Buzdar, A.

Abstract Support: Alliance U10CA180821; Alliance Statistical Center grant U10CA180882; ACOSOG grant U10CA76001 HER2 gene amplification and its corresponding overexpression are present in approximately 12% of invasive breast cancers. While HER2-targeted agents (e.g. trastuzumab, pertuzumab, and lapatinib) are effective treatments, resistance remains a major cause of death from HER2-positive breast cancer. Mechanisms of resistance are poorly understood. Without a molecular understanding of these mechanisms, therapeutic advances will be delayed. We have generated molecular profiles of primary HER2-positive breast cancers treated on a neoadjuvant clinical trial, and compared features associated with response to treatment. The American College of Surgeons Oncology Group (ACOSOG) Z1041 trial in HER2-positive breast cancer was designed to compare the pathologic complete response (pCR) rate of a regimen of paclitaxel and trastuzumab, followed by trastuzumab administered with fluorouracil, epirubicin, and cyclophosphamide (FEC-75) to a regimen of FEC-75 alone followed by paclitaxel and trastuzumab. The trial identified no difference in pCR rates between the regimens (Buzdar et al., The Lancet Oncology 2013). In supplement to the tissues obtained from 37 of the patients enrolled in the Z1041 trial, an additional 11 cases were obtained from a single institution study (201101961) of patients treated with neoadjuvant trastuzumab that had pre-treatment core biopsies suitable for genomic studies. We have extracted genomic DNA from both pretreatment tumor biopsies and blood samples of these 48 patients and performed whole genome (WGS) and exome sequencing. Coincident with these efforts, we have extracted high quality RNA from 42 of the 48 biopsies, and have processed RNA-seq profiles of the tumors. Among patients in this cohort, 24 (50%) achieved a pCR. Because no difference was observed between arms of the Z1041 trial, patients with or without a pCR were directly compared without adjusting for treatment regimen. On average, each tumor and normal sample pair were sequenced to a depth of 49.4x and 32.5x by WGS respectively. In total, 15,027 candidate somatic variants were identified in known genes, including 11,606 missense, 860 nonsense, and 418 frameshift insertions or deletions. Preliminary results identified mutations in HER2 that were associated with the failure to achieve pCR in several cases. Furthermore, tumors assigned to the HER2-enriched subtype by RNA-seq analysis were more likely to achieve a pCR (19 compared to 8) than tumors with genomic features indicative of either the luminal or basal-like subtypes (3 compared to 12); a significant difference in the proportion of cases that achieve pCR (Fisher's exact test p-value = 0.0032). The identification of these features suggests that it may be possible to predict, at the time of diagnosis, those patients who will not respond to the current standard of care for HER2-positive breast cancer. Citation Format: Lesurf R, Griffith O, Griffith M, Watson MA, Hoog J, Ellis MJ, Ota D, Suman VJ, Meric-Bernstam F, Leitch AM, Boughey JC, Unzeitig G, Buzdar AU, Hunt KK, Mardis ER. The genomics of response to neoadjuvant trastuzumab and chemotherapy in HER2-positive breast cancer – Results from the ACOSOG Z1041 (Alliance) trial. [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 PD6-02.

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.