Neoadjuvant Breast Cancer Trials Research Articles

Abstract A019: IGF-1R protein pathway activation is associated with pathologic complete response to an anti-IGF-1R regimen (paclitaxel, ganitumab, and metformin) in the I-SPY2 neoadjuvant breast cancer trial

Abstract BACKGROUND: The addition of PGM followed by doxorubicin/cyclophosphamide versus control was evaluated as neoadjuvant therapy. Here IGF-1R pathway based protein and phosphoprotein (p) biomarkers were examined for their predictive utility. METHODS: Reverse phase protein array evaluated 102 pretreatment PGM and 169 control HER2- specimens. 32 pre-specified biomarker candidates were examined. A logistic regression model adjusted for hormone receptor (HR) status. The Benjamini-Hochberg (BH) method adjusted for multiple hypothesis testing. ROC analysis identified dichotomizing thresholds for select biomarkers. RESULTS: In the entire PGM population in a model adjusting for HR status, higher levels of pIGF-1R (Y1135/Y1136)/IR (Y1150/Y1151) (OR=2.13 p<0.002; BH p<0.05) and lower levels of p27 T187 (OR= 0.41 p<0.002; BH p<0.05) were significantly associated with pCR. Downstream IGF-1R signaling proteins were nominally associated with pCR (IRS-1 S612, p90 RSK S380, FOXO1 T24/FOXO3a T32). In HR+ tumors (n=58), pIGF-1R retained its significant positive association with pCR (OR=4.08 P<0.002; LR p<0.05), with an AUC of 0.79 [95% CI: 0.56-1]. Using an optimal dichotomizing threshold, 16% (9/58) of HR+HER2- were classified pIGF-1R.IR-High; and 56% (5/9) of these patients achieved pCR vs. 6% (3/49) in the pIGF1R.IR-Low subset. In TN patients (n=44), pIGF-1R did not associate with response. However, lower pp27 remained nominally associated with higher pCR rates for PGM treatment (OR=0.42 p<0.009; BH p>0.05) with an AUC of 0.74 [95% CI: 0.58-0.89]; and when optimally dichotomized, 52% (13/25) of pp27 Low TN patients achieved pCR vs. 12% (2/17) in the pp27 High group. None of these PGM-response-predictive biomarkers associated with response in the control arm. Total receptor levels did not associate with response. CONCLUSION: We are the first to show that pre-treatment levels of IGF-1R protein pathway activation-based signaling phosphoproteins, including levels of pIGF-1R, the drug target for ganitumab, may be predictive biomarkers for drugs targeting this receptor especially in the HR+ subset. Citation Format: Emanuel F. Petricoin, Denise M. Wolf, Christina Yau, Julia Wulfkuhle, Laura van ‘t Veer, Rosa I. Gallagher, Gillian L. Hirst, Lamorna Brown-Swigart, Laura J. Esserman, Douglas Yee. IGF-1R protein pathway activation is associated with pathologic complete response to an anti-IGF-1R regimen (paclitaxel, ganitumab, and metformin) in the I-SPY2 neoadjuvant breast cancer trial [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A019.

Treatment efficacy score: a better surrogate for arm-level survival differences in neoadjuvant breast cancer trials?

Neoadjuvant chemotherapy is widely used in the therapy of stage II-III breast cancers and pathologic complete response (pCR; ypT0/is, ypN0) predicts excellent long-term survival. However, the correlation between improvement in pCR rate and survival is highly variable across trials. A major limitation of pCR is that it does not capture downstaging in patients with residual disease. We previously introduced the residual cancer burden (RCB) score that measures pathologic response on a continuous scale. Comparison of RCB score distributions between trial arms reflects treatment efficacy more accurately than differences in pCR rate. We developed the treatment efficacy score (TES) as a new statistical metric that appears to be a better surrogate for trial arm-level survival improvement than pCR rate difference.

Association of baseline ROR1 and ROR2 gene expression with clinical outcomes in the I-SPY2 neoadjuvant breast cancer trial

PurposeROR1 and ROR2 are Type 1 tyrosine kinase-like orphan receptors for Wnt5a that are associated with breast cancer progression. Experimental agents targeting ROR1 and ROR2 are in clinical trials. This study evaluated whether expression levels of ROR1 or ROR2 correlated with one another or with clinical outcomes.MethodsWe interrogated the clinical significance of high-level gene expression of ROR1 and/or ROR2 in the annotated transcriptome dataset from 989 patients with high-risk early breast cancer enrolled in one of nine completed/graduated/experimental and control arms in the neoadjuvant I-SPY2 clinical trial (NCT01042379).ResultsHigh ROR1 or high ROR2 was associated with breast cancer subtypes. High ROR1 was more prevalent among hormone receptor-negative and human epidermal growth factor receptor 2-negative (HR-HER2-) tumors and high ROR2 was less prevalent in this subtype. Although not associated with pathologic complete response, high ROR1 or high ROR2 each was associated with event-free survival (EFS) in distinct subtypes. High ROR1 associated with a worse EFS in HR + HER2- patients with high post-treatment residual cancer burden (RCB-II/III) (HR 1.41, 95% CI = 1.11–1.80) but not in patients with minimal post-treatment disease (RCB-0/I) (HR 1.85, 95% CI = 0.74–4.61). High ROR2 associated with an increased risk of relapse in patients with HER2 + disease and RCB-0/I (HR 3.46, 95% CI = 1.33–9.020) but not RCB-II/III (HR 1.07, 95% CI = 0.69–1.64).ConclusionHigh ROR1 or high ROR2 distinctly identified subsets of breast cancer patients with adverse outcomes. Further studies are warranted to determine if high ROR1 or high ROR2 may identify high-risk populations for studies of targeted therapies.

