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Chien, AJ

Mayo Clinic

Translational Genomics Research Institute

Citations 8

Abstract PD2-01: Personalized serial circulating tumor DNA (ctDNA) analysis in high-risk early stage breast cancer patients to monitor and predict response to neoadjuvant therapy and outcome in the I-SPY 2 TRIAL
Magbanua, MJM, Hirst, GL, Wolf, DM, Ma, AA, Bergin, Emily, Venters, Sara J., Salari, Raheleh, Tin, T., Sawyer, Sarah , Louie, MC, Zimmermann, B, Lin, C-HJ, Liang, WS, Cuyugan, Lori, Chien, AJ, Forero, Andres , Liu, M, Delson, AL, Asare, Smita , Esserman, L., Veer, Laura van’t, Hirst, Gillian L. , Hirst, Gillian L , Swigart, Lamorna Brown , Yau, Christina , Sethi, Himanshu , Wu, Hue-Tsi , Keats, Jonathan J. , Enriquez, D, Tripathy, Debu , DeMichele, Angela

Cancer Research | May 11, 2019 | Volume: 79 | Issue: 4_Supplement | Pages: PD2-01-PD2-01

10.1158/1538-7445.sabcs18-pd2-01 Get It

Abstract ctDNA analysis offers a non-invasive approach for monitoring response and resistance to treatment. Serial ctDNA testing during neoadjuvant therapy (NAT) may provide early indicators of emerging resistance and disease progression. In this study, we analyzed ctDNA from high-risk early breast cancer patients who received NAT and definitive surgery in the I-SPY 2 TRIAL (NCT01042379). We hypothesize that (1) assessment of ctDNA levels early in treatment will improve the performance of molecular and imaging-based predictors of pathologic complete response (pCR) to NAT; and (2) levels of ctDNA after NAT are associated with residual cancer burden and recurrence [distant recurrence free survival (DRFS)]. Methods: ctDNA analysis was performed in 84 high-risk stage II and III breast cancer patients randomized to neoadjuvant investigational agent (n=52), AKT inhibitor MK-2206 (M) in combination with paclitaxel (T) followed by doxorubicin and cyclophosphamide (AC) (M+T->AC), or standard-of-care (T->AC) (n=32). HER2+ patients also received trastuzumab (H). Serial plasma was collected before NAT (T0), early treatment (3 weeks, T1), between regimens (12 weeks, T2), and after NAT prior to surgery (T3). Mutational profiles derived from pretreatment tumor biopsy and normal matched DNA whole exome sequencing were used to design personalized assays targeting 16 patient-specific somatic variants to detect ctDNA in serial plasma. Results: Of the 84 patients in this study, 43% were HR-/HER2- (TNBC), 35% HR+/HER2-, and 23% HER2+. In total, 74% (61 of 83), 35% (28 of 79), 14% (9 of 65), and 8% (5 of 61) were positive for ctDNA at timepoints T0, T1, T2, and T3, respectively. At T0, ctDNA positivity and levels (average number of mutant molecules detected per mL) were significantly associated with increased tumor burden (by clinical and MRI examination), more aggressive tumor biology (as reflected in higher Mammaprint scores and grade) and subtype (HER2+ and TNBC). Twenty-seven percent (27%) of the 84 patients achieved a pCR and all patients who were ctDNA-positive at T3 (n=5) did not achieve a pCR. Currently, data are being collected to: (1) assess the relationship of ctDNA and MRI imaging in predicting tumor response to therapy; (2) examine the relationship of ctDNA levels before and after NAT with 3-year DRFS and event-free survival (EFS). The results of these analyses will be presented at the SABCS 2018 meeting. Conclusions: Our study provides a platform to evaluate the clinical significance of ctDNA for serial monitoring of response to NAT. Accurate and early response prediction by highly sensitive ctDNA analysis can facilitate a timely and judicious change in treatment to improve patients' chances of achieving a pCR. Finally, personalized ctDNA testing may complement imaging and pathologic evaluation of tumor response to fine-tune pCR as a surrogate endpoint for improved DRFS and EFS. Citation Format: Magbanua MJM, Brown-Swigart L, Hirst GL, Yau C, Wolf D, Ma AA, Bergin E, Venters S, Sethi H, Wu H-T, Salari R, Tin T, Sawyer S, Louie M, Zimmermann B, Lin C-HJ, Keats J, Liang WS, Cuyugan L, Enriquez D, Tripathy D, Chien AJ, Forero A, DeMichele A, Liu M, Delson AL, Asare S, Esserman L, van't Veer L, I-SPY 2 Consortium. Personalized serial circulating tumor DNA (ctDNA) analysis in high-risk early stage breast cancer patients to monitor and predict response to neoadjuvant therapy and outcome in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD2-01.
Abstract P2-14-01: The impact of local therapy on locoregional recurrence in women with high risk breast cancer in the neoadjuvant I-SPY2 TRIAL
Suleiman, Linda I. , Price, ER, Singhrao, Ruby , Albain, KS, Chien, AJ, Forero‐Torres, Andres , Wallace, AM, Ellis, ED, Elias, AD, Lang, JE, Lu, Jinghui , Han, HS, Clark, AS, Korde, LA, Nanda, Rita , Northfelt, DW, Khan, QJ, Viscusi, RK, Euhus, DM, Edmiston, KK, Chui, SY, Kemmer, KA, Wood, WC, Liu, MC, Olopade, OI, Leyland-Jones, B, Moulder, SL, Rugo, HS, Schwab, Richard B. , Lo, Simon S. , Beckwith, Heather , Berry, DA, Asare, SM, Esserman, LJ, Boughey, JC , Mukhtar, RA, Khan, Qamar J. , Silverstein, J, Suleiman, L, Yau, Christina , Price, Erin, Yee, Douglas , DeMichele, Angela , Isaacs, Claudine , Pusztai, Lajos , Park, JW, Tripathy, Debu , Helsten, Teresa L.

