Adjuvant dose-dense doxorubicin-cyclophosphamide versus docetaxel-doxorubicin-cyclophosphamide for high-risk breast cancer: First results of the randomised MATADOR trial (BOOG 2004-04)

Background: Dose-dense administration of chemotherapy and the addition of taxanes to anthracycline-based adjuvant chemotherapy have improved breast cancer survival substantially. However, clinical trials directly comparing the additive value of taxanes with dose-dense anthracycline-based chemotherapy are lacking. Patients and methods: In the multicentre, randomised, biomarker discovery Microarray Analysis in breast cancer to Tailor Adjuvant Drugs Or Regimens (MATADOR) trial, patients with pT1-3, pN0-3 breast cancer were randomised (1:1) between six adjuvant cycles of doxorubicin 60 mg/m2 and cyclophosphamide 600 mg/m2 every 2 weeks (ddAC) and six cycles of docetaxel 75 mg/m2, doxorubicin 50 mg/m2 and cyclophosphamide 500 mg/m2 every 3 weeks (TAC). The primary objective was to discover a predictive gene expression profile for ddAC and TAC benefit. Here we report the preplanned secondary end-point recurrence-free survival (RFS) and overall survival (OS). Results: Between 2004 and 2012, 664 patients were randomised. At 5 years, RFS was 87% (95% confidence interval [CI] 83%–91%) in the ddAC-treated patients and 88% (84–92%) in the TAC-treated subgroup (hazard ratio [HR] 0.89, 95% CI 0.62–1.28, P = 0.53). OS at 5 years was 93% (90%–96%) in the ddAC-treated and 94% (91%–97%) in the TAC-treated patients (HR 0.89, 95% CI 0.57–1.39, P = 0.61). Anaemia was more frequent in ddAC-treated patients (62/327 patients [18.9%] versus 15/319 patients [4.7%], P < 0.001) and diarrhoea (21 [6.4%] versus 53 [16.6%], P<0.001) and peripheral neuropathy (15 [4.6%] versus 46 [14.4%], P < 0.001) were observed more often in TAC-treated patients. Conclusions: With a median follow-up of 7 years, no significant differences in RFS and OS were observed between six adjuvant cycles of ddAC and TAC in high-risk breast cancer patients. Trial registration numbers: ISRCTN61893718 and BOOG 2004-04

Carboplatin-cyclophosphamide or paclitaxel without or with bevacizumab as first-line treatment for metastatic triple-negative breast cancer (BOOG 2013-01)

Background: The addition of bevacizumab to chemotherapy conferred a modest progression-free survival (PFS) benefit in metastatic triple-negative breast cancer (mTNBC). However, no overall survival (OS) benefit has been reported. Also, its combination with carboplatin-cyclophosphamide (CC) has never been investigated. Methods: The Triple-B study is a multicenter, randomized phase IIb trial that aims to prospectively validate predictive biomarkers, including baseline plasma vascular endothelial growth factor receptor-2 (pVEGFR-2), for bevacizumab benefit. mTNBC patients were randomized between CC and paclitaxel (P) without or with bevacizumab (CC +/- B or P +/- B). Here we report on a preplanned safety and preliminary efficacy analysis after the first 12 patients had been treated with CC+B and on the predictive value of pVEGFR-2. Results: In 58 patients, the median follow-up was 22.1 months. Toxicity was manageable and consistent with what was known for each agent separately. There was a trend toward a prolonged PFS with bevacizumab compared to chemotherapy only (7.0 vs. 5.2 months; adjusted HR = 0.60; 95% CI 0.33-1.08; p = 0.09), but there was no effect on OS. In this small study, pVEGFR-2 concentration did not predict a bevacizumab PFS benefit. Both the intention-to-treat analysis and the per-protocol analysis did not yield a significant treatment-by-biomarker test for interaction (p(interaction) = 0.69). Conclusions:CC and CC+B are safe first-line regimens for mTNBC and the side effects are consistent with those known for each individual agent. pVEGFR-2 concentration did not predict a bevacizumab PFS benefit.Experimentele farmacotherapi

