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72 citation(s) found for "Veer, Laura van ‘t".

Protein activation mapping and exploratory predictive markers for pCR in triple-negative breast cancer patients treated with neratinib in the I-SPY 2 TRIAL.
Wulfkuhle, Julia , Deng, Jianghong , Hirst, Gillian L. , Liu, Minetta C. , Park, John W., Berry, Donald A. , Veer, Laura van’t, Petricoin, Emanuel F. , Investigators, I-SPY 2 TRIAL, Hirst, Gillian L , Yau, Christina , Wolf, Denise M. , Gallagher, Rosa I. , Swigart, Lamorna Brown , Esserman, Laura J. , Investigators, I-SPY 2 TRIAL

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Journal of Clinical Oncology | March 7, 2019 | Volume: 33 | Issue: 15_suppl | Pages: 1085-1085

10.1200/jco.2015.33.15_suppl.1085 Get It

Pembrolizumab plus standard neoadjuvant therapy for high-risk breast cancer (BC): Results from I-SPY 2.
Nanda, Rita , Liu, Minetta C. , Asare, Smita , Hylton, Nola, Veer, Laura van’t, Perlmutter, Jane , Chien, A. Jo , Forero‐Torres, Andres , Ellis, Erin D. , Han, Heather, Clark, Amy S. , Albain, Kathy S. , Berry, Donald A. , Esserman, Laura, Yau, Christina , Wallace, Anne M. , Boughey, Judy C. , Elias, Anthony , Yee, Douglas , DeMichele, Angela

Mayo Clinic

Journal of Clinical Oncology | September 6, 2018 | Volume: 35 | Issue: 15_suppl | Pages: 506-506

10.1200/jco.2017.35.15_suppl.506 Get It

506 Background: Pembro is an anti-PD-1 antibody with single agent activity in HER2– metastatic BC. I-SPY 2 is a multicenter, phase 2 platform trial which evaluates novel neoadjuvant therapies; the primary endpoint is pathological complete response (pCR, ypT0/Tis ypN0). We report current efficacy results, with final results at ASCO. Methods: Patients (pts) with invasive BC ≥2.5 cm by exam or ≥2 cm by imaging are assigned weekly paclitaxel x 12 (control) +/- an experimental agent, followed by doxorubicin/cyclophosphamide x 4. Combinations of hormone-receptor (HR), HER2, & MammaPrint (MP) status define the 8 signatures studied. MP low HR+ BC is excluded. Adaptive randomization is based on each arm’s Bayesian probability of superiority over control. Graduation by signature is based on an arm’s Bayesian predictive probability of a successful 1:1 randomized phase 3 trial with a pCR endpoint. We provide raw & Bayesian estimated pCR rates adjusted for covariates, time effects over the course of the trial, & serial MRI modeling for pts not yet assessed for pCR surgically. Results: 69 pts were randomized to pembro (HER2- subsets only) from Dec 2015 until it graduated in Nov 2016. 46 pts have undergone surgery (table); the other 23 have on-therapy MRI assessments. In 29 HR–/HER2– (TNBC) pts, pembro increased raw & estimated pCR rates by >50% & 40%, respectively; in 40 HR+/HER– pts, it did so by 13% and 21%. 5 pts had immune-related grade 3 adverse events (AEs); 1 hypophysitis & 4 adrenal insufficiency. 4 pts presented after completion of AC (149-179 d after starting pembro); 1 presented prior to AC (37 d after starting pembro). 7 pts had grade 1-2 thyroid abnormalities. Conclusion: Pembro added to standard therapy improved pCR rates in all HER2- BCs that meet I-SPY 2 eligibility, especially in TNBC. Immune-mediated AEs were observed; pt follow up is ongoing. Clinical trial information: NCT01042379. [Table: see text]
Abstract PD6-14: Analysis of DNA repair deficiency biomarkers as predictors of response to the PD1 inhibitor pembrolizumab: Results from the neoadjuvant I-SPY 2 trial for stage II-III high-risk breast cancer
Sanil, Ashish, Singhrao, Ruby , Investigators, I-SPY 2 TRIAL, Asare, Smita , Berry, Donald A. , Esserman, L., Veer, Laura van ‘t , Nanda, Rita , Yau, Christina , Wolf, Denise M. , Swigart, Lamorna Brown , Hirst, Gillian L. , Investigators, I-SPY 2 TRIAL, DeMichele, Angela , Veer, Laura J. van’t , Liu, Ming , Yee, Douglas

