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Background and Purpose: There is currently lack of recognized imaging criteria for prediction of treatment response to NAST in breast cancer patients. And early identification of treatment response to neoadjuvant systemic therapy (NAST) in Triple Negative Breast Cancer (TNBC) patients is important for appropriate treatment selection and response monitoring. A novel MRI sequence, Magnetic Resonance Image Compilation (MagIC) is capable of simultaneous quantitation of several tissue water properties including longitudinal (T1), transverse (T2) relaxation times, and proton density (PD). In this study we evaluated the ability of a radiomic model extracted from a novel MagIC sequence acquired early during NAST to predict pathologic complete response to NAST in TNBC. Materials and Methods: This IRB approved prospective ARTEMIS trial (NCT02276443) included 184 women (122 training dataset, 62 testing dataset) diagnosed with stage I-III TNBC. All patients were scanned with MagIC on a 3T MRI scanner at baseline (184 patients), and after 4 cycles (156 Patients) of NAST. T1, T2 and PD maps were generated from the source images using SyMRI (SyntheticMR, Linkoping, Sweden). Histopathology at surgery was used to determine pathologic complete response (pCR) which was defined as absence of the invasive cancer in the breast and axillary lymph nodes. 3D contouring of the tumors was performed using an in-house toolbox. 310 (10 first-order, 300 GLCM) textural features were extracted from each map, with total of 930 features/patient. Radiomic features were compared between pCR and non-pCR using Wilcoxon Rank Sum test and Fisher’s exact test. To build a multivariate, predictive model, logistic regression with elastic net regularization was performed for texture feature selection. The tuning parameter was optimized using 5-fold cross-validation based on the average area under curve (AUC) of each fold of a cross-validation using training data. Then the testing data were used to compare model’s performance by AUC. Results: Univariate analysis found 23 PD, 17 T1 and 10 T2 radiomic features at C4 time point to be able to predict pCR status with AUC >70% in both training and testing cohort. The top performing radiomic features were Entropy, Variance, Homogeneity and Energy (Tables1-2). Multivariate radiomics models from C4-PD, and C4-T1 maps showed best performance during both cross validation and independent testing. The radiomic signature of C4-T1 map that included 27features had best performance, with an AUC of 0.77, 0.70 (95% CI: 0.571-0.868) in training and testing cohort respectively. C4-PD map radiomic signature that included 6features was able to predict the pCR status with AUC of 0.73, 0.72 (95% CI: 0.571-0.868) in training and testing cohort respectively. Conclusion: Our data found that MagIC-based radiomics signature could potentially predict pathologic complete response in TNBC early during NAST. This data shows the potential application of MagIC radiomic model for improvement of response assessment in TNBC. Table 1.Best performing radiomic features from PD map after 4 cycles of NAST in TNBC patients.FeatureTraining CohortTraining CohortTraining CohortTesting CohortTesting CohortTesting CohortNAUC95% CINAUC95% CIP-valuePD-mapAngular Variance of Sum entropy1060.73820.6437-0.8328500.73240.5895-0.8752 Table 2.Best performing radiomic features from T1-T2 maps after 4 cycles of NAST in TNBC patients.FeatureTraining CohortTraining CohortTraining CohortTesting CohortTesting CohortTesting CohortNAUC95% CINAUC95% CIP-valueT1-mapAngular Variance of Sum entropy1060.76530.6762-0.8544500.70510.5524-0.8579 Citation Format: Nabil Elshafeey, Ken-Pin Hwang, Beatriz Elena Adrada, Rosalind Pitpitan Candelaria, Medine Boge, Rania M Mahmoud, Huiqin Chen, Jia Sun, Wei Yang, Aikaterini Kotrotsou, Benjamin C Musall, Jong Bum Son, Gary J Whitman, Jessica Leung, Huong Le-Petross, Lumarie Santiago, Deanna Lynn Lane, Marion Elizabeth Scoggins, David Allen Spak, Mary Saber Guirguis, Miral Mahesh Patel, Frances Perez, Abeer H Abdelhafez, Jason B White, Lei Huo, Elizabeth Ravenberg, Wei Peng, Alastair Thompson, Senthil Damodaran, Debu Tripathy, Stacey L Moulder, Clinton Yam, Mark David Pagel, Jingfei Ma, Gaiane Margishvili Rauch. Radiomics model based on magnetic resonance image compilation (MagIC) as early predictor of pathologic complete response to neoadjuvant systemic therapy in triple-negative breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD11-06.

Background: The checkpoint inhibitors atezolizumab (anti-PD-L1) and pembrolizumab (anti-PD-1) are FDA approved for the treatment of patients with PD-L1 positive, metastatic triple negative breast cancer in combination with chemotherapy. The response rates to checkpoint blockade in hormone receptor positive, HER2 negative metastatic breast cancer have been less encouraging (RR 12% for pembrolizumab in KEYNOTE-028 and RR 2.8% for avelumab in the phase 1b trial JAVELIN). We conducted a feasibility trial and enrolled patients with Stage II-III hormone receptor positive, HER2 negative breast cancer to treatment with 2 cycles of durvalumab (anti-PD-L1) plus tremelimumab (anti-CTLA-4) prior to standard neoadjuvant chemotherapy and breast surgery.Methods: Eligible patients were treated with durvalumab at a dose of 1500 mg and tremelimumab at a dose of 75 mg, both administered intravenously, on days 1 and 28. Pre- and post-treatment tumor biopsies and blood samples were available for 5 out of 8 patients and were analyzed by CyTOF, IHC, and NanoString. Patients then received standard neoadjuvant chemotherapy prior to breast surgery. The target enrollment was 20 patients. Results: After 8 patients were enrolled and treated on protocol, the trial was stopped early due to toxicity, slow accrual, and delays in patients receiving standard neoadjuvant chemotherapy. The median age of the patients was 55 (range 39-66) and all 8 patients were women. All patients had ER/PR positive, HER2 negative invasive ductal carcinoma (2 with lobular features, 1 with focal mucinous features) and all patients had clinical Stage II disease. Five patients received both cycles of durvalumab/tremelimumab and the remaining 3 patients only received the first cycle. One patient discontinued therapy out of concern for progression, though repeat breast and lymph node biopsies were benign and she went on to have a pathologic complete response after standard neoadjuvant chemotherapy. The remaining 2 patients discontinued treatment after the first cycle due to Grade 3 colitis (Patient #1) and Grade 3 thyroiditis/adrenal insufficiency (Patient #8). Both patients required treatment with steroids and experienced delays in receiving standard therapy due to these adverse events (AEs). The other AEs reported were all Grade 1 or 2. A post-durvalumab/tremelimumab breast ultrasound was performed in 7 of 8 patients and the percentage change in volume of each patient’s primary breast mass was: -55%, +104% (biopsy benign), +65%, -30%, +90%, -8%, and -53%. Patient #1 (colitis) had chemotherapy administered adjuvantly and Patient #8 (thyroiditis, adrenal insufficiency) declined chemotherapy. Only 1 of 8 patients had a pathologic complete response at the time of surgery. IHC, CYTOF, and gene expression analyses showed an increase in immune cell subsets in tumor stroma post neoadjuvant immunotherapy. Conclusions: We conducted a feasibility trial of neoadjuvant durvalumab plus tremelimumab administered prior to standard neoadjuvant chemotherapy in patients with hormone receptor positive/HER2 negative Stage II or III breast cancer. The trial was stopped early after 2 of 8 patients experienced Grade 3 immune-related adverse events (colitis in 1 patient and thyroiditis/adrenal insufficiency in another patient). Citation Format: Haven R. Garber, Sreyashi Basu, Sonali Jindal, Akshara Singareeka Raghavendra, Lumarie Santiago, Beatriz E. Adrada, Padmanee Sharma, James P. Allison, Jennifer Litton. Durvalumab and tremelimumab before surgery in patients with hormone receptor positive, HER2 negative stage II-III breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-14-14.

