141 research outputs found

    Weekly Paclitaxel plus Capecitabine versus Docetaxel Every 3 Weeks plus Capecitabine in Metastatic Breast Cancer

    Get PDF
    Background. We performed a randomized phase II study comparing efficacy and toxicity of weekly paclitaxel 80 mg/m2 (Weetax) with three weekly docetaxel 75 mg/m2 (Threetax), both in combination with oral capecitabine 1000 mg/m2 twice daily for 2 weeks followed by a 1-week break. Patients. Thirty-seven women with confirmed metastatic breast cancer were randomized. Results. Median TTF was 174 (Weetax) versus 147 days (Threetax) (=0.472). Median OS was 933 (Weetax) versus 464 days (Threetax) (=0.191). Reasons for TTF were PD 8/18 (Weetax), 9/19 (Threetax); and toxicity: 8/18 (Weetax), 8/19 (Threetax). ORR was 72% (Weetax) versus 26% (Threetax) (=0.01). The Threetax-combination resulted in a higher incidence of leuco-/neutropenia compared to Weetax. Grade II anemia was more pronounced in the Weetax group. No difference was found in quality of life. Conclusion. Taxanes in combination with capecitabine resulted in a high level of toxicity. Taxanes and capecitabine should be considered given sequentially and not in combination

    Polymorphisms in the estrogen receptor alpha gene (ESR1), daily cycling estrogen and mammographic density phenotypes

    Get PDF
    Background Single nucleotide polymorphisms (SNPs) involved in the estrogen pathway and SNPs in the estrogen receptor alpha gene (ESR1 6q25) have been linked to breast cancer development, and mammographic density is an established breast cancer risk factor. Whether there is an association between daily estradiol levels, SNPs in ESR1 and premenopausal mammographic density phenotypes is unknown. Methods We assessed estradiol in daily saliva samples throughout an entire menstrual cycle in 202 healthy premenopausal women in the Norwegian Energy Balance and Breast Cancer Aspects I study. DNA was genotyped using the Illumina Golden Gate platform. Mammograms were taken between days 7 and 12 of the menstrual cycle, and digitized mammographic density was assessed using a computer-assisted method (Madena). Multivariable regression models were used to study the association between SNPs in ESR1, premenopausal mammographic density phenotypes and daily cycling estradiol. Results We observed inverse linear associations between the minor alleles of eight measured SNPs (rs3020364, rs2474148, rs12154178, rs2347867, rs6927072, rs2982712, rs3020407, rs9322335) and percent mammographic density (p-values: 0.002–0.026), these associations were strongest in lean women (BMI, ≤23.6 kg/m2.). The odds of above-median percent mammographic density (>28.5 %) among women with major homozygous genotypes were 3–6 times higher than those of women with minor homozygous genotypes in seven SNPs. Women with rs3020364 major homozygous genotype had an OR of 6.46 for above-median percent mammographic density (OR: 6.46; 95 % Confidence Interval 1.61, 25.94) when compared to women with the minor homozygous genotype. These associations were not observed in relation to absolute mammographic density. No associations between SNPs and daily cycling estradiol were observed. However, we suggest, based on results of borderline significance (p values: 0.025–0.079) that the level of 17β-estradiol for women with the minor genotype for rs3020364, rs24744148 and rs2982712 were lower throughout the cycle in women with low (28.5 %) percent mammographic density, when compared to women with the major genotype. Conclusion Our results support an association between eight selected SNPs in the ESR1 gene and percent mammographic density. The results need to be confirmed in larger studies

    Altered dietary behaviour during pregnancy impacts systemic metabolic phenotypes

    Get PDF
    RationaleEvidence suggests consumption of a Mediterranean diet (MD) can positively impact both maternal and offspring health, potentially mediated by a beneficial effect on inflammatory pathways. We aimed to apply metabolic profiling of serum and urine samples to assess differences between women who were stratified into high and low alignment to a MD throughout pregnancy and investigate the relationship of the diet to inflammatory markers.MethodsFrom the ORIGINS cohort, 51 pregnant women were stratified for persistent high and low alignment to a MD, based on validated MD questionnaires. 1H Nuclear Magnetic Resonance (NMR) spectroscopy was used to investigate the urine and serum metabolite profiles of these women at 36 weeks of pregnancy. The relationship between diet, metabolite profile and inflammatory status was investigated.ResultsThere were clear differences in both the food choice and metabolic profiles of women who self-reported concordance to a high (HMDA) and low (LMDA) Mediterranean diet, indicating that alignment with the MD was associated with a specific metabolic phenotype during pregnancy. Reduced meat intake and higher vegetable intake in the HMDA group was supported by increased levels of urinary hippurate (p = 0.044) and lower creatine (p = 0.047) levels. Serum concentrations of the NMR spectroscopic inflammatory biomarkers GlycA (p = 0.020) and GlycB (p = 0.016) were significantly lower in the HDMA group and were negatively associated with serum acetate, histidine and isoleucine (p < 0.05) suggesting a greater level of plant-based nutrients in the diet. Serum branched chain and aromatic amino acids were positively associated with the HMDA group while both urinary and serum creatine, urine creatinine and dimethylamine were positively associated with the LMDA group.ConclusionMetabolic phenotypes of pregnant women who had a high alignment with the MD were significantly different from pregnant women who had a poor alignment with the MD. The metabolite profiles aligned with reported food intake. Differences were most significant biomarkers of systemic inflammation and selected gut-microbial metabolites. This research expands our understanding of the mechanisms driving health outcomes during the perinatal period and provides additional biomarkers for investigation in pregnant women to assess potential health risks