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Cancer Research | February 15, 2018 | Volume: 78 | Issue: 4_Supplement | Pages: PD6-14-PD6-14

10.1158/1538-7445.sabcs17-pd6-14 Get It

Abstract Background: Pembrolizumab (P), an anti-PD-1 immune checkpoint inhibitor, has been approved for treatment of microsatellite instability-high and mismatch repair deficient cancers. In I-SPY 2, patients were randomized to receive standard chemotherapy alone or in combination with an experimental agent. P was one of the experimental agents evaluated in HER2- patients in I-SPY 2 and graduated in the TN, HR+HER2-, and HER2- signatures. We hypothesize that a combination of two signatures predicting response to veliparib/carboplatin therapy in I-SPY 2 [MammaPrint High2 (MP2)/PARPi7-high] and reflecting DNA damage repair deficiency, may also predict response to P. In addition, we also tested 9 gene expression signatures reflecting different aspects of DNA damage and repair: FA, MMR, BER, HR, TLS, NER, NHEJ, DR, and DNA damage sensing (DDS) pathways. Methods: Data from 249 patients (P: 69 and controls: 180) were available. Pre-treatment biopsies were assayed using Agilent gene expression arrays. All I-SPY 2 qualifying biomarker analyses follow a pre-specified analysis plan. We used logistic modeling to assess biomarker performance. A biomarker is considered a specific predictor of P response if it associates with response in the P arm but not the control arm, and if the biomarker x treatment interaction is significant (likelihood ratio test, p<0.05). This analysis is also performed adjusting for HR status as a covariate, and within receptor subsets, sample size permitting. For successful biomarkers, we use Bayesian modeling to estimate the pCR rates of 'predicted sensitive' patients in each arm. Our statistics are descriptive rather than inferential and do not adjust for multiplicities of other biomarkers outside this study. Results: MP2 status associates with pCR in P (OR=7.7; p=0.00021), but also to a lesser extent in the control arm (OR=2.4:p=0.045), with an OR ratio of 3.3 which trends toward significance, even after adjusting for HR status (LR p=0.083). A majority of TN patients are MP2; and TN/MP2 patients have an estimated pCR rate of 67% in P (vs. 23% in control). Although only ~30% of HR+HER2- patients were MP2, their estimated pCR rate in P is 61%, compared to 29% in unselected HR+/HER2- patients. PARPi7 predicted response in the P arm only in the HR+HER2- group (LR p= 0.025), but not in the population as a whole or the TN subtype. Combining MP2 and PARPi7 into MP2/PARPi7-high did not improve performance over MP2 as a single biomarker. Of the 9 DDR pathway signatures tested, both BER and DDS associate with pCR in P, but only DDS (which includes ATM, ATR, CHEK1-2) associates with pCR in the P arm (LR p=0.00029), and not the control arm (LR p=0.53), with a significant interaction with treatment (LR p=0.0064) that retains significance in a model adjusting for HR status. When dichotomized to optimize the biomarker x treatment interaction, the estimated pCR rate is 75% in P vs 18% in control, in the DDS+ subset. Conclusion: In this small study, MP2 status and a DNA damage sensing pathway but not the PARPi7 or other repair pathways show promise as predictive biomarkers for immune checkpoint inhibition therapy in breast cancer. Citation Format: Yau C, Wolf D, Brown-Swigart L, Hirst G, Sanil A, Singhrao R, I-SPY 2 TRIAL Investigators, Asare S, DeMichele A, Berry D, Esserman L, van 't Veer L, Nanda R, Liu M, Yee D. Analysis of DNA repair deficiency biomarkers as predictors of response to the PD1 inhibitor pembrolizumab: Results from the neoadjuvant I-SPY 2 trial for stage II-III high-risk 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 PD6-14.
Abstract PD6-08: Analysis of immune infiltrates (assessed via multiplex fluorescence immunohistochemistry) and immune gene expression signatures as predictors of response to the checkpoint inhibitor pembrolizumab in the neoadjuvant I-SPY 2 trial
Borowsky, Alexander D. , Vandenberg, Scott , Wolf, DM, Nanda, Rita , Liu, M, Asare, Smita , Veer, Laura van’t, Yee, Dean Y., Berry, Daniella R. A. I., Esserman, Laura, Campbell, Matthew T. , Yau, Christina , Wolf, DM, Rimm, David L. , Swigart, Lamorna Brown , Hirst, Gillian L. , DeMichele, Angela