Cancer Research | May 11, 2019 | Volume: 79 | Issue: 4_Supplement | Pages: P2-14-01-P2-14-01

10.1158/1538-7445.sabcs18-p2-14-01 Get It

Abstract Background: In women with breast cancer receiving neoadjuvant chemotherapy, residual cancer burden (RCB) predicts distant recurrence and survival. In those with high risk tumors, locoregional recurrence (LRR) remains a concern, and has been associated with type of local therapy received. We evaluated the impact of local therapy on LRR in the ISPY-2 TRIAL. Methods: Data were analyzed in Stata 14.2, using Chi2 test, log rank test, and a Cox proportional hazards model. RCB was considered a categorical variable (0/1 versus 2/3), as described in prior publications. Breast surgery categories were lumpectomy +/- radiotherapy, or mastectomy +/- radiotherapy. Axillary surgery was defined as sentinel lymph node (SLN) surgery (≤6 nodes removed) or axillary dissection (>6 nodes). Results: Follow up data from the I-SPY2 TRIAL were available for 630 patients (median follow up 2.76 yrs, range 0.4-7.2). Type of local therapy was significantly associated with clinical stage at presentation, with stage III patients most frequently undergoing mastectomy + radiation (p<0.001). Women with higher RCB were more likely to undergo mastectomy than those with lower RCB (61.3% vs 48.8% mastectomy rate, p=0.002), and more likely to receive adjuvant radiotherapy (62.0% vs 53.9%, p=0.048). There was no association between clinical stage, type of surgery, or radiotherapy and LRR (Table). Higher RCB was significantly associated with LRR, with 3 year locoregional recurrence free rate of 95.1% in RCB 0/1 versus 89.9% in RCB 2/3 (p=0.003). In a Cox model adjusting for clinical stage, tumor subtype, surgical therapy, RCB status, nodal radiation, and age, significant predictors for LRR were tumor subtype and RCB status. Hazard ratio (HR) for LRR in those with RCB 0/1 was 0.39 compared to those with RCB 2/3 (95% CI 0.17-0.87, p=0.021). There was no difference in LRR between breast conservation and mastectomy; within the breast conservation group, those who had lumpectomy alone had higher hazard of LRR compared to those having lumpectomy + radiation (HR 3.1, 95% CI 1.1-9.2, p=0.043). Conclusions: Extent of surgical therapy was not associated with local tumor control, regardless of advanced tumor stage at presentation. Rather, tumor biology and response to therapy were the best predictors of LRR. These data highlight the opportunity to minimize the morbidity of extensive surgical therapy for patients with excellent response to systemic therapy. LRR rates by clinical features and treatment status FrequencyLRR RateP valueClinical Stage 0.5I240 (47.5%)5.8% II185 (36.6%)8.7% III80 (15.8%)6.3% Tumor Subtype 0.014ER+PR+Her2-161 (26.4%)3.1% ER+PR-Her2-56 (9.2%)3.6% Her2+176 (28.9%)6.3% Triple negative216 (35.5%)11.1% Local therapy 0.169Lumpectomy85 (13.5%)11.8% Lumpectomy with radiation198 (31.4%)5.6% Mastectomy173 (27.5%)5.2% Mastectomy with radiation174 (27.6%)8.6% Axillary surgery 0.23None5 (0.8%)20% SLN329 (52.2%)5.8% ALND296 (47%)8.5% Axillary radiation 0.535Yes42 (6.7%)9.5% No588 (93.3%)7.0% Axillary management 0.2No surgery or radiation5 (0.8%)20.0% SLN312 (50%)5.3% SLN+Axillary radiation17 (2.7%)8.3% ALND271 (43%)10.3% ALND+Axillary radiation25 (4%)5.4% RCB 0.0020/1293 (50.1%)3.8% 2/3292 (49.9%)10.3% Citation Format: Silverstein J, Suleiman L, Yau C, Price ER, Singhrao R, Yee D, DeMichele A, Isaacs C, Albain KS, Chien AJ, Forero-Torres A, Wallace AM, Pusztai L, 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, Leyland-Jones B, Tripathy D, Moulder SL, Rugo HS, Schwab R, Lo S, Helsten T, Beckwith H, I-SPY 2 TRIAL Consortium, Berry DA, Asare SM, Esserman LJ, Boughey JC, Mukhtar RA. The impact of local therapy on locoregional recurrence in women with high risk breast cancer in the neoadjuvant 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 P2-14-01.
Abstract PD7-06: Molecular subtypes of invasive lobular breast cancer in the I-SPY2 TRIAL
Zhu, Zhenyu , Chien, AJ, Haddad, TC, Esserman, LJ, Veer, Laura van’t, Mukhtar, RA, Yau, C

