Abstract PD9-05: Lack of background parenchymal enhancement suppression in breast MRI during neoadjuvant chemotherapy may be associated with inferior treatment response in hormone receptor positive breast cancer

Purpose

In breast MRI, contrast enhancement of normal fibroglandular tissue is referred to as background parenchymal enhancement (BPE). Hormonal status significantly affects the degree of BPE, potentially due to the association with mammary vascularity and activity1-5. Studies have shown that BPE may be associated with breast cancer survival6, treatment response to neoadjuvant chemotherapy (NAC)7,8 and future breast cancer risk9. In most patients undergoing NAC, BPE is suppressed by the nonspecific anti-proliferative effects of chemotherapy on normal breast and/or ovary5,10. However, some patients exhibit equivalent or even stronger BPE post-NAC compared to pre-NAC. We hypothesized that non-suppressed BPE in post-NAC MRI may be associated with inferior treatment response. This study aimed to investigate the association between BPE suppression and treatment response as defined by pathologic complete response (pCR).

Methods

This study included patients with stage II/III breast cancer enrolled in the I-SPY 2 TRIAL being treated with standard NAC with or without investigational agents. The whole cohort was split into two subgroups based on hormone receptor status (HR+, n= 536; HR-, n=452). Patients underwent dynamic contrast enhanced MRIs at four time points during NAC: baseline (T0), after 3 weeks of the first regimen (T1), inter-regimen (T2), and pre-surgery (T3). Using in-house software, the contralateral breast parenchyma was automatically segmented for the entire breast volume. Quantitative BPE (qBPE) was calculated as the mean early (~150s post-contrast injection) percent enhancement of the central 50% of the axial slices. A breast radiologist reviewed all exams and excluded those where automated segmentation failed to accurately define tissue. For T1, T2 and T3, BPE was categorized based on the change from T0 as suppressed (qBPE < qBPE[T0]) or non-suppressed (qBPE ≥ qBPE[T0]). Chi-squared test was used to examine the association between BPE suppression and pCR, with p<0.05 considered statistically significant.

Results

HR+ cohort: pCR rates were lower for patients with non-suppressed BPE than those with suppressed BPE at every visit (T1-T3) (Table 1). The difference was statistically significant at T2 (p=0.04) and T3 (p=0.01).

Table 1: HR+ cohortpCR rate (%)No. of pCR patientsNo. of non-pCR patientsTotal number of patientsP valueOverall22.8122414536BPE at T1suppressed23.6822663480.45non-suppressed20.532124156BPE at T2suppressed25.7972803770.04*non-suppressed16.01789106BPE at T3suppressed25.7982833810.01*non-suppressed12.5128496

HR- cohort: pCR rates were slightly lower for the non-suppressed BPE group, but no statistically significant association was found (Table 2).

Table 2: HR- cohortpCR rate (%)No. of pCR patientsNo. of non-pCR patientsTotal number of patientsP valueOverall44.7202250452BPE at T1suppressed46.81411603010.66non-suppressed44.45265117BPE at T2suppressed48.81441512950.79non-suppressed47.3434891BPE at T3suppressed49.31461502960.94non-suppressed48.9434588

Conclusion

In HR+ breast cancer, lack of BPE suppression may indicate inferior treatment response. The contrasting results in HR+ and HR- cohorts are noteworthy in terms of the possible relationship between suppression of normal mammary and ovarian activity and treatment response in HR+ cancer.

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Citation Format: Natsuko Onishi, Wen Li, David C. Newitt, Roy Harnish, Jessica Gibbs, Ella F. Jones, Alex Nguyen, Lisa Wilmes, Bonnie N. Joe, Michael J. Campbell, Amrita Basu, Laura J. van’t Veer, Angela DiMichele, Douglas Yee, Donald A. Berry, Kathy S. Albain, Judy C. Boughey, A. Jo Chien, Amy S. Clark, Kirsten K. Edmiston, Anthony D. Elias, Erin D. Ellis, David M. Euhus, Heather S. Han, Claudine Isaacs, Qamar J. Khan, Julie E. Lang, Janice Lu, Jane L. Meisel, Zaha Mitri, Rita Nanda, Donald W. Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K. Viscusi, Anne M. Wallace, Rachel Yung, Michelle E. Melisko, Jane Perlmutter, Hope S. Rugo, Richard Schwab, W. Fraser Symmans, Smita M. Asare, Julie E. Yau, Christina Yau, Laura J. Esserman, Nola M. Hylton. Lack of background parenchymal enhancement suppression in breast MRI during neoadjuvant chemotherapy may be associated with inferior treatment response in hormone receptor positive breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-05.

Abstract P2-20-02: Site of recurrence after neoadjuvant therapy: Clues to biology and impact on endpoints

Background: Achieving a pathologic complete response (pCR) has been shown on the patient level to predict excellent long-term event-free survival outcomes. Residual cancer burden (RCB) quantifies the extent of residual disease for patients who did not achieve pCR. A high proportion of metastatic events to the central nervous system (CNS), a known chemotherapy sanctuary site, was previously observed among the small number of relapses in patients achieving a pCR (Symmans et al 2017), raising the possibility that these CNS events may be independent of response in the breast. I-SPY2 is an adaptively randomized, phase II, platform trial that evaluates new drugs and combinations in the neoadjuvant setting for women with high-risk primary breast cancer. In this study, we evaluated the type and sites of recurrences by RCB classes in the I-SPY 2 TRIAL.