Background: TNBC constitutes an aggressive and heterogeneous group of tumors with variable response to neoadjuvant therapy (NAT) that currently lacks clinically available profiling strategies for prediction. We aimed to develop an integrated model based on imaging, pathological and clinical data capable to predict NAT response in TNBC early during therapy. METHOD AND MATERIALS:125 Stage I-III TNBC patients enrolled in an IRB approved prospective clinical trial (NCT02276433) who had DCE-MRI at baseline (BL) and post 2 cycles (C2) of NAT, and had surgery were included in this analysis. Tumor volume was calculated using 3D measurements at BL and C2 time points DCE-MRI. Percent tumor volume reduction (TVR) between BL and C2 was calculated. Demographic, clinical, and pathological data (age, T and N stage, histology, androgen receptor expression, Ki-67, stromal tumor infiltrating lymphocytes level (sTIL), and PD-L1 expression), and treatment response at surgery (pCR vs non-pCR) were documented. Recursive partitioning was used to identify TVR cutoff value. Multivariate logistic regression and ROC analysis were used to assess associations and build and evaluate predictive models. RESULTS: 61 (49%) TNBC pts showed pCR at surgery, and 64 (51%) non-pCR. Recursive partitioning analysis identified ≥ 55% TVR as the optimal cutoff values for pCR prediction at C2. TVR, N stage and sTIL were significantly associated with pCR in the multivariate analyses (p Citation Format: Gaiane Margishvili Rauch, Rosalind P. Candelaria, Mary Saber Guirguis, Medine Boge, Rania M. M. Mohamed, Nabil Elshafeey, Jia Sun, Gary J Whitman, Jessica Leung, Huong C Le-Petross, Lumarie Santiago, Deanna Lane, Marion Scoggins, David Spak, Miral M Patel, Frances Perez, Jason B. White, Elizabeth Ravenberg, Wei Peng, Debu Tripathy, Vicente Valero, Jennifer Litton, Lei Huo, Clinton Yam, Alastair Thompson, Jingfei Ma, Stacy L. Moulder, Wei Yang, Beatriz E. Adrada. Integrated model for early prediction of neoadjuvant systemic therapy response in triple negative breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD11-07.

Introduction: Neoadjuvant chemotherapy (NACT) is becoming standard of care for presurgical treatment of triple negative breast cancer (TNBC) patients. Achievement of pathological complete response (pCR) after NACT is associated with improved outcomes. There is currently an unmet need in development of imaging and clinical tools for prediction of pCR to NACT in TNBC. We investigated use of deep learning convolution neural networks (CNNs) for early prediction of pCR in a TNBC cohort on the basis of MRI acquired before the initiation and at the midpoint, after completion of four cycles of NACT (C4). Materials and Methods: Baseline and C4 MRIs of 112 TNBC patients were collected from an ongoing prospective clinical trial (NCT02276443). Four patients were excluded because they underwent different treatment for the second regimen. Among the 108 patients, 52 patients (48%) had pCR confirmed at surgery. Positive enhancement integral (PEI) derived from the early phases of DCE MRI, and apparent diffusion coefficients (ADC) derived from DWI MRI (b = 100 and 800 s/mm2), were used for our investigation. The images were aligned and the tumor regions were cropped from all images. All tumor patches were normalized between [0, 1], and were padded to form matrices of the same size of 192×192×64 for PEI, or the size of 192×192×16 for ADC. The CNN was constructed using stacked 3D convolution and MaxPooling layers. It consisted of up to four channels for the inputs (baseline and C4 PEI and ADC). Features extracted from each channel were concatenated and regressed for pCR prediction via three densely connected layers. Binary cross-entropy was used as the loss function for CNN training, and the loss was optimized using an Adam optimizer with the initial learning rate of 0.0001. Because of the currently limited sample size, four-fold cross-validation was used for CNN training and evaluation. The patients were divided into four groups, each group had 27 patients and the pCR:non-pCR ratio was controlled as 13:14. For each fold, one group was reserved as the independent testing group, and the other three groups were combined for network training and internal validation. Receiver operating characteristic (ROC) curve was plotted for each fold of testing, and area under the curve (AUC) was calculated. Final performance of the CNN was determined by averaging the AUCs of the four testing folds. Additionally, to test the prediction efficacy of each input, we trained the CNN under the same settings but used PEI or ADC only as input, and the results were compared. Results: The CNN trained with PEI only achieved an average AUC of 0.65 ± 0.09. The second CNN trained with ADC only achieved an average AUC of 0.72 ± 0.07. The third CNN trained with both PEI and ADC achieved an average AUC of 0.73 ± 0.06. Conclusion and Discussion: Using baseline and mid-treatment MRIs, deep learning CNN showed promising performance to predict pCR in the early course of NACT. The prediction AUC for the independent testing groups was largely improved by using ADC to train the network, indicating that ADC can have more critical information than PEI in assisting pCR prediction during the early course of NACT. Future work includes curation of a larger patient data for network training and evaluation to improve the prediction performance and further validate generalization of the network. We will also explore more advanced network structures, through which the prediction performance can be improved. Four-fold cross-validation AUCs of the network using different data as inputs.PEIADCPEI+ADCFold 10.570.640.66Fold 20.760.800.77Fold 30.660.700.68Fold 40.590.740.79Average0.65 ± 0.090.72 ± 0.070.73 ± 0.06 Citation Format: Zijian Zhou, Nabil A Elshafeey, David E Rauch, Beatriz E Adrada, Rosalind P Candelaria, Mary S Guirguis, Wei Yang, Medine Boge, Rania M Mohamed, Gary J Whitman, Deanna L Lane, Huong C Le-Petross, Jessica WT Leung, Lumarie Santiago, Marion E Scoggins, David A Spak, Miral M Patel, Frances Perez, Debu Tripathy, Vicente Valero, Clinton Yam, Stacy Moulder, Jason B White, Jong Bum Son, Mark D Pagel, Jingfei Ma. Deep learning for early prediction of neoadjuvant chemotherapy response in triple negative breast cancers [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-08-03.

Introduction CEST MRI permits quantitation of macromolecules such as amide proteins that are of interest in cancer metabolism. However, optimal CEST acquisition and analysis methods remain undetermined. In this study, we investigated CEST MRI as an imaging biomarker for early treatment response in 51 TNBC patients receiving NAST and compared the performance with two different CEST saturation power levels and two analysis methods. Methods A total of 51 stage I-III TNBC patients enrolled in the prospective ARTEMIS trial (NCT02276443) had CEST imaging performed on a 3T MRI scanner at baseline before NAST (BL, N = 51), after 2 cycles (C2, N = 37), and 4 cycles (C4, N = 44) of NAST. 33 of the 51 patients had imaging at all 3 time points. 29 of the 33 patients had pathological findings, with N = 16 with pathological complete response (pCR) and N = 13 with non-pCR. Two sets of CEST images using 0.9 and 2.0 µT saturation power levels were acquired and analyzed using the magnetization transfer ratio asymmetry (MTRasym) and the Lorentzian line fitting (Mag3.5) methods, for a total of 4 acquisition/analysis combinations. The group averaged CEST signals, MTRasym at 0.9 and 2.0 µT and Mag3.5 at 0.9 and 2.0 µT, at BL, C2 and C4 were determined and evaluated using unpaired (51 patients) and paired (33 patients) Kruskal-Wallis tests. The Mag3.5 at 0.9 µT and the MTRasym at 2.0 µT were further compared between pCR and non-pCR. The group averaged CEST signals at BL, C2, and C4 were evaluated using the Friedman test for the pCR and the non-PCR groups. Separately, the change in the CEST signal from BL to C2 and C4 was determined for each patient and evaluated using the Mann-Whitney test for both groups. P < 0.05 was considered statistically significant. Results The MTRasym at BL was higher at 2.0 µT than at 0.9 µT. In contrast, the Mag3.5 at BL was higher at 0.9 µT than at 2.0 µT. The MTRasym at 2.0 µT and the Mag3.5 at 0.9 µT decreased during treatment while the MTRasym at 0.9 µT and the Mag3.5 at 2.0 µT were similar. Both the unpaired and the paired Mag3.5 at 0.9 µT showed a significant decrease at C2 and C4 vs. BL (p < 0.01). The unpaired and paired MTRasym at 2.0 µT showed a decrease, although the change was not significant except for the unpaired data at C4. The decrease in the group averaged Mag3.5 at 0.9 µT was significant at C2 vs. BL for the pCR group (p = 0.04), while it was not significant for the pCR group at C4 vs. BL and for the non-pCR group at either C2 or C4 vs. BL. The group averaged MTRasym at 2.0 µT changes were not significant for either the pCR or the non-pCR groups. None of the CEST signal changes on a per patient basis at C2-BL, C4-BL and C4-C2 were significantly different between the pCR and the non-pCR groups. Further, none of the group averaged CEST signals at BL, C2 and C4 were significantly different between the pCR and the non-pCR groups. Conclusion Our study demonstrates that the CEST quantitation in TNBC patients undergoing NAST depends on acquisition and analysis. For a maximum change in the CEST effect, Lorentzian line fitting is better paired with acquisition at a low saturation power (0.9 µT) and MTRasym is better paired with acquisition at a high saturation power (2.0 µT). Further, a significant CEST signal decrease was observed in TNBC patients with pCR after NAST when a 0.9 µT saturation power and the Lorentzian line fitting were used. In comparison, the decrease was not significant in non-pCR patients using the same saturation power and analysis method. The results suggest that the CEST signal acquired at 0.9 µT saturation power and analyzed using Lorentzian line fitting may be able to differentiate between pCR and non-pCR among TNBC patients undergoing NAST. Additional studies with a larger patient population are ongoing to further validate our findings and their potential for determining pCR. Citation Format: Shu Zhang, Gaiane M Rauch, Beatriz E Adrada, Medine Boge, Rania MM Mohamed, Abeer H Abdelhafez, Jong Bum Son, Jia Sun, Nabil A Elshafeey, Jason B White, Deanna L Lane, Jessica WT Leung, Marion E Scoggins, David A Spak, Elsa Arribas, Elizabeth Ravenberg, Lumarie Santiago, Tanya W Moseley, Gary J Whitman, Huong Le-Petross, Benjamin C Musall, Mitsuharu Miyoshi, Xinzeng Wang, Brandy Willis, Stacy Hash, Aikaterini Kotrotsou, Peng Wei, Ken-Pin Hwang, Alastair Thompson, Stacy L Moulder, Rosalind P Candelaria, Wei Yang, Jingfei Ma, Mark D Pagel. Assessment of early response to neoadjuvant systemic therapy (NAST) of triple-negative breast cancer (TNBC) using chemical exchange saturation transfer (CEST) MRI: A pilot study [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 PS3-08.

