Mortality and associated influencing factors among oral cancer patients in western China: A retrospective cohort study from 2016 to 2021.

Few studies have examined oral cancer-related mortality in Guangxi. This study aimed to explore the incidence and characteristics of oral cancer and to identify the risk factors for oral cancer-related mortality. The study was conducted to provide a reference for clinical treatment and to improve the survival rate of patients with oral cancer. A total of 271 patients with oral cancer who were treated in the Stomatology Hospital of Guangxi Medical University from 2016 to 2017 were selected as the research subjects. The follow-up lasted until the middle of 2021. The survival rate and mean survival time of 271 patients were calculated by the Kaplan-Meier method. Cox proportional hazard models and stratified analysis were used to explore the related factors that affect the mortality of patients. Nomogram plots were used to visualize the relationships among multiple variables. Among 271 patients with oral cancer, the 2-year and 5-year overall survival rates were 83.8% and 68.5% respectively. The results of multivariate analysis showed that, age, pathological type, surgery and readmission were significant factors affecting survival. When the above factors were incorporated into nomogram plots and stratified analysis, the results showed that the risk of death after treatment in patients with oral cancer aged > 55 years was 1.693 times higher than that in patients aged ≤ 55 years (HR, hazard ratio [HR] = 1.795, 95% confidence intervals [CI] = 1.073, 3.004). The risk of death after surgical treatment was 0.606 times higher than that without surgical treatment (HR = 0.590, 95% CI = 0.367, 0.948). Patients who were readmitted had a 2.340-fold increased risk of death compared with patients who were not readmitted (HR = 2.340, 95% CI = 1.267,4.321). Older age, surgery, and readmission were risk factors for mortality among patients with oral cancer. The median survival time of 271 patients with oral cancer was 52.0 months. Patients under the age of 55 years old and those who choose surgical treatment tend to have a better prognosis and a longer survival. Oral cancer-related mortality is affected by age, treatment mode, readmission, and other factors. All of these factors are worthy of clinical attention for their prevention and control.

Augmented reality hologram combined with pre-bent distractor enhanced the accuracy of distraction vector transfer in maxillary distraction osteogenesis, a study based on 3D printed phantoms.

Background: Vector control is a significant concern in maxillary distraction osteogenesis (DO). Distraction vector planning on the patient's 3D-printed skull phantom is more intuitive for surgeons and cost-efficient than virtual surgical planning. However, the accuracy of transferring the planned vector to intraoperative (vector transfer) according to the shape of the pre-bent footplate alone is relatively limited. The application of augmented reality (AR) in surgical navigation has been studied for years. However, few studies have focused on its role in maxillary DO vector transfer. This study aimed to evaluate the accuracy of AR surgical navigation combined with the pre-bent distractor in vector transfer by comparing it with the pre-bent distractor alone. Methods: Ten patients with maxillary hypoplasia were enrolled with consent, and three identical 3D-printed skull phantoms were manufactured based on per patient's corresponding pre-operative CT data. Among these, one phantom was for pre-operative planning (n = 10), while and the other two were for the AR+Pre-bending group (n = 10) and the Pre-bending group (n = 10) for the experimental surgery, respectively. In the Pre-bending group, the distraction vector was solely determined by matching the shape of footplates and maxillary surface. In the AR+Pre-bending group, the distractors were first confirmed to have no deformation. Then AR surgical navigation was applied to check and adjust the vector in addition to the steps as in the Pre-bending Group. Results: For the angular deviation of the distraction vector, the AR+Pre-bending group was significantly smaller than the Pre-bending group in spatial (p < 0.001), x-y plane (p = 0.002), and y-z plane (p < 0.001), and there were no significant differences in the x-z plane (p = 0.221). The AR+Pre-bending group was more accurate in deviations of the Euclidean distance (p = 0.004) and the y-axis (p = 0.011). In addition, the AR+Pre-bending group was more accurate for the distraction result. Conclusions: In this study based on 3D printed skull phantoms, the AR surgical navigation combined with the pre-bent distractor enhanced the accuracy of vector transfer in maxillary DO, compared with the pre-bending technique alone.

Systemic Analysis of the Prognosis-Associated Alternative Polyadenylation Events in Breast Cancer.