Methods: I-SPY 2 patients enrolled prior to 11/2016 across 9 experimental and control arms, with available RCB and event-free survival (EFS) data were included in this analysis. The median follow-up is 3.8 years. We summarized the EFS event type, further sub-dividing the distant recurrence events by their site of relapse (CNS-only, CNS and other sites, Non-CNS). We estimated the overall and site-specific distant recurrence incidence in each RCB class at 3 years using a competing risk (Fine-Gray) model. In addition, we assessed the association between RCB and distant recurrence free survival including all distant recurrences (DRFS), as well as excluding the CNS-only recurrences (non-CNS DRFS) using a Cox model. Our statistics do not adjust for multiplicities beyond variables evaluated in this study.

Results: Among 938 subjects, there were 180 EFS events, including 28 (16%) local recurrences (without distant recurrence and/or death) and 152 DRFS events. Among the DRFS events, 25 patients died without a distant recurrence. 127 experienced distant recurrences, including 22 (17.3%) with CNS-only, 16 (12.6%) with CNS and other sites, 87 (68.5%) with non-CNS distant recurrence; 2 (1.6%) patients had missing recurrence site information. Incidence of CNS-only recurrences are low and are similar across RCB classes (pCR/RCB-0 (n=338): 1%, RCB-I (n=129): 3%, RCB-II (n=328): 2%, RCB-III (n=143): 2% at 3 years). In contrast, the incidence of non-CNS recurrences increase with increasing RCB (RCB-0: 2%, RCB-I: 4%, RCB-II: 11%, RCB-III: 19% at 3 years). DRFS of RCB-I patients do not significantly differ from those achieving a pCR/RCB-0 (DRFS at 3 years: 92% vs. 95%, hazard ratio: 1.77 (0.87-3.63)); the small numerical difference is further reduced when the CNS-only recurrences are excluded (non-CNS DRFS at 3 years: 95% vs. 96%, hazard ratio: 1.48 (0.61-3.58)). CNS recurrences among DRFS events are proportionally higher within the pCR (5/16 (31%)) and RCB-I (5/12 (42%)) than in the RCB-II (8/57 (14%)) and RCB-III (4/42 (9%)) groups largely because of the relative low frequency of non-CNS recurrence events.

Conclusions: In our high-risk I-SPY 2 cohort, CNS-only recurrences are uncommon but appear similar across RCB groups, independent of response, suggesting that the CNS is a treatment sanctuary site. In contrast, non-CNS recurrence rates increase as RCB increases. These findings, if confirmed, support the use of RCB to identify patients with excellent outcomes beyond those achieving a pCR; and suggest that inclusion of CNS only recurrences as an outcome event may impact the association between neoadjuvant therapy response and long-term outcome.

Citation Format: Christina Yau, Angela DeMichele, W. Fraser Symmans, Lajos Pusztai, Douglas Yee, Amy S. Clark, Christos Hatzis, Jeffrey B. Matthews, Jodi Carter, Yunn-Yi Chen, Kimberly Cole, Laila Khazai, Molly Klein, Dina Kokh, Gregor Krings, Sunati Sahoo, Kathy S. Albain, A. Jo Chien, Kirsten K. Edmiston, Anthony D. Elias, Erin D. Ellis, David M. Euhus, Heather S. Han, Claudine Isaacs, Qamar J. Khan, Julie E. Lang, Janice Lu, Jane L. Meisel, Zaha Mitri, Rita Nanda, Donald W. Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K. Viscusi, Anne M. Wallace, Rachel Yung, Nola M. Hylton, Judy C. Boughey, Michelle E. Melisko, Jane Perlmutter, Hope S. Rugo, Richard Schwab, Laura J. van' t Veer, Donald A. Berry, Laura J. Esserman. Site of recurrence after neoadjuvant therapy: Clues to biology and impact on endpoints [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P2-20-02.

Abstract PD9-04: Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial

Background: In an adaptive randomized trial, when new treatment combinations are being tested, it is important to be able to identify patients who are progressing on treatment so that they can be changed to a different therapeutic regimen. We know that even within the molecularly high risk patients in I-SPY 2, there is considerable variation in biology. In this study, we will present results of using MRI-calculated functional tumor volume (FTV) to identify tumor progression for each breast cancer subtype.

Methods: Patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Four MRI exams were performed for each patient: pre-NAC (T0), after 3 weeks of NAC (T1), between regimens (T2), and post-NAC (T3). Functional tumor volume (FTV) was calculated at each exam by summing voxels meeting enhancement thresholds. Tumor progression at T1, T2 or T3 was identified by a positive FTV change relative to T0. Visual inspection was used to exclude false progression due to strong background parenchymal enhancement post-contrast, prominent vessels, motion, or insufficient image quality. pCR was defined as no invasive disease in the breast and lymph nodes. Negative predictive value for pCR was defined as:NPV=number of true non-pCRs / number of patients with MRI assessed tumor progressions, where “true non-pCRs” referred to patients who were non-pCRs at surgery and were assessed as progressors by MRI. The analysis was performed in the full cohort and in sub-cohorts defined by HR and HER2 statuses.

Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Total and non-pCR numbers for each subtype, number of patients with tumor progression assessed by MRI at T1, T2, and T3, and NPVs, are shown in Table 1. In the full cohort, the NPV increased consistently over treatment, from T1 (NPV=83%) to T2 (93%), and to T3 (100%). The HER2+ cancer subtypes showed fewer MRI-assessed tumor progressions than HER2- subtypes: e.g. 10/209 (5%) vs. 108/669 (16%) at T1. NPV was 100% for HER2+ subtypes at T1 and T2 except for a single misclassification of a HR- tumor at T1. Only 6 tumor progressors, all HER2- were identified at T3, and all were confirmed at surgery as non-pCRs (NPV=100%). For HR+/HER2-, the NPV increased slightly from 89% at T1 to 91% at T2, while triple negative subtype had a more substantial increase, from 78% to 92%.

Conclusions: Our study showed strong association between tumor progressors assessed by MRI with true non-pCRs after NAC. For HER2+ tumors, although MRI progressors are rare, they strongly indicate non-pCR at all treatment time points, while HER2- subtypes show more accurate results later in treatment. We are evaluating MRI change at 6 weeks to determine if that time point is sufficient to predict progressors.

Table 1 MRI assessed tumor progression at different treatment time pointN/non-pCRs/%non-pCRMRI assessed tumor progressionT1 (after 3 weeks)T2 (inter-regimen)T3 (post-NAC)NNPV (%)NNPV (%)NNPV (%)Full cohort878/572/65%11883.14192.76100%HR+/HER2-344/280/81%4588.91190.93100%HR+/HER2+134/85/63%610021000N/AHR-/HER2+75/23/31%47521000N/Atriple negative325/184/57%6377.82692.33100%

Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Jessica Gibbs, Lisa J Wilmes, Ella F Jones, Bonnie N Joe, Laura S Sit, Christina Yau, A. Jo Chien, Elissa Price, Kathy S Albain, Theresa Kuritza, Kevin Morley, Judy C Boughey, Kathy Brandt, Sadia Choudhery, Amy S Clark, Mark Rosen, Elizabeth S McDonald, Anthony D Elias, Dulcy Wolverton, Kelly Fountain, David M Euhus, Heather S Han, Bethany Niell, Jennifer Drukteinis, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Smita M Asare, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Donald A Berry, Angela DeMichele, Hiroyuki Abe, Deepa Sheth, Kirsten K Edmiston, Erin D Ellis, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Michael Nelson, An Church, Claudine Isaacs, Qamar J Khan, Karen Y Oh, Neda Jafarian, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Pulin Sheth, Linda Hovanessian-Larsen, Mohammad Eghtedari, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Sally Goudreau, Thelma Brown, Laura J Esserman, Nola M Hylton. Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-04.

Effects of Radiotherapy in Early-Stage, Low-Recurrence Risk, Hormone-Sensitive Breast Cancer

Background

Radiotherapy after breast conservation has become the standard of care. Prior meta-analyses on effects of radiotherapy predated availability of gene expression profiling (GEP) to assess recurrence risk and/or did not include all relevant outcomes. This analysis used GEP information with pooled individual-level data to evaluate the impact of omitting radiotherapy on recurrence and mortality.

Methods

We considered trials that evaluated or administered radiotherapy after lumpectomy in women with low-risk breast cancer. Women included had undergone lumpectomy and were treated with hormonal therapy for stage I, ER+ and/or PR+, HER2- breast cancer with Oncotype scores no greater than 18. Recurrence-free interval (RFI), type of RFI (locoregional or distant), and breast cancer-specific and overall survival were compared between no radiotherapy and radiotherapy using adjusted Cox models. All statistical tests were two-sided.

Results

The final sample included 1778 women from seven trials. Omission of radiotherapy was associated with an overall adjusted hazard ratio of 2.59 (95% confidence interval [CI] = 1.38 to 4.89, P = .003) for RFI. There was a statistically significant increase in any first locoregional recurrence (P = .001), but not distant recurrence events (P = .90), or breast cancer-specific (P = .85) or overall survival (P = .61). Five-year RFI rate was high (93.5% for no radiotherapy vs 97.9% for radiotherapy; absolute reduction = 4.4%, 95% CI = 0.7% to 8.1%, P = .03). The effects of radiotherapy varied across subgroups, with lower RFI rates for those with Oncotype scores of less than 11 (vs 11-18), older (vs younger), and ER+/PR+ status (vs other).

Conclusions

Omission of radiotherapy in hormone-sensitive patients with low recurrence risk may lead to a modest increase in locoregional recurrence event rates, but does not appear to increase the rate of distant recurrence or death.