Introduction High levels of TIL at baseline are associated with higher pCR rates and better overall survival in TNBC. Recent studies have also indicated that higher TIL in post-NACT residual disease in TNBC are an important independent predictor of improved survival. We evaluated the role of mid-treatment (post-AC; Adriamycin/Cyclophosphamide) TIL in predicting pCR rates in early-stage TNBC. Methods Of 242 patients with stage I-III TNBC enrolled in the ARTEMIS trial (NCT02276443), 156 patients had pre-AC TIL and pCR status available for this analysis. Both pre-and post-AC TIL counts were available in 29 patients. Post-AC TIL counts for the remaining patients were imputed using linear regression with age, race, stage III, vimentin >50% and post-AC tumor volume reduction. Using these imputed TIL counts we evaluated the association of post-AC TIL with pCR. We also evaluated the change in TIL before and after treatment with AC. Results At baseline the median TIL count was 10% (n=156). In the post-AC samples, the median TIL count was 5%. Using imputed TIL counts, we did not conclude that post-AC TIL was associated with pCR (p= 0.28). Using a cut-point of 15% TIL, our analysis showed that baseline TIL is more strongly correlated with pCR than post-AC TIL (Table 1). In our univariable logistic regression, both baseline TIL and the difference in TIL pre-and post- treatment were significantly associated with pCR (p= 0.0015 and p=0.0068, respectively), however in the multivariable analysis only baseline TIL was significant. Our analysis did show that a decrease in TIL from pre- to post-treatment was significantly associated with pCR (p=0.022). However, this measure was not significant in our logistic regression model when pre-TIL was also included. Conclusion Higher pre-treatment TIL correlated more strongly with pCR rate when compared to post-AC TIL. Pre-treatment high TIL was associated with pCR regardless of changes in TIL pre and post treatment. Table 1. Changes in TIL before and after treatmentBaseline TILPost-AC TILN#pCR (%)LowLow6217 (27%)LowHigh4012 (30%)HighLow2513 (52%)HighHigh2916 (55%)TIL; Low: 15 Citation Format: Nour Abuhadra, Kenneth Hess, Jennifer Litton, Gaiane Rauch, Alastair Thompson, Bora Lim, Beatriz Adrada, Elizabeth Mittendorf, Senthil Damodaran, Rosalind Candelaria, Banu Arun, Wei Tse Yang, Naoto Ueno, Lumarie Santiago, Rashmi Murthy, Nuhad Ibrahim, Sahin Aysegul, William Symmans, Lei Huo, Stacy Moulder. Serial TILs: Evaluating the role of mid-treatment tumor infiltrating lymphocytes (TIL) in predicting pathologic complete response (pCR) in early-stage triple negative breast cancer (TNBC) [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 P1-10-20.

Background: Serial biopsies (bx) of triple-negative breast cancer (TNBC) in the curative neoadjuvant setting provides critical information on dynamic changes in the tumor in response to neoadjuvant systemic therapy (NAST) and can help inform the development of novel therapeutic strategies. However, neoplastic seeding following image guided breast bx has previously been reported in TNBC, raising concerns that serial bx may worsen clinical outcomes. Thus, we sought to determine if serial bx were associated with poorer clinical outcomes (using rates of pathologic complete response [pCR]) in TNBC pts receiving NAST. Methods: We identified 370 TNBC pts who received NAST at MD Anderson Cancer Center from 2011-2017. 200 pts did not have any research bx done (controls) on the index breast carcinoma and 170 pts had at least one research bx done (cases) on the index breast carcinoma as part of the prospective molecular triaging ARTEMIS trial. Baseline characteristics were compared between cases and controls using the Student t-test, Wilcoxon Rank Sum test or Fisher's exact test as appropriate. Univariable and multivariable logistic regression was used to determine if rates of pCR following NAST were significantly different between cases and controls. Results: Demographic characteristics demonstrate no significant differences (Table). However, cases were more likely to have received an anthracycline (99% vs 96%, p=0.02) and a targeted agent (22% vs 0%, p Conclusion: This is the first study examining the impact of serial bx on clinical outcomes in TNBC pts in the curative neoadjuvant setting. Our data suggest that research bx in this setting do not compromise rates of pCR. Baseline and Treatment CharacteristicsCharacteristicControls (n=200)Cases (n=170)p valueMean age - years (standard deviation [SD])52 (12)53 (12)0.54Ethnicity White – n (%)113 (57)115 (68)0.09Black – n (%)48 (24)29 (17) Other – n (%)39 (20)26 (15) Mean tumor size – cm (SD)3.2 (1.4)3.3 (1.7)0.62T stage – n (%) T134 (17)35 (21)0.96T2145 (73)111 (65) T314 (7)17 (10) T47 (4)7 (4) N stage – n (%) N0101 (51)89 (52)0.83N170 (35)55 (32) N27 (4)6 (4) N322 (11)20 (12) Stage – n (%) I19 (10)21 (12)0.74II140 (70)113 (66) III41 (21)36 (21) Grade – n (%) 19 (5)00.14227 (14)22 (13) 3164 (82)148 (87) Neoadjuvant therapy – n (%) Anthracycline191 (96)169 (99)0.02Taxane199 (100)166 (98)0.18Platinum23 (12)23 (14)0.63Targeted agent037 (22) Citation Format: Yam C, Raghavendra A, Hess KR, Adrada BE, Candelaria RP, Damodaran S, Gilcrease MZ, Helgason T, Hortobagyi GN, Huo L, Layman RM, Lim B, Litton JK, Mittendorf EA, Murthy RK, Piwnica-Worms H, Rauch GM, Santiago L, Symmans F, Thompson AM, Tripathy D, Ueno NT, Valero V, Barcenas CH, Moulder SL, Yang W. Impact of serial biopsies in triple-negative breast cancer patients receiving neoadjuvant systemic therapy [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 P1-15-06.

BACKGROUND: Increasing use of neoadjuvant systemic therapy (NAT) for early and locally advanced breast cancer led to critical need for development of tools capable of early treatment response assessment after NAT. Tc-99m sestamibi Molecular breast Imaging (MBI) as a functional imaging modality has a promise to detect changes in the tumor prior to anatomical changes detected by mammogram or ultrasound. PURPOSE: To evaluate the ability of quantitative MBI parameters to predict pathologic complete response (pCR) after completion of NAT in breast cancer patients. MATERIALS AND METHODS: Patients with invasive breast cancer (T1-T4, N0-N3, M0) planned for NAT followed by surgery were enrolled in a prospective IRB approved trial. MBI was performed at baseline and after two cycles of NAT. Patient demographic and tumor biology information (Ki-67, HER2, ER/PR) was collected. MBI images were quantified using a novel approach with corrections for scatter and attenuation and regions of interest (ROI) were drawn over tumors to compute three quantitative MBI uptake metrics for correlation with pathologic response: MBI-specific standardized uptake value (SUV), tumor to background ratio (TBR), and tumor volume. Pathologic complete response was determined based on final histopathology report at the time of surgery as absence of the invasive disease in the breast and axillary lymph nodes. MBI metrics at baseline, after 2 cycles of NAT and interval change were correlated with pCR and tumor biology using the Wilcoxon Rank Sum test, Kruskal-Wallis test or Fisher’s exact test. Statistical analysis was carried out using R (version 3.6.3, R Development Core Team). RESULTS: A total of 70 patients with median age 47.5 years (range 30-77) were included in the analysis. Breast cancer subtypes were: HER2 negative (ER/PR+) 35.7% (25/70), HER2 positive (ER/PR +/-) 35.7% (25/70), and triple negative (HER2-, ER/PR-) 28.6% (20/70). Change in SUV after 2 cycles of NAT was higher in patients with pCR compared to those who did not achieve pCR (mean decrease in SUV of 15.57 and 4.83 respectively, p Citation Format: Miral M Patel, Beatriz E Adrada, Benjamin Lopez, Rosalind P Candelaria, Jia Sun, Medine Boge, Rania M Mohamed, Nabil Elshafeey, Gary Whitman, MD, Huong T Le-Petross, Lumarie Santiago, Marion E Scoggins, Deanna Lane, Tanya Moseley, Galit Zylberman, Jerica Saddler, Jessica WT Leung, Wei T Yang, Vincente Valero, S Cheenu Kappadath, Gaiane M Rauch. Quantitative molecular breast imaging for early prediction of neoadjuvant systemic therapy response in locally advanced breast cancer patients [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-02-03.

