Troy Bremer

Study of the Biologic Effects of Lapatinib, a Reversible Inhibitor of ErbB1 and ErbB2 Tyrosine Kinases, on Tumor Growth and Survival Pathways in Patients With Advanced Malignancies

PURPOSE This was a pilot study to assess the biologic effects of lapatinib on various tumor growth/survival pathways in patients with advanced ErbB1 and/or ErbB2-overexpressing solid malignancies. PATIENTS AND METHODS Heavily pretreated patients with metastatic cancers overexpressing ErbB2 and/or expressing ErbB1 were randomly assigned to one of five dose cohorts of lapatinib (GW572016) administered orally once daily continuously. The biologic effects of lapatinib on tumor growth and survival pathways were assessed in tumor biopsies obtained before and after 21 days of therapy. Clinical response was determined at 8 weeks. RESULTS Sequential tumor biopsies from 33 patients were examined. Partial responses occurred in four patients with breast cancer, and disease stabilization occurred in 11 others with various malignancies. Responders exhibited variable levels of inhibition of p-ErbB1, p-ErbB2, p-Erk1/2, p-Akt, cyclin D1, and transforming growth factor alpha. Even some nonresponders demonstrated varying degrees of biomarker inhibition. Increased tumor cell apoptosis (TUNEL) occurred in patients with evidence of tumor regression but not in nonresponders (progressive disease). Clinical response was associated with a pretreatment TUNEL score > 0 and increased pretreatment expression of ErbB2, p-ErbB2, Erk1/2, p-Erk1/2, insulin-like growth factor receptor-1, p70 S6 kinase, and transforming growth factor alpha compared with nonresponders. CONCLUSION Lapatinib exhibited preliminary evidence of biologic and clinical activity in ErbB1 and/or ErbB2-overexpressing tumors. However, the limited sample size of this study and the variability of the biologic endpoints suggest that further work is needed to prioritize biomarkers for disease-directed studies, and underscores the need for improved trial design strategies in early clinical studies of targeted agents.

A multimarker model to predict outcome in tamoxifen-treated breast cancer patients.

PURPOSE: This study was designed to produce a model to predict outcome in tamoxifen-treated breast cancer patients based on clinicopathologic features and multiple molecular markers. EXPERIMENTAL DESIGN: This was a retrospective study of 324 stage I to III female breast cancer patients treated with tamoxifen for whom standard clinicopathologic data and tumor tissue microarrays were available. Nine molecular markers were studied by semiquantitative immunohistochemistry and/or fluorescence in situ hybridization. Cox proportional hazards analysis was used to determine the contributions of each variable to disease-specific and overall survival, and machine learning was used to produce a model to predict patient outcome. RESULTS: On a univariate basis, the following features were significantly associated with worse survival: high pathologic tumor or nodal class, histologic grade, epidermal growth factor receptor, ERBB2, MYC, or TP53; absent estrogen receptor (ER) or progesterone receptor; and low BCL2. CCND1 and CDKN1B did not reach statistical significance. On a multivariate basis, nodal class, ER, and MYC were statistically significant as independent factors for survival. However, the benefit of ER-positive status was moderated by BCL2, ERBB2, and progesterone receptor. BCL2 and TP53 also interacted as an independent risk factor. A kernel partial least squares polynomial model was developed with an area under the receiver operating characteristic curve of 0.90. CONCLUSIONS: Our data show the predictive value of BCL2, ERBB2, MYC, and TP53 in addition to the standard hormone receptors and clinicopathologic features, and they show the importance of conditional interpretation of certain molecular markers. Our multimarker predictive model performed significantly better than standard guidelines.

CACNA1C polymorphisms are associated with the efficacy of calcium channel blockers in the treatment of hypertension.

Retrospective pharmacogenetic analysis was performed on 120 Caucasian subjects. Subjects were obtained in collaboration with the Estonian Genome Project and Egeen Inc. (CA, USA), who provided blinded medical record and genetic data to the researchers, respectively. Subjects selected from the Estonian Genome Project had a diagnosis of hypertension confirmed by at least two blood pressure measurements and multiple follow-up measurements for assessing calcium channel blocker antihypertensive treatment outcome. Treatment outcome was scored positive if at least three follow-up blood pressure measurements were nonhypertensive and no more than one follow-up measurement was hypertensive (>140/90). The genotypes of 62 single nucleotide polymorphisms (SNPs) in the calcium channel, voltage-dependent, L type, alpha 1C subunit (CACNA1C) gene were obtained for each subject from a blood sample. Univariate analyses with multiple test correction were conducted using family-wise error rate and false discovery rate methods. Three SNPs in CANCA1C had significant associations with antihypertensive outcome, combining to yield a positive treatment outcome of less than 15 to 80%.

