Brandt, KR

Abstract 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<0.00001), and more effective at predicting pCR/RCB-I than predicting pCR alone (AUC: 0.72 vs. 0.65). Larger pre-surgical FTV remains associated with worse DRFS adjusting for subtype (Wald p <0.00001). The RCB index is also significantly associated with DRFS adjusting for subtype (Wald p<0.00001). Adding FTV to a model containing RCB and subtype further improves association with DRFS (LR p=0.0007). RCB-I patients have excellent DRFS (94% at 3 years compared to 95% in the pCR group). Efforts are underway to identify an optimal threshold for dichotomizing pre-surgical FTV and FTV change measures for use in combination with pCR/RCB-I class to generate integrated RCB (iRCB) groups as a composite predictor of DRFS. 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.

Abstract Background In clinically node-negative (cN0) breast cancer patients with triple negative (TN) and HER2+ disease and breast pathological complete response (breast pCR), low rates of nodal positivity after neoadjuvant chemotherapy (NAC) have been demonstrated. In these patients, the omission of surgical axillary staging has been proposed. However, this information is not routinely known preoperatively. We aimed to validate the correlation between pathologic breast response and pathologic nodal status, and evaluate the relationship between response of the breast tumor on MRI and pathologic nodal status after NAC in cN0 patients in the I-SPY2 trial. Methods We identified all patients with cT1-4 cN0 breast cancer prior to NAC from graduated arms of the I-SPY2 trial, a prospective neoadjuvant chemotherapy trial. Absence of residual disease post-NAC was defined as longest diameter (LD) of 0 mm on MRI. Breast pCR was defined as the absence of invasive tumor in the breast at surgery. Associations between ypN0 and patient, MRI, and tumor characteristics were assessed using chi-square tests and univariate regression. Results Of 365 cT1-4 cN0 patients included, 128 had HR+/HER2- tumors (35%), 60 HR+/HER2+ tumors (16%), 34 HR-/HER2+ tumors (9%) and 143 TN tumors (39%). Overall, 283 patients (78%) were ypN0 after NAC and 152 patients (42%) had a breast pCR. ypN0 rate was higher in patients with a breast pCR than those with residual disease (93% vs 66%, p<0.001). Patients with HR-/HER2+ and TN tumors were more likely to be ypN0 (97% and 87% respectively) than patients with HR+/HER2- and HR+/HER2+ disease (66% and 71% respectively, p<0.001). Other characteristics associated with ypN0 were tumor grade (grade I 57%, grade II 66%, grade III 84%; p=0.002), MammaPrint Classification (High Risk 1 68% and High Risk 2 87%; p<0.001) and absence of residual tumor in the breast on MRI (87% vs 72% in patients with evidence of tumor on MRI post-NAC/pre-surgery; p=0.003). In patients with HR-/HER2+, HR+/HER2+, HR-/HER2+ or TN disease and a breast pCR, ypN0 rate was respectively 82%, 96%, 96% and 97% (table 1). In patients with HR+/HER2-, HR+/HER2+, HR-/HER2+ or TN disease and with no evidence of residual disease in the breast on MRI, rate of ypN0 was 71%, 80%, 94% and 96% respectively. Conclusion In cT1-4 cN0 breast cancer patients with HR+/HER2+, HR-/HER2+ and TN tumors and a breast pCR, ypN0 rates after NAC are extremely high. In patients with HR-/HER2+ and TN tumors with no residual breast disease on MRI after NAC and pre-surgery, ypN0 rates are high enough to consider omission of axillary surgery. In patients with HR+ tumors, MRI is unsufficiently predictive for pathological response and can therefore not be used to select ypN0 patients. Research on the prediction of ypN0 in cN+ I-SPY2 patients is ongoing. Nodal status in patients with pCR and absence of residual disease on MRI Number of positive nodesBreast Cancer Subtype0123AllBreast pCR HR+/HER2-27(82)2(6)4(12)033(100)HR+/HER2+24(96)01(4)025(100)HR-/HER2+24(96)1(4)0025(100)TN67(97)2(3)0069(100)Absence of residual disease on MRI HR+/HER2-24(71)7(21)3(9)034(100)HR+/HER2+16(80)3(15)01(5)20(100)HR-/HER2+15(94)1(6)0016(100)TN54(96)2(4)0056(100) Citation Format: van der Noordaa ME, Esserman L, Yau C, Mukhtar R, Price E, Hylton N, 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, van 't Veer L, Hirst G, Lancaster R, Wallace A, Alvaredo M, Symmans F, Asare S, Boughey JC, I-SPY2 Consortium. Role of breast MRI in predicting pathologically negative nodes after neoadjuvant chemotherapy in cN0 patients in the I-SPY2 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 PD4-04.