Background: Triple negative breast cancer (TNBC) has a poor prognosis. In particular, TNBC patients who have significant residual disease at the time of surgery following completion of neoadjuvant systemic therapy (NST) have an especially poor prognosis. In an effort to identify patients who are unlikely to achieve pathologic complete response (pCR), we investigated if pre-treatment breast MRI morphological characteristics and imaging response patterns during NST can predict pCR in TNBC patients. Materials and Methods: As part of a prospective IRB-approved clinical trial (ARTEMIS, NCT02276443), 199 patients with biopsy-proven stage I-III TNBC received NST and were classified as pCR or non-pCR based on histopathology at surgery. Patients underwent breast MRI at baseline (BL), after 2 cycles (C2), and 4 cycles (C4) of Adriamycin-based chemotherapy (AC). Subsequently, patients received either taxane-based NST or targeted therapy guided by mid-treatment imaging response. MRI studies were reviewed by two fellowship-trained breast radiologists who were blinded to the pathology results. ACR MRI BIRADS lexicon (5th Ed) was used to describe BL tumor morphology. Imaging response pattern at C2 and C4 MRI was classified as follows: type 0 (complete), type 1 (concentric shrinkage), type 2 (crumble), type 3 (diffuse enhancement), type 4 (stable), or type 5 (progression). Morphological baseline features and response patterns were summarized and compared to the pCR status on surgical pathology using Fisher’s exact test. P values less than 0.05 were considered statistically significant. Results: Median age was 53 years, range 24-79. Of 199 patients, 95 (48%) had pCR and 104 (52%) had non-pCR. At BL MRI, an irregularly-shaped mass and homogenous or clumped non-mass enhancement were associated with pCR (p=0.026 and p=0.013, respectively). Multifocality, peritumoral edema, and intratumoral necrosis were independent of pCR. Following NST, the most common MRI response pattern was type 1, seen with equal frequency in pCR and non-pCR at C2 (58% and 42%, respectively) and C4 (47% and 53%, respectively). The following response pattern associations were found: type 0 was associated with pCR at both C2 and C4 timepoints (p Citation Format: Mary S Guirguis, Beatriz E Adrada, Rosalind P Candelaria, Jia Sun, Gary J Whitman, Wei T Yang, Medine Boge, Rania M Mohamed, Nabil A Elshafeey, Deanna L Lane, Huong Le-Petross, Jessica WT Leung, Lumarie Santiago, Marion E Scoggins, David A Spak, Miral Patel, Frances Perez, Peng Wei, Debu Tripathy, Jason White, Elizabeth Ravenberg, Lei Huo, Jennifer Litton, Banu Arun, Vincente Valero, Alastair Thompson, Stacy Moulder, Clinton Yam, Gaiane M Rauch. Prediction of response to neoadjuvant systemic therapy in triple negative breast cancer using baseline tumor MRI characteristics and imaging patterns of response [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-03-06.

Background: Gene expression profiling (GEP) has identified several molecularly distinct subtypes of triple negative breast cancer (TNBC). Currently, GEP-based molecular diagnostics are not routinely used in clinical decision making due to the lack of proven benefit, costs involved and long turnaround time. However, two molecularly distinct subtypes of TNBC, the luminal androgen receptor (AR) and mesenchymal subtypes, have surrogate CLIA-certified immunohistochemical (IHC) markers, AR and vimentin (VM), respectively, which have the potential for application in the clinic. Here we report the rates of AR and VM positivity and their association with clinicopathological characteristics in a cohort of TNBC pts receiving NACT. Methods: As part of an ongoing molecular triaging protocol, 144 pts with stage I-III TNBC underwent a pretreatment biopsy for molecular characterization (MC) prior to initiating neoadjuvant chemotherapy (NACT). IHC for AR and VM were performed using commercially available antibodies. AR+ and VM+ were defined as ≥10% and ≥50% staining, respectively. Pts were randomized 2:1 to know (intervention arm, n=93) and not know (control arm, n=51) the MC results. The charts of pts randomized to the intervention arm were reviewed. Categorical variables were analyzed using Fisher's exact test. Ordinal and continuous variables were analyzed using the Wilcoxon rank-sum test and Student's t test as appropriate. Results: 31% (29/93) and 16% (15/93) of pts were AR+ and VM+, respectively. Only 4% (4/93) of pts were both AR+ and VM+. Clinicopathological characteristics are summarized in Table 1. AR+ pts were more likely to have clinically node positive disease as compared to AR- pts (66% vs 34%, p=0.007). There were no significant differences in clinical tumor size or grade between AR+ and AR- pts. VM+ and VM- pts had similar clinicopathological characteristics. Conclusion: Pts with AR+ TNBC were more likely to have node positive disease. The impact of AR+ on long term outcomes should be investigated in prospective studies. Table 1: Association between patient characteristics and AR/VM status AR VM AR+ (n=29)AR- (n=64)p-valueVM+ (n=15)VM- (n=78)p-valueAge - Median (years, interquartile range)58 (48-65)52 (46-61)0.05855 (48-64)56 (47-62)0.88Clinical Tumor Size Mean (cm, standard deviation)3.5 (1.8)3.0 (1.8)0.2872.7 (1.7)3.3 (1.9)0.31T1 – n(%)5 (17)21 (33)0.2307 (47)19 (24)0.098T2 – n(%)21 (72)36 (56) 7 (47)50 (64) T3 – n(%)3 (10)7 (11) 1 (7)9 (12) Clinical Nodal Status Negative – n(%)10 (34)42 (66)0.0078 (53)44 (56)1.00Positive – n(%)19 (66)22 (34) 7 (47)34 (44) Grade 2 – n(%)6 (21)5 (8)0.0763 (20)8 (10)0.293 – n(%)23 (79)59 (92) 12 (80)70 (90) Citation Format: Yam C, Huo L, Hess KR, Litton JK, Yang W, Piwnica-Worms H, Mittendorf EA, Ueno NT, Lim B, Murthy RK, Damodaran S, Helgason T, Thompson AM, Santiago L, Candelaria RP, Rauch GM, Adrada BE, Symmans WF, Gilcrease MZ, Moulder SL. Androgen receptor positivity is associated with nodal disease in triple negative breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-07-22.

Objectives: To evaluate associations between qualitative and quantitative MRI features and tumor infiltrating lymphocytes (TIL) levels in HER2+ subtype of breast cancer, as potential prognostic non-invasive imaging markers for treatment response prediction. Materials and Methods: Retrospective review of breast cancer patients who had MRI at staging, neoadjuvant chemotherapy and surgery from January 1, 2008 through December 31, 2015 was performed. BI-RADS lexicon was used for lesion evaluation. Demographic, imaging, and pathologic data including TIL levels were documented. Quantitative MRI texture analysis was performed using 3 types of textural features (TF): local binary patterns (LBP), gray-level co-occurrence matrix (GLCM), and threshold adjacency statistics (TAS). Associations between MRI quantitative TF, TIL levels, and pathologic complete response (pCR) were evaluated by Pearson correlation and logistic regression. Results: There were 50 HER2+ patients (median age 51 years, range 29-59) with pretreatment MRI and TIL status for analysis; 27 patients had pCR at surgery. Qualitative MRI analysis showed that mass rim-enhancement (p Conclusion: Quantitative tumor texture analysis based on statistical modeling showed specific nine TF indicative of tumor heterogeneity associated with pCR; and seven TF indicative of increased heterogeneity, complexity, and entropy associated with high TIL levels in HER2+ breast cancer. Analysis of associations of MRI quantitative TF with pCR and TIL in HER2+ breast cancer may help to develop prognostic non-invasive imaging markers for treatment response prediction. Citation Format: Rauch GM, Zhu H, Li H, Adrada BE, Santiago L, Candelaria RP, Wang H, Leung J, Litton J, Wu Y, Murthy R, Mittendorf EA, Yang W. Association of quantitative MRI features with tumor infiltrating lymphocytes and treatment response prediction in HER2 positive subtype of breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD2-09.