Simulation Modeling of Cancer Clinical Trials: Application to Omitting Radiotherapy in Low-risk Breast Cancer

Background

We used two models to simulate a proposed noninferiority trial of radiotherapy (RT) omission in low-risk invasive breast cancer to illustrate how modeling could be used to predict the trial's outcomes, inform trial design, and contribute to practice debates.

Methods

The proposed trial was a prospective randomized trial of no-RT vs RT in women age 40 to 74 years undergoing lumpectomy and endocrine therapy for hormone receptor-positive, human epidermal growth factor receptor 2-negative, stage I breast cancer with an Oncotype DX score of 18 or lower. The primary endpoint was recurrence-free interval (RFI), including locoregional recurrence, distant recurrence, and breast cancer death. Noninferiority required the two-sided 90% confidence interval of the RFI hazard ratio (HR) for no-RT vs RT to be entirely below 1.7. Model inputs included published data. The trial was simulated 1000 times, and results were summarized as percent concluding noninferiority and mean (standard deviation) of hazard ratios for Model GE and Model M, respectively.

Results

Noninferiority was demonstrated in 18.0% and 3.7% for the two models. The respective means (SD) of the RFI hazard ratios were 1.8 (0.7) and 2.4 (0.9); most were locoregional recurrences. The mean five-year RFI rates for no-RT vs RT (SD) were 92.7% (2.9%) vs 95.5% (2.2%) and 88.4% (2.0%) vs 94.5% (1.6%). Both models showed little or no difference in breast cancer-specific or overall survival. Alternative definitions of low risk based on combinations of age and grade produced similar results.

Conclusions

The proposed trial was unlikely to show noninferiority of omitting radiotherapy even using alternative definitions of low-risk, as the endpoint included local recurrence. Future trials regarding radiotherapy should address absolute reduction in recurrence and impact of type of recurrence on the patient.

Randomized Trial of Standard Adjuvant Chemotherapy Regimens Versus Capecitabine in Older Women With Early Breast Cancer: 10-Year Update of the CALGB 49907 Trial

PURPOSE

Older women with breast cancer remain under-represented in clinical trials. The Cancer and Leukemia Group B 49907 trial focused on women age 65 years and older. We previously reported the primary analysis after a median follow-up of 2.4 years. Standard adjuvant chemotherapy showed significant improvements in recurrence-free survival (RFS) and overall survival compared with capecitabine. We now update results at a median follow-up of 11.4 years.

PATIENTS AND METHODS

Patients age 65 years or older with early breast cancer were randomly assigned to either standard adjuvant chemotherapy (physician's choice of either cyclophosphamide, methotrexate, and fluorouracil or cyclophosphamide and doxorubicin) or capecitabine. An adaptive Bayesian design was used to determine sample size and test noninferiority of capecitabine. The primary end point was RFS.

RESULTS

The design stopped accrual with 633 patients at its first sample size assessment. RFS remains significantly longer for patients treated with standard chemotherapy. At 10 years, in patients treated with standard chemotherapy versus capecitabine, the RFS rates were 56% and 50%, respectively (hazard ratio [HR], 0.80; P = .03); breast cancer-specific survival rates were 88% and 82%, respectively (HR, 0.62; P = .03); and overall survival rates were 62% and 56%, respectively (HR, 0.84; P = .16). With longer follow-up, standard chemotherapy remains superior to capecitabine among hormone receptor-negative patients (HR, 0.66; P = .02), but not among hormone receptor-positive patients (HR, 0.89; P = .43). Overall, 43.9% of patients have died (13.1% from breast cancer, 16.4% from causes other than breast cancer, and 14.1% from unknown causes). Second nonbreast cancers occurred in 14.1% of patients.

CONCLUSION

With longer follow-up, RFS remains superior for standard adjuvant chemotherapy versus capecitabine, especially in patients with hormone receptor-negative disease. Competing risks in this older population dilute overall survival benefits.

HER family protein expression and activation predicts response to combination T-DM1/pertuzumab in HER2+ patients in the I-SPY 2 TRIAL

3133

Background: T-DM1 (T), a conjugate of the anti-HER2 therapeutic antibody trastuzumab and the microtubule assembly inhibitor emtansine, was administered in combination with pertuzumab (P), an anti-HER2 therapeutic antibody, to HER2+ breast cancer patients in the I-SPY 2 TRIAL, and graduated in all HER2+ subtypes. Pre-specified biomarker analysis was performed to identify candidate biomarkers associated with pCR within the HER family and cell proliferation pathways in patients treated with T+P. We hypothesized that quantitative measurement and activation of HER2 and activation of its major dimerization partner, EGFR would predict response to T+P. Methods: In the T+P treatment arm, 49 had RPPA and pCR data. 40 RPPA endpoints including 14 total/phospho-proteins in the HER family were assessed for association with pCR using logistic regression (likelihood ratio test; p < 0.05). Analysis was also performed adjusting for HR status and within HR subsets. Markers were analyzed individually; multiple comparison correction (Benjamini-Hochberg) was applied to all p-values. Our statistics are descriptive and do not adjust for multiplicities of other biomarkers outside this study. Results: Of the endpoints tested, only quantitative total HER2 expression, phospho-HER2 (Y1248 and Y877), phospho-EGFR (Y1173 and Y1068), and phospho-SHC Y317 had a positive association with response in the population as a whole, and in a model adjusting for HR status (BH p < 0.05). In HR subset analysis, these 5 analytes had uncorrected p < 0.05 regardless of HR subtype but only survived p-value correction in HR+ tumors. Conclusions: Quantitative measurement of HER2 protein positively associates with response to T+P in patients already identified as HER2+ by central IHC and FISH testing. Activation of HER2 and its dimerization partner, EGFR, also associate with response to T+P in HR+ patients. While our results need to be validated in larger prospective trials, they indicate that new approaches to measure more quantitatively the amount and activation state of HER2 and activated EGFR may more effectively identify patients that respond to HER2 targeted therapies than HER2 IHC and FISH alone.

