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The purpose of this study is to evaluate the efficacy and safety of docetaxel plus cyclophosphamide(TC) compared with docetaxel, anthracycline, and cyclophosphamide(TEC) in neoadjuvant treatment of triple negative or HER2 positive breast cancer. Eligible breast cancer patients were randomized to receive six cycles of TC or TEC. The primary end point was pathological complete remission (pCR). Secondary end points included safety, clinical response rate, and survival outcome. One hundred and two patients were initially randomized and 96 patients were available for efficacy analysis. 96.9 % patients were treated with epirubicin as an anthracycline agent. pCR rates were 6.8 % (3/45) and 17.6 % (9/51) in TC and TEC group, respectively, P = 0.113. After a mean follow up of 20 (3–36) months, non-anthracycline-containing TC regimen treatment resulted in a worse event free survival (adjusted hazard ratio [HR] 2.42; 95 % CI1.11–5.30) and disease-free survival (HR 2.85; 95 % CI1.21–6.74) compared with TEC regimen, which was more apparent in triple negative subtype. Severe adverse event rates were similar, except that patients treated with TEC had a higher rate of neutropenia and leucopenia. TEC treatment had a superior survival outcome and trend of higher pCR rate compared with TC in this trial setting, especially in triple negative subtype, which deserves further validation.

ObjectiveA previous study demonstrated that non-anthracycline-containing docetaxel plus cyclophosphamide (TC) regimen was inferior to docetaxel, anthracycline and cyclophosphamide (TAC) in neoadjuvant treatment of triple-negative breast cancer (TNBC) and human epidermal growth factor receptor-2-(HER2)-positive breast cancer in a short-term follow-up. Herein, long-term follow-up survival outcomes have been investigated.MethodsTNBC or HER2-positive patients were randomized to receive 6 cycles of TC or TAC neoadjuvant treatment. The primary endpoint was pathological complete remission (pCR). Secondary endpoints included clinical response rate, event-free survival (EFS), and overall survival (OS).ResultsA cohort of 96 patients consisted of 45 in TC and 51 in TAC arm. With a median follow-up period of 53 (range, 8–76) months, the patients achieving pCR post neoadjuvant chemotherapy exhibited superior EFS and OS than patients without pCR (P<0.05). TAC treatment resulted in consistently better EFS than TC treatment: the estimated 5-year EFS was 66.1% vs. 29.8% (P=0.002). Moreover, the estimated 5-year OS was also in favor of TAC: 88.4% vs. 51.6% (P<0.001). Multivariable analysis demonstrated that the treatment regimen was an independent prognostic factor, and patients treated with TAC had a superior EFS [hazard ratio (HR), 0.48; 95% confidence interval (95% CI), 0.26–0.90; P=0.021] and OS (HR, 0.20; 95% CI, 0.08–0.60; P=0.003). ConclusionsThe updated long-term follow-up data demonstrated a sustained benefit in EFS and OS from anthracycline-containing TAC treatment, indicating that anthracycline is an essential and effective drug in this clinical trial.

Cigarette smoking entails chronic exposure to a mixture of harmful chemicals that trigger molecular changes over time, and is known to increase the risk of developing diseases. Risk assessment in the context of 21st century toxicology relies on the elucidation of mechanisms of toxicity and the identification of exposure response markers, usually from high-throughput data, using advanced computational methodologies. The sbv IMPROVER Systems Toxicology computational challenge (Fall 2015–Spring 2016) aimed to evaluate whether robust and sparse (≤40 genes) human (sub-challenge 1, SC1) and species-independent (sub-challenge 2, SC2) exposure response markers (so called gene signatures) could be extracted from human and mouse blood transcriptomics data of current (S), former (FS) and never (NS) smoke-exposed subjects as predictors of smoking and cessation status. Best-performing computational methods were identified by scoring anonymized participants’ predictions. Worldwide participation resulted in 12 (SC1) and six (SC2) final submissions qualified for scoring. The results showed that blood gene expression data were informative to predict smoking exposure (i.e. discriminating smoker versus never or former smokers) status in human and across species with a high level of accuracy. By contrast, the prediction of cessation status (i.e. distinguishing FS from NS) remained challenging, as reflected by lower classification performances. Participants successfully developed inductive predictive models and extracted human and species-independent gene signatures, including genes with high consensus across teams. Post-challenge analyses highlighted “feature selection” as a key step in the process of building a classifier and confirmed the importance of testing a gene signature in independent cohorts to ensure the generalized applicability of a predictive model at a population-based level. In conclusion, the Systems Toxicology challenge demonstrated the feasibility of extracting a consistent blood-based smoke exposure response gene signature and further stressed the importance of independent and unbiased data and method evaluations to provide confidence in systems toxicology-based scientific conclusions.

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