Background and Purpose:There is currently a lack of recognized imaging criteria for prediction of treatment response to NAST in breast cancer patients with recent reports showing that breast MRI is the most accurate modality for evaluation of NAST response. DCE-MRI evaluates tumor perfusion that influences tumor enhancement at the post-contrast subtraction images and allows for more accurate measurement of changes in tumor volume during NAST. In this study, we evaluated the ability of tumor volumetric changes after 2 and 4 cycles of NAST by longitudinal ultrafast DCE-MRI to predict pathologic complete response (pCR) in TNBC undergoing NAST. Materials and Methods: Stage I-III TNBC patients enrolled in an IRB approved prospective clinical trial (ARTEMIS, NCT02276433) who had ultrafast DCE-MRI at baseline (BL, N=103), post 2 cycles (C2, N=59), and post 4 cycles (C4, N=103) of anthracycline-based NAST,and had surgery, were included in this analysis. Tumor volume was calculated using 3D measurements of the index lesion at BL, C2, and C4. Percent change of tumor volume (%TV) between BL, C2, and C4 was calculated at early (9-12 sec) and delayed (360-480 sec) phases of DCE-MRI. The largest lesion was used for analysis in patients with multicentric or multifocal disease. Demographic, clinical, and pathologic data and treatment response at surgery (pCR versus non-pCR) were documented. Receiver operating characteristics curve (ROC) analysis was performed for prediction of pCR status. Positive predictive value (PPV), negative predictive value (NPV) and Youden Index were used to select %TV cut-off thresholds for pCR prediction.Results: 103 patients (median age, 53 years; range, 24-79 years) were included, 48 (47%) had pCR, and 55 (53%) had non-pCR at surgical pathology. The %TV reduction at C2 DCE-MRI was predictive of pCR on both early phase DCE MRI (AUC, 0.873; CI:0.779-0.968, p < .0001) and delayed phase DCE MRI (AUC, 0.844; CI:0.742-0.947, p < .0001). Optimal thresholds were as follows: 70% TV reduction on early phase DCE MRI with Youden’s index of 1.58 was able to predict pCR correctly for 79% of patients with PPV of 81%; 75% TV reduction on delayed phase with Youden’s Index of 1.44 was able to predict pCR correctly for 71% of patients with PPV of 85%.%TV reduction was also predictive of pCR at the C4 time point on both early phase DCE MRI (AUC, 0.761; CI:0.665-0.856, p < .0001) and delayed phase DCE MRI (AUC, 0.737; CI:0.641-0.833, p < .0001). Optimal thresholds were as follows: 90% TV reduction on early phase DCE MRI with Youden’s index of 1.43 was able to correctly predict pCR in 72% of patients with PPV of 70%; and 90% TV reduction on delayed phase with Youden’s Index of 1.34 was able to predict pCR correctly in 68% of patients with PPV of 71%.Conclusion: Our data shows that percent tumor volume reduction by DCE-MRI after 2 and 4 cycles of NAST was able to predict pCR in TNBC with high accuracy and can be used as an early imaging biomarker of NAST response prediction. Volumetric changes by longitudinal DCE-MRI can be used to differentiate chemoresistant and chemosensitive TNBC patients as early as after 2 cycles of NAST, and can help to triage patients for treatment de-escalation or targeted therapy. Citation Format: Gaiane Margishvili Rauch, Adrada E Beatriz, Rosalind P Candelaria, Nabil Elshafeey, Abeer H Abdelhafez, Benjamin C Musall, Jia Sun, Medina Boge, Rania M.M Mohamed, Jong Bum Son, Shu Zhang, Jessica Leung, Deanna Lane, Marion Scoggins, David Spak, Elsa Arribas, Lumarie Santiago, Gary J Whitman, Huong T. Le-Petross, Tanya W Moseley, Jason B. White, Elizabeth Ravenberg, Ken-Pin Hwang, Peng Wei, Lei Huo, Jennifer K Litton, Vicente Valero, Debu Tripathy, Alastair M Thompson, Mark D Pagel, Jingfei Ma, Wei T Yang, Stacy Moulder. Volumetric changes on longitudinal dynamic contrast enhanced MR imaging (DCE-MRI) as an early treatment response predictor to neoadjuvant systemic therapy (NAST) in triple negative breast cancer (TNBC) patients [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 PD6-07.

Background: Contemporary improved neoadjuvant systemic therapy (NST) for breast cancer may result in a pathologic complete response (pCR) in up to 60% of patients (pts) yet imaging alone has a poor negative predictive value to determine which pts might be spared surgery. This study was designed to evaluate the hypothesis that percutaneous image guided biopsy after NST can accurately identify patients who may forgo surgery. Methods: Prospective single-center IRB approved study of 34 pts with clinical T1-3 N0-3 triple-negative (TN, n=23) or HER2-positive (n=11) invasive ductal cancer who received standard NST and consented for ultrasound/mammography guided vacuum-assisted core biopsy (VACB) and fine-needle aspiration (FNA) biopsy prior to standard surgery. Main outcome measures included accuracy, false-negative rate (FNR), and negative predictive value of image guided biopsy in predicting residual disease after NST. Breast pCR was defined as no residual DCIS or invasive disease. Final biopsy showing atypia and/or suspicion of residual disease was recorded as positive. Results: Median initial maximum tumor size based on imaging and physical exam was 3 cm (1.2-7 cm) and 47.1% had FNA/core biopsy proved nodal metastases. Final median maximum residual tumor size after NST was 0.9 cm (0-4.2 cm) with 94.1% having no palpable abnormality. Median number of VACB (9G) removed following NST was 10 (4-14) and was performed by stereotactic (67.6%) or ultrasound (32.4%) guidance. Overall, a breast pCR occurred in 18 (52.9%) of pts and breast pathologic response was concordant with nodal pathologic response in 33 (97%) of pts (1 pt with a breast pCR had 1/15 nodes with metastases). Overall, VACB combined with FNA following NST had a 100% (95% CI 89.7-100) accuracy, 0% FNR (95% CI 0-20.6), and 100% (95% CI 81.5-100) negative predictive value for determination of residual breast disease. Grade 1 adverse events which resolved from biopsy (bleeding, hematoma, bruising) occurred in 6 pts (17.6%). Conclusions: High rates of pCR among pts with TN/HER2-positive breast cancer receiving NST occur in a significant proportion of pts. The use of image guided VACB/FNA can identify pts after NST where significant residual disease is unlikely. Based on these results, an IRB approved clinical trial will shortly commence for pts with T1-2 TN/HER2-positive breast cancer with documented image guided biopsy proved pCR after NST to be followed by standard definitive whole-breast radiotherapy without surgery.Background: Contemporary improved neoadjuvant systemic therapy (NST) for breast cancer may result in a pathologic complete response (pCR) in up to 60% of patients (pts) yet imaging alone has a poor negative predictive value to determine which pts might be spared surgery. This study was designed to evaluate the hypothesis that percutaneous image guided biopsy after NST can accurately identify patients who may forgo surgery. Methods: Prospective single-center IRB approved study of 34 pts with clinical T1-3 N0-3 triple-negative (TN, n=23) or HER2-positive (n=11) invasive ductal cancer who received standard NST and consented for ultrasound/mammography guided vacuum-assisted core biopsy (VACB) and fine-needle aspiration (FNA) biopsy prior to standard surgery. Main outcome measures included accuracy, false-negative rate (FNR), and negative predictive value of image guided biopsy in predicting residual disease after NST. Breast pCR was defined as no residual DCIS or invasive disease. Final biopsy showing atypia and/or suspicion of residual disease was recorded as positive. Results: Median initial maximum tumor size based on imaging and physical exam was 3 cm (1.2-7 cm) and 47.1% had FNA/core biopsy proved nodal metastases. Final median maximum residual tumor size after NST was 0.9 cm (0-4.2 cm) with 94.1% having no palpable abnormality. Median number of VACB (9G) removed following NST was 10 (4-14) and was performed by stereotactic (67.6%) or ultrasound (32.4%) guidance. Overall, a breast pCR occurred in 18 (52.9%) of pts and breast pathologic response was concordant with nodal pathologic response in 33 (97%) of pts (1 pt with a breast pCR had 1/15 nodes with metastases). Overall, VACB combined with FNA following NST had a 100% (95% CI 89.7-100) accuracy, 0% FNR (95% CI 0-20.6), and 100% (95% CI 81.5-100) negative predictive value for determination of residual breast disease. Grade 1 adverse events which resolved from biopsy (bleeding, hematoma, bruising) occurred in 6 pts (17.6%). Conclusions: High rates of pCR among pts with TN/HER2-positive breast cancer receiving NST occur in a significant proportion of pts. The use of image guided VACB/FNA can identify pts after NST where significant residual disease is unlikely. Based on these results, an IRB approved clinical trial will shortly commence for pts with T1-2 TN/HER2-positive breast cancer with documented image guided biopsy proved pCR after NST to be followed by standard definitive whole-breast radiotherapy without surgery. Citation Format: Kuerer HM, Rauch GM, Krishnamurthy S, Adrada BE, Caudle AS, DeSnyder SM, Santiago L, Lucci A, Hobbs BP, Gilcrease M, Hwang R, Candelaria RP, Chavez Mac-Gregor M, Arribas E, Moseley T, Teshome M, Miggins MV, Smith BD, Valero V, Hunt KK, Yang WT. Feasibility trial for identification of patients for eliminating breast cancer surgery following neoadjuvant systemic therapy [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-16-30.

