Smoking status in relation to serum folate and dietary vitamin intake

Objective Cigarette smoke itself is an abundant source of free radicals and a major cause of oxidative stress, to which plasma antioxidants function as a vital protective and counterbalancing mechanism. The objective of this study was to investigate into the relationship between smoking status and serum and dietary micronutrient concentrations. Design Cross-sectional study Subjects ' Setting 502 farmers from the Valley of Messara in Crete were randomly selected and examined. Complete three-day and 24-hr recall questionnaires were collected along with anthropometrical, physical activity and clinical data from all participating subjects. Results After adjusting for age, gender and number of fasting days adhered to per year, current smokers were found to have a lower dietary intake of vitamin C (112.1 mg vs. 136.4 mg, p = 0.03), fibre (16.6 g vs. 19.1 g, p = 0.006) and fruits and vegetables (339 g vs. 412 g, p = 0.014), while dietary vitamin B1 intake was found to be higher (1.7 mg vs. 1.4 mg, p = 0.02) in comparison to non/ex smokers. Dietary intake of meat, folate and vitami A, E, B2, B6 and B12 did not differ between the groups. Controlling age, gender, fasting days and dietary micronutrient intake, serum folate levels were found to be lower among smokers (geometric mean 15.3 nmol/L vs. 17.7 nmol/L, p = 0.023), while serum iron and vitamin B12 levels were not affected by smoking status. Conclusion Current smoking status affects dietary nutrient intake as well as plasma folate levels. The above coherence between antioxidant depletion and reduced antioxidant intake may predispose smokers to the premature development of tobacco related mortality and morbidity

AKT/mTOR Signaling Modulates Resistance to Endocrine Therapy and CDK4/6 Inhibition in Metastatic Breast Cancers

Endocrine therapy (ET) in combination with CDK4/6 inhibition is routinely used as first-line treatment for HR+/HER2− metastatic breast cancer (MBC) patients. However, 30–40% of patients quickly develop disease progression. In this open-label multicenter clinical trial, we utilized a hypothesis-driven protein/phosphoprotein-based approach to identify predictive markers of response to ET plus CDK4/6 inhibition in pre-treatment tissue biopsies. Pathway-centered signaling profiles were generated from microdissected tumor epithelia and surrounding stroma/immune cells using the reverse phase protein microarray. Phosphorylation levels of the CDK4/6 downstream substrates Rb (S780) and FoxM1 (T600) were higher in patients with progressive disease (PD) compared to responders (p = 0.02). Systemic PI3K/AKT/mTOR activation in tumor epithelia and stroma/immune cells was detected in patients with PD. This activation was not explained by underpinning genomic alterations alone. As the number of FDA-approved targeted compounds increases, functional protein-based signaling analyses may become a critical component of response prediction and treatment selection for MBC patients

Multigene prognostic tests in breast cancer: past, present, future

There is growing consensus that multigene prognostic tests provide useful complementary information to tumor size and grade in estrogen receptor (ER)-positive breast cancers. The tests primarily rely on quantification of ER and proliferation-related genes and combine these into multivariate prediction models. Since ER-negative cancers tend to have higher proliferation rates, the prognostic value of current multigene tests in these cancers is limited. First-generation prognostic signatures (Oncotype DX, MammaPrint, Genomic Grade Index) are substantially more accurate to predict recurrence within the first 5 years than in later years. This has become a limitation with the availability of effective extended adjuvant endocrine therapies. Newer tests (Prosigna, EndoPredict, Breast Cancer Index) appear to possess better prognostic value for late recurrences while also remaining predictive of early relapse. Some clinical prediction problems are more difficult to solve than others: there are no clinically useful prognostic signatures for ER-negative cancers, and drug-specific treatment response predictors also remain elusive. Emerging areas of research involve the development of immune gene signatures that carry modest but significant prognostic value independent of proliferation and ER status and represent candidate predictive markers for immune-targeted therapies. Overall metrics of tumor heterogeneity and genome integrity (for example, homologue recombination deficiency score) are emerging as potential new predictive markers for platinum agents. The recent expansion of high-throughput technology platforms including low-cost sequencing of circulating and tumor-derived DNA and RNA and rapid reliable quantification of microRNA offers new opportunities to build extended prediction models across multiplatform data