Prognostic marker profile to assess risk in stage I-III hormone receptor-positive breast cancer patients

Single markers are insufficient to accurately assess risk of relapse for adjuvant therapy guidance in operable breast cancer patients. In addition, the accuracy and interpretability of current multi‐marker tests is generally limited by their simply additive algorithms and their overlap with clinicopathologic risks. Here, we report the development and validation of a nonlinear algorithm that combines protein (ER, PGR, ERBB2, BCL2 and TP53) and genomic (MYC/8q24) markers with standard clinicopathologic features (tumor size, tumor grade and nodal status) into a global risk assessment profile. The algorithm was trained using statistical pattern recognition in 200 stage I–III hormone receptor‐positive patients treated with hormone therapy. Continuous risk scores (0–10+) were then generated for 232 independent patients. In hormone therapy‐treated patients, the profile achieved a hazard ratio of 6.2 (95% confidence interval [CI], 1.8–20) in high‐ vs. low‐risk groups for time to distant metastasis with the low‐risk group having a 10‐year metastasis rate of just 4% (95% CI, 0–8%). Similar results were achieved in untreated patients and for disease‐specific survival. In multivariate analyses with standard prognostic factors and clinical practice guidelines, the profile was the only significant variable. Furthermore, the profile reclassified as low risk over half of node‐negative patients at elevated risk according to the guidelines, which could have spared such patients from unnecessary cytotoxic chemotherapy. It also accurately identified a group of high‐risk patients within a guideline low‐risk group. In summary, the profile intelligently combines biologically relevant marker pathways and established clinicopathologic risks to help guide breast cancer patients to the most appropriate level of adjuvant therapy.

Abstract P4-11-18: FOXA1 and PR predict ipsilateral event risk and identify a group with strong radiation response in ductal carcinoma in situ (DCIS)

Background: Identification of biomarkers in DCIS is critical to help guide treatment decisions, particularly for patients receiving breast-conserving surgery (BCS). The goal of this study was to assess FOXA1 levels in the context of PR status in primary DCIS to predict ipsilateral invasive and DCIS events, given the established roles of these endocrine signaling factors in breast cancer. Material and Methods: Patients included in this study (n=518) were women diagnosed with DCIS without evidence of invasive cancer treated with BCS, and for whom tumor tissue was evaluable for both PR and FOXA1. An Uppsala University Hospital (UUH) set was diagnosed in 1986-2004 (117 treated and 122 not treated with adjuvant radiation therapy [RT]); and a University of Massachusetts Memorial Hospital (UMass) set was diagnosed in 1999-2008 (195 treated and 84 not treated with RT). Tumors were immunohistochemically stained for PR and FOXA1 and scored by pathologists for percentage (0-100) and intensity (0-3), with the product being calculated for FOXA1 immunoscore (0-300). Patients were considered PR+ when ≥10% of cells stained positively, and immunoscore thresholds of 100 and 270 were used to separate patients into FOXA1 low, intermediate, and high groups. Event rates were assessed for 10-year outcome using Kaplan-Meier survival analysis. Hazard ratios (HR) were determined using Cox proportional hazards analysis. Results: Neither FOXA1 nor PR were prognostic as independent factors for either invasive or DCIS event risk. However, in PR- patients, the invasive event rate decreased with increasing FOXA1 (24%, 4%, and 0%, respectively, in the FOXA1 low, intermediate, and high groups, HR=6.7/bin, p=0.0034), and, in PR+ patients, the invasive event rate increased with increasing FOXA1 (0%, 10%, and 13%, respectively, HR=2.95/bin, p=0.041). In contrast, the DCIS event rate increased in PR- patients with increasing FOXA1 (3%, 12%, and 26%, respectively, HR=2.7/bin, p=0.020), and the DCIS event rate was lower in PR+ patients with elevated FOXA1 levels (28% in FOXA1 low vs. 8% in FOXA1 intermediate plus high, HR=4.0, p=0.011). In the full population, RT-treated patients (n=312) fared better than the unirradiated (n=206) with invasive event rates of 6% and 10%, respectively (HR=0.41, p=0.021). By comparison, the patients with high marker-based invasive event risk (PR-/FOXA1 low and PR+/FOXA1 high, n=191) had a remarkable response to RT–event rate reduced from 19% to 4% (HR=0.13, p Discussion: These results indicate a complex interaction between PR and FOXA1, in which the prognosis for invasive and DCIS events flips both within and between the event types. Thus, the biology that drives these events differs and, in order to predict both event types, risk models must include biomarkers in context. In addition, PR/FOXA1 identify a risk group with remarkably strong RT response with the remaining patients exhibiting no measurable response. Citation Format: Steven P Linke, Troy M Bremer, Pat Whitworth, Aflred Lui, Jess Savala, Yelina Noskina, Todd Barry, Stephen Lyle, Stephanie C Walters, Cherie Taglienti, Karl Simin, Wenjing Zhou, Karin Jirstrom, Rose-Marie Amini, Fredrik Warnberg. FOXA1 and PR predict ipsilateral event risk and identify a group with strong radiation response in ductal carcinoma in situ (DCIS) [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-11-18.