Quantitative MHC II protein expression levels in tumor epithelium to predict response to the PD1 inhibitor pembrolizumab in the I-SPY 2 Trial

2631

Background: Response to immune checkpoint inhibitors has been associated with immune activation and mutational load within a tumor. Previous results in other tumors have implicated MHC II protein tumor cell expression as a response predictor to immune checkpoint inhibitors. In the I-SPY 2 TRIAL, the anti-PD1 therapeutic antibody pembrolizumab (P) was available to HER2-negative subtypes and graduated in both the HR+/HER2- and TNBC signatures. Pre-specified biomarker analysis was performed to test tumor MHC II expression as a predictor of response to P in the I-SPY 2 TRIAL based on its central role in tumor antigen presentation. Methods: 156 patients (P: 67, controls: 89) had RPPA and pCR data. RPPA-based quantitative data for pan-MHC II protein isotypes HLA-DR/DP/DQ/DX and HLA-DR protein isotype was obtained from LCM-enriched tumor epithelium, and protein levels were assessed for association with pCR in the P and control arms separately using the Wilcoxon Rank Sum test (p < 0.05). Analysis was also performed in the HR+ and HR- subgroups. Markers were analyzed individually; p-values are descriptive and were not corrected for multiple comparisons. Results: Across all P- treated patients, the HLA class II molecules –DR and -DR/DP/DQ/DX had a positive association with response to P (p = 0.014 and p = 0.001). Expression of HLA-DR/DP/DQ/DX also had a positive association with response to P in HR+ tumors. Neither of these associations were seen in the control arm samples. Conclusions: The observation of elevation of MHC II protein expression in HER2- responding patients treated with P suggests that activation of antigen peptide exchange facilitated by these molecules in T and B cells may enhance response to P treatment.

CALGB (Alliance) 40603: Long-term outcomes (LTOs) after neoadjuvant chemotherapy (NACT) +/- carboplatin (Cb) and bevacizumab (Bev) in triple-negative breast cancer (TNBC)

591

Background: Both Cb and Bev demonstrate activity when combined with standard chemotherapy in TNBC. CALGB 40603 is a 2x2 randomized trial that previously demonstrated that adding Cb to NACT significantly increased pathologic complete responses in the breast/axilla (pCR), while adding Bev did not (Sikov, JCO 2015). Here we report 5-year LTOs and assess factors that influenced them. Methods: 443 patients with clinical stage II-III previously untreated TNBC received 12 weeks of paclitaxel (wP) +/- Cb then dose-dense AC, +/- Bev before surgery. The primary endpoint was pCR. Analyses of LTOs (event-free survival (EFS), distant recurrence-free interval (DRFI) and overall survival (OS)), impact of residual cancer burden and other variables were secondary. Results: Median follow-up was 5.7 years (y); 5y EFS was 70.9% (95% CI; 66.7%-75.4%), DRFI 76.3% (72.3%-80.5%) and OS 76.9% (72.9%-81.2%). Pretreatment clinical stage and achieving pCR correlated with LTOs, while age, race, subtype (basal-like vs. not) and tumor grade did not. Among pCR 5y EFS was 86.4% vs. 57.5% for non-pCR (HR 0.28, 0.19-0.43), OS was 88.7% vs 66.5% (HR = 0.28, 0.17-0.44). This relationship was similar in all trial arms. Any residual disease conferred poorer outcome; compared with pCR/Residual Cancer Burden (RCB) 0, EFS HRs were 2.29 (1.32-3.97), 3.01 (1.90-4.74), and 9.67 (5.66-16.51) for RCBI, II and III, respectively. There were no improvements in LTOs with Cb (EFS HR 0.99, 0.70-1.40) or Bev (EFS HR 0.91, 0.64-1.29). In an exploratory analysis, receipt of ≥11 doses of wP was associated with better EFS (HR 1.92, 1.33-2.77); this was particularly notable in Cb-treated arms. Conclusions: As expected, regardless of treatment arm pCR was associated with markedly better LTOs, and pts with any residual disease had significantly worse outcomes. The addition of Cb or Bev to standard NACT for TNBC did not improve LTOs in this trial, although it should be noted that the trial was not powered for this endpoint. Omission of chemotherapy doses may result in poorer outcomes, especially among Cb-treated pts, which may warrant further evaluation. Support: U10CA180821; U10CA180882; Genentech; https://acknowledgments.alliancefound.org ; NCT00861705 Clinical trial information: NCT00861705.

