50 research outputs found

    Anticancer Gene Transfer for Cancer Gene Therapy

    Get PDF
    Gene therapy vectors are among the treatments currently used to treat malignant tumors. Gene therapy vectors use a specific therapeutic transgene that causes death in cancer cells. In early attempts at gene therapy, therapeutic transgenes were driven by non-specific vectors which induced toxicity to normal cells in addition to the cancer cells. Recently, novel cancer specific viral vectors have been developed that target cancer cells leaving normal cells unharmed. Here we review such cancer specific gene therapy systems currently used in the treatment of cancer and discuss the major challenges and future directions in this field

    Increasing the reference populations for the 55 AISNP panel: the need and benefits

    Get PDF
    Ancestry inference for an individual can only be as good as the reference populations with allele frequency data on the SNPs being used. If the most relevant ancestral population(s) does not have data available for the SNPs studied, then analyses based on DNA evidence may indicate a quite distantly related population, albeit one among the more closely related of the existing reference populations. We have added reference population allele frequencies for 14 additional population samples (with >1100 individuals studied) to the 125 population samples previously published for the Kidd Lab 55 AISNP panel. Allele frequencies are now publicly available for all 55 SNPs in ALFRED and FROG-kb for a total of 139 population samples. This Kidd Lab panel of 55 ancestry informative SNPs has been incorporated in commercial kits by both ThermoFisher Scientific and Illumina for massively parallel sequencing. Researchers employing those kits will find the enhanced set of reference populations useful

    γ-Glutamyltransferase, but not markers of hepatic fibrosis, is associated with cardiovascular disease in older people with type 2 diabetes mellitus: the Edinburgh Type 2 Diabetes Study

    Get PDF
    AIMS/HYPOTHESIS: We examined the association of prevalent and incident cardiovascular disease (CVD) with chronic liver disease in a cohort of community-based people with type 2 diabetes, in order to clarify the relationship between these two important conditions. METHODS: 1,066 participants with type 2 diabetes aged 60–75 years underwent assessment of a range of liver injury markers (non-specific injury, steatosis, steatohepatitis, fibrosis, portal hypertension). Individuals were followed up for incident cardiovascular events. RESULTS: At baseline there were 370/1,033 patients with prevalent CVD, including 317/1,033 with coronary artery disease (CAD). After a mean follow-up of 4.4 years there were 44/663 incident CVD events, including 27/663 CAD events. There were 30/82 CVD-related deaths. Risk of dying from or developing CVD was no higher in participants with steatosis than in those without (HR 0.90; 95% CI 0.40, 2.00; p > 0.05). The only notable relationship was with γ-glutamyltransferase (GGT) (incident CVD: adjusted HR for doubling GGT 1.24 [95% CI 0.97, 1.59] p = 0.086; incident CAD: adjusted HR 1.33 [95% CI 1.00, 1.78] p = 0.053), suggesting that in our study population, chronic liver disease may have little effect on the development of, or mortality from, CVD. CONCLUSIONS/INTERPRETATION: An independent association between GGT and CVD warrants further exploration as a potentially useful addition to current cardiovascular risk prediction models in diabetes. However, overall findings failed to suggest that there is a clinical or pathophysiological association between chronic liver disease and CVD in elderly people with type 2 diabetes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-015-3575-y) contains peer-reviewed but unedited supplementary material, which is available to authorised users

    Melanocortin-1 Receptor, Skin Cancer and Phenotypic Characteristics (M-SKIP) Project: Study Design and Methods for Pooling Results of Genetic Epidemiological Studies

    Get PDF
    Background: For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia. Design and methods: Based on our experience with the study design of the Melanocortin-1 receptor (MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with random-effects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer development will be studied via logic regression modeling. Discussion: Methodological guidelines to correctly design and conduct pooled-analyses are needed to facilitate application of such methods, thus providing a better summary of the actual findings on specific fields

    Anaemia of acute inflammation: a higher acute systemic inflammatory response is associated with a larger decrease in blood haemoglobin levels in patients with COVID-19 infection

    Full text link
    AIMS: The study tests the hypothesis that a higher acute systemic inflammatory response was associated with a larger decrease in blood hemoglobin levels in patients with Coronavirus 2019 (COVID-19) infection. METHODS: All patients with either suspected or confirmed COVID-19 infection admitted to a busy UK hospital from February 2020 to December 2021 provided data for analysis. The exposure of interest was maximal serum C-reactive protein (CRP) level after COVID-19 during the same admission. RESULTS: A maximal serum CRP >175mg/L was associated with a decrease in blood haemoglobin (-5.0 g/L, 95% confidence interval: -5.9 to -4.2) after adjustment for covariates, including the number of times blood was drawn for analysis.Clinically, for a 55-year-old male patient with a maximum haemoglobin of 150 g/L who was admitted for a 28-day admission, a peak CRP >175 mg/L would be associated with an 11 g/L decrease in blood haemoglobin, compared with only 6 g/L if the maximal CRP was <4 mg/L. CONCLUSIONS: A higher acute systemic inflammatory response is associated with larger decreases in blood haemoglobin levels in patients with COVID-19. This represents an example of anaemia of acute inflammation, and a potential mechanism by which severe disease can increase morbidity and mortality
    corecore