    An NMR-based model to investigate the metabolic phenoreversion of COVID-19 patients throughout a longitudinal study.

    Get PDF
    After SARS-CoV-2 infection, the molecular phenoreversion of the immunological response and its associated metabolic dysregulation are required for a full recovery of the patient. This process is patient-dependent due to the manifold possibilities induced by virus severity, its phylogenic evolution and the vaccination status of the population. We have here investigated the natural history of COVID-19 disease at the molecular level, characterizing the metabolic and immunological phenoreversion over time in large cohorts of hospitalized severe patients (n = 886) and non-hospitalized recovered patients that self-reported having passed the disease (n = 513). Non-hospitalized recovered patients do not show any metabolic fingerprint associated with the disease or immune alterations. Acute patients are characterized by the metabolic and lipidomic dysregulation that accompanies the exacerbated immunological response, resulting in a slow recovery time with a maximum probability of around 62 days. As a manifestation of the heterogeneity in the metabolic phenoreversion, age and severity become factors that modulate their normalization time which, in turn, correlates with changes in the atherogenesis-associated chemokine MCP-1. Our results are consistent with a model where the slow metabolic normalization in acute patients results in enhanced atherosclerotic risk, in line with the recent observation of an elevated number of cardiovascular episodes found in post-COVID-19 cohorts

    Carmustine and methotrexate in combination after whole brain radiation therapy in breast cancer patients presenting with brain metastases: a retrospective study

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Since 1999, patients presenting with brain metastases (BM) from breast cancer (BC) are treated in our institution with a carmustine (BCNU) - methotrexate (MTX) combination. We report here our clinical experience regarding this combination.</p> <p>Patients and Methods</p> <p>Patients were treated by a combination of BCNU 100 mg/m² on day 1 and MTX 600 mg/m² on day 1 and 15 of a 28 day cycle. Treatment was continued until progression or unacceptable toxicity.</p> <p>Results</p> <p>50 patients were treated between 1999 and 2007. 94% of the patients presented with concomitant extra-cerebral disease. Median number of previous metastatic setting chemotherapy regimens was 2 (0-5). Median number of cycles was 3 (1-20). There were 11 objective responses (23% [95%CI 12-37]) among 48 evaluable patients. Median progression-free survival and overall survival (OS) were 4.2 (95%CI: 2.8-5.3) and 6.9 (4.2-10.7) months respectively, with a one-year OS rate of 32% (20-46). Median Relative Dose Intensity for BCNU and MTX were 0.98 (0.31-1.1) and 0.96 (0.57-1.66) respectively. There were 2 presumed treatment-related deaths. One patient developed febrile neutropenia. Performance status, BS-BM score and presence of liver metastases were associated with OS in univariate analysis.</p> <p>Conclusions</p> <p>This combination appears to be effective and well tolerated in good performance status BC patients presenting with BM.</p

    Tumour microvessel density as predictor of chemotherapy response in breast cancer patients

    Get PDF
    The aim of this study was to evaluate the predictive value of intratumoural microvessel density in breast cancer. We studied immunohistochemically primary tumours of 104 patients with metastasised breast cancer who took part in a randomised multicentre trial comparing docetaxel to sequential methotrexate and 5-fluorouracil. Vessels were highlighted with factor VIII staining and counted microscopically. Microvessel density was compared with clinical response to chemotherapy and patient survival. The microvessel density of the primary tumour was not significantly associated with patient's response to chemotherapy, time to progression or overall survival in the whole patient population or in the docetaxel or methotrexate and 5-fluorouracil groups. However, disease-free survival was longer in patients with low microvessel density (P=0.01). These findings suggest that microvessel density of the primary tumour cannot be used as a predictive marker for chemotherapy response in advanced breast cancer

    A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

    Get PDF
    BACKGROUND: Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. METHODOLOGY: We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. CONCLUSIONS: This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking
    corecore