Alternative polyadenylation (APA) is a post-translational modification that occurs during mRNA maturation in humans. Studies suggested that abnormal APA events are associated with the genesis and progression of malignant tumors. Here, we aimed to comprehensively evaluate the prognostic value of APA events involved in breast cancer (BC). Both APA events and clinical information for BC patients were downloaded from The Cancer Genome Atlas (TCGA) database to identify prognosis-related APA events in BC. A total of 462 APA events and 374 APA events were shown to be significantly related to overall survival (OS) and relapse-free survival (RFS), respectively, of BC patients. The TCGA set was randomly divided into a training and a test set. Key prognosis-related APA events were selected by LASSO regression to build prediction signatures for OS and RFS by multivariate Cox regression analysis in the training, test, and whole set. BC patients were stratified into high-risk and low-risk groups based on median risk scores. Kaplan-Meier survival analysis demonstrated that low-risk groups had better OS and RFS than high-risk groups in all three sets. The time-dependent receiver operating characteristic (ROC) curves showed that our signatures had a good predictive ability for survival and recurrence for BC patients in all three sets. The independent prognostic indicators-based nomogram model had excellent performance and considerable net benefit for predicting the OS and RFS in BC. A PPI network was constructed between key prognosis and core regulators associated with APA, consisting of 48 nodes and 244 edges. Functional enrichment analysis also revealed their association with RNA processing and RNA synthesis. Collectively, our data indicate that prognostic signatures based on APA events may be powerful prognostic predictors for OS and RFS in BC.

Long non-coding RNA-based signatures to improve prognostic prediction of breast cancer.

Breast cancer (BC) is a disease of high mortality rate because of high malignant, while early diagnosis and personal management may make a better prognosis possible. This study aimed to establish and validate lncRNAs signatures to improve the prognostic prediction for BC.RNA sequencing data along with the corresponding clinical information of patients with BC were gained from The Cancer Genome Atlas (TCGA). Prognostic differentially expressed lncRNAs were obtained using differentially expressed lncRNAs analysis (P value <.01 and |fold change| > 2) and univariate cox regression (P value <.05). By applying least absolute shrinkage and selection operation (LASSO) Cox regression analysis along with 10-fold cross-validation, 2 lncRNA-based signatures were constructed in the training, test and whole set.A 14-lncRNAs signature and a 10-lncRNAs signature were built for overall survival (OS) and relapse-free survival (RFS) respectively in the 3 sets. BC patients were divided into high-risk groups and low-risk groups depended on median risk score value. Significant differences were found for OS and RFS between 2 groups in the 3 sets. The time-dependent receiver operating characteristic (ROC) curves analysis demonstrated that our lncRNAs signatures had better predictive capacities of survival and recurrence for BC patients as well as enhancing the predictive ability of the tumor node metastasis (TNM) stage system.These results indicate that the 2 lncRNAs signatures with the potential to be biomarkers to predict the prognosis of BC for OS and RFS.

[Effects of TRAM-34 on Proliferation and Invasion of Leukemia Cell Line HL-60].

OBJECTIVE: To investigate the effects of KCa3.1 channel inhibitor TRAM-34 on the proliferation and invasion of leukemia cell line HL-60. METHODS: HL-60 cells at logarithmic growth phase exposed to TRAM-34 at the final concentration of 25, 50, 75 and 100 nmol/L were used as experimental group. The HL-60 cells of control group was cultured in 10% fetal bovine serum-RPMI 1640. The proliferation inhibition rate of TRAM-34 on HL-60 cells was detected by adding MTT solution after 24, 48 and 72 h culture. The cell apoptotic rate and cell cycle distribution of HL-60 cells treated with TRAM-34 were evaluated by flow cytometry with Annexin V-FITC/propidium iodide(PI) double staining or PI single staining. The number of transmembrane cells was detected by Transwell at 24 and 48 h after treatment with TRAM-34. The effect of TRAM-34 on CDK6, P53 and MMP-2 mRNA level was detected by real-time quantitative PCR. RESULTS: Compared with the control group (0 nmol/L), the inhibition rate, apoptosis rate, G0/G1 phase cell proportion and P53 mRNA level all increased, but the percentages of cells in S phase, cell number penetrating the membrane and mRNA levels of CDK6 and MMP-2 in the TRAM-34-treated group decreased (P<0.05) except for 24 h proliferation rate of TRAM-34 at low concentration (25 nmol/L). The effect of TRAM-34 on the above indices was enhanced with the increase of concentration and prolongation of time, and the differences were statistically significant (P<0.05). CONCLUSION: TRAM-34 can inhibit the proliferation and invasion of HL-60 cells, and can induce cell apoptosis and G0/G1 arrest. The time and concentration of TRAM-34 have effect on the malignant behavior of HL-60 cells.