCB within subtypes defined by hormone receptor (HR) andERBB2 status and compared control treatments with investigational treatments that graduated and those that did not graduate. Interventions Neoadjuvant paclitaxel plus/minus 1 of several investigational agents for 12 weeks, then 12 weeks of cyclophosphamide/doxorubicin chemotherapy followed by surgery. Main Outcomes and Measures Residual cancer burden (pathological measure of residual disease) and event-free survival (EFS). Results A total of 938 women (mean [SD] age, 49 [11] years; 66 [7%] Asian, 103 [11%] Black, and 750 [80%] White individuals) from the first 10 investigational agents were included, with a median follow-up of 52 months (IQR, 29 months). Event-free survival worsened significantly per unit of RCB in every subtype of breast cancer (HR-positive/ERBB2-negative: hazard ratio [HZR], 1.75; 95% CI, 1.45-2.16; HR-positive/ERBB2-positive: HZR, 1.55; 95% CI, 1.18-2.05; HR-negative/ERBB2-positive: HZR, 2.39; 95% CI, 1.64-3.49; HR-negative/ERBB2-negative: HZR, 1.99; 95% CI, 1.71-2.31). Prognostic information from RCB was similar from treatments that graduated (HZR, 2.00; 95% CI, 1.57-2.55; 254 [27%]), did not graduate (HZR, 1.87; 95% CI, 1.61-2.17; 486 [52%]), or were control (HZR, 1.79; 95% CI, 1.42-2.26; 198 [21%]). Investigational treatments significantly lowered RCB in HR-negative/ERBB2-negative (graduated and nongraduated treatments) andERBB2-positive subtypes (graduated treatments), with improved EFS (HZR, 0.61; 95% CI, 0.41-0.93) in the exploratory analysis. Conclusions and Relevance In this randomized clinical trial, the prognostic significance of RCB was consistent regardless of subtype and treatment. Effective neoadjuvant treatments shifted the distribution of RCB in addition to increasing pCR rate and appeared to improve EFS. Using a standardized quantitative method to measure response advances the interpretation of efficacy. Trial Registration ClinicalTrials.gov Identifier:NCT01042379

Background With current imaging technologies, assessing response to neoadjuvant chemotherapy (NAC) or neoadjuvant endocrine therapy (NET) remains a challenge for patients with invasive lobular carcinoma (ILC). Therefore, we evaluated imaging features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) before and after neoadjuvant therapy in a cohort of patients with ILC, including the longest tumor diameter (LD), functional tumor volume (FTV), and peak signal enhancement ratio (SER). FTV is the sum of all image voxels enhancing above a set threshold within a defined region, and has been validated as a predictor of recurrence-free survival (RFS) for breast cancer. SER is a measure of contrast wash-in and wash-out and reflects neovascularity of tumors. We determined whether baseline and post-treatment imaging features differed by type of neoadjuvant therapy and if they were associated with RFS in neoadjuvantly treated ILC regardless of treatment type. Methods With institutional review board approval, a retrospective analysis of pre- and post-treatment breast DCE-MRI was performed on a cohort of ILC patients receiving neoadjuvant therapy between 1998 and 2017. We compared pre-treatment, post-treatment, and percent reduction (α) in LD, FTV, and peak SER by neoadjuvant treatment type (i.e. NAC or NET) using the Wilcoxon rank-sum test. Univariate t-tests, Chi-squared tests, analysis of variance, and Spearmen’s correlation were used to evaluate associations of clinicopathologic features and treatment type. Univariate and multivariate associations with RFS in the entire neoadjuvantly treated cohort adjusting for treatment type were evaluated using the log-rank test and Cox proportional hazards models. Results A cohort of 76 patients with pre- and post-treatment MRI were included in this study, of whom 42 (55.3%) received NAC and 34 (44.7%) received NET. The NAC group was significantly younger (55 vs. 60 years, p=0.013), less likely to have stage 1 disease (26.2% vs. 73.5%, p ConclusionPre-treatment peak SER measured by MRI may provide prognostic information beyond standard clinicopathologic variables in patients with ILC receiving either neoadjuvant chemotherapy or endocrine therapy. Further evaluation in a larger ILC cohort is needed to validate our initial findings. Table 1. Comparison of MR imaging features of ILC patients receiving neoadjuvant chemotherapy and neoadjuvant endocrine therapy.Overall(n=76)NAC(n=42)NET(n=34)P-valuePre-treatment (median, IQR)LD (cm)2.7, 1.6-5.44.6, 2.5-71.8, 1.4-3.20.0006FTV (cc)5.8, 2.2-16.48.7, 4.1-24.23.0, 0.9-80.0004SER0.9, 0.8-1.00.9, 0.9-1.00.9, 0.8-1.10.8335Post-treatment (median, IQR)LD (cm)1.1, 0-1.91.0, 0-1.81.3, 0-1.90.6071FTV (cc)0.5, 0.1-1.80.3, 0.1-1.80.7, 0.3-1.80.2196SER0.9, 0.8-1.00.8, 0.8-1.00.9, 0.8-1.10.2321Percent reduction (%)LD44.6, 15.1-10079.6, 33.8-10033.8, 10.1-1000.0958FTV93, 72.5-97.495.8, 90.7-99.172.6, 43.1-94.5 Citation Format: Geraldine Tran, Ella Jones, Wen Li, Kelly Fahrner-Scott, David Newitt, Bonnie Joe, Laura Esserman, Nola Hylton, Rita Mukhtar. DCE-MRI derived imaging features for characterizing invasive lobular breast cancer and predicting recurrence-free survival after neoadjuvant therapy [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 PD6-08.