Abstract Background Women with benign breast disease (BBD) have an increased risk for breast cancer (BC). Almost 30% of all BCs develop in women with prior BBD. Information about the features of the expected BCs after BBD would enable individualized surveillance and prevention strategies for these women. We sought to characterize BCs developing in a large cohort of women with BBD. Methods Our cohort includes 13,485 women who underwent breast biopsy for mammographic or palpable concern between 1967-2001. Biopsy slides were reviewed and classified as nonproliferative (NP), proliferative disease without atypia (PDWA), or atypical hyperplasia (AH). BCs were identified by follow-up questionnaires, medical records, and Tumor Registry data. BC tissues were obtained and reviewed. Results With a median follow-up of 15.8 years, 1273 women developed BC. Most BCs were invasive (81%), among which 61% were ductal, 13% mixed ductal/lobular, and 14% lobular. Two thirds were intermediate or high-grade, and 29% were node positive. Cancer characteristics were similar across the three histologic categories of BBD, with similar frequency of DCIS and invasive disease, tumor size, time to invasive BC, histologic type of BC, nodal positivity and HER2 positivity. Women with AH had a higher frequency of ER+ BC (91%) vs women with PD (80%) or NP (85%), p=0.02. Conclusion A substantial proportion of all BCs develop in women with prior BBD. We show that the majority of BCs after BBD are invasive tumors of ductal type, with a substantial proportion node positive. 84% of cancers were ER-positive. Chemoprevention should be strongly encouraged in higher-risk women with BBD. Citation Format: Visscher DW, Frost MH, Hartmanan LC, Frank RD, Vierkant RA, McCullough AE, Winham SJ, Vachon C, Ghosh K, Brandt KR, Farrell AM, Tarabishy Y, Hieken TJ, Haddad TC, Kraft RA, Radisky DC, Degnim AC. Clinicopathologic features of breast cancers that develop in women with previous benign breast disease. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-10-19.

Abstract Background: Mammographic density, the variation in fat, epithelial and stromal tissues seen on screening mammography, is a strong risk factor for breast cancer and can be modified by hormonal agents. Changes in density from tamoxifen or postmenopausal hormone (PMH) use are associated with risk, suggesting that density may be a surrogate marker of therapeutic efficacy. Aromatase inhibitors (AIs) are given as adjuvant therapy in hormone receptor positive postmenopausal breast cancer and are known to decrease levels of estrone and estradiol in both serum and breast tissue. Our goal here was to examine the influence of AIs on mammographic density in women with early breast cancer. Methods: We conducted a case-control study of postmenopausal breast cancer patients initiating adjuvant AI therapy (anastrozole or exemestane) on protocols NCIC CTG MA27, NCCTG N063I and MC (Mayo Clinic) 0532. Eligibility included; an intact contralateral breast with no prior surgery; a screening mammogram within twelve months before AI initiation and at 9-15 months on therapy; no prior endocrine therapy and informed consent. Controls were sampled from the Mayo Mammography Health Study, a cohort of 19,924 receiving screening mammography at the Mayo Clinic, and matched to cases on age, prior PMH use, baseline body mass index (BMI) and interval between mammograms. Pre-treatment and on-study mammograms for cases (corresponding mammograms for controls) were digitized. Change in percent density was estimated on the craniocaudal view of the non-cancerous breast using two methods: a subjective assessment of change by an expert radiologist (within 5%; 5-10% increase, 10-25% increase, 25%+ increase, 5-10% decrease, 10-25% decrease and 25%+ decrease) and a quantitative assessment of absolute change using a computer-assisted thresholding program (Cumulus). Analyses compared magnitude of change in density by both the subjective and quantitative methods between cases and matched controls. Results: 574 pairs were eligible for analyses (MA27-505 cases; N063I-12 cases; MC0532-57 cases). Characteristics of the two groups are shown in the table below. Using either density estimation method, there was a greater decrease in density among women on AI therapy vs. matched controls. In 33% (95% CI: 29-37%) of pairs, there was at least a one greater category decrease for the case relative to her control by subjective estimation. In 14% (95% CI: 11-18%) of the pairs, there was at least a 5% greater decrease for the case relative to her control by quantitative estimation. Data will be available according to AI class (non-steroidal versus steroidal) in November. Conclusions: In the largest report to date to examine the influence of AI therapy on mammographic density, we provide evidence that AI is associated with decreases in density in a small subgroup of women. We are currently examining factors that influence these AI-associated decreases in density and whether these differences are unique to one class of AI. (Supported in part by NIH grants P50CA116201, U01GM61388, U10CA77202, U10CA25224) Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P2-09-03.

