Pancreatic cancer (PC) is a lethal solid malignancy with resistance to traditional chemotherapy. Recently, considerable studies have demonstrated the ubiquitous antitumor properties of gene therapy mediated by the oncolytic vaccinia virus. The second mitochondrial-derived activator of caspase (Smac) has been identified as an innovative tumor suppressor that augments the chemosensitivity of cancer cells. However, the therapeutic value of oncolytic vaccinia virus (oVV)-mediated Smac gene transfer in pancreatic cancer is yet to be elucidated. In the present study, oncolytic vaccinia virus expressing Smac (second mitochondrial-derived activator of caspase) (oVV-Smac) was used to examine its beneficial value when used alone or with gemcitabine in pancreatic cancer in vitro and in vivo. The expression of Smac was evaluated by western blot analysis and quantitative polymerase chain reaction, oVV-Smac cytotoxicity by MTT assay, and apoptosis by flow cytometry and western blot analysis. Furthermore, the inhibitory effect of oVV-Smac combined with gemcitabine was also evaluated. The results indicated that oVV-Smac achieved high levels of Smac, greater cytotoxicity, and potentiated apoptosis. Moreover, co-treatment with oVV-Smac and gemcitabine resulted in a synergistic effect in vitro and in vivo. Therefore, our findings advance oVV-Smac as a potential therapeutic candidate in pancreatic cancer and indicated the synergistic effects of co-treatment with oVV-Smac and gemcitabine.

Purpose Gastric cancer is often detected in the late stages, due to which its mortality rate remains high. Early detection of gastric cancer could significantly improve the prognosis of patients since the survival rate of early gastric cancer after treatment exceeds 96%. This study aimed to analyze early gastric cancer (EGC) risk factors and construct a nomogram model to predict EGC patients. Methods A retrospective study was conducted on 589 patients, including 325 patients with EGC and 264 patients with benign gastric disease. Age, sex, neutrophil to lymphocyte ratio (NLR), creatinine, hypertension, diabetes and other clinical data were collected accordingly. A nomogram was then constructed using univariate analysis and multivariate analysis. Moreover, a correction curve and AUCs were utilized to determine the accuracy of our model. Results Our findings revealed that sex, age, NLR, creatinine, basophil, hypertension and diabetes were risk factors for EGC. A predictive nomogram model was constructed based on the above risk factors showing good consistency and accuracy (AUC = 0.77), the validation cohort showed good consistency(AUC = 0.776). Conclusion The nomogram model presented good reliability, and it will help clinicians to predict and diagnose EGC patients timely while avoiding unnecessary gastrectomy.