In this proof-of-concept work, we have developed a 3D-CNN architecture that is guided by the tumor mask for classifying several patient-outcomes in breast cancer from the respective 3D dynamic contrast-enhanced MRI (DCE-MRI) images. The tumor masks on DCE-MRI images were generated using pre- and post-contrast images and validated by experienced radiologists. We show that our proposed mask-guided classification has a higher accuracy than that from either the full image without tumor masks (including background) or the masked voxels only. We have used two patient outcomes for this study: (1) recurrence of cancer after 5 years of imaging and (2) HER2 status, for comparing accuracies of different models. By looking at the activation maps, we conclude that an image-based prediction model using 3D-CNN could be improved by even a conservatively generated mask, rather than overly trusting an unguided, blind 3D-CNN. A blind CNN may classify accurately enough, while its attention may really be focused on a remote region within 3D images. On the other hand, only using a conservatively segmented region may not be as good for classification as using full images but forcing the model's attention toward the known regions of interest.

BackgroundEarlier age at onset of pubertal events and longer intervals between them (tempo) have been associated with increased breast cancer risk. It is unknown whether the timing and tempo of puberty are associated with adult breast density, which could mediate the increased risk.MethodsFrom 1988 to 1997, girls participating in the Dietary Intervention Study in Children (DISC) were clinically assessed annually between ages 8 and 17 years for Tanner stages of breast development (thelarche) and pubic hair (pubarche), and onset of menses (menarche) was self-reported. In 2006–2008, 182 participants then aged 25–29 years had their percent dense breast volume (%DBV) measured by magnetic resonance imaging. Multivariable, linear mixed-effects regression models adjusted for reproductive factors, demographics, and body size were used to evaluate associations of age and tempo of puberty events with %DBV.ResultsThe mean (standard deviation) and range of %DBV were 27.6 (20.5) and 0.2–86.1. Age at thelarche was negatively associated with %DBV (ptrend = 0.04), while pubertal tempo between thelarche and menarche was positively associated with %DBV (ptrend = 0.007). %DBV was 40% higher in women whose thelarche-to-menarche tempo was 2.9 years or longer (geometric mean (95%CI) = 21.8% (18.2–26.2%)) compared to women whose thelarche-to-menarche tempo was less than 1.6 years (geometric mean (95%CI) = 15.6% (13.9–17.5%)).ConclusionsOur results suggest that a slower pubertal tempo, i.e., greater number of months between thelarche and menarche, is associated with higher percent breast density in young women. Future research should examine whether breast density mediates the association between slower tempo and increased breast cancer risk.

Objective To assess the negative predictive value (NPV) of breast MRI in detecting residual disease after neoadjuvant chemotherapy (NAC) in women with invasive breast cancer, overall and by tumor subtype. Methods An institutional review board approved retrospective study from January 2010 through December 2016 identified patients with invasive breast cancer who achieved complete MRI response to NAC, defined as the absence of residual enhancement in the tumor bed above background parenchymal enhancement. During the study period, it was our routine practice to assign a BI-RADS 1 or 2 assessment to these cases. The NPV was defined as the ability of a complete MRI response to predict pathologic complete response (pCR) at final surgical pathology. Statistical analyses were performed using a Fisher exact test. Results Among 244 patients who underwent MRI to assess NAC response, 38 (16%) were determined to have complete MRI response by the interpreting radiologist. Of these, 20/38 (53%) had pCR. Complete MRI response did not significantly predict pCR for the total group (P < 0.9). However, NPVs significantly varied by molecular subtype (P < 0.004). True negative MRIs by tumor subtype were 2/10 (20%) for hormone receptor (HR)+/HER2–, 3/10 (30%) for HR+/HER2+, 6/8 (75%) for HR–/HER+, and 9/10 (90%) for triple negative (TN) subtypes. Complete MRI response significantly predicted pCR for only the TN subtype (NPV 90%; P < 0.02). Conclusions In patients with complete MRI response, 53% had pCR. While MRI lacks sufficient NPV to obviate the need for surgical excision, it may add prognostic value for certain molecular subtypes. The TN subtype demonstrated the highest NPV.

Background The change in apparent diffusion coefficient (ADC) measured from diffusion-weighted imaging (DWI) has been shown to be predictive of pathologic complete response (pCR) for patients with locally invasive breast cancer undergoing neoadjuvant chemotherapy. Purpose To investigate the additive value of tumor ADC in a multicenter clinical trial setting. Study type Retrospective analysis of multicenter prospective data. Population In all, 415 patients who enrolled in the I-SPY 2 TRIAL from 2010 to 2014 were included. Field strength/sequence 1.5T or 3T MRI system using a fat-suppressed single-shot echo planar imaging sequence with b-values of 0 and 800 s/mm2 for DWI, followed by a T1-weighted sequence for dynamic contrast-enhanced MRI (DCE-MRI) performed at pre-NAC (T0), after 3 weeks of NAC (T1), mid-NAC (T2), and post-NAC (T3). Assessment Functional tumor volume and tumor ADC were measured at each MRI exam; pCR measured at surgery was assessed as the binary outcome. Breast cancer subtype was defined by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. Statistical tests A logistic regression model was used to evaluate associations between MRI predictors with pCR. The cross-validated area under the curve (AUC) was calculated to assess the predictive performance of the model with and without ADC. Results In all, 354 patients (128 HR+/HER2-, 60 HR+/HER2+, 34 HR-/HER2+, 132 HR-/HER2-) were included in the analysis. In the full cohort, adding ADC predictors increased the AUC from 0.76 to 0.78 at mid-NAC and from 0.76 to 0.81 at post-NAC. In HR/HER2 subtypes, the AUC increased from 0.52 to 0.65 at pre-NAC for HR+/HER2-, from 0.67 to 0.73 at mid-NAC and from 0.72 to 0.76 at post-NAC for HR+/HER2+, from 0.71 to 0.81 at post-NAC for triple negatives. Data conclusion The addition of ADC to standard functional tumor volume MRI showed improvement in the prediction of treatment response in HR+ and triple-negative breast cancer. Level of evidence 2 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2019;50:1742-1753.