Abstract Background: Women with benign breast disease are at elevated breast cancer risk. In order to accurately predict a woman's individual risk of breast cancer, a breast cancer risk-prediction model is needed that incorporates significant breast cancer risk factors. This report describes two factors: tissue based assessment of lobular involution, and radiological marker- mammographic density (MD). Lobular involution, or physiologic atrophy of the breast glandular epithelium, is inversely associated with breast cancer risk. MD is a strong positive risk factor for breast cancer. With increasing age, the extent of lobular involution increases while MD decreases. However, it is unclear whether involution and MD represent independent breast cancer risk factors. We examined breast cancer risk associated with lobular involution and MD in women with benign breast disease (BBD) to determine whether these features are independently associated with breast cancer risk.Methods: Using the Mayo Clinic Surgical and Pathology Indices, 9376 women ages 18 to 85 with benign excisional breast biopsy between January 1, 1967 and December 31, 1991 were identified and formed the Mayo BBD cohort. We studied a sub-cohort of women diagnosed with BBD between 1985 and 1991 (when MD was clinically assessed and recorded) who had a mammogram within 6 months of the BBD diagnosis. Breast cancer outcomes were determined through the Mayo medical records and a study-specific questionnaire. Lobular involution extent was assessed in background tissue as 'none' (0% lobules involuted), 'partial' (1-74% lobules involuted) or 'complete' (≥75% lobules involuted). MD was classified as Wolfe's parenchymal pattern (PP) as N1/ fatty; P1; P2; and DY/ homogenously dense. Hazard ratios and confidence intervals were calculated using Cox regression analyses, adjusting for confounders: age, parity, BMI, BBD histology, menopausal status, family history, PP and involution extent.Results: A total of 2666 women in the Mayo BBD cohort, with biopsies between 1985 and 1991, had a mammogram within 6 months of the breast biopsy. The mean age at biopsy was 54.6 years. After a mean follow-up of 13.3 years, 172 (6.5%) women developed breast cancer. After adjustment for PP and other confounders, women with no or partial involution had elevated risk compared to women with complete involution (HR 2.62 [95% CI 1.39, 4.94] for no involution and 1.61 [95% CI 1.03, 2.53] for partial involution; complete involution as reference group; p for trend 0.003). Moreover, women with dense breasts were at greater risk compared to women with nondense breasts (HR 1.67 [95% CI 1.0, 2.73] for DY pattern, 1.96 [95% CI 1.2 – 3.21] for P2, 1.23 [95% CI 0.67, 2.26] for P1; N1 category as reference group; p for trend 0.02). Multivariate analyses also showed that women with the combination of no involution and dense breasts had greater risk compared to those with complete involution and nondense breasts (HR 4.08 [95% CI 1.72, 9.68]).Conclusion: Lobular involution and MD are both risk factors for breast cancer; this report is the first to demonstrate that each provides unique information about breast cancer risk. These findings emphasize the potential for inclusion of both these factors in future breast cancer risk-prediction models. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6064.