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Cancer Research | February 15, 2018 | Volume: 78 | Issue: 4_Supplement | Pages: PD6-08-PD6-08

10.1158/1538-7445.sabcs17-pd6-08 Get It

Abstract Background: Pembrolizumab (Pembro), an anti-PD-1 immune checkpoint inhibitor, has been approved for the treatment of a variety of cancers including melanoma, non-small cell lung cancer, head and neck squamous cell carcinoma, and urothelial carcinoma. Pembro was recently evaluated in HER2- breast cancer patients in the neoadjuvant I-SPY 2 TRIAL and graduated in the triple negative (TN), HR+HER2-, and HER2- signatures. HER2- patients were randomized to receive Pembro+paclitaxel followed by doxorubicin/cyclophosphamide (P+T -> AC) vs. T -> AC. We and others have shown that TN breast cancers tend to have high numbers of immune infiltrates, including T cells and tumor associated macrophages (TAMs). We evaluated expression signatures representing 14 immune cell types (TILs, T cells, CD8 T cells, exhausted T cells, Th1, Tregs, cytotoxic cells, NK, NK CD56dim, dendritic cells, mast cells, B cells, macrophages, and neutrophils) as specific predictors of response to Pembro. Methods: Data from 248 patients (Pembro: 69; controls: 179) were available. Pre-treatment biopsies were assayed using Agilent gene expression arrays. Signature scores are calculated by averaging cell type specific genes. All I-SPY 2 qualifying biomarker analyses follow a pre-specified analysis plan. We used logistic modeling to assess biomarker performance. A biomarker is considered a specific predictor of Pembro response if it associates with response in the Pembro arm but not the control arm, and if the biomarker x treatment interaction is significant (likelihood ratio test, p<0.05). This analysis is also performed adjusting for HR status as covariates, and within receptor subsets. For successful biomarkers, we use Bayesian modeling to estimate the pCR rates of 'predicted sensitive' patients in each arm. Our statistics are descriptive rather than inferential and do not adjust for multiplicities of other biomarkers outside this study. Results: 10 out of the 14 cell-type signatures tested are associated with response in the Pembro arm. Higher expression levels of 9 of these cell-type signatures are associated with higher pCR rates (T cells, exhausted T cells, Th1, cytotoxic cells, NK, NK CD56dim, dendritic cells, B cells, and macrophages), whereas higher mast cell signature expression is associated with non-pCR. Interestingly, many of these same signatures also associate or trend towards association with response in the control arm; and in a model adjusting for HR status, only 3 of these signatures (Th1, B cells and dendritic cells) show significant interaction with treatment. Within the whole population and the TN subtype, the dendritic cell signature is the strongest predictor of specific response to Pembro (OR/1SD: 4.04 and 4.4, LR p < 0.001 overall and in TN). Although other immune signatures (T cells, exhausted T cells, NK, and macrophages) also associate with response in the Pembro arm in the TN subtype, only the dendritic cell and Th1 signatures have a significant interaction with treatment. In contrast, in the HR+HER2- subtype, only 3 signatures (Th1, B cells, and mast cells) associate with response to Pembro; but none of these signatures have significant interaction with treatment. Of note, in both the Pembro and control arms, HR+HER2- patients with higher average mast cell marker expression have lower pCR rates (OR/1SD: 0.33 and 0.51, LRp: 0.006 and 0.04 in Pembro and control arm). Conclusion: As expected, multiple immune cell expression signatures are predictive of response in the Pembro arm; but only dendritic cells and Th1 cells are specific to Pembro in both the population as a whole and the TN subtype. Interestingly, the presence of mast cells may impede response, especially in HR+HER2- patients. Correlation of these signatures with multiplex-IF immune markers is pending. Citation Format: Campbell M, Yau C, Borowsky A, Vandenberg S, Wolf D, Rimm D, Nanda R, Liu M, Brown-Swigart L, Hirst G, Asare S, van't Veer L, Yee D, DeMichele A, Berry D, Esserman L. Analysis of immune infiltrates (assessed via multiplex fluorescence immunohistochemistry) and immune gene expression signatures as predictors of response to the checkpoint inhibitor pembrolizumab in the neoadjuvant I-SPY 2 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 PD6-08.