Cancer Research | May 11, 2019 | Volume: 79 | Issue: 4_Supplement | Pages: PD7-06-PD7-06

10.1158/1538-7445.sabcs18-pd7-06 Get It

Abstract Background: Invasive lobular carcinoma (ILC) of the breast has distinct histological and molecular variations compared to invasive ductal carcinoma (IDC), including absence of the adhesion protein E-cadherin. Recently, molecular subtypes within ILC have been described, with an analysis from The Cancer Genome Atlas (Ciriello et al) identifying three distinct groups within ILC based on gene expression—reactive-like, immune-related, and proliferative. In this study, we applied this 60-gene classifier to a locally advanced cohort of ILC and mixed ILC/IDC cases from patients screening for the I-SPY 2 neoadjuvant chemotherapy trial. Methods: The I-SPY 2 TRIAL is open to women with more locally advanced, clinically/molecularly (as assessed by MammaPrint) high risk breast cancer. HR+HER2- MammaPrint Low risk patients ineligible for I-SPY 2 randomization are invited to join a MP Low risk registry. 131 ILC and mixed ILC/IDC tumors from these cohorts (I-SPY 2: n=80; low risk registry: n=51) with pre-treatment Agilent microarrays were available for analysis. We used the Classification to Nearest Centroid technique to assign TCGA subtype to our cohort. We assessed association between TCGA subtype, clinical covariates and response to therapy using a chi-square test. We also evaluated the Euclidean distance between each sample and the three subtype centroids. In an exploratory analysis, we used consensus clustering based on the 1000 most varying genes within the HR+HER2- I-SPY ILC cases to generate new unsupervised groupings, and assessed the concordance with the TCGA reactive-like, immune-related and proliferative subtype assignments. Results: Of the 131 patients included, most (79%) were HR+HER2-, 11% were HR+HER2+, 2% were HR-HER2+ and 8% were HR-HER2- for a total of 10% HR-. 66 were pure ILC, while 65 were mixed ILC/IDC. Upon applying the TCGA 60-gene classifier, the distribution of ILC subtypes was as follows: 33 (25%) were classified as reactive-like, 50 (38%) were immune-related, and 48 (37%) were proliferative. 64% of triple negative cases were reactive-like; while the HR+HER2- and HER2+ cases were more likely to be in the proliferative or immune-related subtype (p=0.037). Among the 80 I-SPY 2 cases, the overall pathologic complete response rate was low (16%) but equivalent to the overall HR+HER2- I-SPY2 population (16%). This did not differ across the groups defined by the TCGA ILC subtypes (p=0.79). Interestingly, a subset of cases assigned as reactive-like and immune-related were of similar distance to the proliferative subtype centroid as patients assigned to the