Abstract Abstract #4037 Background: Mammographic breast density is a strong and consistent risk factor for breast cancer. Women with dense tissue in over 60 to 75% of the breast are at 4 to 6 times greater risk than women with little or no density. However, the biology of breast density is not well understood and studies at the tissue level are limited. We present the first report of a tissue-based study of breast density, sampling mammographically dense and non-dense areas of the breast of healthy women with the goal of examining histologic correlates.
 Materials and Methods: Healthy women volunteers aged 40 to 85 years, with no breast symptoms, normal screening mammogram within 6 months, and no personal history of breast cancer were considered eligible. Women with breast-related symptoms, those on endocrine therapy, or with bleeding tendencies were excluded from participation. Sixty consecutive eligible women were enrolled in the study- results are based on the first 34 participants. Eligible women underwent an ultrasound-guided, core-needle breast biopsy of mammographically dense and non-dense areas of the breast, performed by a single experienced radiologist. Quantitative assessment of breast tissue from dense and non-dense areas was performed for epithelium, stroma, and fat. In addition, we assessed the difference in the extent of lobular involution (complete, partial and none) between dense and non-dense areas. We used means and SD to describe distributions in each tissue type. Signed rank test was used to assess within woman differences between dense and non-dense tissue.
 Results: The mean age of the participants was 50.1 years (range 40 to 79 years). The histological findings are outlined below.
 
 Dense tissue is comprised of increased stroma and epithelium and decreased fat, consistent with prior reports on breast density. The finding of 'no involution' was greater in dense tissue compared to non-dense tissue (24% versus 8.8%); non-dense tissue had greater proportion of complete involution compared to dense tissue (82.5% versus 35.2%).
 Discussion: This report is the first to quantify histology in tissue sampled from dense and non-dense regions of the healthy breast. We find a dramatic difference in tissue composition between dense and non-dense tissue in the breast. Future studies using this tissue to assess molecular markers will further help to characterize pathways through which density may increase breast cancer risk. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 4037.

Abstract Abstract #4033 Background: Aromatase activity within the breast is a source of estrogen that may cause breast cancer. Mammographic density (MD) is a risk factor for breast cancer whose biologic basis is unknown. Our study compared aromatase expression in tissue from dense and non-dense areas of the breasts of healthy volunteers.
 Methods: Participants were 40+ yrs, had a screening mammogram with visible MD, no history of cancer and were not on endocrine therapy. Ultrasound-guided core biopsies were done within 6 months of mammography to obtain three paired cores from mammographically dense and non-dense regions of the breast. Immunostaining for aromatase expression employed the streptavidin-biotin amplification method using the recently developed 677 mouse monoclonal antibody. Immunoreactivity (IR) was scored in terms of proportion of cells staining positive for aromatase (PPC) (0=<1%, 1=1-25%, 2=26-50%, 3=51+% (and 4=75%+ for adipocytes)) and relative immunointensity (0=none, 1=weak, 2=moderate, 3=intense) for each cell type (stroma, normal ductal epithelium, adipocytes). A composite score weighting the PPC by their relative intensity (range 0-9; 0-12 for adipocytes) was also calculated. The sum of the composite score across the three cell types provided a global assessment of aromatase IR. Repeated measures analyses evaluated differences in aromatase IR for dense compared to non-dense tissue within and across cell types. Parameter estimates (β) indicated the average difference between dense and non-dense IR.
 Results: 18 (37%) of the 49 participants were premenopausal (median age 46 yrs). Summing across cell types, the global composite score showed increased aromatase IR on sections sampled from dense vs. non-dense regions (β=5.3,p<0.001). This global difference reflected increased aromatase IR in the stroma and normal ductal epithelium from dense sections (vs. non-dense). For 42 women with >1% stromal cells on each section, there was evidence for increased IR on dense sections as indicated by the greater PPCs (β=0.9), relative intensity (β=0.7) and composite score (β=2.7)(p's<0.001). Similarly, for 20 women with >1% normal ductal epithelium in both dense and non-dense sections, there was a greater composite score (β=1.4,p=0.004) for cells on dense sections although differences for PPC (β=0.3,p=0.11) and relative intensity (β=0.3,p=0.09) did not reach statistical significance. No differences were seen in IR for adipocytes from the two density regions (46 women). Findings were unchanged with adjustment for covariates, including proportions of each cell type per section.
 Conclusions: There is strong evidence for increased aromatase expression in the stromal and normal ductal epithelium of dense vs. non-dense tissue. These results support ongoing research into mammographic density as a biomarker of effect of aromatase inhibitors. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 4033.