Background: Patients achieving a pathologic complete response (pCR) following neoadjuvant therapy have significantly improved event-free survival relative to those who do not; and pCR is an FDA-accepted endpoint to support accelerated approval of novel agents/combinations in the neoadjuvant treatment of high risk early stage breast cancer. Previous studies have shown that recurrence risk increased with increasing burden of residual disease (as assessed by the RCB index). As well, these studies suggest that patients with minimum residual disease (RCB-I class) also have favorable outcomes (comparable to those achieving a pCR) within high risk tumor subtypes. In this study, we assess whether integrating RCB with MRI functional tumor volume (FTV), which in itself is prognostic, can improve prediction of distant recurrence free survival (DRFS); and identify a subset of patients with minimal residual disease with comparable DRFS as those who achieved a pCR. Imaging tools can then be used to identify the subset that will do well early and guide the timing of surgical therapy. Method: We performed a pooled analysis of 596 patients from the I-SPY2 TRIAL with RCB, pre-surgical MRI FTV data and known follow-up (median 2.5 years). We first assessed whether FTV predicts residual disease (pCR or pCR/RCB-I) using ROC analysis. We applied a power transformation to normalize the pre-surgical FTV distribution; and assessed its association with DRFS using a bi-variate Cox proportional hazard model adjusting for HR/HER2 subtype. We also fitted a bivariate Cox model of RCB index adjusting for subtype; and assessed whether adding pre-surgical FTV to this model further improves association with DRFS using a likelihood ratio (LR) test. For the Cox modeling, penalized splines approximation of the transformed FTV and RCB index with 2 degrees of freedom was used to allow for non-linear effects of FTV and RCB on DRFS. Result: Pre-surgical MRI FTV is significantly associated with DRFS (Wald p Conclusion: Pre-surgical MRI FTV is effective at predicting minimal residual disease (RCB0/I) in the I-SPY 2 TRIAL. Despite the association between FTV and RCB, FTV appears to provide independent added prognostic value (to RCB and subtype), suggesting that integrating MRI volume measures and RCB into a composite predictor may improve DRFS prediction. Citation Format: Hylton NM, Symmans WF, Yau C, Li W, Hatzis C, Isaacs C, Albain KS, Chen Y-Y, Krings G, Wei S, Harada S, Datnow B, Fadare O, Klein M, Pambuccian S, Chen B, Adamson K, Sams S, Mhawech-Fauceglia P, Magliocco A, Feldman M, Rendi M, Sattar H, Zeck J, Ocal I, Tawfik O, Grasso LeBeau L, Sahoo S, Vinh T, Yang S, Adams A, Chien AJ, Ferero-Torres A, Stringer-Reasor E, Wallace A, Boughey JC, Ellis ED, Elias AD, Lang JE, Lu J, Han HS, Clark AS, Korde L, Nanda R, Northfelt DW, Khan QJ, Viscusi RK, Euhus DM, Edmiston KK, Chui SY, Kemmer K, Wood WC, Park JW, Liu MC, Olopade O, Tripathy D, Moulder SL, Rugo HS, Schwab R, Lo S, Helsten T, Beckwith H, Haugen PK, van't Veer LJ, Perlmutter J, Melisko ME, Wilson A, Peterson G, Asare AL, Buxton MB, Paoloni M, Clennell JL, Hirst GL, Singhrao R, Steeg K, Matthews JB, Sanil A, Berry SM, Abe H, Wolverton D, Crane EP, Ward KA, Nelson M, Niell BL, Oh K, Brandt KR, Bang DH, Ojeda-Fournier H, Eghtedari M, Sheth PA, Bernreuter WK, Umphrey H, Rosen MA, Dogan B, Yang W, Joe B, I-SPY 2 TRIAL Consortium, Yee D, Pusztai L, DeMichele A, Asare SM, Berry DA, Esserman LJ. Refining neoadjuvant predictors of three year distant metastasis free survival: Integrating volume change as measured by MRI with residual cancer burden [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 P2-07-03.

Background: Invasive lobular carcinoma of the breast (ILC) has higher rates of false negative imaging than invasive ductal carcinoma, and lower rates of neoadjuvant therapy (NAT) use. We evaluated the accuracy of Breast Imaging Reporting And Data System (BIRADS) findings on magnetic resonance imaging (MRI) after either neoadjuvant chemotherapy or endocrine therapy, and determined whether imaging change correlates with disease free survival. Methods: We queried a database of 674 ILC cases treated at UCSF from 1981-2017 and identified all patients treated with NAT. We reviewed MRI reports and recorded BIRADS descriptors of findings, maximal tumor diameter for mass or non-mass enhancement (NME), and subjective radiologist comments on progression or improvement. We used the t-test, chi-squared test, Pearson's correlation, and Kaplan Meier survival estimates to evaluate the accuracy of MRI after NAT compared to true tumor size on pathology, and the relationship between imaging change and disease free interval in Stata 14.2. Results: Of 136 patients with ILC treated with NAT, we included 101 women who had a post-treatment breast MRI report available. Of these, 58.4% received neoadjuvant chemotherapy, and 41.6% neoadjuvant endocrine therapy. After NAT, MRI findings were mass only in 43%, both mass/NME in 33%, NME only in 18%, and neither in 5%. Maximal diameter of mass on post-treatment MRI underestimated true size by a mean of 3.3 cm (range -3.6 to 15.3 cm). NME size on post-treatment MRI underestimated true size by a mean of 1.87 cm (range -7.2 to 9.7 cm). Mass size on MRI underestimated true size by ≥1 cm in 61.5% of cases; this size discrepancy was associated with increased positive margins (46.4% versus 20%, p=0.011). NME size on MRI underestimated true size by at ≥1 cm in 65.6%. The correlation coefficient between mass size on MRI and true size was 0.34 (p=0.0041), which increased to 0.67 (p Table 1.Patient and tumor characteristics. Neoadjuvant chemotherapy (n=59)Neoadjuvant endocrine therapy (n=42)P valueMean age (yrs, 95% CI)53.6 (50.9-56.3)61.3 (58.4-64.1)0.0002Subtype 0.105ER+ PR+ HER2-29 (53.7%)23 (62.16%) ER+ PR- HER2-14 (25.9%)13 (35.14%) ER- PR- HER2-1 (1.85%)0 HER2+10 (18.5%)1 (2.7%) Grade 0.076114 (25%)16 (38.1%) 237 (66.1%)26 (61.9%) 35 (8.93%)0 Surgical stage Conclusions: Maximal tumor diameter on MRI after NAT in ILC vastly underestimates true tumor size. While these findings suggest using caution when using an MRI for surgical planning in patients with ILC, particularly if there is associated NME, the trend towards improved disease free survival in those with a subjective improvement is intriguing and suggests that MRI changes could become an early predictor of outcomes. Citation Format: Fahrner-Scott KE, Wong JM, Piper M, Ewing C, Alvarado M, Esserman LJ, Hylton N, Mukhtar RA. Accuracy of MRI after neoadjuvant therapy for invasive lobular carcinoma of the breast [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 P1-15-15.