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

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 (&gt;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&lt;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 P2-07-03: Refining neoadjuvant predictors of three year distant metastasis free survival: Integrating volume change as measured by MRI with residual cancer burden

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&lt;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 &lt;0.00001). The RCB index is also significantly associated with DRFS adjusting for subtype (Wald p&lt;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 P3-08-04: Transient state change, but not permanent subtype change, after HER2-targeted therapy for HER2-positive breast cancer

Background: In CALGB 40601 (Alliance, NCT00770809), a neoadjuvant phase III trial of paclitaxel and trastuzumab with or without lapatinib for 12 weeks for patients with HER2-positive breast cancer, 33% of pretreatment tumors were Luminal A subtype, however, 69% of post-treatment samples with residual disease were Luminal A subtype. In addition, 71% of Luminal B (12/17) and 67% of HER2-Enriched (6/9) tumors changed into Luminal A, while 80% of Luminal A (20/24) remained Luminal A (Carey et al. J Clin Oncol. 2016). It is not known whether this shift to Luminal A was transient or permanent.

Methods: We selected matched pairs of pre- and post-treatment 40601 samples with tumor purity &gt;10% based upon DNA analyses to ensure all samples contained tumor. PAM50 intrinsic subtyping was applied to the 40601 samples gene expression data using a two-step normalization process based on The Genome Cancer Atlas, and PAM50 training set. In addition, a HER2-enriched expression subtype patient-derived xenograft (PDX) tumor called WHIM35, was studied and was either untreated (n=10), or treated with lapatinib at 220 mg/kg for 1 week (wk) (n=5), for 2 wks (n=8), or for 3 wks (n=4). We also treated WHIM35 tumors with lapatinib for 2 wks (on) and then removed laptinib for 1 wk (off) (n=6), or for 2 wks on and 2-4 wk off (n=6), and finally for 3 wks on, and 1 wk off (n=3). PAM50 intrinsic subtyping was applied to the PDX gene expression data and subtype assessed as well as a genomic-based proliferation score. ANOVA p-values were calculated by comparing median values across all gene signature or correlation scores.

Results: We found 10 pairs of 40601 samples that kept their tumor purity values, however, their subtype changed to Luminal A after treatment (i.e., in the residual disease), and in these cases no minor tumor subclone became a dominant clone in the post treatment sample. Pretreatment subtypes were 6 Luminal B, 3 Luminal A, and 1 HER2-enriched. The tumor purity values did not change after the treatments, but correlation to Luminal A was significantly higher (p=0.01), while correlation to HER2-enriched (p=0.004) and proliferation signature scores (p=0.003) were significantly lower in the post-treatment samples. Among the WHIM35 PDX tumors, one sample changed its subtype from HER2-enriched to Luminal A after the lapatinib treatment and the rest remained HER2-enriched, suggesting environmental differences between patient samples and the PDX model. However, correlation to Luminal A was significantly higher in all lapatinib treated WHIM35 samples (p=8.3e-12), and notably went back to the initial low levels just one week after removing lapatinib. Likewise, correlation to HER2-enriched (p=1.2e-10) and proliferation signature scores (p=6.2e-12) also got lower while treated with lapatinib, but went back to the initial levels after cessation of treatment.

Conclusions: Our findings suggest that the apparent subtype change during HER2-targeting therapy is not permanent, but is more likely a transient state change from a HER2-enriched subtype into a more Luminal A-like state. When we plan additional treatment strategies using residual disease phenotypes, it may not be clear what is the true subtype of the sample due to this inherent plasticity.

Citation Format: Tanioka M, Parker JS, Henry LN, Tolaney S, Dang C, Krop IE, Harris L, Polley M, Berry DA, Winer EP, Carey LA, Perou CM. Transient state change, but not permanent subtype change, after HER2-targeted therapy for HER2-positive breast cancer [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 P3-08-04.

MK-2206 and Standard Neoadjuvant Chemotherapy Improves Response in Patients With Human Epidermal Growth Factor Receptor 2-Positive and/or Hormone Receptor-Negative Breast Cancers in the I-SPY 2 Trial

PURPOSE

The phosphatidylinositol 3-kinase/Akt/mammalian target of rapamycin is a key pathway of survival and therapeutic resistance in breast cancer. We evaluated the pan-Akt inhibitor MK-2206 in combination with standard therapy in patients with high-risk early-stage breast cancer.

PATIENTS AND METHODS

I-SPY 2 is a multicenter, phase II, open-label, adaptively randomized neoadjuvant platform trial that screens experimental therapies and efficiently identifies potential predictive biomarker signatures. Patients are categorized by human epidermal growth factor receptor 2 (HER2), hormone receptor (HR), and MammaPrint statuses in a 2 × 2 × 2 layout. Patients within each of these 8 biomarker subtypes are adaptively randomly assigned to one of several experimental therapies, including MK-2206, or control. Therapies are evaluated for 10 biomarker signatures, each of which is a combination of these subtypes. The primary end point is pathologic complete response (pCR). A therapy graduates with one or more of these signatures if and when it has an 85% Bayesian predictive probability of success in a hypothetical phase III trial, adjusting for biomarker covariates. Patients in the current report received standard taxane- and anthracycline-based neoadjuvant therapy without (control) or with oral MK-2206 135 mg/week.

