Prognostic Impact of Polymorphisms in the CASPASE Genes on Survival of Patients with Colorectal Cancer
CANCER RESEARCH AND TREATMENT
Authors: Choi, Jun Young; Kim, Jong Gwang; Lee, You Jin; Chae, Yee Soo; Sohn, Sang Kyun; Moon, Joon Ho; Kang, Byung Woog; Jung, Min Kyu; Jeon, Seong Woo; Park, Jun Seok; Choi, Gyu Seog
Abstract
Purpose This study analyzed potentially functional polymorphisms in CASPASE (CASP) genes and their impact on the prognosis for Korean colorectal cancer patients. Materials and Methods A total of 397 consecutive patients with curatively resected colorectal adenocarcinoma were enrolled in this study. Genomic DNA from these patients was extracted from fresh colorectal tissue, and the 10 polymorphisms in the CASP3, CASP6, CASP7, CASP8, CASP9, and CASP10 genes were determined using a reverse transcription polymerase chain reaction genotyping assay. Results The median patient age was 63 years, and 218 (54.9%) patients had colon cancer, while 179 (45.1%) patients had rectal cancer. Univariate and multivariate survival analysis including pathologic stage, patient age, differentiation, and carcinoembryonic antigen level demonstrated that these polymorphisms were not associated with either disease-free or overall survival. Conclusion None of the 10 polymorphisms in the CASP genes investigated in this study was found to be an independent prognostic marker for Korean patients with curatively resected colorectal cancer.
A structural proteomics filter: prediction of the quaternary structural type of hetero-oligomeric proteins on the basis of their sequences
JOURNAL OF APPLIED CRYSTALLOGRAPHY
Authors: Carugo, Oliviero
Abstract
A protein chain can correspond to a monomeric protein or it can form, together with other chains, oligomeric assemblies, which can be either homo-oligomers or hetero-oligomers. In the latter case, the three-dimensional structure of the single protein chain is unlikely to be determined, since it will probably be difficult to express and crystallize. A computational method is presented here that allows one to predict if a chain participates in hetero-oligomeric assemblies, on the basis of its amino acid composition, with accuracy close to 80%. Such a technique should improve the success rate of structural biology projects.