Abstract P5-13-18: Upregulation of immune response biomarkers by ribociclib plus endocrine therapy (ET) in paired tumor samples from phase I studies

Abstract Background: In addition to inhibiting cell cycle progression, CDK4/6 inhibitors have been found to modulate anti-cancer immune response (Goel S, et al. Nature. 2017;548:471-475). Data from preclinical studies suggested multiple mechanisms—involving changes in both cancer cells and immune cells—by which CDK4/6 inhibition can enhance anti-cancer immunity. These mechanisms include increased antigen presentation, interferon response triggering, and regulatory T-cell suppression. Clinical correlates to preclinical observations have so far been obtained using paired biopsies from neoadjuvant breast cancer trials (Johnston S, et al. J Clin Oncol. 2019;37:178-189; Hurvitz S, et al. Clin Cancer Res. 2020; ;26:566-80). Here, we describe a gene expression analysis of paired pre- and on-treatment biopsies from CLEE011A2115C and CLEE011X2107, two phase I clinical trials evaluating ribociclib in combination with ET in the metastatic breast cancer (MBC) setting. Methods: The nCounter PanCancer IO 360 Panel (NanoString) was used to quantify expression of 770 genes in 7 pairs of tumor samples (baseline vs. cycle 1 day 15) from two phase I trials in the MBC setting (5 patients from CLEE011A2115C and 2 from CLEE011X2107). All patients were treated with ribociclib and an ET. Pairwise differential gene expression analysis of individual genes and previously published immune-related gene signatures was conducted (Bedognetti D, et al. Curr Opin Oncol. 2015;27:433-444). Results: Many genes that were markedly suppressed with treatment (eg, MKI67, MYC, CDK2, CCNB1, TYMS, and DNMT1) were related to proliferation, DNA replication, and G1/S transition of the cell cycle, as expected. Interestingly, expression of numerous genes involved in immune response was increased. These were mostly interferon-regulated genes; particularly, a gene signature indicative of a T cell-inflamed tumor microenvironment (Ayers M, et al. J Clin Invest. 2017;127:2930-2940) was upregulated. Immune-related genes tended to preferentially increase with treatment in patients who later experienced a clinical response. Since bulk RNA from tumor biopsies was analyzed, we could not distinguish whether the observed expression changes reflected increased infiltration by immune cells or an endogenous interferon response in cancer cells. The latter could be triggered by DNMT1 suppression (as previously described), which then promotes T cell-mediated immunity by increasing antigen presentation and chemokine production in cancer cells. Conclusions: This analysis was conducted with a small sample size and is considered hypothesis generating; further investigation is needed. Cell cycle and proliferation markers showed robust suppression by ribociclib-based treatment regimens, as expected. Conversely, a notable increase in immune-related genes was detected that tended to occur preferentially in patients who later experienced more favorable clinical outcomes. Both changes occurred early (cycle 1 day 15). To our knowledge, this is the first clinical biomarker report of immune activation mediated by CDK4/6 inhibition in MBC. Citation Format: Dejan Juric, Chong Ma, Ralph Tiedt, Yoon-Sim Yap, Joanne Chiu, Pamela Munster, Roohi Ismail-Khan, Laura Garcia-Estevez, Ingrid A. Mayer, Carlos Becerra, Nadia Solovieff, Agnes Lteif, Faye Su, Yen-Shen Lu. Upregulation of immune response biomarkers by ribociclib plus endocrine therapy (ET) in paired tumor samples from phase I studies [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-13-18.

Abstract P5-14-09: How exclusion criteria adversely affects the enrolment of underserved groups in breast cancer clinical trials