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.

Purpose To determine if the change in tumor apparent diffusion coefficient (ADC) at diffusion-weighted (DW) MRI is predictive of pathologic complete response (pCR) to neoadjuvant chemotherapy for breast cancer. Materials and Methods In this prospective multicenter study, 272 consecutive women with breast cancer were enrolled at 10 institutions (from August 2012 to January 2015) and were randomized to treatment with 12 weekly doses of paclitaxel (with or without an experimental agent), followed by 12 weeks of treatment with four cycles of anthracycline. Each woman underwent breast DW MRI before treatment, at early treatment (3 weeks), at midtreatment (12 weeks), and after treatment. Percentage change in tumor ADC from that before treatment (ΔADC) was measured at each time point. Performance for predicting pCR was assessed by using the area under the receiver operating characteristic curve (AUC) for the overall cohort and according to tumor hormone receptor (HR)/human epidermal growth factor receptor 2 (HER2) disease subtype. Results The final analysis included 242 patients with evaluable serial imaging data, with a mean age of 48 years ± 10 (standard deviation); 99 patients had HR-positive (hereafter, HR+)/HER2-negative (hereafter, HER2-) disease, 77 patients had HR-/HER2- disease, 42 patients had HR+/HER2+ disease, and 24 patients had HR-/HER2+ disease. Eighty (33%) of 242 patients experienced pCR. Overall, ΔADC was moderately predictive of pCR at midtreatment/12 weeks (AUC = 0.60; 95% confidence interval [CI]: 0.52, 0.68; P = .017) and after treatment (AUC = 0.61; 95% CI: 0.52, 0.69; P = .013). Across the four disease subtypes, midtreatment ΔADC was predictive only for HR+/HER2- tumors (AUC = 0.76; 95% CI: 0.62, 0.89; P < .001). In a test subset, a model combining tumor subtype and midtreatment ΔADC improved predictive performance (AUC = 0.72; 95% CI: 0.61, 0.83) over ΔADC alone (AUC = 0.57; 95% CI: 0.44, 0.70; P = .032.). Conclusion After 12 weeks of therapy, change in breast tumor apparent diffusion coefficient at MRI predicts complete pathologic response to neoadjuvant chemotherapy. © RSNA, 2018 Online supplemental material is available for this article.

Ductal carcinoma in situ (DCIS) is a risk factor for the subsequent development of invasive breast cancer. High-risk features include age 5 cm, high-grade, palpable mass, hormone receptor negativity, and HER2 positivity. We have previously shown that immune infiltrates are positively associated with these high-risk features, suggesting that manipulating the immune microenvironment in high-risk DCIS could potentially alter disease progression. Patients with high-risk DCIS were enrolled in this 3 × 3 phase 1 dose-escalation pilot study of 2, 4, and 8 mg intralesional injections of the PD-1 immune checkpoint inhibitor, pembrolizumab. Study participants received two intralesional injections, three weeks apart, prior to surgery. Tissue from pre-treatment biopsies and post-treatment surgical resections was analyzed using multiplex immunofluorescence (mIF) staining for various immune cell populations. The intralesional injections were easily administered and well-tolerated. mIF analyses demonstrated significant increases in total T cell and CD8+ T cell percentages in most patients after receiving pembrolizumab, even at the 2 mg dose. T cell expansion was confined primarily to the stroma rather than within DCIS-containing ducts. Neither cleaved caspase 3 (CC3) staining, a marker for apoptosis, nor DCIS volume (as measured by MRI) changed significantly following treatment. Intralesional injection of pembrolizumab is safe and feasible in patients with DCIS. Nearly all patients experienced robust total and CD8+ T cell responses. However, we did not observe evidence of cell death or tumor volume decrease by MRI, suggesting that additional strategies may be needed to elicit stronger anti-tumor immunity.

We investigated whether serial measurements of circulating tumor DNA (ctDNA) and functional tumor volume (FTV) by magnetic resonance imaging (MRI) can be combined to improve prediction of pathologic complete response (pCR) and estimation of recurrence risk in early breast cancer patients treated with neoadjuvant chemotherapy (NAC). We examined correlations between ctDNA and FTV, evaluated the additive value of ctDNA to FTV-based predictors of pCR using area under the curve (AUC) analysis, and analyzed the impact of FTV and ctDNA on distant recurrence-free survival (DRFS) using Cox regressions. The levels of ctDNA (mean tumor molecules/mL plasma) were significantly correlated with FTV at all time points (p p p = 0.25). In contrast, ctDNA-positivity after NAC provided significant additive value to FTV in identifying patients with increased risk of metastatic recurrence and death (p = 0.004). In this pilot study, we demonstrate that ctDNA and FTV were correlated measures of tumor burden. Our preliminary findings based on a limited cohort suggest that ctDNA at surgery improves FTV as a predictor of metastatic recurrence and death. Validation in larger studies is warranted.

