Prediction of factors influencing the timing and prognosis of early tracheostomy in patients with multiple rib fractures: A propensity score matching analysis.

Objective: To investigate the factors affecting the timing and prognosis of early tracheostomy in multiple rib fracture patients. Methods: A retrospective case-control study was used to analyze the clinical data of 222 patients with multiple rib fractures who underwent tracheotomy in the Affiliated Hospital of Yangzhou University from February 2015 to October 2021. According to the time from tracheal intubation to tracheostomy after admission, the patients were divided into two groups: the early tracheostomy group (within 7 days after tracheal intubation, ET) and late tracheostomy group (after the 7th day, LT). Propensity score matching (PSM) was used to eliminate the differences in baseline characteristics Logistic regression was used to predict the independent risk factors for early tracheostomy. Kaplan-Meier and Cox survival analyses were used to analyze the influencing factors of the 28-day survival. Results: According to the propensity score matching analysis, a total of 174 patients were finally included in the study. Among them, there were 87 patients in the ET group and 87 patients in the LT group. After propensity score matching, Number of total rib fractures (NTRF) (P < 0.001), Acute respiratory distress syndrome (ARDS) (P < 0.001) and Volume of pulmonary contusion(VPC) (P < 0.000) in the ET group were higher than those in the LT group. Univariate analysis showed that the patients who underwent ET had a higher survival rate than those who underwent LT (P = 0.021). Pearson's analysis showed that there was a significant correlation between NTRF and VPC (r = 0.369, P = 0.001). A receiver operating characteristic(ROC)curve analysis showed that the areas under the curves were 0.832 and 0.804. The best cutoff-value values of the VPC and NTRF were 23.9 and 8.5, respectively. The Cox survival analysis showed that the timing of tracheostomy (HR = 2.51 95% CI, 1.12-5.57, P = 0.004) and age (HR = 1.53 95% CI, 1.00-2.05, P = 0.042) of the patients had a significant impact on the 28-day survival of patients with multiple rib fractures. In addition, The Kaplan-Meier survival analysis showed that the 28-day survival of patients in the ET group was significantly better than that of the LT group, P = 0.01. Conclusions: NTRF, ADRS and VPC are independent risk factors for the timing and prognosis of early tracheotomy. A VPC ≥ 23.9% and/or an NTRF ≥ 8.5 could be used as predictors of ET in patients with multiple rib fractures. Predicting the timing of early tracheostomy also need prediction models in the future.

Bioinformatics Analysis Screened and Identified Key Genes as Potential Biomarkers for Progression of Lung Cancer.

OBJECTIVE: To screen and identify key genes as potential biomarkers of lung cancer using bioinformatics analysis. STUDY DESIGN: Observational study. PLACE AND DURATION OF STUDY: Department of Critical Care Medicine, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning Province, China, from August 2018 to April 2021. METHODOLOGY: Independent microarray datasets (GSE85841 and GSE118370) were downloaded from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were screened using GEO2R. Cytohubba was employed to identify the hub genes. Cellular component analysis, hierarchical clustering, and survival analyses of hub genes were performed via BiNGO, UCSC, and cBioPorta. A series of analyses of FGF2 and PIK3R1 were conducted using Oncomine. RESULTS: A total of 463 DEGs were identified and 11 hub genes were determined. BDNF, FGF2, JAK2, NCAM1, CAV1, TJP1, and PIK3R1 may affect the survival probability and life expectancy of lung cancer patients, but the p-values were not statistically significant. FGF2 and PIK3R1 had the highest node degrees, 40 and 32 respectively. The expression of FGF2 and PIK3R1 were significantly lower in the 4 lung cancer data sets compared with non-lung cancer tissues. And the low expression of FGF2 and PIK3R1 is related to tumor grades, family history of cancer, multiple tumors present, and prior therapy of lung cancer. CONCLUSION: Evaluation of FGF2 and PIK3R1 as potential biomarkers can contribute to the subsequent theoretical analysis of potential molecular mechanisms and development of lung cancer, so that the diagnosis of lung cancer may be more accurate, and it is possible to provide therapeutic and prognostic medicine targets. KEY WORDS: Lung neoplasms, Differentially expressed genes, Bioinformatical analysis, Microarray analysis, biomarkers.

Flubendazole, FDA-approved anthelmintic, targets breast cancer stem-like cells.