Abstract BackgroundThere have been recent calls globally to improve clinical trial participation by underserved or under-represented patient groups. Underserved groups are populations unrepresented or disengaged from medical research or services despite having a disproportionately high healthcare burden. In breast cancer research, disparity in clinical trial participation of underserved groups and how this affects results and conclusions is not well researched. The purpose of this study is to assess inclusion and exclusion criteria in published phase III breast cancer clinical trials, over the last 10 years, that exclude underserved groups.MethodsMedline was searched for phase III randomised control trials evaluating interventional drugs for breast cancer in high-impact journals (Impact factor >3) published between January 1st 2010 and December 31st 2020.ResultsForty clinical trials were included. These included 22 metastatic, 10 adjuvant and 8 neo-adjuvant breast cancer trials. All 40 trials (100 %) had multiple exclusions that directly, or indirectly, affected underserved groups for clinical and non-clinical reasons. All trials apart from one did not explicitly justify the applied inclusion and exclusion criteria. Conclusions. The underserved groups directly excluded, as outlined in the results were elderly patients > 65 years and adolescents, patients with cognitive impairment or psychiatric conditions, pregnant and lactating women and patients with brain metastases. As well as being directly excluded, these and other underserved groups are also indirectly excluded by the eligibility criteria to a large extent, for example, bloodborne virus exclusions may affect trial participation of lower socioeconomic populations and the LGBTQ+ community. The trials we reviewed required participants to have a high level of renal, cardiac and hepatic functioning. Certain underserved groups are more likely to have organ impairment. For example, elderly people are more likely to have renal, liver or cardiac impairment due to co-morbidities or age alone. Healthy black individuals are more likely to have a higher baseline creatinine and lower Creatinine Clearance (Cr Cl) compared to white counterparts Clinical trial eligibility criteria both directly and indirectly excludes underserved groups from breast. cancer research. It is necessary to revise future eligibility criteria to further progress considerations on the inclusion of underserved groups in breast cancer research. Table 1.Clinical Trial Exclusions for Clinical ReasonsExclusion (N=40)CriteriaN %Upper age exclusion18 – 65 years only61518 – 70 years only512.518 – 75 years only25No upper age exclusion2767.5Lower age exclusion>18 years40100Prior or concurrent malignancy exclusionStrict exclusion*820≥ 3 years since diagnosis717.5≥5 years since diagnosis2050≥10 years since diagnosis25No exclusion37.5Blood borne virus exclusion:HIV:Strict exclusion*2870Excluded if on HAART25No exclusion1025Hepatitis B/C:Strict exclusion*2152.5Allowed if treated**37.5No exclusion1640Organ function exclusion:CardiacLVEF (%):>551025>502050No exclusion1025RenalCreatinine (mg/dl) >1.5 X ULN or Cr CL >60ml/min2665Creatinine (mg/dl) >2.5 X ULN or Cr Cl >50ml/min717.5Cr Cl >30410No exclusion/adequate function for treatment37.5HepaticAST/ALT:>1.5 X ULN1537.5>2.5 X ULN820>3.5 X ULN717.5>5 X ULN615No exclusion/adequate function for treatment410Brain or leptomeningeal metastases exclusion: (N=22)Strict exclusion*940.9Untreated or symptomatic or on steroids1359.1No exclusion00ECOG performance status exclusion:ECOG=0 or 12665ECOG=0 to 21435ECOG=0 to 300Exclusion on pregnant or lactating women:Pregnant or lactating women excluded40100 Table 2.Clinical Trial Exclusions for Non-clinical Reasons.Exclusion (N=40)CriteriaN%Language exclusion:English or other language00All languages acceptable40100Cognitive impairment exclusion:Strict exclusion820No direct exclusion3280Psychiatric history exclusion:Strict exclusion717.5Allowed if treated1640Total with exclusions2357.5No direct exclusion1742.5OtherInvestigator assessment regarding ability to comply with protocol3075Written Consent required40100 Citation Format: Carolyn Moloney, Frances Shiely. How exclusion criteria adversely affects the enrolment of underserved groups in breast cancer clinical trials [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-14-09.

Abstract P3-03-04: Challenges of achieving high image quality on breast MRI for quantitative measurements in the I-SPY 2 TRIAL

Abstract Purpose. To illustrate image quality issues that may impact quantitative measurements used to assess treatment response in a multi-site clinical trial. Background. Quantitative longitudinal measurements on breast MRI are used to assess patient response to neoadjuvant treatment in the multi-site I-SPY 2 TRIAL. A standardized MR protocol is distributed to sites prior to site initiation. Previous work presented image quality issues1, which may affect measurements that rely on automated computerized methods. Functional tumor volume (FTV), a primary imaging biomarker monitoring treatment response, was more predictive of pathological complete response for protocol adherent exams compared to non-adherent exams2. Image quality may also impact background parenchymal enhancement (enhancement level of normal fibroglandular tissue), which is being investigated as a secondary imaging biomarker. This presentation will show example images demonstrating the challenges of quantitative MR analysis in a multi-site clinical trial. Image quality issues include:. Motion. Motion due to patient movement during the MRI may result in skin, fat, and breast tissue being poorly defined and blurry. Mis-registration between pre- and post-contrast can cause errors in measurements. Threshold variation. For image processing, two signal intensity thresholds are applied to pixels within the region of interest (ROI), which may be adjusted when less than 50% of the tumor is segmented. The percent enhancement threshold is lowered when poorly enhancing areas of tumor are not segmented. The background threshold is lowered when a bright pixel within the ROI of the pre-contrast images causes relatively darker areas of the tumor to be poorly segmented. Scan duration variation. Scan duration is the time required to scan each T1-weighted acquisition phase. Scan duration variations occur if scan duration is outside the specified protocol range or differs from the scan duration of the patient’s baseline MRI. Longer scan duration may result in overestimation of FTV. Field of View. Field of view (FOV) is the anatomical area being imaged and is directly related to spatial resolution, which plays a key role in the FTV measurement. Incorrect FTV monitoring can occur if FOV is inconsistent between visits, outside the specified protocol range, or is overlarge for the patient. Discussion. The image quality required for measurements used to assess treatment response in I-SPY 2 differs from the image quality that is acceptable for diagnostic evaluation, including BIRADS category, longest diameter measurements, and visual assessment of washout characteristics. In I-SPY 2, 21 sites use a variety of MRI platforms. Since quantitative measurements are increasingly used to monitor treatment response and guide clinical decision-making, high quality images are essential. Strategies must be implemented to minimize imaging issues and further refine the quantitative measurements. Ongoing studies are examining the impact of image quality factors on accuracy of treatment response prediction. References. 1.Gibbs J et al. Abstract PS11-08: Operational standardization and quality assurance yield high acceptance rate for breast MRI in the I-SPY 2 TRIAL. Poster Session Abstracts. American Association for Cancer Research; 2021. 2.Onishi N et al. Impact of MRI Protocol Adherence on Prediction of Pathological Complete Response in the I-SPY 2 Neoadjuvant Breast Cancer Trial. Tomography. 2020 Jun. Table 1.Image quality issues observed in 1,749 I-SPY 2 MRIs submitted June 2019 to June 2021Image Quality IssueExams (percentage of total)Motion568 (32%)Threshold variation104 (6%)Scan duration variation83 (5%)FOV229 (13%) Citation Format: Teffany Joy Bareng, Jessica E Gibbs, Natsuko Onishi, David C Newitt, Barbara LeStage, I-SPY 2 TRIAL Imaging Working Group, I-SPY 2 TRIAL Coordinators, Nola M Hylton. Challenges of achieving high image quality on breast MRI for quantitative measurements in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-03-04.

