Differential Benefit of Adjuvant Docetaxel-Based Chemotherapy in Patients With Early Breast Cancer According to Baseline Body Mass Index.

PURPOSE: Lipophilic drugs, such as taxanes, have a high affinity for adipose tissue and a resulting higher volume of distribution. Here, we reanalyzed clinical trial data to investigate whether the efficacy of docetaxel-based chemotherapy differs from non-docetaxel-based chemotherapy in patients with breast cancer according to their baseline body mass index (BMI). PATIENTS AND METHODS: We retrospectively analyzed data from all of the patients in the adjuvant BIG 2-98 trial (ClinicalTrials.gov identifier: NCT00174655; N = 2,887) comparing non-docetaxel- to docetaxel-containing chemotherapy. BMI (kg/m2) was categorized as follows: 18.5 to < 25, lean; 25 to < 30, overweight; and ≥ 30, obese. Disease-free survival (DFS) was the primary endpoint, and overall survival (OS) was the secondary endpoint. A second-order interaction was assessed among treatment, BMI, and estrogen receptor (ER) status. RESULTS: There was no difference in DFS or OS according to BMI in the non-docetaxel group, while reduced DFS and OS were observed with increasing BMI category in the docetaxel group. Adjusted hazard ratios for DFS and OS were, respectively, 1.12 (95% CI, 0.98 to 1.50; P = .21) and 1.27 (95% CI, 1.01 to 1.60; P = .04) for overweight versus lean groups and were 1.32 (95% CI, 1.08 to 1.62; P = .007) and 1.63 (95% CI, 1.27 to 2.09; P < .001), respectively, for obese versus lean groups. Similar results were obtained when considering ER-negative and ER-positive tumors separately and when considering only patients who received a relative dose intensity ≥ 85% for docetaxel. A joint modifying role of BMI and ER status on treatment effect was evident for DFS (adjusted P = .06) and OS (adjusted P = .04). CONCLUSION: This retrospective analysis of a large adjuvant trial highlights a differential response to docetaxel according to BMI, which calls for a body composition-based re-evaluation of the risk-benefit ratio of the use of taxanes in breast cancer. These results now must be confirmed in additional series.

Predicting Anthracycline Benefit: TOP2A and CEP17-Not Only but Also.

PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite as measured with a centromere enumeration probe (CEP17) predicted sensitivity to anthracyclines, we report here an individual patient-level pooled analysis of data from five trials comparing anthracycline-based chemotherapy with CMF (cyclophosphamide, methotrexate, and fluorouracil) as adjuvant chemotherapy for early breast cancer. PATIENTS AND METHODS: Fluorescent in situ hybridization for CEP17, HER2, and TOP2A was performed in three laboratories on samples from 3,846 of 4,864 eligible patients from five trials evaluating anthracycline-containing chemotherapy versus CMF. Methodologic differences did not affect HER2-to-CEP17 ratios but necessitated different definitions for CEP17 duplication: > 1.86 observed copies per cell for BR9601, NEAT, Belgian, and DBCG89D trials and > 2.25 for the MA.5 trial. RESULTS: Fluorescent in situ hybridization data were available in 89.3% (HER2), 83.9% (CEP17), and 80.6% (TOP2A) of 3,846 patient cases with available tissue. Both CEP17and TOP2A treatment-by-marker interactions remained significant in adjusted analyses for recurrence-free and overall survival, whereas HER2 did not. A combined CEP17 and TOP2A-adjusted model predicted anthracycline benefit across all five trials for both recurrence-free (hazard ratio, 0.64; 95% CI, 0.51 to 0.82; P = .001) and overall survival (hazard ratio, 0.66; 95% CI, 0.51 to 0.85; P = .005). CONCLUSION: This prospectively planned individual-patient pooled analysis of patient cases from five adjuvant trials confirms that patients whose tumors harbor either CEP17 duplication or TOP2A aberrations, but not HER2 amplification, benefit from adjuvant anthracycline chemotherapy.

Cyclophosphamide dose intensification may circumvent anthracycline resistance of p53 mutant breast cancers.