Predictors of Chemosensitivity in Triple Negative Breast Cancer: An Integrated Genomic Analysis

Background: Triple negative breast cancer (TNBC) is a highly heterogeneous and aggressive disease, and although no effective targeted therapies are available to date, about one-third of patients with TNBC achieve pathologic complete response (pCR) from standard-of-care anthracycline/taxane (ACT) chemotherapy. The heterogeneity of these tumors, however, has hindered the discovery of effective biomarkers to identify such patients. Methods and Findings: We performed whole exome sequencing on 29 TNBC cases from the MD Anderson Cancer Center (MDACC) selected because they had either pCR (n = 18) or extensive residual disease (n = 11) after neoadjuvant chemotherapy, with cases from The Cancer Genome Atlas (TCGA; n = 144) and METABRIC (n = 278) cohorts serving as validation cohorts. Our analysis revealed that mutations in the AR- and FOXA1-regulated networks, in which BRCA1 plays a key role, are associated with significantly higher sensitivity to ACT chemotherapy in the MDACC cohort (pCR rate of 94.1% compared to 16.6% in tumors without mutations in AR/FOXA1 pathway, adjusted p = 0.02) and significantly better survival outcome in the TCGA TNBC cohort (log-rank test, p = 0.05). Combined analysis of DNA sequencing, DNA methylation, and RNA sequencing identified tumors of a distinct BRCA-deficient (BRCA-D) TNBC subtype characterized by low levels of wild-type BRCA1/2 expression. Patients with functionally BRCA-D tumors had significantly better survival with standard-of-care chemotherapy than patients whose tumors were not BRCA-D (log-rank test, p = 0.021), and they had significantly higher mutation burden (p < 0.001) and presented clonal neoantigens that were associated with increased immune cell activity. A transcriptional signature of BRCA-D TNBC tumors was independently validated to be significantly associated with improved survival in the METABRIC dataset (log-rank test, p = 0.009). As a retrospective study, limitations include the small size and potential selection bias in the discovery cohort. Conclusions: The comprehensive molecular analysis presented in this study directly links BRCA deficiency with increased clonal mutation burden and significantly enhanced chemosensitivity in TNBC and suggests that functional RNA-based BRCA deficiency needs to be further examined in TNBC. © 2016 Jiang et al

Increasing consistency of disease biomarker prediction across datasets

Microarray studies with human subjects often have limited sample sizes which hampers the ability to detect reliable biomarkers associated with disease and motivates the need to aggregate data across studies. However, human gene expression measurements may be influenced by many non-random factors such as genetics, sample preparations, and tissue heterogeneity. These factors can contribute to a lack of agreement among related studies, limiting the utility of their aggregation. We show that it is feasible to carry out an automatic correction of individual datasets to reduce the effect of such 'latent variables' (without prior knowledge of the variables) in such a way that datasets addressing the same condition show better agreement once each is corrected. We build our approach on the method of surrogate variable analysis but we demonstrate that the original algorithm is unsuitable for the analysis of human tissue samples that are mixtures of different cell types. We propose a modification to SVA that is crucial to obtaining the improvement in agreement that we observe. We develop our method on a compendium of multiple sclerosis data and verify it on an independent compendium of Parkinson's disease datasets. In both cases, we show that our method is able to improve agreement across varying study designs, platforms, and tissues. This approach has the potential for wide applicability to any field where lack of inter-study agreement has been a concern. © 2014 Chikina, Sealfon