proliferative subtype. When we used consensus clustering to identify new subsets within our locally advanced ILC cohort, our unsupervised groupings had only 32% concordance with the TCGA ILC subtype assignments. Conclusion: The low concordance between our consensus cluster groupings and the TCGA subtype groupings may reflect underlying differences within a locally advanced cohort of ILC cases, like I-SPY, that may not be captured in the 60-gene classifier developed from the overall lower stage TCGA cohort. These findings suggest that considerable molecular heterogeneity exists in lobular cancers, which merits further investigation. Citation Format: Zhu Z, Yau C, Chien AJ, Haddad T, Esserman LJ, van't Veer L, Mukhtar RA, I-SPY2 Consortium. Molecular subtypes of invasive lobular breast cancer 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 PD7-06.
Abstract P2-07-03: Refining neoadjuvant predictors of three year distant metastasis free survival: Integrating volume change as measured by MRI with residual cancer burden
Hylton, NM, Symmans, WF, Li, W, Albain, KS, Krings, Gregor , Wei, Shuyi , Harada, Shigeyoshi , Datnow, Brian, Fadare, Oluwole , Klein, Matthew Nicholas, Chen, Boyi , Adamson, Kathi, Sams, Sharon B. , Mhawech‐Fauceglia, Paulette , Magliocco, Anthony M., Feldman, Merrill I., Rendi, Mara H. , Sattar, H, Zeck, Jay , Ocal, IT , Tawfik, OW, LeBeau, Lauren, Sahoo, Sunati , Vinh, Tuyethoa N., Chien, AJ, Ferero-Torres, A, Stringer-Reasor, Erica , Wallace, AM, Boughey, JC , Ellis, ED, Elias, AD, Lang, JE , Han, HS, Clark, AS, Korde, LA, Nanda, Rita , Northfelt, DW, Khan, QJ, Viscusi, RK, Euhus, DM, Edmiston, KK, Chui, SY, Kemmer, Kathleen, Wood, WC, Liu, MC, Olopade, OI, Tripathy, Debashish, Moulder, SL, Rugo, HS, Schwab, Richard J. , Lo, Su-Shun, Beckwith, Heather , Haugen, PK, Veer, LJ van't, Perlmutter, Jane , Melisko, ME, Wilson, Ann, Peterson, Gertrude, Asare, AL, Buxton, MB, Clennell, JL, Hirst, GL, Singhrao, Ruby , Steeg, Katherine, Sanil, Ashish, Sm, Berry, Abe, Hajime , Wolverton, Dulcy , Crane, EP, Ward, Kevin R. , Nelson, M.K., Niell, BL, Brandt, KR, Bang, DH, Eghtedari, Mohammad , Sheth, PA, Bernreuter, W K, Umphrey, H, Rosen, M., Yang, Wei , Joe, Bonnie N. , Asare, SM, Berry, DA, Esserman, L., Khan, Qamar J. , Hirst, Gillian L. , Hirst, Gillian L , Yau, Christina , Hatzis, Christos , Isaacs, Claudine , Chen, Yung‐Yi , Krings, G, Harada, S, Pambuccian, Stefan E. , Feldman, M, Yang, S, Adams, A, Lu, J, Park, JW, Schwab, R, Lo, S, Helsten, Teresa L. , Peterson, G, Paoloni, M, Matthews, JB, Berry, SM, Oh, K, Ojeda-Fournier, Haydee , Dogan, Basak E , Yee, Douglas , Pusztai, Lajos , DeMichele, Angela

Cancer Research | May 11, 2019 | Volume: 79 | Issue: 4_Supplement | Pages: P2-07-03-P2-07-03

