Elevated S100A8 protein expression in breast cancer cells and breast tumor stroma is prognostic of poor disease outcome.

PURPOSE: Elevated S100A8 expression has been observed in cancers of the bladder, esophagus, colon, ovary, and breast. S100A8 is expressed by breast cancer cells as well as by infiltrating immune and myeloid cells. Here we investigate the association of elevated S100A8 protein expression in breast cancer cells and in breast tumor stroma with survival outcomes in a cohort of breast cancer patients. PATIENTS AND METHODS: Tissue microarrays (TMA) were constructed from breast cancer specimens from 417 patients with stage I-III breast cancer treated at the University of Michigan Comprehensive Cancer Center between 2004 and 2006. Representative regions of non-necrotic tumor and distant normal tissue from each patient were used to construct the TMA. Automated quantitative immunofluorescence (AQUA) was used to measure S100A8 protein expression, and samples were scored for breast cancer cell and stromal S100A8 expression. S100A8 staining intensity was assessed as a continuous value and by exploratory dichotomous cutoffs. Associations between breast cancer cell and stromal S100A8 expression with disease-free survival and overall survival were determined using the Kaplan-Meier method and Cox proportional hazard models. RESULTS: High breast cancer cell S100A8 protein expression (as indicated by AQUA scores), as a continuous measure, was a significant prognostic factor for OS [univariable hazard ratio (HR) 1.24, 95% confidence interval (CI) 1.00-1.55, p = 0.05] in this patient cohort. Exploratory analyses identified optimal S100A8 AQUA score cutoffs within the breast cancer cell and stromal compartments that significantly separated survival curves for the complete cohort. Elevated breast cancer cell and stromal S100A8 expression, indicated by higher S100A8 AQUA scores, significantly associates with poorer breast cancer outcomes, regardless of estrogen receptor status. CONCLUSIONS: Elevated breast cancer cell and stromal S1008 protein expression are significant indicators of poorer outcomes in early stage breast cancer patients. Evaluation of S100A8 protein expression may provide additional prognostic information beyond traditional breast cancer prognostic biomarkers.

CYP2D6 genotype is not associated with survival in breast cancer patients treated with tamoxifen: results from a population-based study.

PURPOSE: A number of studies have tested the hypothesis that breast cancer patients with low-activity CYP2D6 genotypes achieve inferior benefit from tamoxifen treatment, putatively due to lack of metabolic activation to endoxifen. Studies have provided conflicting data, and meta-analyses suggest a small but significant increase in cancer recurrence, necessitating additional studies to allow for accurate effect assessment. We conducted a retrospective pharmacogenomic analysis of a prospectively collected community-based cohort of patients with estrogen receptor-positive breast cancer to test for associations between low-activity CYP2D6 genotype and disease outcome in 500 patients treated with adjuvant tamoxifen monotherapy and 500 who did not receive any systemic adjuvant therapy. METHODS: Tumor-derived DNA was genotyped for common, functionally consequential CYP2D6 polymorphisms (*2, *3, *4, *6, *10, *41, and copy number variants) and assigned a CYP2D6 activity score (AS) ranging from none (0) to full (2). Patients with poor metabolizer (AS = 0) phenotype were compared to patients with AS > 0 and in secondary analyses AS was analyzed quantitatively. Clinical outcome of interest was recurrence free survival (RFS) and analyses using long-rank test were adjusted for relevant clinical covariates (nodal status, tumor size, etc.). RESULTS: CYP2D6 AS was not associated with RFS in tamoxifen treated patients in univariate analyses (p > 0.2). In adjusted analyses, increasing AS was associated with inferior RFS (Hazard ratio 1.43, 95% confidence interval 1.00-2.04, p = 0.05). In patients that did not receive tamoxifen treatment, increasing CYP2D6 AS, and AS > 0, were associated with superior RFS (each p = 0.0015). CONCLUSIONS: This population-based study does not support the hypothesis that patients with diminished CYP2D6 activity achieve inferior tamoxifen benefit. These contradictory findings suggest that the association between CYP2D6 genotype and tamoxifen treatment efficacy is null or near null, and unlikely to be useful in clinical practice.

Statistical controversies in clinical research: building the bridge to phase II-efficacy estimation in dose-expansion cohorts.

BACKGROUND: Regulatory agencies and others have expressed concern about the uncritical use of dose expansion cohorts (DECs) in phase I oncology trials. Nonetheless, by several metrics-prevalence, size, and number-their popularity is increasing. Although early efficacy estimation in defined populations is a common primary endpoint of DECs, the types of designs best equipped to identify efficacy signals have not been established. METHODS: We conducted a simulation study of six phase I design templates with multiple DECs: three dose-assignment/adjustment mechanisms multiplied by two analytic approaches for estimating efficacy after the trial is complete. We also investigated the effect of sample size and interim futility analysis on trial performance. Identifying populations in which the treatment is efficacious (true positives) and weeding out inefficacious treatment/populations (true negatives) are competing goals in these trials. Thus, we estimated true and false positive rates for each design. RESULTS: Adaptively updating the MTD during the DEC improved true positive rates by 8-43% compared with fixing the dose during the DEC phase while maintaining false positive rates. Inclusion of an interim futility analysis decreased the number of patients treated under inefficacious DECs without hurting performance. CONCLUSION: A substantial gain in efficiency is obtainable using a design template that statistically models toxicity and efficacy against dose level during expansion. Design choices for dose expansion should be motivated by and based upon expected performance. Similar to the common practice in single-arm phase II trials, cohort sample sizes should be justified with respect to their primary aim and include interim analyses to allow for early stopping.

Polymorphisms in drug-metabolizing enzymes and steady-state exemestane concentration in postmenopausal patients with breast cancer.

Discovery of clinical and genetic predictors of exemestane pharmacokinetics was attempted in 246 postmenopausal patients with breast cancer enrolled on a prospective clinical study. A sample was collected 2 h after exemestane dosing at a 1- or 3-month study visit to measure drug concentration. The primary hypothesis was that patients carrying the low-activity CYP3A4*22 (rs35599367) single-nucleotide polymorphism (SNP) would have greater exemestane concentration. Additional SNPs in genes relevant to exemestane metabolism (CYP1A1/2, CYP1B1, CYP3A4, CYP4A11, AKR1C3/4, AKR7A2) were screened in secondary analyses and adjusted for clinical covariates. CYP3A4*22 was associated with a 54% greater exemestane concentration (P<0.01). Concentration was greater in patients who reported White race, had elevated aminotransferases, renal insufficiency, lower body mass index and had not received chemotherapy (all P<0.05), and CYP3A4*22 maintained significance after adjustment for covariates (P<0.01). These genetic and clinical predictors of exemestane concentration may be useful for treatment individualization in patients with breast cancer.