The combination of PD-L1 inhibitor durvalumab and PARP inhibitor olaparib added to standard paclitaxel neoadjuvant chemotherapy (durvalumab/olaparib/paclitaxel [DOP]) was investigated in the phase II I-SPY2 trial of stage II/III HER2-negative breast cancer. Seventy-three participants were randomized to DOP and 299 to standard of care (paclitaxel) control. DOP increased pathologic complete response (pCR) rates in all HER2-negative (20%-37%), hormone receptor (HR)-positive/HER2-negative (14%-28%), and triple-negative breast cancer (TNBC) (27%-47%). In HR-positive/HER2-negative cancers, MammaPrint ultra-high (MP2) cases benefited selectively from DOP (pCR 64% versus 22%), no benefit was seen in MP1 cancers (pCR 9% versus 10%). Overall, 12.3% of patients in the DOP arm experienced immune-related grade 3 adverse events versus 1.3% in control. Gene expression signatures associated with immune response were positively associated with pCR in both arms, while a mast cell signature was associated with non-pCR. DOP has superior efficacy over standard neoadjuvant chemotherapy in HER2-negative breast cancer, particularly in a highly sensitive subset of high-risk HR-positive/HER2-negative patients.

Metabolic imaging of the primary breast tumor with 18F-fluorodeoxyglucose ([18F]FDG) PET may assist in predicting treatment response in the neoadjuvant chemotherapy (NAC) setting. Dedicated breast PET (dbPET) is a high-resolution imaging modality with demonstrated ability in highlighting intratumoral heterogeneity and identifying small lesions in the breast volume. In this study, we characterized similarities and differences in the uptake of [18F]FDG in dbPET compared to whole-body PET (wbPET) in a cohort of ten patients with biopsy-confirmed, locally advanced breast cancer at the pre-treatment timepoint. Patients received bilateral dbPET and wbPET following administration of 186 MBq and 307 MBq [18F]FDG on separate days, respectively. [18F]FDG uptake measurements and 20 radiomic features based on morphology, tumor intensity, and texture were calculated and compared. There was a fivefold increase in SULpeak for dbPET (median difference (95% CI): 4.0 mL−1 (1.8–6.4 mL−1), p = 0.006). Additionally, spatial heterogeneity features showed statistically significant differences between dbPET and wbPET. The higher [18F]FDG uptake in dbPET highlighted the dynamic range of this breast-specific imaging modality. Combining with the higher spatial resolution, dbPET may be able to detect treatment response in the primary tumor during NAC, and future studies with larger cohorts are warranted.

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.

BACKGROUND: The Eastern Cooperative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 multicenter trial helped confirm the potential of diffusion-weighted MRI for improving differential diagnosis of suspicious breast abnormalities and reducing unnecessary biopsies. A prespecified secondary objective was to explore the relative value of different approaches for quantitative assessment of lesions at diffusion-weighted MRI. PURPOSE: To determine whether alternate calculations of apparent diffusion coefficient (ADC) can help further improve diagnostic performance versus mean ADC values alone for analysis of suspicious breast lesions at MRI. MATERIALS AND METHODS: This prospective trial (ClinicalTrials.gov identifier: NCT02022579) enrolled consecutive women (from March 2014 to April 2015) with a Breast Imaging Reporting and Data System category of 3, 4, or 5 at breast MRI. All study participants underwent standardized diffusion-weighted MRI (b = 0, 100, 600, and 800 sec/mm(2)). Centralized ADC measures were performed, including manually drawn whole-lesion and hotspot regions of interest, histogram metrics, normalized ADC, and variable b-value combinations. Diagnostic performance was estimated by using the area under the receiver operating characteristic curve (AUC). Reduction in biopsy rate (maintaining 100% sensitivity) was estimated according to thresholds for each ADC metric. RESULTS: Among 107 enrolled women, 81 lesions with outcomes (28 malignant and 53 benign) in 67 women (median age, 49 years; interquartile range, 41–60 years) were analyzed. Among ADC metrics tested, none improved diagnostic performance versus standard mean ADC (AUC, 0.59–0.79 vs AUC, 0.75; P = .02–.84), and maximum ADC had worse performance (AUC, 0.52; P < .001). The 25th-percentile ADC metric provided the best performance (AUC, 0.79; 95% CI: 0.70, 0.88), and a threshold using median ADC provided the greatest reduction in biopsy rate of 23.9% (95% CI: 14.8, 32.9; 16 of 67 BI-RADS category 4 and 5 lesions). Nonzero minimum b value (100, 600, and 800 sec/mm(2)) did not improve the AUC (0.74; P = .28), and several combinations of two b values (0 and 600, 100 and 600, 0 and 800, and 100 and 800 sec/mm(2); AUC, 0.73–0.76) provided results similar to those seen with calculations of four b values (AUC, 0.75; P = .17–.87). CONCLUSION: Mean apparent diffusion coefficient calculated with a two–b-value acquisition is a simple and sufficient diffusion-weighted MRI metric to augment diagnostic performance of breast MRI compared with more complex approaches to apparent diffusion coefficient measurement. © RSNA, 2020 Online supplemental material is available for this article.