10.1158/1538-7445.sabcs18-p2-07-03 Get It

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 P6-09-03: 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
Melisko, ME, Chien, AJ, Poage, GM, Salganik, Max, Schnabel, CA, Ruddy, KJ, Blackwell, Kimberly

Cancer Research | February 15, 2018 | Volume: 78 | Issue: 4_Supplement | Pages: P6-09-03-P6-09-03

10.1158/1538-7445.sabcs17-p6-09-03 Get It

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 GS3-08: Pathological complete response predicts event-free and distant disease-free survival in the I-SPY2 TRIAL
DeMichele, A., Symmans, F., Albain, KS, Hylton, NM, Forero‐Torres, Andres , Veer, LJ van't, Perlmutter, Jane , Rugo, HS, Melisko, Michelle , Krings, Gregor , Datnow, Brian, Hasteh, Farnaz, Tipps, Ann , Weidner, Noel, Tickman, Ronald, Thornton, Steven , Amin, K M, Chen, B, Keeney, Gary L., Ocal, Tolgay I., Klipfel, Nancy, Sattar, Husain, Mueller, Jeffery, Gwin, K, Zeck, Jay , Duan, Xiuzhen, Erşahin, Çağatay, Gamez, R, Troxell, Megan L. , Mansoor, Adnan , LeBeau, Lauren, Sams, Sharon B. , Wisell, J. , Wei, Shi , Vinh, Tuyethoa N., Stamatakos, MD, Tawfik, Ossama , Rendi, Mara H. , Minton, S., Magliocco, Anthony M., Sahoo, Sunati , Fang, Y, Singhrao, Ruby , Asare, SM, Wallace, AM, Chien, AJ, Ellis, ED, Han, HS, Clark, AS, Boughey, JC , Elias, AD, Nanda, Rita , Korde, Larissa A. , Northfelt, Donald W. , Edmiston, KK, Viscusi, Rebecca K., Haley, Barbara , Kemmer, Kathleen, Zelnak, Amelia, Berry, DA, Esserman, L., Yee, Douglas , Isaacs, Claudine , Yau, Christina , Chen, Yung‐Yi , Balassanian, Ronald , Zhang, Hongtao , Thornton, S, Ritter, Jacob , Klein, Martin , Feldman, Michael D. , Baker, Gabrielle M. , Kallakury, Bhaskar , Harada, Shuko , Fan, F, Adams, Amy Louise , Fang, Y, Hirst, Gillian L. , Murthy, Ravi , Lang, Julie E. , Khan, Qamar J.

Cancer Research | February 15, 2018 | Volume: 78 | Issue: 4_Supplement | Pages: GS3-08-GS3-08