Design of phase III trials with long-term survival outcomes based on short-term binary results.

Pathologic complete response (pCR) is a common primary endpoint for a phase II trial or even accelerated approval of neoadjuvant cancer therapy. If granted, a two-arm confirmatory trial is often required to demonstrate the efficacy with a time-to-event outcome such as overall survival. However, the design of a subsequent phase III trial based on prior information on the pCR effect is not straightforward. Aiming at designing such phase III trials with overall survival as primary endpoint using pCR information from previous trials, we consider a mixture model that incorporates both the survival and the binary endpoints. We propose to base the comparison between arms on the difference of the restricted mean survival times, and show how the effect size and sample size for overall survival rely on the probability of the binary response and the survival distribution by response status, both for each treatment arm. Moreover, we provide the sample size calculation under different scenarios and accompany them with the R package survmixer where all the computations have been implemented. We evaluate our proposal with a simulation study, and illustrate its application through a neoadjuvant breast cancer trial.

Locoregional recurrence risk after neoadjuvant chemotherapy: A pooled analysis of nine prospective neoadjuvant breast cancer trials

AimThis pooled analysis aimed to evaluate locoregional recurrence (LRR) rates of breast cancer (BC) after neoadjuvant chemotherapy (NACT) and to identify independent LRR predictors. Methods10,075 women with primary BC from nine neoadjuvant trials were included. The primary outcome was the cumulative incidence rate of LRR as the first event after NACT. Distant recurrence, secondary malignancy or death were defined as competing events. For identifying LRR predictors, surgery type, pathological complete response (pCR), BC subtypes and other potential risk factors were evaluated. ResultsMedian followup was 67 months (range 0–215), overall LRR rate was 9.5%, 4.1% in pCR versus 9.5% in non-pCR patients. Younger age, clinically positive lymph nodes, G3 tumours, non-pCR and TNBC but not surgery type were independent LRR predictors in multivariate analysis. Among BC subtypes, 5-year cumulative LRR rates were associated with higher risk in non-pCR versus pCR patients, which was significant for HR+/HER2- (5.9% vs 3.9%; HR = 2.32 [95%CI 1.22–4.43]; p = 0.011); HR-/HER2+ (14.8% vs 3.1%; HR = 4.26 [94%CI 2.35–7.71]; p < 0.001) and TNBC (18.5% vs 4.2%; HR = 4.10 [95%CI 2.88–5.82]; p < 0.001) but not for HR+/HER2+ (8.1% vs 4.8%; HR = 1.56 [95%CI 0.85–2.85]; p = 0.150). Within non-pCR subgroup, LRR risk was higher for HR-/HER2+ and TNBC vs HR+/HER2- (HR = 2.05 [95%CI 1.54–2.73]; p < 0.001 and HR = 2.77 [95%CI 2.27–3.39]; p < 0.001, respectively). ConclusionsThis pooled analysis demonstrated that young age, node-positive and G3 tumours, as well as TNBC, and non-pCR significantly increased the risk of LRR after NACT. Hence, there is a clear need to investigate better multimodality therapies in the post-neoadjuvant setting for high-risk patients.

Abstract P1-21-08: Application of machine learning to elucidate the biology predicting response in the I-SPY 2 neoadjuvant breast cancer trial

