103 resultados para Biology, Bioinformatics
Resumo:
Chemotherapy response rates for advanced colorectal cancer remain disappointingly low, primarily because of drug resistance, so there is an urgent need to improve current treatment strategies. To identify novel determinants of resistance to the clinically relevant drugs 5-fluorouracil (5-FU) and SN38 (the active metabolite of irinotecan), transcriptional profiling experiments were carried out on pretreatment metastatic colorectal cancer biopsies and HCT116 parental and chemotherapy-resistant cell line models using a disease-specific DNA microarray. To enrich for potential chemoresistance-determining genes, an unsupervised bioinformatics approach was used, and 50 genes were selected and then functionally assessed using custom-designed short interfering RNA(siRNA) screens. In the primary siRNA screen, silencing of 21 genes sensitized HCT116 cells to either 5-FU or SN38 treatment. Three genes (RAPGEF2, PTRF, and SART1) were selected for further analysis in a panel of 5 colorectal cancer cell lines. Silencing SART1 sensitized all 5 cell lines to 5-FU treatment and 4/5 cell lines to SN38 treatment. However, silencing of RAPGEF2 or PTRF had no significant effect on 5-FU or SN38 sensitivity in the wider cell line panel. Further functional analysis of SART1 showed that its silencing induced apoptosis that was caspase-8 dependent. Furthermore, silencing of SART1 led to a downregulation of the caspase-8 inhibitor, c-FLIP, which we have previously shown is a key determinant of drug resistance in colorectal cancer. This study shows the power of systems biology approaches for identifying novel genes that regulate drug resistance and identifies SART1 as a previously unidentified regulator of c-FLIP and drug-induced activation of caspase-8. Mol Cancer Ther; 11(1); 119-31. (C) 2011 AACR.
Resumo:
Fasciola hepatica secretes cathepsin L proteases that facilitate the penetration of the parasite through the tissues of its host, and also participate in functions such as feeding and immune evasion. The major proteases, cathepsin L1 (FheCL1) and cathepsin L2 (FheCL2) are members of a lineage that gave rise to the human cathepsin Ls, Ks and Ss, but while they exhibit similarities in their substrate specificities to these enzymes they differ in having a wider pH range for activity and an enhanced stability at neutral pH. There are presently 13 Fasciola cathepsin L cDNAs deposited in the public databases representing a gene family of at least seven distinct members, although the temporal and spatial expression of each of these members in the developmental stage of F. hepatica remains unclear. Immunolocalisation and in situ hybridisation studies, using antibody and DNA probes, respectively, show that the vast majority of cathepsin L gene expression is carried out in the epithelial cells lining the parasite gut. Within these cells the enzyme is packaged into secretory vesicles that release their contents into the gut lumen for the purpose of degrading ingested host tissue and blood. Liver flukes also express a novel multi-domain cystatin that may be involved in the regulation of cathepsin L activity. Vaccine trials in both sheep and cattle with purified native FheCL1 and FheCL2 have shown that these enzymes can induce protection, ranging from 33 to 79%, to experimental challenge with metacercariae of F. hepatica, and very potent anti-embryonation/hatch rate effects that would block parasite transmission. In this article we review the vaccine trials carried out over the past 8 years, the role of antibody and T cell responses in mediating protection and discuss the prospects of the cathepsin Ls in the development of first generation recombinant liver fluke vaccines. Author Keywords: Helminths; Trematodes; Parasites; Cathepsins; Proteases; Vaccines; Immunology; Biochemistry
Resumo:
The aim of the 5-year European Union (EU)-Integrated Project GEnetics of Healthy Aging (GEHA), constituted by 25 partners (24 from Europe plus the Beijing Genomics Institute from China), is to identify genes involved in healthy aging and longevity, which allow individuals to survive to advanced old age in good cognitive and physical function and in the absence of major age-related diseases. To achieve this aim a coherent, tightly integrated program of research that unites demographers, geriatricians, geneticists, genetic epidemiologists, molecular biologists, bioinfomaticians, and statisticians has been set up. The working plan is to: (a) collect DNA and information on the health status from an unprecedented number of long-lived 90+ sibpairs (n = 2650) and of younger ethnically matched controls (n = 2650) from 11 European countries; (b) perform a genome-wide linkage scannning in all the sibpairs (a total of 5300 individuals); this investigation will be followed by linkage disequilibrium mapping (LD mapping) of the candidate chromosomal regions; (c) study in cases (i.e., the 2650 probands of the sibpairs) and controls (2650 younger people), genomic regions (chromosome 4, D4S1564, chromosome 11, 11.p15.5) which were identified in previous studies as possible candidates to harbor longevity genes; (d) genotype all recruited subjects for apoE polymorphisms; and (e) genotype all recruited subjects for inherited as well as epigenetic variability of the mitochondrial DNA (mtDNA). The genetic analysis will be performed by 9 high-throughput platforms, within the framework of centralized databases for phenotypic, genetic, and mtDNA data. Additional advanced approaches (bioinformatics, advanced statistics, mathematical modeling, functional genomics and proteomics, molecular biology, molecular genetics) are envisaged to identify the gene variant(s) of interest. The experimental design will also allow (a) to identify gender-specific genes involved in healthy aging and longevity in women and men stratified for ethnic and geographic origin and apoE genotype; (b) to perform a longitudinal survival study to assess the impact of the identified genetic loci on 90+ people mortality; and (c) to develop mathematical and statistical models capable of combining genetic data with demographic characteristics, health status, socioeconomic factors, lifestyle habits.