Background and Purpose:Early and accurate assessment ofbreast cancer response to NAST is important for patient management. In this study, we investigated the value of radiomic phenotypes derived from semi-quantitative and quantitative DCE-MRI parametric maps for early prediction of NASTresponse in TNBC patients. MATERIALS AND METHODS:This IRB approved study included 74 patients with stage I-III TNBC who were enrolled in the prospective ARTEMIS trial (NCT02276443). Pathologic complete response (pCR) and non-pCR were assessed by surgical histopathology after NAST (pCR=34; non-pCR=40).MRI scans were obtained at 3 time points during the NAST treatment with every 2-week anthracycline-based chemotherapy (AC): at baseline (BSL=74), post-2 cycles of AC (C2= 27) and post-4 cycles of AC (C4= 27). Patients went on to receive taxane-based chemotherapy prior to surgery. Tumor regions of interest (ROIs) were segmented by a breast radiologist at the early-phase subtractions of DCE-MRI scans using in-house developed software, followed by co-registration of the ROIs with quantitative (Ktrans, Veand Kep), and semi-quantitative DCE parametric maps (Maximum Slope Increase (MSI), Positive Enhancement Integral (PEI) and Peak Signal Enhancement Ratio (SER)).A total of 93 first order radiomic features were extracted from the tumor ROIs of each time point semi-quantitative DCE parametric map, while a total of 390 extracted radiomic features (first order-histogram features and second order grey-level-co-occurrence matrix) were extracted from each quantitative DCE parametric map using an in-house developed Matlab software.Radiomic features at each time point and changes between the 3 time points were compared between pCR and non-pCR using Wilcoxon Rank Sum test and Fisher’s exact test. Area under the receiver operating characteristics curve (AUC) was used to determine which features predicted pCR.Logistic regression was performed for feature selection, and used to build the radiomic phenotype model. The model performance was assessed by leave-one-out cross validation and 3-fold cross validation. RESULTS:Thirty-three radiomic features from PEI map were significantly different between pCR and non-pCR. The PEI most significant features were changesbetween BSL and C4 in skewness, mean and median (AUC=0.87, 0.85 and 0.87, p= Citation Format: Nabil Elshafeey, Beatriz E Adrada, Rosalind P Candelaria, Abeer H Abdelhafez, Benjamin C Musall, Jia Sun, Medine Boge, Rania M.M Mohamed, Hagar S Mahmoud, Jong Bum Son, Aikaterini Kotrosou, Shu Zhang, Jessica Leung, Deanna Lane, Marion Scoggins, David Spak, Elsa Arribas, Lumarie Santiago, Gary J. Whitman, Huong T Le-Petross, Tanya W Moseley, Jason B White, Elizabeth Ravenberg, Ken-Pin Hwang, Peng Wei, Jennifer K Litton, Lei Huo, Debu Tripathy, Vicente Valero, Alastair M Thompson, Stacy Moulder, Wei T Yang, Mark D Pagel, Jingfei Ma, Gaiane M Rauch. Radiomic phenotypes from dynamic contrast-enhanced MRI (DCE-MRI) parametric maps for early prediction of response to neoadjuvant systemic therapy (NAST) in triple negative breast cancer (TNBC) patients [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 PD6-06.

Background and Purpose: TNBC is comprised of biologically aggressive tumors with diverse clinical behavior and response to chemotherapy. Prediction of disease response to NACT is critical to the development of personalized medicine in TNBC. We evaluated first-order radiomic features from quantitative ADC maps of the tumor and peritumoral region as discriminators of response to NACT in TNBC patients. Materials and Methods: This IRB-approved prospective study (ARTEMIS trial, NCT02276443) included 34 patients with biopsy proven stage I-III TNBC who underwent evaluation of treatment response by multi-parametric MRI. Patients had a baseline MRI (BL) and a second MRI after 4 cycles (C4) of their treatment. After completion of NACT, all patients underwent surgery and were classified as pathologic complete response (pCR) or non-pCR. Both MRI exams included T2W series, a dynamic contrast enhanced series (DCE), a conventional diffusion weighted imaging (DWI) series, and a reduced field of view (rFOV) DWI series. Tumor volumes were contoured by an experienced breast radiologist on ADC maps with reference to b1000 DWI images. Regions with necrosis or clip artifacts were excluded from the contour. Peritumoral regions were defined as a 5 mm rim of tissue surrounding the tumor based on DCE series, T2-weighted images with fat suppression and ADC maps. Thirteen first-order radiomic features, including mean, minimum, maximum, percentiles, kurtosis and skewness at a single measurement and the difference between BL and C4 were compared between pCR and non-pCR using Receiver Operating Characteristic (ROC) curve and Wilcoxon rank sum test. Results: The kurtosis of tumor at C4 by conventional DWI was significantly higher in non-pCR than in pCR patients (AUC=0.785, p=0.0097). The change in kurtosis from BL to C4 by conventional DWI was also significantly higher in non-pCR than in pCR patients (AUC=0.73, p=0.043). The skewness of tumor at C4 by rFOV DWI scan was significantly lower in pCR than non-pCR patients (AUC=0.73, p=0.023). The 10th percentile of the peritumoral region’s ADC was significantly different between pCR and non-pCR (mean=1.19, SD is ± 0.27 10-3 mm2/s vs mean=1.34, SD ± 0.27 10-3 mm2/s respectively, AUC=0.70, p=0.048). The kurtosis and 25th percentile of the ADC of peritumoral region were borderline significantly different between pCR and non-pCR (AUC=0.69, p=0.067; AUC=0.69, p= 0.073 respectively). Conclusion: ADC first-order radiomic features from tumor and peritumoral region in TNBC may be useful for predicting treatment response to NACT. Larger study is necessary and is currently in progress to validate these findings. Citation Format: Beatriz E. Adrada, Abeer H. Abdelhafez, Benjamin C. Musall, Kenneth R. Hess, Jong Bum Son, Mark D. Pagel, Ken-Pin Hwang, Rosalind P. Candelaria, Lumarie Santiago, Gary J. Whitman, Huong Le-Petross, Tanya W. Moseley, Elsa Arribas, Deanna L. Lane, Marion E. Scoggins, David A. Spak, Jessica W.T. Leung, Senthil Damodaran, Bora Lim, Vicente Valeo, Jason B White, Alastair M. Thompson, Jennifer K. Litton, Stacy L. Moulder, Jingfei Ma, Wei T. Yang, Gaiane M Rauch. Quantitative apparent diffusion coefficient (ADC) radiomics of tumor and peritumoral regions as potential predictors of treatment response to neoadjuvant chemotherapy (NACT) in triple negative breast cancer (TNBC) patients [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-02-03.

Background: The LAR subtype of triple negative breast cancer (TNBC) was defined using the Vanderbilt genomic signature in cell lines. The characteristics of this population remain unclear. Methods: We collected the clinicopathological, molecular and imaging characteristics of the LAR population who were enrolled in the ARTEMIS trial, a prospective trial to treat women with TNBC to receive neoadjuvant anthracycline therapy followed by experimental arms based on biomarker versus taxane. The ultrasonography-based response assessment was performed at baseline, after 2 and 4 cycles of anthracycline chemotherapy. The Vanderbilt genomic signature was used to classify the TNBC into the basal-like 1, basal-like 2, immunomodulatory, mesenchymal, mesenchymal stem-like and luminal androgen receptor (LAR) subtypes. The clinical data for this analysis included age, race, menopausal status, TNM stage and BRCA mutation status. Pathological and molecular characteristics included histologic subtype, nuclear grade, Ki67, vimentin expression, androgen receptor (AR) immunohistochemical (IHC) nuclear staining, stromal tumor infiltrating lymphocytes (TIL) percentage and residual cancer burden (RCB) at surgery. Results: Total 28 patients with the LAR signature were analyzed. The characteristics are showed in the table: AgeRaceno. (%)Clinical Stageno. (%)AR IHC StainingBRCA Mutationno. (%)Median (yr)55White19 (68)IA1 (4)Median (%)52No mutation16 (57)Distribution(%)no. (%)Asian3 (11)IIA6 (21)Distribution (%)no(%)Mutation present018-402 (7)Black2 (7)IIB10 (36)6014 (50)American Indian1 (3)IIIB051-751 (3,5)Unknown5 (18)IIIC5 (18)76-10012 (43)Not available1 (3,5)Menopauseno. (%)Histologic subtypeno. (%)Ki67Stromal TILno. (%)Vimentin expressionno. (%)Postmenopausal23 (82)IDC24 (87)Median (%)40 Relevant characteristics are: median age of 55 years, 82% postmenopausal, 89% breast tumor size > 2cm, 79% with lymph node involvement, no BRCA mutation detected, 75% nuclear grade III, 46% with Ki67 ≥ 20%, median AR IHC staining of 52%, 85% vimentin expression of Conclusion: The LAR subgroup harbors unique characteristics that require further confirmation in larger cohorts. Citation Format: James Crespo, Seth Sahil, Elizabeth Ravenberg, Lei Huo, Kenneth Hess, Lumarie Santiago, Beatriz Adrada, Gaiane Rauch, Damodaran Senthil, Rashmi Murthy, Jennifer Litton, Debu Tripathy, Naoto Ueno, Stacy Moulder, Bora Lim. Characterization of the LAR subtype triple negative breast cancer population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1409.