Abstract Background: Machine learning relies on algorithms that learn patterns in large, complex datasets to predict outcomes. The adaptive, neoadjuvant I-SPY 2 TRIAL evaluates novel agents added to standard therapy, and identifies their most responsive subtype. While previously proposed genes/signatures reflecting an agent’s mechanism of action predicted pathologic complete response (pCR) in some treatment arms/subtypes, not all arms had strong predictive biomarkers. We leverage machine learning to explore the limitations of using only known mechanisms of action in predicting pCR, and the extent to which biology outside known drug action improves response prediction in the first 10 arms of the trial. Methods: Our study involves 986 patients with pre-treatment gene expression and pCR data across 10 treatment arms including inhibitors of HER2: neratinib (N), pertuzumab (P), TDM1/P; AKT (MK-2206; M); IGF1R (ganitumab); HSP90 (ganetespib); PARP/DNA repair (veliparib/carboplatin; VC); ANG1/2 (AMG386); immune checkpoints (pembrolizumab; Pembro); and a shared control arm (Ctr). Each arm/receptor subtype group was evaluated independently for groups with at least 20 patients (n=19), with 25% of data held out as independent test sets. We implemented a 3-fold cross validation technique with 10 repeats using Random Forest ensemble algorithm with recursive feature elimination. In combination with clinical data, a three-pronged feature-selection approach was employed: (1) restricted to mechanism of action genes: AKT/PI3K/HER (m=10 genes), IGF1 (m=11), HSP90 (m=88), DNA repair (m=79), TIE1/2 (m=11), and immune (m=61), as well as HER2 amplicon genes; (2) expanded to include targeted pathways for all 10 agents/combinations plus ESR1 and proliferation genes (m=339); (3) an unbiased whole genome approach (m=17,990). Models were considered predictive if AUROC ≥ 0.75, Sensitivity ≥ 0.6 and Specificity ≥ 0.6 in cross validation and independent test sets. Results: Table 1 summarizes the results of our analysis (Yes=predictive; NA=no/insufficient data). Prediction of pCR using only genes reflecting the known mechanism of the drug succeeded in 5 subgroups, with DNA repair genes predicting VC response and immune genes predicting Pembro response in HR+HER2- and HR-HER2- subsets, and AKT/PI3K/HER + HER2 amplicon genes predicting (P) response in HR+HER2+ patients. Expansion of the feature set to include genes associated with all mechanisms of action of all drugs proved sufficient to produce good predictive models in 8 of 19 subgroups. Examples include DNA repair + immune genes predicting response to ganitumab in HR+HER2- and to (N) in HR+HER2+. An unbiased approach using all data yielded predictive power in 8 of 19 subgroups, including 5 with no predictive models from the first two approaches. Examples include HR-HER2- (N) predictors enriched for metabolic, cell division and membrane protein proteolytic processes; HR+HER2+ TDM1/P enriched for metabolic, stress response and cell cycle processes; and HR-HER2- MK-2206 predictors containing Ser/Thr kinases. In total, we identify predictive biomarkers in 14 of 19 subgroups across the three feature selection approaches. Conclusion: Our results suggests that hypothesis driven analysis restricted to assumed mechanisms of action of the experimental agents may be insufficient, and that exploration of possible off target effects may be needed to understand the underlying biology of response or resistance. Table 1. Model results across feature selection approachesHR+HER2-HR-HER2-HR+HER2+HR-HER2+Number of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedNumber of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedNumber of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedNumber of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedneratinib (pan anti-HER)NA32NoNoYes42NoYesYes23NoNoYespertuzumab (anti-HER2)NANA29YesYesNoNATDM1/Pertuzumab (anti-HER2)NANA35NoNoYesNAMK−2206 (AKT inhibitor)28NoNoNo32NoNoYesNANAganitumab (IGFR inhibitor)58NoYesNo48NoNoNoNANAganetespib (HSP90 inhibitor)48NoYesYes45NoNoNoNANAvelirapib/carboplatin (PARP inhibitor/DNA damage)33YesYesNo39YesYesNoNANAAMG386 (ANG1/2 inhibitor)62NoYesYes53NoNoNoNANApembrolizumab (immune checkpoint inhibitor)38YesYesNo29YesNoNoNANAHER2+ controlNANANANAHER2- control94NoNoYes84NoNoNoNANA Citation Format: Rosalyn W. Sayaman, Denise M. Wolf, Christina Yau, Julie Wulfkuhle, Emanuel Petricoin, Lamorna Brown-Swigart, Smita M. Asare, Gillian L. Hirst, Laura Sit, Nicholas O'Grady, Diane Hedistian, I-SPY 2 TRIAL Consortium, Laura J. Esserman, Mark A. LaBarge, Laura J van 't Veer. Application of machine learning to elucidate the biology predicting response in the I-SPY 2 neoadjuvant breast cancer 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 P1-21-08.

Abstract OT1-03-04: The importance of central pathology pCR review in an international multicenter neoadjuvant study in HER2 positive early breast cancer - Results of the ABP 980 LILAC trial

Abstract Pathological complete response (pCR) after neoadjuvant therapy is an accepted surrogate endpoint for breast cancer registration trials and is a strong prognostic biomarker especially in high-risk tumor biology. The LILAC study, a comparative trial for the trastuzumab biosimilar ABP 980, was the first international multicenter neoadjuvant breast cancer trial using local and central pathology review for pCR. Here we report concordance between local and central review for the most commonly used pCR definitions. This study included 725 patients with early HER2-positive breast cancer, comparing neoadjuvant ABP 980 and trastuzumab reference product (RP) in combination with anthracycline and taxane-containing chemotherapy. Equivalence of both arms was defined at a significance level of 0.05 by comparing the 2-sided 90% confidence interval (CI) for the risk difference (RD) of pCR between ABP 980 and RP within a predefined margin (-13%, 13%) using definition 2 as described below. pCR was evaluated in local laboratories and in a central laboratory blinded to the local result. The purpose of the independent, central review was to reduce the inter-pathologist variability and provide a more consistent assessment. Central review was performed by 2 independent pathologists; in cases of discordance the specimen was reviewed and decided by a third pathologist (adjudicator). The pCR definition in the primary analysis was no invasive breast cancer in breast and axillary nodes, regardless of ductal carcinoma in situ (DCIS). No invasive tumor in the breast was pCR definition 1, no invasive breast cancer in breast and axillary nodes regardless of DCIS was pCR definition 2, and no invasive breast cancer in breast and axillary nodes and absence of DCIS was pCR definition 3. The RDs and CIs were evaluated for local and central pCR review for all 3 pCR definitions. The results of the neoadjuvant LILAC study have been reported previously, demonstrating no clinically meaningful differences between ABP 980 and RP in HER2-positive early breast cancer. Of the 696 subjects who underwent surgery and had specimens evaluable for pCR review by the local pathologists, 669 specimens were available for central review. Rates of pCR in the local review were 51.1% (ABP 980) and 45% (RP) for definition 1, 48% (ABP 980) and 40.5% (RP) for definition 2, and 37.7% (ABP 980) and 29.6% (RP) for definition 3. The corresponding pCR rates in the central review were 51.3% and 47.3% for definition 1, 47.8% and 41.8% for definition 2, and 29.9% and 26.1% for definition 3. The CI for RD was within the predefined margins for pCR definition 1 in local and central review, whereas it exceeded the prespecified margin in local review for pCR definitions 2 and 3. In the central review the CI was within the margin for the pCR definitions 2 and 3, with the difference between local and central pathology review 1.6% for pCR definition 2 and 4.4% for pCR definition 3, respectively. RDs (90% CI) for all 3 pCR definitions are shown in the Table. The LILAC study demonstrated that a central pathology review for pCR is feasible in a large, international, multicenter neoadjuvant breast cancer trial. Our results show that concordance between local and central pathology can decrease with increasing complexity of the pCR definition. Based on the results, it may be justified to include a central pathology review in neoadjuvant multicenter breast cancer trials with strict pCR definitions. Citation Format: Hanz-Christian Kolberg, Marco Colleoni, Georgia Savva Demetriou, Patricia Santi, Hans Tesch, Yasuhiro Fujiwara, Vladimir Hanes. The importance of central pathology pCR review in an international multicenter neoadjuvant study in HER2 positive early breast cancer - Results of the ABP 980 LILAC 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 OT1-03-04.