Cancer stem-like cell (CS-like cell) is considered to be responsible for recurrence and drug resistance events in breast cancer, which makes it a potential target for novel cancer therapeutic strategy. The FDA approved flubendazole, has been widely used in the treatment of intestinal parasites. Here, we demonstrated a novel effect of flubendazole on breast CS-like cells. Flubendazole inhibited breast cancer cells proliferation in dose- and time-dependent manner and delayed tumor growth in xenograft models by intraperitoneal injection. Importantly, flubendazole reduced CD44high/CD24low subpopulation and suppressed the formation of mammosphere and the expression of self-renewal related genes including c-myc, oct4, sox2, nanog and cyclinD1. Moreover, we found that flubendazole induced cell differentiation and inhibited cell migration. Consistently, flubendazole reduced mesenchymal markers (ß-catenin, N-cadherin and Vimentin) expression and induced epithelial and differentiation marker (Keratin 18) expression in breast cancer cells. Mechanism study revealed that flubendazole arrested cell cycle at G2/M phase and induced monopolar spindle formation through inhibiting tubulin polymerization. Furthermore, flubendazole enhanced cytotoxic activity of conventional therapeutic drugs fluorouracil and doxorubicin against breast cancer cells. In conclusion, our findings uncovered a remarkable effect of flubendazole on suppressing breast CS-like cells, indicating a novel utilization of flubendazole in breast cancer therapy.

Aurora kinase a suppresses metabolic stress-induced autophagic cell death by activating mTOR signaling in breast cancer cells.

Aberrant Aur-A signaling is associated with tumor malignant behaviors. However, its involvement in tumor metabolic stress is not fully elucidated. In the present study, prolonged nutrient deprivation was conducted into breast cancer cells to mimic metabolic stress in tumors. In these cells, autophagy was induced, leading to caspase-independent cell death, which was blocked by either targeted knockdown of autophagic gene ATG5 or autophagy inhibitor 3-Methyladenine (3-MA). Aur-A overexpression mediated resistance to autophagic cell death and promoted breast cancer cells survival when exposed to metabolic stress. Moreover, we provided evidence that Aur-A suppressed autophagy in a kinase-dependent manner. Furthermore, we revealed that Aur-A overexpression enhanced the mammalian target of rapamycin (mTOR) activity under metabolic stress by inhibiting glycogen synthase kinase 3ß (GSK3ß). Inhibition of mTOR activity by rapamycin sensitized Aur-A-overexpressed breast cancer cells to metabolic stress-induced cell death. Consistently, we presented an inverse correlation between Aur-A expression (high) and autophagic levels (low) in clinical breast cancer samples. In conclusion, our data provided a novel insight into the cyto-protective role of Aur-A against metabolic stress by suppressing autophagic cell death, which might help to develop alternative cell death avenues for breast cancer therapy.

Up-regulation of P21 inhibits TRAIL-mediated extrinsic apoptosis, contributing resistance to SAHA in acute myeloid leukemia cells.

BACKGROUND/AIM: P21, a multifunctional cell cycle-regulatory molecule, regulates apoptotic cell death. In this study we examined the effect of altered p21 expression on the sensitivity of acute myeloid leukemia cells in response to HDAC inhibitor SAHA treatment and investigated the underlying mechanism. METHODS: Stably transfected HL60 cell lines were established in RPMI-1640 with supplementation of G-418. Cell viability was measured by MTT assay. Western blot was applied to assess the protein expression levels of target genes. Cell apoptosis was monitored by AnnexinV-PE/7AAD assay. RESULTS: We showed HL60 cells that that didn't up-regulate p21 expression were more sensitive to SAHA-mediated apoptosis than NB4 and U937 cells that had increased p21 level. Enforced expression of p21 in HL60 cells reduced sensitivity to SAHA and blocked TRAIL-mediated apoptosis. Conversely, p21 silencing in NB4 cells enhanced SAHA-mediated apoptosis and lethality. Finally, we found that combined treatment with SAHA and rapamycin down-regulated p21 and enhanced apoptosis in AML cells. CONCLUSION: We conclude that up-regulated p21 expression mediates resistance to SAHA via inhibition of TRAIL apoptotic pathway. P21 may serve as a candidate biomarker to predict responsiveness or resistance to SAHA-based therapy in AML patients. In addition, rapamycin may be an effective agent to override p21-mediated resistance to SAHA in AML patients.