Predicting therapy resistance and toxicity in breast cancer patients

Breast cancer is one of the most common types of cancer worldwide. Despite advances in systemic treatment leading to increased survival rates, a substantial number of patients still dies of the disease. A personalized treatment strategy is needed to further improve breast cancer survival. Both prognostic and predictive biomarkers are indispensable for an individualized treatment plan. Although several prognostic markers are currently used in the clinic, predictive markers are scarce. This thesis describes the identification of predictive biomarkers for survival benefit and toxicity of systemic treatment for early or metastatic breast cancer patients in four different studies. The primary aim of the MATADOR trial was to identify a gene expression profile that predicts survival benefit of adjuvant dose dense scheduled doxorubicin and cyclophosphamide (ddAC) or conventionally scheduled docetaxel, doxorubicin and cyclophosphamide (TAC). Using RNA-sequencing data, we identified a gene expression profile with prognostic value, but limited predictive capacity. However, enrichment in immune-related gene expression appeared to be associated with favorable outcome after TAC, but not after ddAC in patients with a basal tumor. Assessing the clinical applicability of this association using tumor infiltrating lymphocytes, we found that triple negative breast cancer (TNBC) patients with high TILs (≥20%) had a numerically longer RFS when treated with TAC than treated with ddAC, while patients with low TILs (<20%) derived more benefit from ddAC, with a significant interaction. Also, we assessed previously described potential biomarkers for toxicity of the two regimens. Whereas genetic variants in FGFR4 were associated with the occurrence of febrile neutropenia and genetic variants in TECTA and GSTP1 with peripheral neuropathy, most associations could not be replicated in our cohort. The GAIN-2 study showed that intensified, sequential epirubicin, paclitaxel and cyclophosphamide (ETC) resulted in similar disease free survival (DFS) and OS as concurrently given epirubicin and cyclophosphamide followed by paclitaxel and capecitabine (EC-TX). We assessed the BRCA1-like profile as predictor of superior survival of intensified chemotherapy with ETC. However, DFS and OS were not significantly different between the BRCA1-like subgroups, nor between the treatments when split by BRCA1-like subgroup. In phase 1b of the POSEIDON study we aimed to find the recommended phase 2 dose (RP2D) of PI3K inhibitor taselisib combined with tamoxifen. In metastatic ER-positive breast cancer patient, the RP2D of taselisib was 4mg QD. Responses were more abundant in patients with PIK3CA mutant disease. Phase 2 of the POSEIDON study will indicate whether taselisib and tamoxifen prolong PFS compared with placebo and tamoxifen and whether PIK3CA mutation status can be used as predictive biomarker for survival benefit of taselisib. In the Triple-B study, we aimed to evaluate two biomarkers for survival benefit: baseline plasma VEGF receptor 2 (pVEGFR-2) levels for the addition of bevacizumab and the BRCA1-like profile for alkylating or platinum-based chemotherapy. Interim analysis showed that PFS was significantly longer in bevacizumab-treated patients compared with patients who were treated with chemotherapy only. In this small cohort, pVEGFR-2 level could not be validated as predictive biomarker for survival benefit of bevacizumab

Predicting therapy resistance and toxicity in breast cancer patients

Breast cancer is one of the most common types of cancer worldwide. Despite advances in systemic treatment leading to increased survival rates, a substantial number of patients still dies of the disease. A personalized treatment strategy is needed to further improve breast cancer survival. Both prognostic and predictive biomarkers are indispensable for an individualized treatment plan. Although several prognostic markers are currently used in the clinic, predictive markers are scarce. This thesis describes the identification of predictive biomarkers for survival benefit and toxicity of systemic treatment for early or metastatic breast cancer patients in four different studies. The primary aim of the MATADOR trial was to identify a gene expression profile that predicts survival benefit of adjuvant dose dense scheduled doxorubicin and cyclophosphamide (ddAC) or conventionally scheduled docetaxel, doxorubicin and cyclophosphamide (TAC). Using RNA-sequencing data, we identified a gene expression profile with prognostic value, but limited predictive capacity. However, enrichment in immune-related gene expression appeared to be associated with favorable outcome after TAC, but not after ddAC in patients with a basal tumor. Assessing the clinical applicability of this association using tumor infiltrating lymphocytes, we found that triple negative breast cancer (TNBC) patients with high TILs (≥20%) had a numerically longer RFS when treated with TAC than treated with ddAC, while patients with low TILs (<20%) derived more benefit from ddAC, with a significant interaction. Also, we assessed previously described potential biomarkers for toxicity of the two regimens. Whereas genetic variants in FGFR4 were associated with the occurrence of febrile neutropenia and genetic variants in TECTA and GSTP1 with peripheral neuropathy, most associations could not be replicated in our cohort. The GAIN-2 study showed that intensified, sequential epirubicin, paclitaxel and cyclophosphamide (ETC) resulted in similar disease free survival (DFS) and OS as concurrently given epirubicin and cyclophosphamide followed by paclitaxel and capecitabine (EC-TX). We assessed the BRCA1-like profile as predictor of superior survival of intensified chemotherapy with ETC. However, DFS and OS were not significantly different between the BRCA1-like subgroups, nor between the treatments when split by BRCA1-like subgroup. In phase 1b of the POSEIDON study we aimed to find the recommended phase 2 dose (RP2D) of PI3K inhibitor taselisib combined with tamoxifen. In metastatic ER-positive breast cancer patient, the RP2D of taselisib was 4mg QD. Responses were more abundant in patients with PIK3CA mutant disease. Phase 2 of the POSEIDON study will indicate whether taselisib and tamoxifen prolong PFS compared with placebo and tamoxifen and whether PIK3CA mutation status can be used as predictive biomarker for survival benefit of taselisib. In the Triple-B study, we aimed to evaluate two biomarkers for survival benefit: baseline plasma VEGF receptor 2 (pVEGFR-2) levels for the addition of bevacizumab and the BRCA1-like profile for alkylating or platinum-based chemotherapy. Interim analysis showed that PFS was significantly longer in bevacizumab-treated patients compared with patients who were treated with chemotherapy only. In this small cohort, pVEGFR-2 level could not be validated as predictive biomarker for survival benefit of bevacizumab