Background: Triple negative breast cancer (TNBC) is molecularly heterogeneous disease. Genomic profiling to identify the distinct TNBC subtypes is costly with long turnaround time. Early ultrasound after two cycles of neoadjuvant chemotherapy (NAC) has the potential to identify patients who are likely to have pathological complete response. Suspected non-responder patients can undergo comprehensive genetic testing and triaged for specific targeted therapeutic trials. Aim: To determine the value of ultrasound evaluation after two cycles of NAC to predict complete pathologic response in TNBC breast cancer patients. Methods: 98 patients enrolled in “A randomized triple Negative Breast Cancer Enrolling Trial to Confirm Molecular Profiling Improves Survival” (Artemis) at the University of Texas MD Anderson Cancer Center had ultrasound evaluation before treatment and after two cycles of NAC (Adriamycin and Cyclophosphamide). Three-dimensional measurements of the tumor were obtained at baseline and after 2 cycles of the NAC. Change in the tumor volume after 2 cycles of NAC was calculated. Residual cancer Volume (RCB) was calculated based on the final histopathology at surgery. Linear regression analysis evaluated associations between residual cancer burden (RCB) and change in volume of the index tumor. Results: Median tumor size at diagnosis was 3 cm, range 0.6-11.9cm. Median size after two cycles was 2 cm, range 0.6-12.8 cm. RCB 0-I was seen in 55% of patients (54/98). Linear regression analysis demonstrated that of 22 patients with volume reduction >75%, 18 patients (82%) had RCB0-I (95%CI, 61%-93%). Conclusion: Our data suggest that ultrasound exam after 2 cycles of NAC can identify TNBC patients who are unlikely to respond to standard NAC. These non-responder TNBC patients can be triaged for additional genetic testing and subsequent targeted clinical trials. Study on the larger number of patients is currently on the way. Citation Format: Adrada BE, Candelaria R, Moulder S, Lane D, Santiago L, Arribas E, Hess KR, Valero V, Thompson A, Helgason T, Ravenberg E, Yang W, Rauch GM. Early ultrasound evaluation for prediction of treatment response to neoadjuvant chemotherapy in triple negative breast cancer patients [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 P6-02-10.

Purpose: To report preliminary data in a pilot study evaluating the ability of Tc99m sestamibi Molecular Breast Imaging (MBI) to predict response and assess residual disease at the completion of neoadjuvant chemotherapy (NAC) in breast cancer patients. Materials and Methods: Patients with localized, invasive breast cancer (T1-T4, N0-N3, M0) planned for NAC were enrolled in this prospective IRB approved clinical trial. All patients had digital mammography (DM), ultrasound (US), and MBI at baseline (T0), after 2 NAC cycles (T1), and at after NAC completion (T2). Tumor size and volume changes were compared with residual disease at surgery. MBI images were corrected for scatter and attenuation using a novel approach and regions of interest (ROI) were drawn over tumors to compute three quantitative MBI uptake metrics for correlation with pathologic response: tumor to background ratio (TBR), fractional activity uptake (FAU), and MBI-specific standardized uptake value (SUV). ROC analysis was performed. Results: Patients (n=25) who completed NAC, had 75 imaging time points and had surgery, were included in this analysis. Median age was 49 years (range 31 -77). Eleven patients (11/25, 44%) had complete pathologic response (pCR). Absolute TBR values after 2 cycles (T1) and before surgery (T2) had highest correlation with pCR (AUC 0.81; 95% CI 0.63 to 0.99, p=0.01, and AUC 0.78; 95% CI 0.59 to 0.97, p=0.015, respectively). Change in SUV after 2 cycles, Δ SUV1 (T1-T0), (AUC 0.84; 95% CI 0.66 to 1.00, p=0.01) and change in SUV prior to surgery, Δ SUV2 (T2-T0) (AUC 0.80; 95% CI 0.60 to 1.00, p=0.02), were most predictive of pCR. Tumor size and volume showed modest specificity for detecting residual disease, and was highest for MBI (79%), followed by MMG (64%), and lowest for US (55%). Conclusion: Quantitative MBI metrics show promise for the prediction of pCR in breast cancer patients undergoing NAC. Establishment of quantitative metrics for the early prediction of tumor response during NAC of breast cancer patients may provide an alternate to influencing NAC choice early in the management algorithm. Further investigation with a larger sample size is warranted. Citation Format: Rauch GM, Adrada BE, Kappadath C, Candelaria RP, Huang ML, Santiago L, Moseley T, Scoggins ME, Knudtson JD, Lopez BP, Hess KR, Krishnamurthy S, Moulder S, Valero V, Yang W. Quantitative assessment of tumor response to neoadjuvant chemotherapy in women with locoregional invasive breast cancer using Tc99m sestamibi molecular breast imaging - preliminary results [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-01-02.

Background: Image-guided percutaneous needle biopsy of the breast is a common procedure. In breast cancer patients (pts) undergoing core biopsies and surgical resection on the same day, the rate of tumor cell displacement along the needle track has been reported to be up to 50%. However, the clinical significance of this finding in triple negative breast cancer (TNBC) patients (pts) undergoing serial biopsies while receiving neoadjuvant chemotherapy (NACT) is unknown. Here we report the incidence of needle-track seeding (NTS) in a cohort of TNBC pts enrolled on a molecular triaging protocol involving serial biopsies of the index breast lesion. Methods: We reviewed the clinical records of 144 consecutive TNBC pts enrolled on a molecular triaging protocol at MD Anderson Cancer Center. Per protocol, all pts underwent a pre-treatment research biopsy and were initiated on anthracycline based NACT (AC). Pts with inadequate response to front-line NACT were encouraged to undergo additional biopsies of the index breast lesion prior to switching therapies. Serial breast ultrasound (US) was performed to monitor therapeutic response and incidental evidence of needle-track seeding noted on US was documented. Results: Clinicopathological characteristics of the pts are summarized in Table 1. 89% (128/144) of pts had a diagnostic breast biopsy done at another center prior to presenting at MDACC. To date, we have performed 209 US guided biopsies of index breast lesions in 144 pts. 92% (193/209) of these biopsies were done mainly for research purposes. 1.4% (2/144) of pts were found to have evidence of NTS on follow up US. The first pt had a T1N0 (1.9cm), grade 3, invasive ductal carcinoma (IDC) at diagnosis. She underwent a diagnostic biopsy followed by a research biopsy before initiating AC. She was found to have NTS as well as progression of disease (PD) on follow up US after 2 cycles of AC. The second pt had a T2N0 (3cm), grade 3 IDC at diagnosis. She underwent a diagnostic biopsy at another center, followed by a research biopsy before initiating AC. Like the first pt, she was found to have NTS and PD on follow up US after 2 cycles of AC. Both pts are currently on neoadjuvant clinical trials of novel agents. Conclusion: The rate of NTS detected on US in TNBC pts undergoing serial biopsies of index breast lesions while receiving NACT is low and further studies are needed to determine the impact of serial biopsies on long term outcomes in TNBC. Table 1: Patient CharacteristicsCharacteristicN=144Age - Median (years, interquartile range)55 (46-62)Tumor Size Mean (cm, standard deviation)3.4 (2.2)T1 – n(%)35 (24)T2 – n(%)89 (62)T3 – n(%)19 (13)T4 – n(%)1 (1)Clinical Nodal Status Negative – n(%)74 (51)Positive – n(%)70 (49)Grade 1 – n(%)1 (1)2 – n(%)17 (12)3 – n(%)124 (86)Unknown – n(%)2 (1)Histologic Subtype Invasive ductal carcinoma – n(%)121 (84)Invasive lobular carcinoma – n(%)2 (1)Mixed ductal and lobular carcinoma – n(%)3 (2)Metaplastic carcinoma – n(%)13 (9)Not specified – n(%)5 (3)Laterality Right – n(%)72 (50)Left – n(%)72 (50) Citation Format: Yam C, Santiago L, Candelaria RP, Adrada BE, Rauch GM, Hess KR, Litton JK, Piwnica-Worms H, Mittendorf EA, Ueno NT, Lim B, Murthy RK, Damodaran S, Helgason T, Huo L, Thompson AM, Gilcrease MZ, Symmans WF, Moulder SL, Yang W. Risk of needle-track seeding with serial ultrasound guided biopsies in triple negative breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P6-03-05.

