Purpose: To build a dual-energy computed tomography (DECT) delta radiomics model to predict chemotherapeutic response for far-advanced gastric cancer (GC) patients. A semi-automatic segmentation method based on deep learning was designed, and its performance was compared with that of manual segmentation. Methods: This retrospective study included 86 patients with far-advanced GC treated with chemotherapy from September 2016 to December 2017 (66 and 20 in the training and testing cohorts, respectively). Delta radiomics features between the baseline and first follow-up DECT were modeled by random forest to predict the chemotherapeutic response evaluated by the second follow-up DECT. Nine feature subsets from confounding factors and delta radiomics features were used to choose the best model with 10-fold cross-validation in the training cohort. A semi-automatic segmentation method based on deep learning was developed to predict the chemotherapeutic response and compared with manual segmentation in the testing cohort, which was further validated in an independent validation cohort of 30 patients. Results: The best model, constructed by confounding factors and texture features, reached an average AUC of 0.752 in the training cohort. Our proposed semi-automatic segmentation method was more time-effective than manual segmentation, with average saving-time of 11.2333 ± 6.3989 minutes and 9.9889 ±5.5086 minutes in the testing cohort and the independent validation cohort, respectively (both p < 0.05). The predictive ability of the semi-automatic segmentation was also better than that of the manual segmentation both in the testing cohort and the independent validation cohort (AUC: 0.728 vs. 0.687 and 0.828 vs. 0.749, respectively). Conclusion: DECT delta radiomics serves as a promising biomarker for predicting chemotherapeutic response for far-advanced GC. Semi-automatic segmentation based on deep learning shows the potential for clinical use with increased reproducibility and decreased labor costs compared to the manual version.

Background: The current model for predicting prognosis and chemotherapy response of patients with gastric adenocarcinoma is the TNM staging system, which may lack adequate accuracy and evaluations of molecular features at the individual level. We aimed to develop a prediction model to assess the individualized prognosis and responsiveness to fluorouracil-based adjuvant chemotherapy. Method: This retrospective study concluded 2 independent cohorts of patients with GAC. The expression of dysbindin was quantified and evaluated the association with the overall survival for GAC patients. A prediction model for postoperative overall survival was generated and internally and externally validated. The interaction between dysbindin expression and PACT was detected in advanced GAC patients. Results: Of the 637 patients enrolled in the study, 425 were men (66.7%) with a mean (SD) age of 59.79 (9.81) years. High levels of dysbindin expression predicted a poor prognosis in patients with GAC. Multivariate analysis demonstrated dysbindin expression was an independent prognostic predictor of overall survival in the test, validation and combined cohorts. A prognostic predictive model incorporating age, dysbindin expression, pathological differentiation, Lauren's classification and the TNM staging system was established. This model had better predictive accuracy for overall survival than the traditional TNM staging system and was internally and externally validated. More importantly, advanced GAC patients with low dysbindin expression were likely to benefit from fluorouracil-based PACT. Conclusion: The risk stratification model incorporating dysbindin expression and TNM staging system showed better predictive accuracy. Advanced GAC patients with low dysbindin expression revealed better response of fluorouracil-based adjuvant chemotherapy.

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide, but the overall prognosis remains disappointing especially in the advanced-stage patients. Aberration expression of Aurora kinases is tumorigenic and thus it has attracted interests as therapeutic targets in cancer treatment. Here, we investigated the proteomic response of HCC Hep3B cells to danusertib (Danu), a pan-Aurora kinase inhibitor, and then validated the proteomic results based on stable-isotope labeling by amino acids in cell culture (SILAC). The proteomic data identified that Danu modulated the expression of 542 protein molecules (279 up-regulated; 260 down-regulated; 3 stable). Ingenuity pathway analysis (IPA) and KEGG pathway analysis identified 107 and 24 signaling pathways were regulated by Danu, respectively. IPA analysis showed cellular growth and proliferation, and cell death and survival were among the top five molecular and cellular functions regulated by Danu. The verification experiments showed that Danu inhibited the proliferation of Hep3B cells with a 24-hr IC50 value of 22.03 µM. Danu treatment also arrested Hep3B cells in G2/M phase via regulating the expression of key cell cycle regulators and induced apoptosis via mitochondria-dependent pathway in a dose-dependent manner. Besides, Danu induced a marked autophagy, and inhibition of autophagy enhanced the anticancer effects of Danu, indicating a cyto-protective role of Danu-induced autophagy. Our proteomic data and Western blotting assays showed the PI3K/Akt/mTOR signaling pathway was involved in the inducing effect of Danu on apoptosis and autophagy. Collectively, our findings have demonstrated that the Aurora kinases inhibition with danusertib results in global proteomic response and exerts anticancer effects in Hep3B cells involving regulation of cell cycle, apoptosis and autophagy and associated signaling pathways.