`Is the Hypothesis Correct’ or `Is it not’? Bayesian Evaluation of One Informative Hypthesis in ANOVA.

Researchers in the behavioral and social sciences often have one informative hypothesis with respect to the state of affairs in the population from which they sampled their data. The question they would like an answer to is ‘‘Is the Hypothesis Correct’’ or ‘‘Is it Not.’’ Classical statistics has not yet provided an approach with which this question can be answered. In this paper it will be shown that there is a Bayesian approach that does provide an answer to this question. Using two ANOVA examples the context of this paper will be sketched. Subsequently it will be shown how the Bayes factor can be used to quantify the support in the data for an informative hypothesis (‘‘It is’’) and its complement (‘‘It is not’’). Subsequently, the performance of the method proposed will be evaluated by means of error probabilities and evaluation of the robustness with respect to violations of the assumption of homogeneous within group variances. Finally, the methodology will be elaborated and it will be illustrated how the approach proposed can be implemented using WinBUGS

Techno-economic analysis of biomethanol production via hybrid steam reforming of glycerol with natural gas

The present article deals with the techno-economic assessment of the hybrid steam reforming (HSR) process of glycerol (obtained via transesterification) together with natural gas to produce biomethanol via the synthesis gas route. In this techno-economic assessment, a model is developed in the UniSim Design Suite process simulator using different glycerol amounts up to 54% (on a carbon basis) together with natural gas to produce synthesis gas at reforming conditions of 900 °C, S/C3. The techno-economic analysis shows that at the current market scenario (Oct–Dec 2012) with a natural gas price of 0.2 €/Nm3 and with an assumed glycerol price of 200 €/tonne, the average cost of biomethanol is estimated as 433 €/tonne for a feed of 54 wt % of glycerol (on a carbon basis) with natural gas, which is 75 €/tonne higher than for the methanol obtained via only natural gas steam reforming. It is concluded that biomethanol from a HSR process becomes more attractive when the natural gas price exceeds 0.45 €/Nm3 or when glycerol is available at lesser than 90 €/tonne. Splitting the production capacity in methanol and biomethanol according to the feed composition would result in a price of 358 €/tonne and 470–500 €/tonne of methanol and biomethanol, respectively, depending on the amount of glycerol in the feed. This means that currently, biomethanol is not competitive with methanol unless special arrangements are made (regulations, subsidies) to promote the use of biomethanol. For example, the EC Renewable Energy Directive1 states that the energy content of biofuels from wastes and residues (for instance crude glycerol) counts double. From the sensitivity analysis, it is concluded that feedstock prices and total capital investment have major influence on the final product value of biomethanol. Furthermore, it is concluded that at the current price scenario, utilizing glycerol either in the furnace or in the reformer has no effect on the cost price. However, burning is not an option since the biomethanol will not contain the required C14 isotop

Daily Oral Ibandronate With Adjuvant Endocrine Therapy in Postmenopausal Women With Estrogen Receptor-Positive Breast Cancer (BOOG 2006-04): Randomized Phase III TEAM-IIB Trial