Objective: The aim of this study was to evaluate ability of quantitative analysis of MRI features to distinguish triple negative (TN) and HER2 positive (HER2+) subtypes of breast cancer, which have different biological characteristics, exhibiting different growth patterns and response to treatment. Materials and Method: Breast cancer patients, who had MRI exam of the breast in our institution at the time of staging for breast carcinoma and who subsequently had surgery (segmentectomy or mastectomy) from January 1, 2008 through December 31, 2015 were identified. All lesions were evaluated by radiologists in accordance with the BI-RADS lexicon. The patient's age, breast cancer histology, multifocality/multicentricity (MF/MC), lesion size, axillary lymphadenopathy (LAN), MRI morphologic and enhancement characteristics were documented. Quantitative MRI feature analysis was performed using shape, texture, and histogram based features. Machine-learning-based (Xgboost) models were used to predict subtypes, and Leave-one-out cross-validation (LOOCV) was used to avoid model overfitting. Statistical significance was determined using the Student's t-test. Results: Total of 105 patients, 51 patients with TN and 54 patients with HER2+ breast cancer were included in analysis. Mean age for TN was 50 (range 29-79)) years old and for HER2+ was 49 (range 25-70) years old. Axillary LAN and MF/MC disease was seen more commonly in HER2+ patients when compared to TN patients, but didn't reach statistical significance (13 vs 7, p=0.9; and 31 vs 20, p=0.06, respectively). Mass rim enhancement was associated with TN subtype and irregular mass enhancement was associated with HER2+ subtype of breast cancer (p Conclusion: The quantitative MRI features show promise in distinguishing TN and HER2+ breast cancer subtypes reflecting their underlying biological characteristics and may be used as predictive quantitative biological markers. Further studies in a larger cohort evaluating associations with treatment response are underway. FeatureIndexP-valueSurface to volume ratioShape30.005Difference VarianceGLCM110.005Difference EntropyGLCM100.009Inverse Difference MomentGLCM50.01875 percentile in histogramHistogram50.043Sum AverageGLCM60.044Median in histogramHistogram 30.08025 percentile in histogramHistogram 40.095VolumeShape10.104Max in histogramHistogram 10.105 Citation Format: Rauch GM, Li H, Zhu H, Adrada BE, Santiago L, Candelaria RP, Wang H, Leung J, Thompson A, Litton J, Wu Y, Lim B, Moulder S, Mittendorf EA, Yang W. Quantitative MRI features analysis for differentiation of triple negative and HER2 positive subtypes of breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-02-04.

BACKGROUND: Patient-derived xenograft (PDX) models of breast cancer replicate the diverse histologic and molecular features of patient tumors and provide a renewable source of human tumor tissue. However, collection of tissue by core needle biopsy is problematic due to patient discomfort, bleeding risk and the limited number of passes a patient can tolerate. Several studies have catalogued the maintenance of molecular features of patient tumors in PDX models of breast cancer. METHODS: To support the neoadjuvant molecular diagnostic and drug development program in triple negative breast cancer (TNBC), a pilot study was conducted to determine if fine needle aspiration (FNA) could be used for building PDX models. Subsequently, PDX models are being established in alignment with ongoing clinical trials at MDACC. The molecular evolution of patient's tumors, matched with PDXs engrafted from their tumors, is under study throughout the neoadjuvant treatment of TNBC using RNA sequencing, whole-exome sequencing, deep sequencing of cancer genes, and histologic analyses. RESULTS: To date, 20 established PDX models have been developed and stable PDX models continue to be generated at a rate of 2-3 per month. Several of these models are derived from serial FNAs derived from patients throughout neoadjuvant treatment. These models retain histologic and molecular features of the original patient tumors. Serial patient biopsies, matched with PDX models, have enabled measurement of the mutational and transcriptomic evolution in vivo of TNBC undergoing neoadjuvant treatment. We have standardized the use of FNAs to generate PDX models both pre- and post-neoadjuvant therapy in the following ongoing neoadjuvant clinical trials: 1. MDACC 2014-0185 (PI Stacy Moulder, 360 patients), 'ARTEMIS: A Randomized TNBC-Enrolling trial to confirm Molecular profiling Improves Survival' 2. MDACC 2014-0045 (PI Jennifer Litton, 20+ patients), 'A pilot study of BMN673 as a neoadjuvant study in patients with a diagnosis of invasive breast cancer and a deleterious BRCA mutation' CONCLUSION: We demonstrated that PDX models from tissue collected by FNA recapitulate the biology and clinical course of the patient's tumor. Sequencing analyses revealed that neoadjuvant chemotherapy and PDX engraftment enrich for cancer gene mutations. We observe association of the rate of successful PDX engraftment with clinical parameters such as the patient's residual cancer burden (RCB) status at the time of surgery (upon completion of neoadjuvant treatment). In addition, we observe that PDX models derived from serial patient biopsies throughout treatment are more resistant to chemotherapy treatment. These models recapitulate the variety of chemotherapy responses observed in patients with TNBC and serve as powerful tools for preclinical biomarker and discovery studies. Citation Format: Echeverria GV, Cai S, Tu Y, McCoy A, Lau R, Redwood A, Rauch G, Adrada B, Candelaria R, Santiago L, Thompson A, Litton J, Moulder S, Symmans F, Chang JT, Piwnica-Worms H. A molecularly annotated collection of breast cancer patient-derived xenograft models aligned with ongoing clinical trials built from fine needle aspiration samples throughout neoadjuvant treatment [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-05-01.

BACKGROUND: While targeted therapy has improved survival for ER+ and HER2+ breast cancers, no such therapy exists for TNBC. Nearly 50% of TNBC patients treated with neoadjuvant chemotherapy (taxane/anthracycline-based) will have insensitive disease manifested as extensive residual disease (RCB-II or III). This is associated with high chance of recurrence within 3 years of diagnosis. Through the Moon Shot program at MD Anderson, we have created a biomarker-driven drug development strategy (ARTEMIS: A Randomized, TNBC Enrolling trial to confirm Molecular profiling Improves Survival) to identify novel targeted therapies for chemo-insensitive disease in TNBC. In the ARTEMIS trial, patients with localized TNBC undergo biopsy for molecular profiling prior to the start of initial anthracycline-based chemotherapy. Results of molecular characterization along with diagnostic imaging is then used to identify patients with chemo-insensitive disease and inform second phase of neoadjuvant therapy to overcome intrinsic drug resistance. The mesenchymal subtype of TNBC is characterized by high incidence of PI3K pathway alterations. Consequently, preclinical models have demonstrated response to PI3K inhibitors in this subtype. Metaplastic breast cancers constitute approximately 30% of tumors characterized as ‘claudin-low/mesenchymal’ by gene expression profiling. A combination regimen consisting of liposomal doxorubicin, bevacizumab and mTOR inhibitors temsirolimus or everolimus (DAT or DAE) has demonstrated responses (including durable complete responses) in patients with advanced metaplastic breast cancers. PRIMARY OBJECTIVE: Determine the rate of pathologic complete response (pCR/RCB-0) or minimal residual disease (RCB-I) after 4 cycles of DAE for treatment of mesenchymal TNBC deemed to be chemo-insensitive after first phase of neoadjuvant therapy in the ARTEMIS trial TRIAL DESIGN AND STATISTICAL METHODS: Patients deemed to have chemo-insensitive mesenchymal TNBC identified through the ARTEMIS trial would be enrolled into this non-randomized phase II study. Considering that patients without response to initial chemotherapy have a very low chance (5%) of achieving pCR with additional cycles of chemotherapy, it would be clinically meaningful to see pCR improved to 20% in this population. Estimating pCR (RCB-0) or RCB-I as response, a two-stage Gehan-type design will be employed with 14 patients in the first stage. This design has a 49% chance of terminating after the first stage if the true response rate is 0.05, 23% chance if the true rate is 0.10, 10% chance if the true rate is 0.15 and 4% chance if the true rate is 0.20. If at least one patient responds, 23 more will be enrolled for a total of 37 patients. With 37 patients enrolled, the 95% confidence interval for a 0.20 response rate will extend from 0.10 to 0.35. BRIEF ELIGIBILITY CRITERIA: Inclusion: early stage TNBC patients enrolled in the ARTEMIS trial with adequate organ, bone marrow and cardiac function Exclusion: patients with metastatic disease, medical illness that increases chance of moderate to severe toxicity, pregnant or lactating. CORRELATIVE SCIENCE: correlate mesenchymal signatures and PI3K pathway aberrations and vimentin expression by IHC with response Citation Format: Senthil Damodaran, Ken Hess, Maia Rauch, Beatrice Astrada, Lumarie Santiago, Jennifer Litton, Elizabeth Mittendorf, Bora Lim, Naoto Ueno, Debu Tripathy, Alastair Thompson, Mike Gilcrease, Wei Yang, Helen Piwnica-Worms, W. Fraser Symmans, Stacy L. Moulder. NCT02456857: A phase II trial of liposomal doxorubicin, bevacizumab and everolimus (DAE) in patients with localized triple-negative breast cancer (TNBC) with tumors predicted insensitive to standard neoadjuvant chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr CT062. doi:10.1158/1538-7445.AM2017-CT062