RESULTS

MK-2206 graduated with 94 patients and 57 concurrently randomly assigned controls in 3 graduation signatures: HR-negative/HER2-positive, HR-negative, and HER2-positive. Respective Bayesian mean covariate-adjusted pCR rates and percentage probability that MK-2206 is superior to control were 0.48:0.29 (97%), 0.62:0.36 (99%), and 0.46:0.26 (94%). In exploratory analyses, MK-2206 evinced a numerical improvement in event-free survival in its graduating signatures. The most significant grade 3-4 toxicity was rash (14% maculopapular, 8.6% acneiform).

CONCLUSION

The Akt inhibitor MK-2206 combined with standard neoadjuvant therapy resulted in higher estimated pCR rates in HR-negative and HER2-positive breast cancer. Although MK-2206 is not being further developed at this time, this class of agents remains of clinical interest.

Integrated Analysis of RNA and DNA from the Phase III Trial CALGB 40601 Identifies Predictors of Response to Trastuzumab-Based Neoadjuvant Chemotherapy in HER2-Positive Breast Cancer

Purpose: Response to a complex trastuzumab-based regimen is affected by multiple features of the tumor and its microenvironment. Developing a predictive algorithm is key to optimizing HER2-targeting therapy.Experimental Design: We analyzed 137 pretreatment tumors with mRNA-seq and DNA exome sequencing from CALGB 40601, a neoadjuvant phase III trial of paclitaxel plus trastuzumab with or without lapatinib in stage II to III HER2-positive breast cancer. We adopted an Elastic Net regularized regression approach that controls for covarying features within high-dimensional data. First, we applied 517 known gene expression signatures to develop an Elastic Net model to predict pCR, which we validated on 143 samples from four independent trials. Next, we performed integrative analyses incorporating clinicopathologic information with somatic mutation status, DNA copy number alterations (CNA), and gene signatures.Results: The Elastic Net model using only gene signatures predicted pCR in the validation sets (AUC = 0.76). Integrative analyses showed that models containing gene signatures, clinical features, and DNA information were better pCR predictors than models containing a single data type. Frequently selected variables from the multiplatform models included amplifications of chromosome 6p, TP53 mutation, HER2-enriched subtype, and immune signatures. Variables predicting resistance included Luminal/ER⁺ features.Conclusions: Models using RNA only, as well as integrated RNA and DNA models, can predict pCR with improved accuracy over clinical variables. Somatic DNA alterations (mutation, CNAs), tumor molecular subtype (HER2E, Luminal), and the microenvironment (immune cells) were independent predictors of response to trastuzumab and paclitaxel-based regimens. This highlights the complexity of predicting response in HER2-positive breast cancer. Clin Cancer Res; 24(21); 5292-304. ©2018 AACR.

Signature program: a platform of basket trials

Investigating targeted therapies can be challenging due to diverse tumor mutations and slow patient accrual for clinical studies. The Signature Program is a series of 8 phase 2, agent-specific basket protocols using a rapid study start-up approach involving no predetermined study sites. Each protocol evaluated 1 agent (buparlisib, dovitinib, binimetinib, encorafenib, sonidegib, BGJ398, ceritinib, or ribociclib) in patients with solid or hematologic malignancies and an actionable mutation. The primary endpoint of each study was the clinical benefit rate (ie, complete or partial response, or stable disease) at 16 weeks. A total of 192 individual sites were opened in the United States, with a median start-up time of 3.6 weeks. The most common tumor types among the 595 treated patients were colorectal (9.2%), non-small cell lung adenocarcinoma (9.1%), and ovarian (8.4%). Frequent genetic alterations were in PIK3CA, RAS, p16, and PTEN. Overall, 30 partial or complete responses were observed with 6 compounds in 16 tumor types. The Signature Program presents a unique and successful approach for rapid signal finding across multiple tumors and allowed various agents to be evaluated in patients with rare alterations. Incorporating these program features in conventional studies could lead to improved trial efficiencies and patient outcomes.

Introduction to the Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Models

The Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Working Group is a consortium of National Cancer Institute-sponsored investigators who use statistical and simulation modeling to evaluate the impact of cancer control interventions on long-term population-level breast cancer outcomes such as incidence and mortality and to determine the impact of different breast cancer control strategies. The CISNET breast cancer models have been continuously funded since 2000. The models have gone through several updates since their inception to reflect advances in the understanding of the molecular basis of breast cancer, changes in the prevalence of common risk factors, and improvements in therapy and early detection technology. This article provides an overview and history of the CISNET breast cancer models, provides an overview of the major changes in the model inputs over time, and presents examples for how CISNET breast cancer models have been used for policy evaluation.