The predictive value of p53 for the efficacy of front-line anthracycline-based chemotherapy regimens has been a matter of significant controversy. Anthracyclines are usually combined with widely different doses of alkylating agents, which may significantly modulate tumor response to these combinations. We analyzed three series of de novo stage II-III breast cancer patients treated front line with anthracycline-based regimens of various cyclophosphamide dose intensities: 65 patients with estrogen receptor (ER)(-) tumors treated with anthracyclines alone (Institut Jules Bordet, Brussels), 51 unselected breast cancer patients treated with intermediate doses of cyclophosphamide (MD Anderson Cancer Center, Houston, TX), and 128 others treated with a dose-dense anthracycline-cyclophosphamide combination (St. Louis, Paris). After chemotherapy and surgery, pathologic complete response (pCR) was evaluated. p53 status was determined by a yeast functional assay on the pretreatment tumor sample. In a multivariate analysis of the pooled results, a lack of ER expression and high-dose cyclophosphamide administration were associated with a higher likelihood of pCR. A sharp statistical interaction was detected between p53 status and cyclophosphamide dose intensity. Indeed, when restricting our analysis to patients with ER(-) tumors, we confirmed that a mutant p53 status was associated with anthracycline resistance, but found that p53 inactivation was required for response to the dose-intense alkylating regimen. The latter allowed very high levels of pCR in triple-negative tumors. Thus, our data strongly suggest that cyclophosphamide dose intensification in ER(-) p53-mutated breast cancer patients could significantly improve their response.

Genomic grade index is associated with response to chemotherapy in patients with breast cancer.

PURPOSE The genomic grade index (GGI) is a 97-gene measure of histological tumor grade. High GGI is associated with decreased relapse-free survival in patients receiving either endocrine or no systemic adjuvant therapy. Herein we examined whether GGI predicts pathologic response to neoadjuvant chemotherapy in patients with HER-2-normal breast cancer. METHODS Gene expression data (gene chips) was generated from fine-needle aspiration biopsies (n = 229) prospectively collected before neoadjuvant paclitaxel, fluorouracil, doxorubicin, and cyclophosphamide chemotherapy. Pathologic response was quantified using the residual cancer burden (RCB) method. The association between the GGI and pathologic response was assessed in univariate and multivariate analyses. The performance of a response predictor combining clinical variables and GGI was evaluated under cross-validation. Results Eighty-five percent of grade 1 tumors had low GGI, 89% of grade 3 tumors had high GGI, and 63% of grade 2 tumors had low GGI. Among both estrogen receptor (ER)-positive and -negative cancers, high GGI score was associated with pathologic complete response (RCB-0) or minimal residual disease (RCB-1). A multivariate model combining GGI and clinical parameters had an overall accuracy of 71%, compared with 58% for the GGI alone, for prediction of pathologic response. However, high GGI score was also associated with significantly worse distant relapse-free survival in patients with ER-positive cancer (P = .005), and was not associated with survival in patients with ER-negative cancer. CONCLUSION High GGI is associated with increased sensitivity to neoadjuvant paclitaxel plus fluorouracil, adriamycin, and cyclophosphamide chemotherapy in both ER-negative and ER-positive patients, but it remains a predictor of worse survival in ER-positive patients.

The "Oncosimulator": a multilevel, clinically oriented simulation system of tumor growth and organism response to therapeutic schemes. Towards the clinical evaluation of in silico oncology.

The "Oncosimulator" is at the same time a concept of multilevel integrative cancer and (treatment affected) normal tissue biology, an algorithmic construct and a software tool which aims at supporting the clinician in the process of optimizing cancer treatment on the patient individualized basis. Additionally it is a platform for better understanding and exploring the natural phenomenon of cancer as well as training doctors and interested patients alike. In order to achieve all of these goals it has to undergo a thorough clinical optimization and validation process. This is one of the goals of the European Commission funded integrated project "ACGT: Advancing Clinicogenomic Trials on Cancer". Nephroblastoma (Wilms' tumor) and breast cancer have been selected to serve as two paradigms to clinically specify and evaluate the "Oncosimulator" as well as the emerging domain of in silico oncology.