Body mass index and breast cancer survival: a Mendelian randomization analysis
Guo, Qi , Burgess, Stephen , Bolla, Manjeet K. , Wang, Qin , Abraham, Jean , Aittomäki, Kristiina, Andrulis, Irene L. , Apicella, Carmel, Berg, Christine D. , Blomqvist, Carl , Bojesen, Stig E. , Brand, Judith S. , Brenner, Hermann , Burwinkel, Barbara , Caldas, Carlos , Campa, Daniele , Canzian, Federico , Chang‐Claude, Jenny , Couch, Fergus J. , Darabi, Hatef, Diver, W. Ryan , Earl, Helena , Eccles, Diana M, Ekici, Arif B. , Eriksson, Mikael , Evans, D. Gareth , Fasching, Peter A. , Figueroa, Jonine D. , Flesch‐Janys, Dieter, Flyger, Henrik, Gapstur, Susan M. , Gaudet, Mia M. , Glendon, Gord, Grip, Mervi, Haeberle, Lothar, Haiman, Christopher A., Hamann, Ute, Hankinson, Susan E. , Hein, Alexander , Hiller, Louise , Hogervorst, Frans B.L., Holleczek, Bernd , Hooning, Maartje J. , Hoover, Robert N. , Humphreys, Keith , Hunter, David J., Hüsing, Anika , Jakubowska, Anna , Jukkola‐Vuorinen, Arja , Kabisch, Maria, Investigators, kConFab/AOCS, Knight, Julia A. , Koppert, Linetta B. , Kosma, Veli‐Matti , Kristensen, Vessela N. , Lambrechts, Diether , Li, Jingmei , Lindblom, Annika , Lindström, Sara, Lissowska, Jolanta , Lubiński, Jan , Machiela, Mitchell J. , Mannermaa, Arto, Manoukian, Siranoush , Margolin, Sara , Marmé, F., McLean, Catriona , Menéndez, Primitiva, Mulligan, Anna Marie , Muranen, Taru , Neven, Patrick , Nielsen, Sune F. , Nordestgaard, Børge G. , Perez, Jose IA, Peterlongo, Paolo , Phillips, Kelly‐Anne , Poole, Christopher, Pylkäs, Katri , Radice, Paolo , Rüdiger, Thomas , Sawyer, Elinor J. , Schumacher, Fredrick R. , Seynaeve, Caroline, Shah, Mitul , Smeets, Ann , Southey, Melissa C. , Tollenaar, Rob A.�E.�M. , Tomlinson, Ian , Ulmer, Hans-Ulrich, Vachon, Celine M. , Ouweland, Ans MW van den, Veer, Laura J. van’t , Wildiers, Hans , Winqvist, Robert , Zamora, M. Pilar , Chenevix‐Trench, Georgia , Dörk, Thilo , Easton, Douglas F. , García‐Closas, Montserrat , Kraft, Peter , Hopper, John L. , Pharoah, Paul D.P., Eccles, Diana , Bowtell, David D.L. , Lambrechts, Diether , Vachon, Celine, Turman, Constance , Lush, Michael J. , Arndt, Volker , Benı́tez, Javier , Bonanni, Bernardo , Broeks, Annegien , Chanock, Stephen Jacob , Chin, Suet‐Feung , Couch, Fergus J. , Cox, Angela , Cross, Simon S. , Cybulski, Cezary , Czene, Kamila , Devilee, Peter , Dunning, Alison M. , Eriksson, Mikael , Giles, Graham G. , Gronwald, Jacek , Hall, Per N , Hankinson, Susan E. , Hartikainen, Jaana M. , Hooning, Maartje J. , Kaaks, Rudolf , Kataja, Vesa , Investigators, kConFab/AOCS, Marchand, Loı̈c Le , Mannermaa, Arto, Martens, John W.M. , Milne, Roger L. , Nevanlinna, Heli , Olson, Janet E. , Rahman, Nazneen , Rudolph, Anja , Seibold, Petra , Tsimiklis, Helen , Vachon, Celine M. , Willett, Walter C. , Zheng, Wei , Schmidt, Marjanka K. , Dörk, Thilo , Lambrechts, Diether , Peterlongo, Paolo , Hein, Alexander , Eccles, Diana , Radice, Paolo , Lissowska, Jolanta , Caldas, Carlos , Evans, D Gareth , Southey, Melissa C , Canzian, Federico , Jakubowska, Anna , Lambrechts, Diether , Brenner, Hermann , Li, Jingmei , Muranen, Taru A , García-Closas, Montserrat , Ekici, Arif B , Kraft, Peter , Chenevix-Trench, Georgia , Figueroa, Jonine D , Machiela, Mitchell J , Hüsing, Anika , Bowtell, David D , Pylkäs, Katri , Manoukian, Siranoush , Lubinski, Jan , Bojesen, Stig E , Phillips, Kelly-Anne , Wildiers, Hans , Mclean, Catriona , Lindblom, Annika , Sawyer, Elinor J

