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Background: Gastric cancer is a common and lethal disease throughout the world. This study was designed and carried out to determine the five-year survival rate of gastric cancer patients who had undergone surgical treatment at Taleghani Hospital of Tehran, and to assess its associated factors. Materials and Methods: In this historical-cohort study, information obtained from a total of 213 gastric cancer patients who underwent surgery at Taleghani Hospital of Tehran between 2003 and 2008 was included. In the analyses, Kaplan-Meier method, log-rank test, Cox proportional hazards model, and Lin-Ying additive hazards model were used. Results: The five-year survival rate and the median life expectancy in the studied patients were 14.6% and 29.6 months, respectively. Two covariates showed significant impacts on the gastric cancer patients’ data in both models: age at diagnosis and tumor size. We found that pathologic stage was significant under the Lin-Ying model (P=0.043) however, it was not significant under the Cox model (P=0.069). Other clinicopathological characteristics were not statistically significant (P>0.05). Conclusion: Since Cox and Lin-Ying models consider different aspects of the association between risk factors and the study outcome, it seems desirable to use both of them as complementary models but not as alternative models to obtain a more comprehensive understanding of data. This study showed that the early detection of patients in younger ages and in primary stages is important to decrease the risk of death in patients with gastric cancer and to increase the survival rate.

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Background: Gastric cancer is the second leading cause of mortality due to cancer worldwide and it is the most common type of cancer in Iran. The aim of this study was to assess the effects of prognostic factors on the survival of patients with gastric cancer using the penalized spline in Cox model and compare it with Cox proportional hazards model. Materials and Methods: In this retrospective study, information obtained from a total of 216 gastric cancer patients who underwent surgery at Taleghani Hospital of Tehran between 2003 and 2008 years was included. Cox proportional hazards model and penalized spline in Cox model were used. R software was used for data analysis. The efficacy of these models was compared according to Akaike information criterion. Results: The five-year survival rate was 30% and the mean follow-up time was 16.60±15.28 months. Survival mean and median were 46 and 30 months, respectively. The analysis of Cox proportional hazards and penalized spline models resulted in age at diagnosis and tumor size as prognostic factors for survival time (P<0.05). Also, Akaike information criterion and survival curve for patients with a tumor size over 35 mm and age at diagnosis over 45 years were equal in both models. Conclusion: Cox proportional hazards and penalized spline models generated similar results thus, it is more appropriate to use Cox proportional hazards model because of its ease of interpretation and capability of modeling both continuous and discrete covariates. This study also showed if gastric cancer is diagnosed early, the relative risk of death will reduce.

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Background: Nitric oxide is synthesized in endothelial cells by eNOS and acts as a pleiotropic regulator involved in carcinogenesis. Most gastric cancers develop from stomach epithelial cells therefore, NO may play a role in their development. Polymorphisms of eNOS have been shown to be associated with cancer susceptibility. In the present study, we investigated the association of the eNOS genotypes with gastric cancer risk in Guilan Population.

Materials and Methods: In this case-control study, we analyzed the Glu298Asp polymorphism of eNOS in 87 patients with gastric cancer and 90 healthy controls. The genotyping of eNOS polymorphism was performed using polymerase chain reaction–restriction fragment length polymorphism assays. All statistical analyses were conducted by the MedCalc statistical software.

Results: No association between the eNOS genotypes and gastric cancer risk was found. Among the 87 patients, 45 had Glu/Glu, 38 were Glu/Asp, and 4 were Asp/Asp. In the control group, 44 had Glu/Glu, 40 were Glu/Asp, and 6 were Asp/Asp. We found no significant differences in allele and genotype frequencies between control and patient specimens.

Conclusion: We found that there was no association between this polymorphism and gastric cancer risk. Results suggest that eNOS polymorphism may play a role in inhibition of gastric cancer. However, larger population-based studies are needed for clarifying the role of eNOS polymorphism in gastric cancer.

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Background: Circulating microRNAs are promising biomarkers in diagnosis and assessment of cancerous patients. Quantitative Real-time PCR assay is a sensitive test for evaluating the levels of miRNAs expression. Nevertheless, there is no concurrence on selecting appropriate reference genes for qPCR analysis of miRNAs in circulation. Therefore, the current study aimed to select a suitable reference gene for normalizing the RT-qPCR assay results in plasma samples of patients with gastric cancer.

Materials and Methods: Based on previously published studies, three molecules SNORD47, U6 RNA, and miR-103 were selected as the candidate reference genes. After RNA extraction from plasma samples of 40 patients with gastric cancer and 40 healthy individuals, expression levels of these molecules were evaluated using Real-time PCR method.

Results: The results showed that the developed assays are able to diagnose their specified targets by a suitable linear range. By comparing patients and control groups, although the expression levels of miR-103 molecule were not equal between the two groups (p= 0.017), SNORD47 and U6 RNAs had similar expression levels. However, the variations of SNORD47 expression were lower that U6 RNA.

Conclusion: Based on the results of the current study, the SNORD47 molecule has a stable expression levels in plasma samples of patients with gastric cancer and normal individuals and can be used as an appropriate reference gene for normalizing the quantitative data of qPCR assay.