Objective Women with advanced HER2− breast cancer have limited treatment options. Breast MRI functional tumor volume (FTV) is used to predict pathologic complete response (pCR) to improve treatment efficacy. In addition to FTV, background parenchymal enhancement (BPE) may predict response and was explored for HER2− patients in the I-SPY-2 TRIAL. Methods Women with HER2− stage II or III breast cancer underwent prospective serial breast MRIs during four neoadjuvant chemotherapy timepoints. BPE was quantitatively calculated using whole-breast manual segmentation. Logistic regression models were systematically explored using pre-specified and optimized predictor selection based on BPE or combined with FTV. Results A total of 352 MRI examinations in 88 patients (29 with pCR, 59 non-pCR) were evaluated. Women with hormone receptor (HR)+HER2− cancers who achieved pCR demonstrated a significantly greater decrease in BPE from baseline to pre-surgery compared to non-pCR patients (odds ratio 0.64, 95% confidence interval (CI): 0.39–0.92, P = 0.04). The associated BPE area under the curve (AUC) was 0.77 (95% CI: 0.56–0.98), comparable to the range of FTV AUC estimates. Among multi-predictor models, the highest cross-validated AUC of 0.81 (95% CI: 0.73–0.90) was achieved with combined FTV+HR predictors, while adding BPE to FTV+HR models had an estimated AUC of 0.82 (95% CI: 0.74–0.92). Conclusion Among women with HER2− cancer, BPE alone demonstrated association with pCR in women with HR+HER2− breast cancer, with similar diagnostic performance to FTV. BPE predictors remained significant in multivariate FTV models, but without added discrimination for pCR prediction. This may be due to small sample size limiting ability to create subtype-specific multivariate models.

Breast parenchymal enhancement (BPE) has shown association with breast cancer risk and response to neoadjuvant treatment. However, BPE quantification is challenging, and there is no standardized segmentation method for measurement. We investigated the use of a fully automated breast fibroglandular tissue segmentation method to calculate BPE from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for use as a predictor of pathologic complete response (pCR) following neoadjuvant treatment in the I-SPY 2 TRIAL. In this trial, patients had DCE-MRI at baseline (T0), after 3 weeks of treatment (T1), after 12 weeks of treatment and between drug regimens (T2), and after completion of treatment (T3). A retrospective analysis of 2 cohorts was performed: one with 735 patients and another with a final cohort of 340 patients, meeting a high-quality benchmark for segmentation. We evaluated 3 subvolumes of interest segmented from bilateral T1-weighted axial breast DCE-MRI: full stack (all axial slices), half stack (center 50% of slices), and center 5 slices. The differences between methods were assessed, and a univariate logistic regression model was implemented to determine the predictive performance of each segmentation method. The results showed that the half stack method provided the best compromise between sampling error from too little tissue and inclusion of incorrectly segmented tissues from extreme superior and inferior regions. Our results indicate that BPE calculated using the half stack segmentation approach has potential as an early biomarker for response to treatment in the hormone receptor–negative and human epidermal growth factor receptor 2–positive subtype.

In recent years, neoadjuvant treatment trials have shown that breast cancer subtypes identified on the basis of genomic and/or molecular signatures exhibit different response rates and recurrence outcomes, with the implication that subtype-specific treatment approaches are needed. Estrogen receptor-positive (ER+) breast cancers present a unique set of challenges for determining optimal neoadjuvant treatment approaches. There is increased recognition that not all ER+ breast cancers benefit from chemotherapy, and that there may be a subset of ER+ breast cancers that can be treated effectively using endocrine therapies alone. With this uncertainty, there is a need to improve the assessment and to optimize the treatment of ER+ breast cancers. While pathology-based markers offer a snapshot of tumor response to neoadjuvant therapy, non-invasive imaging of the ER disease in response to treatment would provide broader insights into tumor heterogeneity, ER biology, and the timing of surrogate endpoint measurements. In this review, we provide an overview of the current landscape of breast imaging in neoadjuvant studies and highlight the technological advances in each imaging modality. We then further examine some potential imaging markers for neoadjuvant treatment response in ER+ breast cancers.

The presented analysis of multisite, multiplatform clinical oncology trial data sought to enhance quantitative utility of the apparent diffusion coefficient (ADC) metric, derived from diffusion-weighted magnetic resonance imaging, by reducing technical interplatform variability owing to systematic gradient nonlinearity (GNL). This study tested the feasibility and effectiveness of a retrospective GNL correction (GNC) implementation for quantitative quality control phantom data, as well as in a representative subset of 60 subjects from the ACRIN 6698 breast cancer therapy response trial who were scanned on 6 different gradient systems. The GNL ADC correction based on a previously developed formalism was applied to trace-DWI using system-specific gradient-channel fields derived from vendor-provided spherical harmonic tables. For quantitative DWI phantom images acquired in typical breast imaging positions, the GNC improved interplatform accuracy from a median of 6% down to 0.5% and reproducibility of 11% down to 2.5%. Across studied trial subjects, GNC increased low ADC (&lt, 1 µm2/ms) tumor volume by 16% and histogram percentiles by 5%–8%, uniformly shifting percentile-dependent ADC thresholds by ∼0.06 µm2/ms. This feasibility study lays the grounds for retrospective GNC implementation in multiplatform clinical imaging trials to improve accuracy and reproducibility of ADC metrics used for breast cancer treatment response prediction.

Mean tumor apparent diffusion coefficient (ADC) of breast cancer showed excellent repeatability but only moderate predictive power for breast cancer therapy response in the ACRIN 6698 multicenter imaging trial. Previous single-center studies have shown improved predictive performance for alternative ADC histogram metrics related to low ADC dense tumor volume. Using test/retest (TT/RT) 4 b-value diffusion-weighted imaging acquisitions from pretreatment or early-treatment time-points on 71 ACRIN 6698 patients, we evaluated repeatability for ADC histogram metrics to establish confidence intervals and inform predictive models for future therapy response analysis. Histograms were generated using regions of interest (ROIs) defined separately for TT and RT diffusion-weighted imaging. TT/RT repeatability and intra- and inter-reader reproducibility (on a 20-patient subset) were evaluated using wCV and Bland–Altman limits of agreement for histogram percentiles, low-ADC dense tumor volumes, and fractional volumes (normalized to total histogram volume). Pearson correlation was used to reveal connections between metrics and ROI variability across the sample cohort. Low percentiles (15th and 25th) were highly repeatable and reproducible, wCV &lt, 8.1%, comparable to mean ADC values previously reported. Volumetric metrics had higher wCV values in all cases, with fractional volumes somewhat better but at least 3 times higher than percentile wCVs. These metrics appear most sensitive to ADC changes around a threshold of 1.2 μm2/ms. Volumetric results were moderately to strongly correlated with ROI size. In conclusion, Lower histogram percentiles have comparable repeatability to mean ADC, while ADC-thresholded volumetric measures currently have poor repeatability but may benefit from improvements in ROI techniques.