Background: DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is known to function in several types of cancer. In this study, we investigated the expression and clinicopathologic significance of DNA-PKcs in laryngeal squamous cell carcinoma (LSCC). Methods: We conducted a retrospective study of 208 patients with advanced-stage LSCC treated at Sun Yat-sen University Cancer Center, Guangzhou, China. We assessed DNA-PKcs and p16INK4a (p16) status using immunohistochemistry. We examined the association between DNA-PKcs expression and clinicopathologic features and survival outcomes. To evaluate the independent prognostic relevance of DNA-PKcs, we used univariate and multivariate Cox regression models. We estimated overall survival (OS) and distant metastasis-free survival (DMFS) using the Kaplan-Meier method. Results: Immunohistochemical analyses revealed that 163/208 (78.4%) of the LSCC tissue samples exhibited high DNA-PKcs expression. High DNA-PKcs expression was significantly associated with survival outcomes (P = 0.016) and distant metastasis (P = 0.02; chi-squared test). High DNA-PKcs expression was associated with a significantly shorter OS and DMFS than low DNA-PKcs expression (P = 0.029 and 0.033, respectively; log-rank test), and was associated with poor OS in the p16-positive subgroup (P = 0.047). Multivariate analysis identified DNA-PKcs as an independent prognostic indicator of OS and DMFS in all patients (P = 0.039 and 0.037, respectively). Conclusions: Our results suggest that patients with LSCC in whom DNA-PKcs expression is elevated have a higher incidence of distant metastasis and a poorer prognosis. DNA-PKcs may represent a marker of tumor progression in patients with p16-positive LSCC.

The proto-oncogene c-Myb plays an important role in cell proliferation, and its upregulation affects the development of glioblastomas. G-quadruplexes are secondary DNA or RNA structures that usually form in the promoter region of oncogenes, including c-Myb, and regulate the expression of these genes. The traditional Chinese medicine, brucine, is a ligand of the G-quadruplexes located in the promoter region of c-Myb. The present study investigated the therapeutic effects and mechanism of action of brucine in U87, LN18, and LN229 cells in vitro and in vivo. Our results showed that brucine suppressed the growth of these cells in vitro by arresting the cell cycle and reducing c-Myb expression. Dual-luciferase reporter assays showed that brucine inhibited c-Myb expression by targeting the guanine-rich sequence that forms G-quadruplexes in the c-Myb promoter. Moreover, U87 tumors were suppressed by brucine in a tumor xenograft nude mouse model. Therefore, brucine is potentially effective for treating glioblastomas.

Background: A novel inflammation-and nutrition-based scoring system based on red blood cell distribution width and body mass index (COR-BMI) has prognostic value in nasopharyngeal carcinoma (NPC). Here, we assessed the prognostic value of COR-BMI in NPC. Methods: Retrospective study of 2,318 patients with non-metastatic NPC treated at Sun Yat-sen University Cancer Center was conducted. Patients were stratified into three groups using the COR-BMI score, which is based on two objective and easily measurable parameters: red blood cell distribution width (RDW) and body mass index (BMI). Kaplan-Meier survival analyses were used to compare groups; multivariate Cox proportional models were used to calculate overall survival (OS) and disease-free survival (DFS). Results: Four-year overall survival (OS) rates were 88.7%, 84.5%, and 71.4% for patients with COR-BMI scores of 0, 1, and 2 respectively (P = 0.006). Multivariate Cox proportional hazard analysis revealed COR-BMI was an independent predictor of OS (HR for COR-BMI 1: 1.239, 95% CI: 1.012-1.590; HR for COR-BMI 2: 2.367, 95% CI: 1.311-4.274, P = 0.013), but not DFS (P = 0.482). In subgroup analysis of metastatic NPC, OS rates decreased as COR-BMI increased. In patients with a COR-BMI score of 1, radiotherapy plus chemotherapy led to better OS than radiotherapy alone. Conclusions: COR-BMI may serve as an indicator of poor prognosis in both NPC and metastatic NPC. Radiotherapy plus chemotherapy may benefit patients with a COR-BMI score of 1.