188P - Risk factors for locoregional recurrence (LRR) after neoadjuvant chemotherapy: Pooled analysis of prospective neoadjuvant breast cancer (BC) trials

188P - Risk factors for locoregional recurrence (LRR) after neoadjuvant chemotherapy: Pooled analysis of prospective neoadjuvant breast cancer (BC) trials

HSR19-106: Association Between Pathological Complete Responses and Long-Term Survival Outcomes Among Triple-Negative Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

Objective: Pathological complete response (pCR) has been a commonly used endpoint in neoadjuvant trials for breast cancer (BC). A pooled analysis of 12 neoadjuvant BC trials by Cortazar et al (2014) reported a positive association between pCR and long-term survival outcomes among patients with general BC and certain subtypes including triple negative BC (TNBC). To update and extend the evidence to assess the association of pCR and survival outcomes in TNBC, this study reviewed and summarized cohort studies and recent clinical trials in the literature. Methods: English publications reporting association between pCR and survival outcomes among TNBC patients receiving neoadjuvant chemotherapy were searched in MEDLINE, EMBASE, Cochrane CENTRAL, and Northern Light Sciences Conference Abstracts. Full-text publications from all years and conference abstracts since year 2016 were identified. Relevant clinical trials, real-world evidence (RWE) studies, and meta-analyses were included for review and extraction. Results: Of total 1,880 publications retrieved, 35 reported association between pCR and survival outcomes for neoadjuvant TNBC (9 clinical trials, 21 RWE studies, and 5 pooled/meta-analyses). The sample size of TNBC patients varied between 25 and 1,645. Different pCR definitions were used across studies, of which absence of tumor in the breast and axillary nodes was most common (N=29). The prognostic impact of pCR was evaluated for multiple survival outcomes: overall survival (OS; N=19), disease-free survival (DFS; N=14), relapse-free survival (RFS; N=7), event-free survival (N=5), distant DFS (N = 4), and local RFS (N=2). Kaplan-Meier analysis was used to assess the association between pCR and these outcomes in 31 studies. Clear separation of survival curves in favor of pCR was observed in all the studies. Log-rank tests were conducted in 18 studies, and statistically significant association was reported in majority of them, except for 1 RWE study with small sample size (N=35) and 1 pooled analysis with a different pCR definition (absence of tumor in the breast) than most of the others. Cox proportional hazards model was used in 17 studies, wherein hazard ratios of survival outcomes comparing pCR vs non-pCR ranged from 0.08 to 0.53. Conclusions: Despite divergent study designs and pCR definitions, evidence from both clinical and real-world settings consistently suggest that pCR is a strong predictor of OS and other survival outcomes among TNBC patients.

Features of MRI stromal enhancement with neoadjuvant chemotherapy: a subgroup analysis of the ACRIN 6657/I-SPY TRIAL.

.Although the role of cancer-activated stroma in malignant progression has been well investigated, the influence of an activated stroma in therapy response is not well understood. Using retrospective pilot cohorts, we previously observed that MRI detected stromal contrast enhancement was associated with proximity to the tumor and was predictive for relapse-free survival in patients with breast cancer receiving neoadjuvant chemotherapy. Here, to evaluate the association of stromal contrast enhancement to therapy, we applied an advanced tissue mapping technique to evaluate stromal enhancement patterns within 71 patients enrolled in the I-SPY 1 neoadjuvant breast cancer trial. We correlated MR stromal measurements with stromal protein levels involved in tumor progression processes. We found that stromal percent enhancement values decrease with distance from the tumor edge with the estimated mean change ranging to () for time points T2 through T4. While not statistically significant, we found a decreasing trend in global stromal signal enhancement ratio values with the use of chemotherapy. There were no statistically significant differences between MR enhancement measurements and stromal protein levels. Findings from this study indicate that stromal features characterized by MRI are impacted by chemotherapy and may have predictive value in a larger study.

Abstract 855: p53 isoform Ä133p53â triple negative breast cancer and increased relapse with neoadjuvant taxanes

