Polymorphism of SMAD 7 gene [rs2337104] and risk of colorectal cancer in an Iranian population: a case-control study

The purpose of this study was to evaluate the influence of intronic polymorphism of the SMAD7 [Mothers Against Decantaplegic Homolog 7] gene [rs2337104] on the risk of colorectal cancer [CRC] and clinicopathological features in an Iranian population. SMAD7 has been identified as an antagonist of transforming growth factor beta [TGF-b]-mediating fibrosis, carcinogenesis, and inflammation. Regarding to the recent genome-wide scan, a risk locus for colorectal cancer at 18q21 has been found, which maps to the SMAD7 gene. This case-control study was performed on 109 CRC patients and 109 healthy controls recruited in Taleghani Hospital. The genotyping of all samples were done by TaqMan assay via an ABI 7500 Real Time PCR System [Applied Biosystems] with DNA from peripheral blood. The association of this polymorphism with the risk of CRC and clinico pathological features was investigated. Our results indicated that there were no significant association between genotypic and allelic frequencies of SMAD7 polymorphism [rs2337104] and CRC risk in our population. Although the T allele is the most frequent one in this population and its frequency was 86.7% in patients compared with 91.7% in controls [OR=1.705, 95% CI= 0.916-3.172]. Also, the SMAD7 genotypes were not associated with any clinicopathological characteristics in CRC patients [P>0.05]. For the first time, this study results revealed that this SMAD7 polymorphism couldn't be a potential risk factor for CRC or a prognostic biomarker for prediction of clinicopathological features in an Iranian population. A large-scale case-control study is needed to validate our results

Protein-protein interaction networks [PPI] and complex diseases

The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic [and physiologic] mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network