10.1158/1538-7445.sabcs17-gs3-08 Get It

Abstract Background: Pathological complete response (pCR) is accepted by FDA as a surrogate endpoint for accelerated approval of targeted agents in combination with chemotherapy based on better long-term outcomes compared to residual disease (Cortazar 2014). Methods: The multi-center, adaptively-randomized I-SPY2 platform trial uses pCR as the primary endpoint to identify investigational agents that will improve outcomes in women with stage 2/3 breast cancer with high risk of early recurrence, across all signatures, based on hormone receptor (HR), HER2, and 70-gene (MammaPrint) status. For patients with HR+ HER2- tumors, only 70-gene (Mammaprint) high-risk patients are enrolled. To date, 1200+ patients have been randomized to one of 14 arms: control (paclitaxel followed by AC); veliparib/carboplatin; neratinib; MK2206; trebananib; trastuzumab/pertuzumab; ado-trastuzumab emtansine/pertuzumab; pembrolizumabx4; ganitumab/metformin; ganetespib; PLX-3397. 7 agents graduated in at least one signature (> 85% probability of success in a 300-patient phase III confirmatory trial); 2 did not graduate; 1 stopped for toxicity, and 3 are enrolling (patritumab/trastuzumab, talazoparib/irinotecan, pembrolizumabx8). Local pathologists were centrally trained using the Residual Cancer Burden (RCB) assessment to ensure uniform evaluation and response classification; RCB 0 = pCR. Results: We evaluated the relationship between pCR and event free (EFS) and distant disease free survival (DDFS) in the first 522 pts (median follow-up:2.5 years). 180 pts achieved pCR (36%) while 338 did not (RCB=1-3). There were 82 EFS and 65 DRFS events. Over the entire group (including all arms), pCR was highly associated with 3-year EFS (p<0.001 for both). Pts achieving pCR had a 3% recurrence risk (RR) at 3 years; those with non-pCR had 24% RR over this time period. For distant recurrence, the 3-year RR with pCR was 2%, compared to 20% in pts with non-pCR. As expected, pCR rates varied by breast cancer subtype (HR+/HER2: 18% (35/196), HR+/HER2+: 40% (33/82), HR-/HER2+:68% (34/50), HR-/HER2-:41% (76/188)). The relationship between pCR and EFS was significant and clinically impactful within each subtype. 3-year survival (pCR group)Hazard Ratio OverallOverallHR+/HER2-HER2+TNBCEFS97%0.08 (0.03-0.23)0.14 (0.02-1.04)0 (NA)0.11 (0.03-0.37)DDFS98%0.08 (0.03-0.26)0.17 (0.01-1.23)0 (NA)0.09 (0.02-0.40) Conclusions: The first long-term efficacy results from the I-SPY2 TRIAL demonstrate that achieving pCR is a very strong surrogate endpoint for improved EFS and DDFS in a high-risk population, across all treatment arms, regardless of subtype. I-SPY2 shows substantially lower estimated EFS hazards for patients achieving pCR, compared to the 5 yr EFS hazard ratio for pCR vs not in Cortazar (hazard ratio 0.49), demonstrating important differences between a metaanalysis compared to a platform trial with uniform high-risk eligibility, standardized pathology assessment, and multiple targeted therapies. Our data support the use of pCR as a primary endpoint for accelerated approval of new drugs if EFS is evaluated in the same population. Based on these findings, the I-SPY2 TRIAL will test whether therapy can be deescalated or escalated for individual patients with the goal of achieving pCR for all. Citation Format: Yee D, DeMichele A, Isaacs C, Symmans F, Yau C, Albain KS, Hylton NM, Forero-Torres A, van't Veer LJ, Perlmutter J, Rugo HS, Melisko M, Chen Y-Y, Balassanian R, Krings G, Datnow B, Hasteh F, Tipps A, Weidner N, Zhang H, Tickman R, Thornton S, Ritter J, Amin K, Klein M, Chen B, Keeney G, Ocal T, Feldman M, Klipfel N, Sattar H, Mueller J, Gwin K, Baker G, Kallakury B, Zeck J, Duan X, Ersahin C, Gamez R, Troxell M, Mansoor A, Grasso LeBeau L, Sams S, Wisell J, Wei S, Harada S, Vinh T, Stamatakos MD, Tawfik O, Fan F, Adams A, Rendi M, Minton S, Magliocco A, Sahoo S, Fang Y, Hirst G, Singhrao R, Asare SM, Wallace AM, Chien AJ, Ellis ED, Han HS, Clark AS, Boughey JC, Elias AD, Nanda R, Korde L, Murthy R, Lang J, Northfelt D, Khan Q, Edmiston KK, Viscusi R, Haley B, Kemmer K, Zelnak A, Berry DA, Esserman LJ. Pathological complete response predicts event-free and distant disease-free survival in the I-SPY2 TRIAL [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 GS3-08.
Abstract P6-11-04: The evaluation of ganitumab/metformin plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 trial
Veer, Laura van’t, Sanil, Ashish, Yau, C, Forero, Andres , Chien, AJ, Wallace, AM, Moulder, SL, Albain, KS, Kaplan, HG, Elias, AD, Haley, BB, Boughey, JC , Kemmer, KA, Korde, LA, Minton, S., Lang, J. , Buxton, MB, Hylton, NM, Symmans, WF, Lyandres, Julia, Perlmutter, Jane , Esserman, LJ, Berry, DA, Yee, Douglas , Paoloni, Marco , Isaacs, Claudine , Nanda, R, DeMichele, Angela , Hogarth, Michael A. , Berry, Donald A.