Abstract Background: Studies of TP53 mutation, protein expression and modifications of the p53 network in breast cancer yield a complexity which has so far hindered substantive clinical progress. The effects of p53 mutation and p53 protein expression in breast cancer is dependent on the breast cancer subtype and stressors involved. Since identifying differential expression of p53 isoform mRNAs in breast cancer a decade ago, we have demonstrated associations between individual p53 isoforms (p53â, p53ã, Ä133p53á, Ä133p53â), breast cancer cell behaviour and clinical outcomes. Co-expressed combinations of isoforms may influence canonical p53 (p53á), whether mutant or wild type. Patterns of p53 isoform co-expression may hold the key to understanding p53 functionality, responses to therapy and disease behaviour in breast cancer. Methods: Expression of p53á, p53â, p53ã, Ä133p53á, Ä133p53â, Ä133p53ã by reverse-transcription PCR was analysed for the EORTC 10994 neoadjuvant breast cancer trial. In 469 available primary breast tumors, 223 patients had been randomised to a preoperative anthracycline regimen (fluorouracil, epirubicin, cyclophosphamide [FEC]) and 246 patients to receive a taxane based regimen (three cycles of docetaxel followed by three cycles of docetaxel + epirubicin [T-ET]). TP53 status was assessed by use of the yeast functional assay (FASAY) on biopsy samples that contained at least 20% tumour cells. Breast tumor subtypes: HER2 positive, triple-negative (TNBC), luminal-A, luminal-B (HER2 negative) and luminal-B (HER2 positive) were determined using the pathological markers recommended by the St Gallen breast cancer consensus guidelines. The primary endpoint was progression-free survival (PFS) with 9 years median follow up at the time of analysis. Results: All cancers expressed multiple p53 isoform mRNAs; none expressed canonical p53 mRNA (p53á) alone. There was a strong association between the p53 isoforms with 4 combinations of co-expressed p53 mRNAs predominated. Expression patterns included: (a) 285 tumours co-expressed p53á, p53â, p53ã, Ä133p53á, and Ä133p53ã; (b) 122 tumours co-expressed p53á, p53â, p53ã, Ä133p53á, Ä133p53â and Ä133p53ã (c) in 25 Ä133p53 negative tumors, p53á, p53â and p53ã were co-expressed (d) 22 p53â negative tumors co-expressed p53á, p53ã, Ä133p53á and Ä133p53ã. While no individual p53 isoform expression was associated with PFS, among the 104 TNBC expressing all p53 isoforms (pattern (b), Ä133p53â positive tumors), patients had 11.31 times greater risk of relapse when treated with T-ET than when treated with FEC (95%CI 1.91-66.99, p&amp;lt;0.0075). Conclusions: Corroborating the experimental and animal model data that p53 isoform expression, p53 mutation and p53 protein expression influence the pluripotent nature of p53, patients bearing Ä133p53â positive TNBC may benefit more from treatment with FEC than T-ET in the neoadjuvant setting. Citation Format: Jean-Christophe Bourdon, Alexandra Diot, Valerie Meuray, Leen Slaets, Richard Iggo, Herve Bonnefoi, David Cameron, Alastair M. Thompson. p53 isoform Ä133p53â triple negative breast cancer and increased relapse with neoadjuvant taxanes. [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 855.

Serum carbonic anhydrase IX as predictive marker for efficacy of bevacizumab: A biomarker analysis from the GeparQuinto phase III neoadjuvant breast cancer trial.

11505Background: Appropriate biomarkers to guide selection of patients for treatment with bevacizumab are still urgently needed. In this study, we analyzed serum levels of carbonic anhydrase IX (sC...

Cancer Stem Cell Hypothesis: Implication for Cancer Prevention and Treatment

BACKGROUND: Cancer is a disease of genomic instability, evasion of immune cells, and adaptation of the tumor cells to the changing environment. Genetic heterogeneity caused by tumors and tumor microenvironmental factors forms the basis of aggressive behavior of some cancer cell populations.CONTENT: Cancers arise in self-renewing cell populations and that the resulting cancers, like their normal organ counterparts, are composed of hierarchically organized cell populations. Self – renewing “cancer stem cells” (CSC) maintain tumor growth and generate the diverse populations constituting the tumor bulk. CSCs in multiple tumor types have been demonstrated to be relatively resistant to radiation and chemotherapy. The clinical relevance of these studies has been supported by neoadjuvant breast cancer trials that demonstrated increases in the proportions of CSCs after therapy. The CSC hypothesis has tremendously important clinical implications.SUMMARY: In summary, a large and accumulating body of evidence supports the CSC hypothesis, which has important implications for cancer prevention and therapy. The ultimate test of this hypothesis will require clinical trials demonstrating that targeting of these pathways reduces cancer incidence and improves outcomes for patients with cancer.KEYWORDS: Somatic mutation, tumor heterogeneity, metastasis, epithelial-mesenchymal transition, CSC niche

Neoadjuvant trials in early breast cancer: pathological response at surgery and correlation to longer term outcomes - what does it all mean?

BackgroundNeoadjuvant breast cancer trials are important for speeding up the introduction of new treatments for patients with early breast cancer and for the highly productive translational research which they facilitate. Meta-analysis of trial data shows clear correlation between pathological response at surgery after neoadjuvant chemotherapy and longer-term outcomes at an individual patient level. However, this does not appear to be present on individual trial level analysis, when correlating improved outcome for the investigational arm for the primary endpoint (pathological response) with longer-term outcomes.DiscussionThe correlation between pathological response and longer-term outcomes in trials is dependent on many factors. These include definitions of pathological response, both complete and partial; assessment methods for pathological response at surgery; subtype and prognosis of breast cancer at diagnosis; number of patients recruited; adjuvant treatments; the mechanism of action of the investigational drug; the length of follow-up at the time of reporting; the definitions used in longer-term outcomes analysis; clonal heterogeneity; and new adaptive trial designs with additional neo/adjuvant treatments. Future developments of neoadjuvant breast cancer trials are discussed. With so many factors influencing the correlation of longer-term outcomes for trial-level data, we conclude that the main focus of neoadjuvant trials should remain the primary endpoint of pathological response.SummaryNeoadjuvant breast cancer trials are very important investigational studies that will continue to increase our understanding of the disease and offer the potential of more rapid introduction of new treatments for women with high-risk early breast cancer. In the future, we are likely to see both novel trial designs adopted in the neoadjuvant context and modifications of neo/adjuvant treatments for pathological non-responders within clinical trials. Both of these have the intention of improving longer-term outcomes for patients who do not have a good pathological response to first-line neoadjuvant treatment. If successful, these developments are likely to reduce further any positive correlation between pathological response and longer-term outcomes.