A Bayesian Simulation Model for Breast Cancer Screening, Incidence, Treatment, and Mortality

BACKGROUND

The important but complicated research questions regarding the optimization of mammography screening for the detection of breast cancer are unable to be answered through any single trial or a simple meta-analysis of related trials. The Cancer Intervention and Surveillance Network (CISNET) breast groups provide answers using complex statistical models to simulate population dynamics. Among them, the MD Anderson Cancer Center (Model M) takes a unique approach by not making any assumptions on the natural history of breast cancer, such as the distribution of the indolent time before detection, but simulating only the observable part of a woman's disease and life.

METHODS

The simulations start with 4 million women in the age distribution found in the year 1975, and follow them over several years. Input parameters are used to describe their breast cancer incidence rates, treatment efficacy, and survival. With these parameters, each woman's history of breast cancer diagnosis, treatment, and survival are generated and recorded each year. Research questions can then be answered by comparing the outcomes of interest, such as mortality rates, quality-adjusted life years, number of false positives, differences between hypothetical scenarios, such as different combinations of screening and treatment strategies. We use our model to estimate the relative contributions of screening and treatments on the mortality reduction in the United States, for both overall and different molecular (ER, HER2) subtypes of breast cancer.

RESULTS

We estimate and compare the benefits (life-years gained) and harm (false-positives, over-diagnoses) of mammography screening strategies with different frequencies (annual, biennial, triennial, mixed) and different starting (40 and 50 years) and end ages (70 and 80 years).

CONCLUSIONS

We will extend our model in future studies to account for local, regional, and distant disease recurrences.

Abstract GS3-02: Invasive disease-free survival and gene expression signatures in CALGB (Alliance) 40601, a randomized phase III neoadjuvant trial of dual HER2-targeting with lapatinib added to chemotherapy plus trastuzumab

Purpose

Dual HER2 targeting increases pathologic complete response (pCR) rate to neoadjuvant therapy and improves outcomes in both early and metastatic HER2-positive disease. CALGB 40601 is a randomized phase III trial examining the impact of dual HER2 blockade consisting of trastuzumab (H) and lapatinib (L) added to paclitaxel (T) on pCR, considering tumor and microenvironment molecular features. We previously found that pCR was numerically but not significantly increased with dual therapy, and that tumor molecular subtype and evidence of immune activation significantly and independently affected pCR (Carey et al, JCO 2016). In this secondary analysis, we sought to evaluate the effects of treatment arm and gene expression-defined subgroups on invasive disease free survival (IDFS).

Patients and Methods

Patients (Pts) with stage II to III HER2-positive breast cancer underwent tumor biopsy followed by random assignment with equal probabilityto paclitaxel plus trastuzumab alone (TH) or with the addition of lapatinib (THL) for 16 weeks before surgery. A paclitaxel plus lapatinib (TL) arm was closed early based on reports of futility from other trials. A secondary endpoint was IDFS, defined as the time from surgery until local or distant recurrence, new primary, or death from any cause, whichever was first. Gene expression signatures were identified by RNA sequencing.

Results

Between 12/2008 and 2/2012, 305 pts were enrolled. 261 pts had IDFS and gene expression information available (THL, n = 103; TH, n =101; TL, n = 57); there were no significant differences in clinical characteristics between this subset and the entire population. The median IDFS follow-up was 4.6 years with 40 IDFS events having occurred (THL, n=7; TH, n=19; TL, n=14). IDFS was significantly longer in the THL arm compared to standard TH (HR=0.34; 95% CI: 0.14-0.82; p=0.02). IDFS was also significantly longer among pCR than non-pCR pts (HR=0.40; 95% CI: 0.19-0.81; p=0.01), and did not differ by hormone receptor (HR) status, clinical stage, tumor size, race, menopausal status or age. Among gene expression signatures, only immune activation measured by an IgG signature was associated with longer IDFS (HR=0.71; 95% CI: 0.51-0.98; p=0.04); this signature was previously also associated with pCR. Multivariate analysis showed dual therapy (HR=0.35; p=0.02), pCR (HR=0.36; p=0.01), IgG (HR=0.69; p=0.05), and molecular subtype (LumA vs HER2E, HR=0.24, p=0.005) were associated with longer IDFS. A subgroup analysis by hormone receptor status revealed that among pts with HR+ disease, pts with luminal A experienced longer IDFS (HR=0.23; p=0.02) compared to those with luminal B or HER2-enriched molecular subtypes.

Conclusion

Dual HER2-targeting with lapatinib added to 16 weeks of TH produced significantly longer IDFS than TH alone, despite modest effects on pCR. Similar to pts with HER2-negative disease, pts with luminal A had better IDFS than those with other molecular subtypes. Immune activation as measured by RNA-based signature independently predicted both pCR and IDFS.

Support: U10CA180882, U10CA180821, U24CA196171, P50-CA58823, Susan G Komen, BCRF

Citation Format: Krop IE, Hillman D, Polley M-Y, Tanioka M, Parker J, Huebner L, Henry NL, Tolaney SM, Dang C, Harris L, Berry DA, Perou CM, Partridge A, Winer EP, Carey LA. Invasive disease-free survival and gene expression signatures in CALGB (Alliance) 40601, a randomized phase III neoadjuvant trial of dual HER2-targeting with lapatinib added to chemotherapy plus trastuzumab [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 GS3-02.