Melisko, ME

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: HR+ breast cancer in younger vs older patients may have distinct biological features. The Breast Cancer Index (BCI) is a gene expression-based assay that includes two component biomarkers: the HoxB13/IL17BR (H/I ratio), an endocrine response biomarker; and the molecular grade index (MGI), a set of proliferation-related genes. The objective of this study was to assess age-related associations with endocrine sensitivity (H/I), proliferative status (MGI), and quantitative expression of ER and PR. Methods: Data were extracted from the BCI Clinical Database for Correlative Studies, an IRB-approved de-identified database containing clinicopathologic and molecular variables from clinical cases submitted for BCI testing. Molecular results from H/I, MGI, and quantitative (qPCR–based) ER and PR were analyzed across age groups. Chi-squared tests and ANOVA were used to compare the results between age groups (<40y, 40-49y, 50-59y, 60-69y, and ≥70y). Results: Analyses included 19,126 patients (median age at diagnosis 58.6y; 4.5% <40y, 20.6% 40-49y, 28.9% 50-59y, 32.5% 60-69y, and 13.6% ≥70y). Proliferation status (MGI) was significantly higher in patients <40y and 40-49y compared to older groups (P<.0001).H/I analysis indicated a similar distribution of high versus low endocrine responsiveness across all groups (P=.94), except the 40-49y group, in which fewer patients had high H/I (44.2% in <40y, 39.4% in 40-49y, 43.7% in 50-59y, 43.7% in 60-69y, and 43.1% in ≥70y; P=.0001). Median qER increased with age (P<0.0001), while qPR was similar across all age groups except for the 40-49y group (P=.57), in which expression was higher (P<.0001). Conclusion: Results from >19,000 patients with early-stage HR+ breast cancer and BCI testing showed a broad distribution in all variables. Tumors from the youngest patients (<40y) had the highest expression of proliferative genes and the lowest quantitative ER expression. However, endocrine response, according to the H/I biomarker, does not appear to be strongly linked to age. Citation Format: Melisko M, Chien AJ, Poage GM, Salganik M, Schnabel CA, Ruddy KJ, Blackwell K. Gene expression patterns in younger versus older HR+ breast cancer patients: An age-related analysis of HoxB13/IL17BR (H/I), proliferation status, and quantitative hormone receptor expression [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 P6-09-03.

Abstract Background: 1/3 of women with metastatic HER2+ breast cancer will develop central nervous system (CNS) metastases yet evidence-based treatments for women with progressive CNS disease are limited. Neratinib is an irreversible inhibitor of erbB1, HER2, and erbB4 which has promising activity in HER2+ breast cancer. Preclinical evidence suggests it may cross the blood brain barrier. Trial Design: This is a multicenter, phase II, open-label study of neratinib for patients with HER2+ breast cancer and brain metastases. Neratinib is administered at 240 mg orally daily during a 28 day cycle. Two cohorts will be enrolled: Cohort 1 will enroll 40 patients with progressive CNS disease; cohort 2 will enroll ≤5 patients who are candidates for surgical excision of intracranial disease. Surgical candidates receive neratinib 7–21 days preoperatively and resume postoperatively. All patients are re-staged every 2 cycles. Those who develop non-CNS progression have an option to extend therapy with trastuzumab+neratinib. Circulating tumor cells (CTC) are collected at baseline and progression; neurocognitive testing, HADS and EORTC QLQ30/BN20 measures are administered at baseline, cycle 2, cycle 3, and progression (cohort 1). Intracranial tumor, cerebrospinal fluid (CSF), and plasma are collected at surgery (cohort 2). Specific Aims: The primary endpoint is CNS objective response rate (ORR) by composite criteria. Additional endpoints include: non-CNS ORR, progression-free survival, overall survival (OS), site of 1st progression, and toxicity. Correlative and exploratory endpoints include association of CTC count and OS and longitudinal neurocognitive function and quality of life. In an exploratory analysis (cohort 2), we will quantify neratinib concentrations in CSF, intracranial tissue, and plasma and examine associations with response. Eligibility: Patients must have confirmed HER2+ metastatic disease with ≥1 parenchymal brain lesion measuring ≥10 mm that is new or progressed after completing ≥1 line of standard CNS-directed treatment (cohort 1) or CNS disease that is amenable for surgery, including those without prior CNS treatments (cohort 2). Additional eligibility criteria (cohorts 1,2) include: adequate performance status and end organ/marrow function, and ejection fraction ≥50%. Any number of prior lines of therapy is allowed, including prior lapatinib. Statistical Methods: Cohort 1 has a 2-stage design with up to 40 patients. CNS ORR is defined as ≥50% reduction in sum volume of CNS target lesions, without evidence of new lesions, progression of non-target CNS lesions, non-CNS disease progression, worsening neurological symptoms, or increase in corticosteroids. CNS lesion measurements are performed centrally by the Harvard Tumor Imaging Metrics Core. If 1/18 patients have a CNS response in the 1st stage, another 22 patients will enroll. With this design, if ≥5 of 40 patients achieve a CNS response, the drug will be deemed worthy of future study. This 2-stage design has 92% power to distinguish between a true CNS ORR of 20% and a null of 6% (one-sided type I error rate=9%). Accrual: Accrual has begun. Target=45 (cohort 1=40, cohort 2=5) Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr OT1-1-11.