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International Journal of Epidemiology | June 29, 2017 | Volume: 46 | Issue: 6 | Pages: 1814-1822

10.1093/ije/dyx131 | PMID 29232439 Get It

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.

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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

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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.
Abstract CT106: Efficacy of pertuzumab/trastuzumab/paclitaxel over standard trastuzumab/paclitaxel therapy for HER2+ breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL
Buxton, Meredith , Chia, Stephen, Veer, Laura van’t, Chien, Jo, Moulder, Stacy L. , Albain, Kathy S. , Kemmer, Kathleen, Haley, Barbara , Minton, Susan, Forero, Andres , Nanda, Rita , Korde, Larissa A. , Viscuzi, Rebecca, Rugo, Hope, Schwab, Richard B. , Symmans, Fraser, Paoloni, Melissa, Lyandres, Julia, Perlmutter, Jane , Sanil, Ashish, Berry, Don, Investigators, I-SPY 2 TRIAL, DeMichele, Angela , Wallace, Anne M. , Kaplan, Henry G. , Lang, Julie E. , Yee, Douglas , Isaacs, Claudine , Boughey, Judy C. , Elias, Anthony , Hylton, Nola M. , Hogarth, Michael A. , Yau, Christina , Esserman, Laura J. , Berry, Donald A. , Investigators, I-SPY 2 TRIAL

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Cancer Research | July 26, 2016 | Volume: 76 | Issue: 14_Supplement | Pages: CT106-CT106

