The Oncogenic and Immunological Roles of Apoptosis Antagonistic Transcription Factors in Human Tumors: A Pan-Cancer Analysis.

Background: Apoptosis-antagonizing transcription factor (AATF) participates in tumor progression in multiple cancer types. However, its role across cancers is not well understood. Methods: Data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and Human Protein Atlas (HPA) were used to analyze the multiomic roles of AATF in 33 tumor types, including gene and protein expression, survival prognosis, gene mutation, DNA methylation, protein phosphorylation, AATF coexpressed genes and their enrichment analysis, and immunological analysis. Results: In TCGA and GTEx databases, 31 tumors and their corresponding normal tissues had AATF expression data, and it was differentially expressed in 29 of them. AATF was elevated in 27 tumors, decreased in 2 tumors, and was a risk factor for overall survival (OS) in 8 tumors and a risk factor for disease-free survival (DFS) in 4 tumors. AATF expression levels in various cancer types were significantly correlated with the infiltration levels of cancer-associated fibroblasts, endothelial cells, CD4+ T cells, B cells, myeloid dendritic cells, eosinophils, and macrophages. The immune checkpoints PD-1, PD-L1, and CTLA4 were positively correlated with AATF expression in bladder urothelial carcinoma (BLCA), kidney chromophobe (KICH), and prostate adenocarcinoma (PRAD). Conclusion: In cancer, AATF expression is generally higher than that in normal tissue, and it is also associated with immunomodulation-related genes. AATF may be a risk factor for poor prognosis across cancers.

Identification of novel biomarkers in septic cardiomyopathy via integrated bioinformatics analysis and experimental validation.

Purpose: Septic cardiomyopathy (SCM) is an important world public health problem with high morbidity and mortality. It is necessary to identify SCM biomarkers at the genetic level to identify new therapeutic targets and strategies. Method: DEGs in SCM were identified by comprehensive bioinformatics analysis of microarray datasets (GSE53007 and GSE79962) downloaded from the GEO database. Subsequently, bioinformatics analysis was used to conduct an in-depth exploration of DEGs, including GO and KEGG pathway enrichment analysis, PPI network construction, and key gene identification. The top ten Hub genes were identified, and then the SCM model was constructed by treating HL-1 cells and AC16 cells with LPS, and these top ten Hub genes were examined using qPCR. Result: STAT3, SOCS3, CCL2, IL1R2, JUNB, S100A9, OSMR, ZFP36, and HAMP were significantly elevated in the established SCM cells model. Conclusion: After bioinformatics analysis and experimental verification, it was demonstrated that STAT3, SOCS3, CCL2, IL1R2, JUNB, S100A9, OSMR, ZFP36, and HAMP might play important roles in SCM.

Minimally Invasive Myxoma Resection: A Single-Center 5 Years' Experience.

BACKGROUND: There is an increasing demand for minimally invasive myxoma resection. This study aimed to investigate the safety and feasibility of minimally invasive myxoma resection. METHODS: In this retrospective study, we collected information from 95 patients who underwent myxoma resection between January 2016 and December 2020. Based on the operative approach, the patients were divided into the minimally invasive myxoma resection (Mini-MR) group (N = 30) and the sternotomy myxoma resection (SMR) group (N = 65). Intraoperative and postoperative data were compared between the two groups. RESULTS: The postoperative ventilator-assisted time, CSICU time, and postoperative hospital stay were shorter in the Mini-MR group than in the SMR (13.05 ± 4.98 vs. 17.07 ± 9.52 h; 1.73 ± 0.29 vs. 2.27 ± 1.53 d; 6.20 ± 1.50 vs. 9.48 ± 3.37 d, respectively), and the difference was statistically significant (P < 0.05). Mini-MR had lower postoperative drainage and blood transfusion rate in the first 24 h compared with SMR (38.93 ± 69.62 vs. 178.25 ± 153.06 ml; 26.6% vs. 63.1%), and the differences were statistically significant (P < 0.05). CONCLUSION: Mini-MR has the advantages of less CSICU stay time, less ventilator time, less postoperative drainage in the first 24h, less blood transfusion, fewer postoperative hospital stays, and faster recovery. Mini-MR is a safe and feasible surgical procedure for myxoma resection.