University at Buffalo

About: University at Buffalo is a education organization based out in Buffalo, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 33773 authors who have published 63840 publications receiving 2278954 citations. The organization is also known as: UB & State University of New York at Buffalo.

Breast Cancer Risk in Premenopausal Women Is Inversely Associated with Consumption of Broccoli, a Source of Isothiocyanates, but Is Not Modified by GST Genotype

Abstract: The role of vegetable consumption in relation to breast cancer risk is controversial. Anticarcinogenic compounds may be present only in specific vegetables, thereby attenuating findings for total vegetable intake. Cruciferous vegetables contain precursors of isothiocyanates (ITCs), which may be chemopreventive through potent inhibition of phase I, and induction of phase II enzymes, such as glutathione S-transferases (GSTs). We investigated associations between consumption of cruciferous vegetables, sources of ITCs, and breast cancer risk, and potential modification of relations by GSTM1 and GSTT1 genotypes. Cases (n = 740) were Caucasian women with incident breast cancer identified from all major hospitals in Erie and Niagara counties. Community controls (n = 810) were frequency matched to cases by age and county. An in-depth interview including a validated FFQ was administered in person. Odds ratios (ORs) and 95% CIs were used to estimate relative risks. Consumption of cruciferous vegetables, particularly broccoli, was marginally inversely associated with breast cancer risk in premenopausal women [4th quartile OR = 0.6, 95% CI (0.40-1.01), P = 0.058]. Associations were weaker or null among postmenopausal women. No significant effects of GST genotype on risk were observed in either menopausal group. These data indicate that cruciferous vegetables may play an important role in decreasing the risk of premenopausal breast cancer.

The incidence and significance of anti-natalizumab antibodies: Results from AFFIRM and SENTINEL

Abstract: Objective: To determine the incidence and clinical effects of antibodies that develop during treatment with natalizumab. Methods: In two randomized, double-blind, placebo-controlled studies (natalizumab safety and efficacy in relapsing remitting multiple sclerosis [MS, AFFIRM] and safety and efficacy of natalizumab in combination with interferon β-1a [INFβ1a] in patients with relapsing remitting MS [SENTINEL]) of patients with relapsing multiple sclerosis, blood samples were obtained at baseline and every 12 weeks to determine the presence of antibodies against natalizumab. Antibodies to natalizumab were measured using an ELISA. Patients were categorized as “transiently positive” if they had detectable antibodies (≥0.5 μg/mL) at a single time point or “persistently positive” if they had antibodies at two or more time points ≥6 weeks apart. Results: In the AFFIRM study, antibodies were detected in 57 of 625 (9%) of natalizumab-treated patients: Twenty (3%) were transiently positive and 37 (6%) were persistently positive. Persistently positive patients showed a loss of clinical efficacy as measured by disability progression ( p ≤ 0.05), relapse rate ( p = 0.009), and MRI ( p ≤ 0.05) compared with antibody-negative patients. In transiently positive patients, full efficacy was achieved after approximately 6 months of treatment, the time when patients were becoming antibody negative. The incidence of infusion-related adverse events was significantly higher in persistently positive patients. Results of SENTINEL were similar to AFFIRM, except with regard to sustained disability progression; differences between persistently positive and antibody-negative patients were not statistically significant. Conclusions: The incidence of persistent antibody positivity associated with natalizumab is 6%. Reduced clinical efficacy is apparent in persistently positive patients. Patients with a suboptimal clinical response or persistent infusion-related adverse events should be considered for antibody testing. GLOSSARY: BLQ = below the limit of quantification; EDSS = Expanded Disability Status Scale; Gd+ = gadolinium enhancing; IFNβ1a = interferon β-1a; MS = multiple sclerosis; MSFC = multiple sclerosis functional composite; OD = optical density.

Detection of epithelial ovarian cancer using 1H‐NMR‐based metabonomics

Abstract: Currently available serum biomarkers are insufficiently reliable to distinguish patients with epithelial ovarian cancer (EOC) from healthy individuals. Metabonomics, the study of metabolic processes in biologic systems, is based on the use of (1)H-NMR spectroscopy and multivariate statistics for biochemical data generation and interpretation and may provide a characteristic fingerprint in disease. In an effort to examine the utility of the metabonomic approach for discriminating sera from women with EOC from healthy controls, we performed (1)H-NMR spectroscopic analysis on preoperative serum specimens obtained from 38 patients with EOC, 12 patients with benign ovarian cysts and 53 healthy women. After data reduction, we applied both unsupervised Principal Component Analysis (PCA) and supervised Soft Independent Modeling of Class Analogy (SIMCA) for pattern recognition. The sensitivity and specificity tradeoffs were summarized for each variable using the area under the receiver-operating characteristic (ROC) curve. In addition, we analyzed the regions of NMR spectra that most strongly influence separation of sera of EOC patients from healthy controls. PCA analysis allowed correct separation of all serum specimens from 38 patients with EOC (100%) from all of the 21 premenopausal normal samples (100%) and from all the sera from patients with benign ovarian disease (100%). In addition, it was possible to correctly separate 37 of 38 (97.4%) cancer specimens from 31 of 32 (97%) postmenopausal control sera. SIMCA analysis using the Cooman's plot demonstrated that sera classes from patients with EOC, benign ovarian cysts and the postmenopausal healthy controls did not share multivariate space, providing validation for the class separation. ROC analysis indicated that the sera from patients with and without disease could be identified with 100% sensitivity and specificity at the (1)H-NMR regions 2.77 parts per million (ppm) and 2.04 ppm from the origin (AUC of ROC curve = 1.0). In addition, the regression coefficients most influential for the EOC samples compared to postmenopausal controls lie around delta3.7 ppm (due mainly to sugar hydrogens). Other loadings most influential for the EOC samples lie around delta2.25 ppm and delta1.18 ppm. These findings indicate that (1)H-NMR metabonomic analysis of serum achieves complete separation of EOC patients from healthy controls. The metabonomic approach deserves further evaluation as a potential novel strategy for the early detection of epithelial ovarian cancer.