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Background: p53 gene therapy has been examined in several clinical trials, however, the results of those trials have mostly been unsatisfactory due to the low efficacy of this therapy. Leptomycin B (LMB) is an antibiotic originally isolated from Streptomyces that has the ability to inhibit the export of proteins containing a nuclear export signal from the nucleus to the cytoplasm. Currently, it has been shown that p53 protein has a nuclear export signal. In this study, we assessed whether LMB augments the transduced p53 gene effect. Methods: Antiproliferative effect of LMB was assessed in human esophageal squamous cancer cell lines. Accumulation of p53 protein into the nucleus by LMB was observed by fluorescence microscopy. The combined effect of p53 and LMB was evaluated in in vitro experiments. Results: LMB induced cell death in a dose-dependent manner and p53 drastically accumulated in the nucleus after LMB treatment. The combinatory treatment of p53 gene and LMB significantly increases the efficiency compared to either agent alone. Conclusions: Our findings suggest that LMB has a potent ability to augment the effect of the tumor suppressor p53 in esophageal squamous cancer cell lines and that it is a promising component in p53 gene therapy.

Background: Intratumoral heterogeneity is a well-recognized characteristic feature of cancer. The purpose of this study is to assess the heterogeneity of the intratumoral glucose metabolism using fractal analysis, and evaluate its prognostic value in patients with esophageal squamous cell carcinoma (ESCC). Methods: 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) studies of 79 patients who received curative surgery were evaluated. FDG-PET images were analyzed using fractal analysis software, where differential box-counting method was employed to calculate the fractal dimension (FD) of the tumor lesion. Maximum standardized uptake value (SUVmax) and FD were compared with overall survival (OS). Results: The median SUVmax and FD of ESCCs in this cohort were 13.8 and 1.95, respectively. In univariate analysis performed using Cox's proportional hazard model, T stage and FD showed significant associations with OS (p = 0.04, p < 0.0001, respectively), while SUVmax did not (p = 0.1). In Kaplan-Meier analysis, the low FD tumor (<1.95) showed a significant association with favorable OS (p < 0.0001). In wthe multivariate analysis among TNM staging, serum tumor markers, FD, and SUVmax, the FD was identified as the only independent prognostic factor for OS (p = 0.0006; hazards ratio 0.251, 95% CI 0.104-0.562). Conclusion: Metabolic heterogeneity measured by fractal analysis can be a novel imaging biomarker for survival in patients with ESCC.

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