PURPOSE Primary endocrine therapy for ductal carcinoma in situ (DCIS) as a potential alternative to surgery has been understudied. This trial explored the feasibility of a short-term course of letrozole and sought to determine whether treatment results in measurable radiographic and biologic changes in estrogen receptor (ER)–positive DCIS. PATIENTS AND METHODS A phase II single-arm multicenter cooperative-group trial was conducted in postmenopausal patients diagnosed with ER-positive DCIS without invasion. Patients were treated with letrozole 2.5 mg per day for 6 months before surgery. Breast magnetic resonance imaging (MRI) was obtained at baseline, 3 months, and 6 months. The primary end point was change in 6-month MRI enhancement volume compared with baseline. RESULTS Overall, 79 patients were enrolled and 70 completed 6 months of letrozole. Of these, 67 patients had MRI data available for each timepoint. Baseline MRI volumes ranged from 0.004 to 26.3 cm3. Median reductions from baseline MRI volume (1.4 cm3) were 0.6 cm3 (61.0%) at 3 months ( P < .001) and 0.8 cm3 (71.7%) at 6 months ( P < .001). Consistent reductions were seen in median baseline ER H-score (228; median reduction, 15.0; P = .005), progesterone receptor H-score (15; median reduction, 85.0; P < .001), and Ki67 score (12%; median reduction, 6.3%; P = .007). Of the 59 patients who underwent surgery per study protocol, persistent DCIS remained in 50 patients (85%), invasive cancer was detected in six patients (10%), and no residual DCIS or invasive cancer was seen in nine patients (15%). CONCLUSIONS In a cohort of postmenopausal women with ER-positive DCIS, preoperative letrozole resulted in significant imaging and biomarker changes. These findings support future trials of extended endocrine therapy as primary nonoperative treatment of some DCIS.

PURPOSEThe phosphatidylinositol 3-kinase/Akt/mammalian target of rapamycin is a key pathway of survival and therapeutic resistance in breast cancer. We evaluated the pan-Akt inhibitor MK-2206 in combination with standard therapy in patients with high-risk early-stage breast cancer.PATIENTS AND METHODSI-SPY 2 is a multicenter, phase II, open-label, adaptively randomized neoadjuvant platform trial that screens experimental therapies and efficiently identifies potential predictive biomarker signatures. Patients are categorized by human epidermal growth factor receptor 2 (HER2), hormone receptor (HR), and MammaPrint statuses in a 2 × 2 × 2 layout. Patients within each of these 8 biomarker subtypes are adaptively randomly assigned to one of several experimental therapies, including MK-2206, or control. Therapies are evaluated for 10 biomarker signatures, each of which is a combination of these subtypes. The primary end point is pathologic complete response (pCR). A therapy graduates with one or more of these signatures if and when it has an 85% Bayesian predictive probability of success in a hypothetical phase III trial, adjusting for biomarker covariates. Patients in the current report received standard taxane- and anthracycline-based neoadjuvant therapy without (control) or with oral MK-2206 135 mg/week.RESULTSMK-2206 graduated with 94 patients and 57 concurrently randomly assigned controls in 3 graduation signatures: HR-negative/HER2-positive, HR-negative, and HER2-positive. Respective Bayesian mean covariate-adjusted pCR rates and percentage probability that MK-2206 is superior to control were 0.48:0.29 (97%), 0.62:0.36 (99%), and 0.46:0.26 (94%). In exploratory analyses, MK-2206 evinced a numerical improvement in event-free survival in its graduating signatures. The most significant grade 3-4 toxicity was rash (14% maculopapular, 8.6% acneiform).CONCLUSIONThe Akt inhibitor MK-2206 combined with standard neoadjuvant therapy resulted in higher estimated pCR rates in HR-negative and HER2-positive breast cancer. Although MK-2206 is not being further developed at this time, this class of agents remains of clinical interest.

The combination of PD-L1-inhibitor durvalumab and PARP-inhibitor olaparib (DOP) in addition to standard neoadjuvant chemotherapy was investigated in the phase II I-SPY2 platform trial of stage II/III HER2-negative breast cancer. Seventy-three HER2-negative participants were randomized to DOP and 299 to standard of care control. DOP graduated in all subtypes, increasing pCR rates in all HER2-negative (22 to 37%), HR-positive/HER2-negative (14% to 28%), TNBC (27% to 47%). In HR-positive/HER2-negative cancers, pCR rate in MammaPrint ultra high (MP2) cases was considerably higher than MP1, 64% vs 22%. Overall,12.3% of patients in the experimental arm experienced immune-related grade 3 adverse events vs. 1.3% in control. Gene expression signatures associated with immune response were positively associated with pCR in both arms, while a mast cell signature was associated with non-pCR. DOP has potential benefits over standard neoadjuvant therapy in HER2-negative early breast cancer, particularly in a highly sensitive subset of high-risk HR-positive/HER2-negative patients.