Cancer Research | March 1, 2017 | Volume: 77 | Issue: 4_Supplement | Pages: P6-11-04-P6-11-04

10.1158/1538-7445.sabcs16-p6-11-04 Get It

Abstract Background: I-SPY 2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes to evaluate novel agents when added to standard neoadjuvant therapy for women with high-risk stage II/III breast cancer - investigational agent(I) +paclitaxel(T) qwk, doxorubicin & cyclophosphamide(AC) q2-3 wk x 4 vs. T/AC (control arm). The primary endpoint is pathologic complete response (pCR) at surgery. The goal is to identify/graduate regimens that have ≥85% Bayesian predictive probability of success (statistical significance) in a 300-patient phase 3 neoadjuvant trial defined by hormone-receptor (HR) & HER2 status & MammaPrint (MP). Regimens may also leave the trial for futility (< 10% probability of success) or following accrual of maximum sample size (10%< probability of success <85%). We report the results for experimental arm Ganitumab, a type I insulin-like growth factor receptor (IGF1R) inhibitor. IGF1R inhibitors are known to induce insulin resistance and all patients assigned to Ganitumab received metformin. Methods: Women with tumors ≥2.5cm were eligible for screening. MP low/HR+ and HER2+ tumors were ineligible for randomization. Hemoglobin A1C≥ 8.0% were ineligible. MRI scans (baseline, 3 cycles after start of therapy, at completion of weekly T and prior to surgery) were used in a longitudinal statistical model to improve the efficiency of adaptive randomization. Ganitumab was given at 12mg/kg q2 weeks and metformin at 850mg PO BID, while receiving ganitumab. Analysis was intention to treat with patients who switched to non-protocol therapy counted as non-pCRs. Ganitumab/metformin was open only to HER2- patients, and eligible for graduation in 3 of 10 pre-defined signatures: HER2-, HR+HER2- and HR-HER2-. Results: Ganitumab/metformin did not meet the criteria for graduation in the 3 signatures tested. When the maximum sample size was reached, accrual to this arm stopped. Ganitumab/metformin was assigned to 106 patients; there were 128 controls. We report probabilities of superiority for Ganitumab/metformin over control and Bayesian predictive probabilities of success in a neoadjuvant phase 3 trial equally randomized between Ganitumab/metformin and control, for each of the 3 biomarker signatures, using the final pathological response data from all patients. Safety data will be presented. SignatureEstimated pCR Rate (95% probability interval)Probability Ganitumab/ Metformin Is Superior to ControlPredictive Probability of Success in Phase 3 Ganitumab/ Metformin N = 106Control N = 128 All HER2-22% (13%-31%)16% (10%-23%)89%33%HR+/HER2-14% (4%-24%)12% (4%-19%)66%21%HR-/HER2-32% (17%-46%)21% (11%-32%)91%51% Conclusion: The I-SPY 2 adaptive randomization study estimates the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial. The value of I-SPY 2 is to give insight about the performance of an investigational agent's likelihood of achieving pCR. For Ganitumab/metformin, no subtype came close to the efficacy threshold of 85% likelihood of success in phase 3, and this regimen does not appear to impact upfront reduction of tumor burden. Our data do not support its continued development for the neoadjuvant treatment of breast cancer. Citation Format: Yee D, Paoloni M, van't Veer L, Sanil A, Yau C, Forero A, Chien AJ, Wallace AM, Moulder S, Albain KS, Kaplan HG, Elias AD, Haley BB, Boughey JC, Kemmer KA, Korde LA, Isaacs C, Minton S, Nanda R, DeMichele A, Lang JE, Buxton MB, Hylton NM, Symmans WF, Lyandres J, Hogarth M, Perlmutter J, Esserman LJ, Berry DA. The evaluation of ganitumab/metformin plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 trial [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 P6-11-04.
Abstract P6-11-02: Efficacy of Hsp90 inhibitor ganetespib plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 trial
Forero, Andres , Buxton, MB, Symmans, WF, Chien, AJ, Boughey, JC , Elias, AD, Moulder, SL, Minton, S., Kaplan, HG, Albain, KS, Wallace, AM, Haley, BB, Korde, LA, Nanda, Rita , Lang, JE , Kemmer, KA, Hylton, NM, Veer, Laura van’t, Lyandres, Julia, Perlmutter, Jane , Sanil, Ashish, Berry, DA, Esserman, LJ, Yee, Douglas , DeMichele, Angela , Isaacs, Claudine , Paoloni, Marco , Hogarth, Michael A. , Yau, Christina

