A Population-Based Study of IGF Axis Polymorphisms and the Esophageal Inflammation, Metaplasia, Adenocarcinoma Sequence

BACKGROUND & AIMS: Insulin-like growth factor (IGF) axis plays a key role in cell development, proliferation, and survival and is implicated in the etiology of several cancers. Few studies have examined the relationship between genetic variation of this axis and esophageal adenocarcinoma (EAC) or its precursors. METHODS: In a population-based case-control study, we investigated the association of common polymorphisms of IGF-1, IGF-2, IGF-1 receptor, IGF binding protein -3, growth hormones (GH) 1 and GH2, and GH receptor with reflux esophagitis (RE), Barrett esophagus (BE), and EAC. Two hundred and thirty RE, 224 BE, 227 EAC cases, and 260 controls were studied. Gene polymorphisms were identified using publicly available online resources; 102 IGF axis tag and putatively functional single-nucleotide polymorphisms (SNPs) were analyzed using MassARRAY iPLEX and Taqman assays. Results were analyzed using Haploview.
RESULTS: Three polymorphisms were disease-associated. IGF1 SNP rs6214 was associated with BE (adjusted P = .039). Using GG genotype as reference, odds ratio for BE in AA (wild-type) was 0.43 (95% confidence interval [CI], 0.24-0.75). GH receptor SNP rs6898743 was associated with EAC (adjusted P = .0112). With GG as reference, odds ratio for EAC in CC (wildtype) genotype was 0.42 (95% CI, 0.23-0.76). IGF1 (CA)(17) 185-bp allele was associated with RE (adjusted P = .0116). Using IGF1(non17) as reference, odds ratio for RE in IGF1(17) carriers was 7.29 (95% CI, 1.57-46.7).
CONCLUSIONS: In this study, 3 polymorphisms of IGF genes were associated with EAC or its precursors. These polymorphisms may be markers of disease risk; independent validation of our findings is required. These results suggest the IGF pathway is involved in EAC development.

The DUB/USP17 deubiquitinating enzymes: A gene family within a tandemly repeated sequence, is also embedded within the copy number variable Beta-defensin cluste

Background: The DUB/USP17 subfamily of deubiquitinating enzymes were originally identified as immediate early genes induced in response to cytokine stimulation in mice (DUB-1, DUB-1A, DUB-2, DUB-2A). Subsequently we have identified a number of human family members and shown that one of these (DUB-3) is also cytokine inducible. We originally showed that constitutive expression of DUB-3 can block cell proliferation and more recently we have demonstrated that this is due to its regulation of the ubiquitination and activity of the 'CAAX' box protease RCE1.

Results: Here we demonstrate that the human DUB/USP17 family members are found on both chromosome 4p16.1, within a block of tandem repeats, and on chromosome 8p23.1, embedded within the copy number variable betadefensin cluster. In addition, we show that the multiple genes observed in humans and other distantly related mammals have arisen due to the independent expansion of an ancestral sequence within each species. However, it is also apparent when sequences from humans and the more closely related chimpanzee are compared, that duplication events have taken place prior to these species separating.

Conclusions: The observation that the DUB/USP17 genes, which can influence cell growth and survival, have evolved from an unstable ancestral sequence which has undergone multiple and varied duplications in the species examined marks this as a unique family. In addition, their presence within the beta-defensin repeat raises the question whether they may contribute to the influence of this repeat on immune related conditions.

Dual Sequence Simulated Annealing with Round-Robin Approach for University Course Timetabling

The university course timetabling problem involves assigning a given number of events into a limited number of timeslots and rooms under a given set of constraints; the objective is to satisfy the hard constraints (essential requirements) and minimize the violation of soft constraints (desirable requirements). In this study we employed a Dual-sequence Simulated Annealing (DSA) algorithm as an improvement algorithm. The Round Robin (RR) algorithm is used to control the selection of neighbourhood structures within DSA. The performance of our approach is tested over eleven benchmark datasets. Experimental results show that our approach is able to generate competitive results when compared with other state-of-the-art techniques.