Back to Authors

Hirst, GL

Mayo Clinic

Translational Genomics Research Institute

Citations 2

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 P2-07-03: 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.