10.1158/1538-7445.am2016-ct106 Get It

Abstract Background: Pathologic complete response (pCR) is an established prognostic biomarker for aggressive HER2+ breast cancer (BC). Improving pCR rates may identify new therapies that improve survival. Pertuzumab (P) has established survival benefit in the metastatic setting, and received accelerated approval in the neoadjuvant setting when combined with trastuzumab (H) and docetaxel(D) as part of a complete treatment regimen for early breast cancer. We tested its ability, when combined with standard therapy (paclitaxel, T, and H) to improve pCR (ypT0ypN0) over TH in the adaptively randomized, phase II, I-SPY 2 neoadjuvant trial. Methods: Enrolled patients (pts) had invasive BC ?2.5 cm in HER2-positive subsets. Pts were adaptively randomized to control (TH, qwk x 12) or THP (P, q3wk x 4) followed by doxorubicin/cyclophosphamide (AC) x 4 and surgery. To compare THP to TH we utilized all control pts accrued over the course of the trial, adjusting for potential differences due to time period treated, which were informed by the several other treatment arms that have been in the trial. Adaptive assignment to the experimental arms was based on current Bayesian probabilities of superiority over control. “Graduation” by signature and futility stopping were based upon Bayesian predictive probability of success in a 2-arm, N = 300 phase III randomized 1:1 trial of THP vs. TH with pCR endpoint. Results: THP met the predictive probability criterion and graduated in 3 signatures: all HER2+, HER2+/HR+, and HER2+/HR- (See Table 1). Final accrual: 44 THP and 31 TH. Safety data will be shown. Conclusions: I-SPY 2's standing platform trial efficiently evaluates agents in biomarker-defined pt subsets. THP -> AC substantially improves pCR rates over standard TH -> AC in all 3 HER2+ signatures, including HR+ and HR- subsets. APHINITY, a trial of adjuvant pertuzumab with a primary outcome of invasive disease-free survival, is ongoing. Table 1Signature*Estimated pCR Rate (95% probability interval)Signature*THPControl (TH)Probability THP Is Superior to ControlPredictive Probability of Success in Phase IIIHER2+54% (38%-70%)22% (5%-39%)99.8%96%HER2+/HR+44% (24%-63%)17% (0%-34%)99%91%HER2+/HR-74% (53%-95%)33% (6%-59%)99.8%98%*HR = Hormone Receptor Citation Format: Meredith Buxton, Angela M. DeMichele, Stephen Chia, Laura van't Veer, Jo Chien, Anne Wallace, Henry Kaplan, Julie Lang, Douglas Yee, Claudine Isaacs, Stacy Moulder, Kathy Albain, Judy Boughey, Kathleen Kemmer, Barbara Haley, Susan Minton, Andres Forero, Rita Nanda, Anthony Elias, Larissa Korde, Rebecca Viscuzi, Hope Rugo, Richard Schwab, Fraser Symmans, Melissa Paoloni, Nola Hylton, Michael Hogarth, Julia Lyandres, Jane Perlmutter, Ashish Sanil, Christina Yau, Laura Esserman, Don Berry, I-SPY 2 TRIAL Investigators. Efficacy of pertuzumab/trastuzumab/paclitaxel over standard trastuzumab/paclitaxel therapy for HER2+ breast cancer: Results from the neoadjuvant I-SPY 2 TRIAL. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr CT106.
High‐throughput automated scoring of Ki67 in breast cancer tissue microarrays from the Breast Cancer Association Consortium
Howat, William , Daley, Frances , Zabaglo, Lila, McDuffus, Leigh‐Anne, Blows, Fiona M., Coulson, Penny , Ali, H. Raza , Benı́tez, Javier , Brenner, Hermann , Stegmaier, Christa, Mannermaa, Arto, Chang‐Claude, Jenny , Sinn, Hans‐Peter , Tollenaar, Rob A.�E.�M. , Devilee, Peter , Figueroa, Jonine D. , Sherman, Mark E., Lissowska, Jolanta , Hewitt, Stephen M. , Eccles, Diana , Hooning, Maartje J. , Deurzen, Carolien HM van, Investigators, kConFab, Bolla, Manjeet K. , Wang, Qin , Jones, Michael E. , Schoemaker, Minouk J. , Leeuwen, Flora E. van , Veer, Laura van’t, Swerdlow, Anthony J. , Orr, Nick , Dowsett, Mitch , Easton, Douglas F. , Schmidt, Marjanka K. , García‐Closas, Montserrat , Abubakar, Mustapha , Milne, Roger L. , Mannermaa, Arto, Rudolph, Anja , Couch, Fergus J. , Hollestelle, Antoinette , Martens, John W.M. , Deurzen, Carolien HM van, Broeks, Annegien , Pharoah, Paul D.P. , Eccles, Diana , Swerdlow, Anthony J , Lissowska, Jolanta , Sinn, Peter , Jones, Michael E , Brenner, Hermann , García-Closas, Montserrat , Schmidt, Marjanka K , Benitez, Javier , Figueroa, Jonine D , Devilee, Peter , Schoemaker, Minouk J , Orr, Nick

Mayo Clinic

The Journal of Pathology: Clinical Research | March 2, 2016 | Volume: 2 | Issue: 3 | Pages: 138-153

10.1002/cjp2.42 | PMID 27499923 Get It

AbstractAutomated methods are needed to facilitate high‐throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large‐scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37–0.87) and study (kappa range = 0.39–0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p‐value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000–4,500 cells: kappa = 0.78) than those with lower counts (50–500 cells: kappa = 0.41; p‐value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre‐ and post‐analytical quality control procedures are necessary in order to ensure satisfactory performance.
Abstract P3-06-29: MammaPrint High1/High2 risk class as a biomarker of response to neratinib plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL
Sanil, Ashish, Chien, Jo, Nanda, Rita , Chiu, Steven, Albain, Kathy S. , Kaplan, Hank, Moulder, Stacey, Viscusi, Rebecca K., Northfelt, Donald W. , Edmiston, Kirsten K., Styblo, Toncred M., Haley, Barbara , Flynn, Susan, Buxton, Meredith , Hylton, Nola, Paoloni, Melissa, Berry, Don, Liu, Minetta C. , Park, John W., Veer, Laura van ‘t , Yau, Christina , Wolf, Denise M. , Wallace, Anne M. , Boughey, Judy C. , Yee, Douglas , Tripathy, Debu , DeMichele, Angela , Isaacs, Claudine , Elias, Anthony , Swigart, Lamorna Brown , Hirst, Gillian L. , Symmans, W. Fraser , Esserman, Laura J. , Berry, Donald A. , Veer, Laura J. van’t