Cancer Research | March 1, 2017 | Volume: 77 | Issue: 4_Supplement | Pages: P6-11-02-P6-11-02

10.1158/1538-7445.sabcs16-p6-11-02 Get It

Abstract Background:Pathologic complete response(pCR) after neoadjuvant therapy is an established prognostic biomarker for high-risk breast cancer(BC). Improving pCR rates may identify new therapies that improve survival. I-SPY 2 uses response-adaptive randomization within biomarker subtypes to evaluate novel agents when added to standard neoadjuvant therapy for women with high-risk stage II/III breast cancer; the goal is to identify regimens that have ≥85% Bayesian predictive probability of success (statistical significance) in a 300-patient phase 3 neoadjuvant trial defined by hormone-receptor (HR), HER2 status and MammaPrint (MP). We report the results for Ganetespib, a selective inhibitor of Hsp90 that induces the degradation/deactivation of key drivers of tumor initiation, progression, angiogenesis, and metastasis.Ganetespib + taxanes previously have resulted in a superior therapeutic response compared to monotherapy in multiple solid tumor models including BC. Methods:Women with tumors ≥2.5cm were eligible for screening and participation. MP low/HR+ tumors were ineligible for randomization. QTcF >470msec and HbA1C >8.0% were ineligible. MRI scans (baseline, +3 cycles, following weekly paclitaxel, T, and pre-surgery) were used in a longitudinal statistical model to improve the efficiency of adaptive randomization. Ganetespib was given with weekly T at 150 mg/m2 IV weekly (3 weeks on, 1 off). Patients were premedicated (dexamethasone 10mg and diphenhydramine HCl 25-50 mg, or therapeutic equivalents). Analysis was intention to treat with patients who switched to non-protocol therapy counted as non-pCRs. The Ganetespib regimen was open only to HER2- patients, and eligible for graduation in 3 of 10 pre-defined signatures: HER2-, HR+/HER2- and HR-/HER2-. Results:Ganetespib did not meet the criteria for graduation in the 3 signatures tested. When the maximum sample size was reached, accrual stopped. Ganetespib was assigned to 93 patients; there were 140 controls. We report probabilities of superiority for Ganetespib over control and Bayesian predictive probabilities of success in a neoadjuvant phase 3 trial equally randomized between Ganetespib and control, for the 3 biomarker signatures, using the final pCR data from all patients. Safety data will be presented. SignatureEstimated pCR Rate (95% probability interval)Probability Ganetespib Is Superior to ControlPredictive Probability of Ganetespib Success in a Phase 3 Trial Ganetespib N = 93Control N = 140 All HER2-26% (16%-37%)18% (8%-28%)91%47%HR+/HER2-15% (4%-27%)14% (4%-24%)60%19%HR-/HER2-38% (23%-53%)22% (9%-35%)96%72% Conclusion:The I-SPY 2 adaptive randomization model efficiently evaluates investigational agents in the setting of neoadjuvant BC. The value of I-SPY 2 is that it provides insight as to the regimen's likelihood of success in a phase 3 neoadjuvant study. Although no signature reached the efficacy threshold of 85% likelihood of success in phase 3, we observed the most impact in HR-/HER2- patients, with a 16% improvement in pCR rate. While our data do not support the continued development of Ganetespib alone for neoadjuvant BC, combinations with Ganetespib, which could potentiate its effect, may be worth pursuing in I-SPY 2 or similar trials. Citation Format: Forero A, Yee D, Buxton MB, Symmans WF, Chien AJ, Boughey JC, Elias AD, DeMichele A, Moulder S, Minton S, Kaplan HG, Albain KS, Wallace AM, Haley BB, Isaacs C, Korde LA, Nanda R, Lang JE, Kemmer KA, Hylton NM, Paoloni M, van't Veer L, Lyandres J, Perlmutter J, Hogarth M, Yau C, Sanil A, Berry DA, Esserman LJ. Efficacy of Hsp90 inhibitor ganetespib plus standard neoadjuvant therapy in high-risk breast cancer: Results from the I-SPY 2 trial [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 P6-11-02.