PURPOSE For postmenopausal patients with breast cancer, previous subgroup analyses have shown a modest benefit from adjuvant bisphosphonate treatment. However, the efficacy of oral nitrogen-containing bisphosphonates such as ibandronate is unclear in this setting. TEAM-IIB investigates adjuvant ibandronate in postmenopausal women with estrogen receptor-positive (ER+) breast cancer. METHODS TEAM-IIB is a randomized, open-label, multicenter phase III study. Postmenopausal women with stage I-III ER+ breast cancer and an indication for adjuvant endocrine therapy (ET) were randomly assigned 1:1 to 5 years of ET with or without oral ibandronate 50 mg once daily for 3 years. Major ineligibility criteria were bilateral breast cancer, active gastroesophageal problems, and health conditions that might interfere with study treatment. Primary end point was disease-free survival (DFS), analyzed in the intention-to-treat population. RESULTS Between February 1, 2007, and May 27, 2014, 1,116 patients were enrolled, 565 to ET with ibandronate (ibandronate arm) and 551 to ET alone (control arm). Median follow-up was 8.5 years. DFS was not significantly different between the ibandronate and control arms (HR, 0.97; 95% CI, 0.76 to 1.24; log-rank P = .811). Three years after random assignment, DFS was 94% in the ibandronate arm and 91% in the control arm. Five years after random assignment, this was 89% and 86%, respectively. In the ibandronate arm, 97/565 (17%) of patients stopped ibandronate early because of adverse events. Significantly more patients experienced GI issues, mainly dyspepsia, in the ibandronate arm than in the control arm (89 [16%] and 54 [10%], respectively; P < .003). Eleven patients in the ibandronate arm developed osteonecrosis of the jaw. CONCLUSION In postmenopausal women with ER+ breast cancer, adjuvant ibandronate 50 mg once daily does not improve DFS and should not be recommended as part of standard treatment regimens

Differential survival and therapy benefit of patients with breast cancer are characterized by distinct epithelial and immune cell microenvironments

Purpose: Extensive work in preclinical models has shown that microenvironmental cells influence many aspects of cancer cell behavior, including metastatic potential and their sensitivity to therapeutics. In the human setting, this behavior is mainly correlated with the presence of immune cells. Here, in addition to T cells, B cells, macrophages, and mast cells, we identified the relevance of nonimmune cell types for breast cancer survival and therapy benefit, including fibroblasts, myoepithelial cells, muscle cells, endothelial cells, and seven distinct epithelial cell types.Experimental Design: Using single-cell sequencing data, we generated reference profiles for all these cell types. We used these reference profiles in deconvolution algorithms to optimally detangle the cellular composition of more than 3,500 primary breast tumors of patients that were enrolled in the SCAN-B and MATADOR clinical trials, and for which bulk mRNA sequencing data were available.Results: This large data set enables us to identify and subsequently validate the cellular composition of miaoenvironments that distinguish differential survival and treatment benefit for different treatment regimens in patients with primary breast cancer. In addition to immune cells, we have identified that survival and therapy benefit are characterized by various contributions of distinct epithelial cell types.Conclusions: From our study, we conclude that differential survival and therapy benefit of patients with breast cancer are characterized by distinct microenvironments that include specific populations of immune and epithelial cells.Experimentele farmacotherapi

Differential survival and therapy benefit of patients with breast cancer are characterized by distinct epithelial and immune cell microenvironments

Purpose: Extensive work in preclinical models has shown that microenvironmental cells influence many aspects of cancer cell behavior, including metastatic potential and their sensitivity to therapeutics. In the human setting, this behavior is mainly correlated with the presence of immune cells. Here, in addition to T cells, B cells, macrophages, and mast cells, we identified the relevance of nonimmune cell types for breast cancer survival and therapy benefit, including fibroblasts, myoepithelial cells, muscle cells, endothelial cells, and seven distinct epithelial cell types.Experimental Design: Using single-cell sequencing data, we generated reference profiles for all these cell types. We used these reference profiles in deconvolution algorithms to optimally detangle the cellular composition of more than 3,500 primary breast tumors of patients that were enrolled in the SCAN-B and MATADOR clinical trials, and for which bulk mRNA sequencing data were available.Results: This large data set enables us to identify and subsequently validate the cellular composition of miaoenvironments that distinguish differential survival and treatment benefit for different treatment regimens in patients with primary breast cancer. In addition to immune cells, we have identified that survival and therapy benefit are characterized by various contributions of distinct epithelial cell types.Conclusions: From our study, we conclude that differential survival and therapy benefit of patients with breast cancer are characterized by distinct microenvironments that include specific populations of immune and epithelial cells