Mayo Clinic

Cancer Research | May 4, 2015 | Volume: 75 | Issue: 9_Supplement | Pages: P3-06-29-P3-06-29

10.1158/1538-7445.sabcs14-p3-06-29 Get It

Abstract Background: Further stratification of the 70-gene MammaPrintTM signature into ‘high’ and ‘ultra-high’ risk groups may help predict chemo-sensitivity. In I-SPY 2, patients were classified as MammaPrint High1 (MP1) or MammaPrint (ultra) High2 (MP2), with MP2 defined as MP_score <-0.154. MP1/MP2 classification was added to HR and HER2 to define the cancer subtypes used in the I-SPY 2 adaptive randomization engine. Neratinib (N), one of the experimental agents evaluated in I-SPY 2, graduated in the HR-HER2+ signature. All patients received at least standard chemotherapy (paclitaxel followed by doxorubicin/cyclophosphamide; T->AC). HER2- patients were randomized to receive N+T- >AC vs. T->AC. For HER2+ patients, neratinib was administered in place of trastuzumab (N+T->AC vs. H+T->AC). Here, we assess the performance of MP1/MP2 class as a specific biomarker of neratinib response. Methods: 115 patients in the neratinib arm and 76 concurrently randomized controls had Agilent 44K microarrays and pCR data available for analysis. We assess association between MP1/MP2 and response in the neratinib and control arms alone using Fisher’s exact test, and relative performance between arms (biomarker x treatment interaction, likelihood ratio p < 0.05) using a logistic model. This analysis is also performed adjusting for HR status as a covariate, and in receptor subsets. Our study is exploratory with no claims for generalizability of the data. Statistical calculations are descriptive (e.g. p-values are measures of distance with no inferential content). Our analyses do not adjust for multiplicities of other biomarkers in the trial but outside this study. Results: There are 133 MP1 patients (neratinib: 74, Control: 59) and 58 MP2 patients (neratinib: 41, Control: 17), 84% (49) of which are Her2-. The distribution of pCR rates among MP1/MP2 dichotomized groups are summarized in Table 1. Neratinib (n=115)Control (n=76)MP1 (n=74)MP2 (n=41)MP1 (n=59)MP2 (n=17)HER2- (n=105)0 / 1715 / 337 / 395 / 16HER2+ (n=86)22 / 574 / 85 / 200 / 1 MP2, one of the 10 eligible signatures, did not meet the graduation threshold; and MP1/MP2 did not show a significant biomarker x treatment interaction (OR in neratinib relative to control arm = 1.25). The MP1/MP2 x treatment interaction remains non-significant after adjustment for HR and HER2 status (p=0.54). In HER2- patients receiving neratinib, 45% (15/33) of MP2 patients achieved a pCR, compared to 0% (0/17) of MP1 patients. In the HER2- controls, there is a 31% pCR rate in MP2 (5/16) vs. 18% in MP1 (7/39) patients (OR=2.14). This difference in performance between treatment arms appears significant (p=0.041). 90% of HER2+ patients are MP1, thus MP1/MP2 status x treatment interaction within the HER2+ subtype cannot be evaluated. Conclusion: Within the I-SPY 2 population as a whole, MP1/MP2 stratification does not appear to be a specific biomarker of response to neratinib relative to the control arm. The number of HER2- patients is small and precludes any definitive conclusion, but these data motivate further investigation of the biological mechanisms distinguishing MP1 from MP2 to better understand chemotherapy and/or neratanib responsiveness. Citation Format: Christina Yau, Denise M Wolf, Ashish Sanil, Jo Chien, Anne Wallace, Judy Boughey, Doug Yee, Debu Tripathy, Angela DeMichele, Rita Nanda, Steven Chiu, Claudine Isaacs, Kathy Albain, Hank Kaplan, Stacey Moulder, Rebecca Viscusi, Donald Northfelt, Kirsten Edmiston, Anthony Elias, Toncred Styblo, Barbara Haley, Lamorna Brown-Swigart, Susan Flynn, Gillian L Hirst, Meredith Buxton, Nola Hylton, Melissa Paoloni, W Fraser Symmans, Laura Esserman, Don Berry, Minetta C Liu, John W Park, Laura van 't Veer. MammaPrint High1/High2 risk class as a biomarker of response to neratinib plus standard neoadjuvant therapy for breast cancer in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-06-29.