Modern radiation therapy is delivered with great precision, in part by relying on high-resolution multi-dimensional anatomical imaging to define targets in space and time. The development of quantitative imaging (QI) modalities capable of monitoring biologic parameters has the potential to provide deeper insight into tumor biology and facilitate more personalized clinical decision-making. The Quantitative Imaging Network (QIN) was established by the National Cancer Institute (NCI) to advance and validate these QI modalities in the context of oncology clinical trials, emphasizing the great clinical need for this technology. In particular, the QIN has significant interest in the application of QI to widen the therapeutic window of radiation therapy. QI modalities have great promise in radiation oncology and will help address significant clinical needs including finer prognostication, more specific target delineation, reduction of normal tissue toxicity, identification of radioresistant disease, and clearer interpretation of treatment response. Patient-specific quantitative information is being incorporated into radiation treatment design in ways such as dose escalation and adaptive replanning, with the intent of improving outcomes while lessening treatment morbidities. This review discusses the current vision of the QIN, current areas of investigation, and how it hopes to enhance the integration of QI into the practice of radiation oncology.

Background Quantitative diffusion-weighted imaging (DWI) MRI is a promising technique for cancer characterization and treatment monitoring. Knowledge of the reproducibility of DWI metrics in breast tumors is necessary to apply DWI as a clinical biomarker. Purpose To evaluate the repeatability and reproducibility of breast tumor apparent diffusion coefficient (ADC) in a multi-institution clinical trial setting, using standardized DWI protocols and quality assurance (QA) procedures. Study type Prospective. Subjects In all, 89 women from nine institutions undergoing neoadjuvant chemotherapy for invasive breast cancer. Field strength/sequence DWI was acquired before and after patient repositioning using a four b-value, single-shot echo-planar sequence at 1.5T or 3.0T. Assessment A QA procedure by trained operators assessed artifacts, fat suppression, and signal-to-noise ratio, and determine study analyzability. Mean tumor ADC was measured via manual segmentation of the multislice tumor region referencing DWI and contrast-enhanced images. Twenty cases were evaluated multiple times to assess intra- and interoperator variability. Segmentation similarity was assessed via the Sorenson-Dice similarity coefficient. Statistical tests Repeatability and reproducibility were evaluated using within-subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), agreement index (AI), and repeatability coefficient (RC). Correlations were measured by Pearson's correlation coefficients. Results In all, 71 cases (80%) passed QA evaluation: 44 at 1.5T, 27 at 3.0T; 60 pretreatment, 11 after 3 weeks of taxane-based treatment. ADC repeatability was excellent: wCV = 4.8% (95% confidence interval [CI] 4.0, 5.7%), ICC = 0.97 (95% CI 0.95, 0.98), AI = 0.83 (95% CI 0.76, 0.87), and RC = 0.16 * 10-3 mm2 /sec (95% CI 0.13, 0.19). The results were similar across field strengths and timepoint subgroups. Reproducibility was excellent: interreader ICC = 0.92 (95% CI 0.80, 0.97) and intrareader ICC = 0.91 (95% CI 0.78, 0.96). Data conclusion Breast tumor ADC can be measured with excellent repeatability and reproducibility in a multi-institution setting using a standardized protocol and QA procedure. Improvements to DWI image quality could reduce loss of data in clinical trials. Level of evidence 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1617-1628.

BACKGROUND Multi-b-valued/multi-shell diffusion provides potentially valuable metrics in breast MRI but suffers from low signal-to-noise ratio and has potentially long scan times. PURPOSE To investigate the effects of model-based denoising with no loss of spatial resolution on multi-shell breast diffusion MRI; to determine the effects of downsampling on multi-shell diffusion; and to quantify these effects in multi-b-valued (three directions per b-value) acquisitions. STUDY TYPE Prospective ("fully-sampled" multi-shell) and retrospective longitudinal (multi-b). SUBJECTS One normal subject (multi-shell) and 10 breast cancer subjects imaging at four timepoints (multi-b). FIELD STRENGTH/SEQUENCE 3T multi-shell acquisition and 1.5T multi-b acquisition. ASSESSMENT The "fully-sampled" multi-shell acquisition was retrospectively downsampled to determine the bias and error from downsampling. Mean, axial/parallel, radial diffusivity, and fractional anisotropy (FA) were analyzed. Denoising was applied retrospectively to the multi-b-valued breast cancer subject dataset and assessed subjectively for image noise level and tumor conspicuity. STATISTICAL TESTS Parametric paired t-test (P

PURPOSE: Carbohydrate intake increases postprandial insulin secretion and may affect breast density, a strong risk factor for breast cancer, early in life. We examined associations of adolescent and early adulthood intakes of total carbohydrates, glycemic index/load, fiber, and simple sugars with breast density among 182 young women. METHODS: Diet was assessed using three 24-h recalls at each of five Dietary Intervention Study in Children (DISC) clinic visits when participants were age 10–19 years and at the DISC06 Follow-Up Study clinic visit when participants were age 25–29 years. Associations between energy-adjusted carbohydrates and MRI-measured percent dense breast volume (%DBV) and absolute dense breast volume (ADBV) at 25–29 years were quantified using multivariable-adjusted mixed-effects linear models. RESULTS: Adolescent sucrose intakes and premenarcheal total carbohydrates intakes were modestly associated with higher %DBV (mean %DBV(Q1 vs Q4), 16.6 vs 23.5% for sucrose; and 17.2 vs 22.3% for premenarcheal total carbohydrates, all P(trend) ≤ 0.02), but not with ADBV. However, adolescent intakes of fiber and fructose were not associated with %DBV and ADBV. Early adulthood intakes of total carbohydrates, glycemic index/load, fiber, and simple sugars were not associated with %DBV and ADBV. CONCLUSIONS: Insulinemic carbohydrate diet during puberty may be associated with adulthood breast density, but our findings need replication in larger studies. Clinical Trials Registration ClinicalTrials.gov Identifier, NCT00458588 April 9, 2007; NCT00000459 October 27, 1999