P2-12-25: Blinded Multi-Site Validation of a Pathology-Based Prognostic Marker Profile for Operable Hormone Receptor-Positive Breast Cancer.

Background We previously reported development and preliminary validation of a marker profile with a risk of recurrence algorithm for patients with operable hormone receptor (HR)-positive breast cancer using tissue microarrays. The profile includes ER, PR, HER2, EGFR, BCL2, and p53 (assessed by IHC) and MYC/8q24 (assessed by FISH). It also directly incorporates the standard clinicopathologic risk factors tumor size, tumor grade, and nodal status to the extent that their prognostic value is not replaced by the molecular markers. Here, we demonstrate validation of the profile in a blinded multi-site study conducted on whole sections. Material and methods : The study was conducted in a blinded fashion using an independent data management firm (Synteract, Carlsbad, CA). Eligible patients were females diagnosed between 1985 and 1997 with HR-positive stage I-IIIA breast cancer treated only with hormone therapy after definitive surgery for whom sufficient tumor samples were available for testing. Slides with FFPE tumor tissue sections and associated clinicopathologic, treatment, and outcome data were provided by four clinical sites through the NCI-funded Cooperative Breast Cancer Tissue Resource program: Fox-Chase Cancer Center (Philadelphia, PA) (n=106), Kaiser Permanente Northwest (Portland, OR) (n=165), University of Miami (FL) (n=55), and Washington University St. Louis (MO) (n=74). Marker assays, scoring, and calculation of risk scores using a predefined algorithm were conducted at Clarient, a CLIA-certified laboratory. The algorithm assigned a risk score to each patient on a scale of 0 to 10+, and a predefined threshold of 3.8 was used to separate patients into low and high risk groups. Results: Complete data for all seven markers was obtained in 349 of the 400 patients. The algorithm defined 28% of the patients (n=99) as high-risk and 72% of the patients (n=250) as low-risk. The high-risk and low-risk patient groups had 10-year distant metastasis rates of 34% and 9%, respectively, resulting in a hazard ratio of 4.7 (95% CI, 2.3−7.8, p Discussion : This blinded study, using a predefined algorithm and threshold, validates the prognostic and clinical utility of the multi-marker profile to help guide the appropriate level of adjuvant treatment in breast cancer patients. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P2-12-25.

Immunohistochemistry-based marker profile accurately predicts risk in operable, hormone receptor-positive patients.

Abstract #1062 Background: The performance of current prognostic breast cancer tests is limited, because they only address simple additive molecular risks, and the results are often difficult to interpret in the context of overlapping clinicopathologic risks. Gene expression-based tests can be further confounded by contamination with non-tumor cells. Our goal was to develop a protein-based profile that addresses these limitations. Methods: ER, PR, Her2, EGFR, BCL2, p27/Kip1, and p53 (IHC) and MYC (FISH) were scored in tumor cells of FFPE tissue from patients with operable, pN0-2, hormone receptor-positive breast cancer at two clinical sites. A consensus prognostic model was trained using robust cross-validation in 290 hormone therapy (HT)-treated patients using statistical pattern recognition methods to account for complex marker interactions. Tumor grade, pT, and pN were directly incorporated into the model to the extent they were not replaced by the molecular markers. Continuous risk scores ranging from 0 to 10+ were generated for the 290 HT-treated patients, 90 untreated patients, and 119 patients treated with chemotherapy and HT. Results: A predetermined threshold of 3.8 separated HT-treated patients into high and low risk groups with hazard ratios of 8.8 (p 15%, NPI >3.4, and St. Gallen intermediate/high), the profile reclassified as low risk 84%, 81%, and 85% of pN0 patients, and 43%, 43%, and 32% of pN1 patients, respectively. The reclassified patients had 7.0, addition of chemotherapy produced a >20% DSS benefit at 8 years (p=0.04). Conclusion: This 8-marker profile with super-additive algorithm achieved significantly higher classification accuracy than treatment guidelines and could aid selection of the most appropriate level of adjuvant therapy in patients with operable breast cancer.
 Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 1062.