Standardization of pathologic evaluation and reporting of postneoadjuvant specimens in clinical trials of breast cancer: recommendations from an international working group

Neoadjuvant systemic therapy is being used increasingly in the treatment of early-stage breast cancer. Response, in the form of pathological complete response, is a validated and evaluable surrogate end point of survival after neoadjuvant therapy. Thus, pathological complete response has become a primary end point for clinical trials. However, there is a current lack of uniformity in the definition of pathological complete response. A review of standard operating procedures used by 28 major neoadjuvant breast cancer trials and/or 25 sites involved in such trials identified marked variability in specimen handling and histologic reporting. An international working group was convened to develop practical recommendations for the pathologic assessment of residual disease in neoadjuvant clinical trials of breast cancer and information expected from pathology reports. Systematic sampling of areas identified by informed mapping of the specimen and close correlation with radiological findings is preferable to overly exhaustive sampling, and permits taking tissue samples for translational research. Controversial areas are discussed, including measurement of lesion size, reporting of lymphovascular space invasion and the presence of isolated tumor cells in lymph nodes after neoadjuvant therapy, and retesting of markers after treatment. If there has been a pathological complete response, this must be clearly stated, and the presence/absence of residual ductal carcinoma in situ must be described. When there is residual invasive carcinoma, a comment must be made as to the presence/absence of chemotherapy effect in the breast and lymph nodes. The Residual Cancer Burden is the preferred method for quantifying residual disease in neoadjuvant clinical trials in breast cancer; other methods can be included per trial protocols and regional preference. Posttreatment tumor staging using the Tumor–Node–Metastasis system should be included. These recommendations for standardized pathological evaluation and reporting of neoadjuvant breast cancer specimens should improve prognostication for individual patients and allow comparison of treatment outcomes within and across clinical trials.

1910 Genomic Prognostic Profile (PAM50) and clinical-pathological characteristics in breast cancer: A prospective description of the associations found in clinical practicez

The relationship between achievement of a pathologic complete response (pCR) and favorable long-term outcome varies among breast cancer subtypes. We aimed to highlight which neoadjuvant treatment strategy could be most successful in each breast cancer subtype. A recent FDA meta-analysis on randomized neoadjuvant breast cancer trials suggests that the survival differences of patients with or without a pCR were less pronounced in luminal A-like tumors, despite the overall favorable prognosis of these patients. Moreover, even though the strong prognostic effect of pCR in HER2 positive and TNBC, the NOAH study was the only trial which showed a trend in surrogacy of pCR for long-term outcome in HER2-positive subtype. Results from GeparTrio study suggest that patients with hormone-positive tumors might need a response-guided approach, with either an intensification of treatment in case of an early response or a change to other chemotherapy in case of no early response. Furthermore, data from German neoadjuvant trials confirm that an increasing number of chemotherapy cycles is associated with a higher pCR rate, especially in patients with HER2-positive/hormone-positive tumors. In line with these suggestions, Tryphaena study showed a pCR rate that exceeding the 60% threshold, the highest pCR results presented in a large multicenter study. In TNBC, the highest pCR rate in the German neoadjuvant studies was obtained with the simultaneous application of docetaxel, doxorubicin and cyclophosphamide for 6 cycles. However, as shown in GaparQuinto and NSABP 40 trials, treatment effect in TNBC might be further maximized by adding bevacizumab, and two randomized neoadjuvant trials are expected this year to report data on the efficacy of carboplatin.

PG 6.02 Preventing invasive breast cancer in women at high risk based on benign/in situ pathology

1. The higher risk of second primary cancer may affect decisions in BRCA carriers about primary surgical option: breast conservation vs. bilateral mastectomies. 2. The SOFT data show the advantage of ovarian suppression plus hormonal therapy in premenopausal women requiring chemotherapy in treatment of their hormone receptor positive tumors. BRCA carriers would more likely undergo risk-reducing bilateral salpingo-oophorectomies rather than LHRH-agonist therapy. 3. Data from two neoadjuvant trials in triple negative breast cancer (GeparSEXTO and Alliance 4003) show an advantage for the use of platinum in BRCA carriers: The TNT trial shows a similar advantage in metastatic disease. Additional tumor biomarkers may predict response better than BRCA1/2 mutation status. 4. BRCA1/2 mutation carriers are eligible for the BIG/NRG adjuvant parp inhibitor trial, OlympiA, and other neoadjuvant trials. 5. BRCA mutation status may affect interventions to reduce the risk of additional primary cancers of the ovary (RRSO) and melanoma. Family members may use the information to reduce their risks of breast cancer, ovarian cancer, prostate cancer and possibly pancreatic cancer. Mechanisms of acquired resistance against therapies targeting the DNA repair pathways are emerging. In addition, genetic testing now frequently includes evaluation of additional genes that have been associated with increased breast cancer risk, including TP53, PTEN, STK11, and CDH1, as well as an expanding group of moderate penetrance genes. Many women are now offered panels of genes for assessment of their risk either as a comprehensive germline test or following a negative BRCA1/2 examination. These genes do not yet affect treatment options, but may be used to assess risk of additional primary tumors and options for reducing those risks. These data suggest that womenwith early onset breast cancer, triple negative breast cancers and other features suggesting hereditary predisposition underlying the diagnosis should consider genetic evaluation. The results may affect their own breast cancer care, and the cancer risk assessment among their family members. Disclosure of Interest: Grants/research support: Myriad Genetics, Novartis (self); Novartis, Pfizer (spouse). Honoraria or consultation fees: Novartis, Pfizer (spouse); Pfizer (self).