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem

Dietary and other lifestyle correlates of serum folate concentrations in a healthy adult population in Crete, Greece: a cross-sectional study

BACKGROUND: Folate has emerged as a key nutrient for optimising health. Impaired folate status has been identified as a risk factor for cardiovascular disease, various types of cancers, and neurocognitive disorders. The study aimed at examining the distribution and determinants of serum folate concentrations in a healthy adult population in Crete, Greece. METHODS: A cross-sectional sample of 486 healthy adults (250 men, 236 women) aged 39 ± 14 years, personnel of the Medical School and the University Hospital of Crete in Greece, was examined. Serum folate and vitamin B(12 )concentrations were measured by microbiological assay, and total homocysteine was determined fluorometrically and by high-pressure liquid chromatography. Lifestyle questionnaires were completed, and nutrient intakes and food consumption were assessed by 24-h dietary recalls. Multivariate analyses were performed using SPSS v10.1. RESULTS: The geometric mean (95% confidence interval) concentrations of serum folate were 15.6 μmol/l (14.6–16.8) in men and 19.2 μmol/l (17.9–20.7) in women (p < 0.001). Inadequate folate levels (≤7 nmol/l) were present in 6.8% of men and 2.1% of women (p < 0.001). Approximately 76% of men and 87% of women did not meet the reference dietary intake for folate (400 μg/day). Serum folate was inversely related to total homocysteine levels (p < 0.001). Increased tobacco and coffee consumption were associated with lower folate concentrations (p < 0.05 for both) but these associations disappeared after controlling for nutrient intakes. In multivariate analysis, intakes of MUFA, fibre, calcium, magnesium, folate, and vitamins A, E, C, B(1), and B(6 )were positively associated with serum folate. Consumption of potatoes, legumes, fruits, and vegetables were favourably related to the serum folate status. CONCLUSION: Serum folate concentrations were associated with various demographic, lifestyle and dietary factors in healthy Cretan adults. Large-scale epidemiological studies should be conducted within the general Greek adult population to assess the prevalence of impaired folate status and further examine associations with dietary patterns and chronic disease risk. Considering the importance of folate in health maintenance, it is important to increase the public's awareness of modifiable lifestyle patterns and diet and tobacco use in particular, which may be associated with improved folate status

Atherogenic risk factors among preschool children in Crete, Greece

Objective: To investigate the presence of atherogenic factors among preschool children of Crete, Greece. Materials and Methods: This was a cross-sectional study. The study population included 1189 children, aged four to seven years, examined from January to May 2005, in public kindergartens. Biochemical, anthropometric, and blood pressure measurements were performed. Results: Of the boys 27.4% were classified as overweight or obese (obese 10.8%). The respective percentage for girls was 28.5% (obese 9%); 7.4% percent of the boys and 7.9% of the girls had blood pressure above the ninety-fifth percentile. TC of > 200 mg / dl was found in 14.4% and LDL-C of > 130 mg / dl in 13.8% of the children. Children with serum TG of > 100 mg / dl had a significantly higher mean WC and BMI than those with triglyceride levels of ≤ 80 mg / dl (59.7 vs. 55.9 cm and 17.9 vs. 16.6 kg / m 2 ; P < 0.05). Similarly, children with HDL-C < 45 mg / dl had significantly higher WC and BMI than children with HDL-C ≥ 60 mg / dl (57.7 vs. 53.5 cm and 17.1 vs. 16.5 kg / m 2 ; P < 0.05). Obese children had an Odds Ratio of 2.87 (95% confidence interval, 1.05 − 7.85, P = 0.041) for hypertriglyceridemia, as compared to non-obese children. Conclusion: Levels of obesity and especially central obesity were strongly related to other atherogenic risk factors in Cretan preschool children indicating the presence of this major public health problem in early ages

Use of genomic grade index (GGI) to predict pathologic response to preoperative chemotherapy in breast cancer

Abstract 541info:eu-repo/semantics/publishe