Prediction of non-muscle invasive bladder cancer recurrence using deep learning of pathology image.

We aimed to build a deep learning-based pathomics model to predict the early recurrence of non-muscle-infiltrating bladder cancer (NMIBC) in this work. A total of 147 patients from Xuzhou Central Hospital were enrolled as the training cohort, and 63 patients from Suqian Affiliated Hospital of Xuzhou Medical University were enrolled as the test cohort. Based on two consecutive phases of patch level prediction and WSI-level predictione, we built a pathomics model, with the initial model developed in the training cohort and subjected to transfer learning, and then the test cohort was validated for generalization. The features extracted from the visualization model were used for model interpretation. After migration learning, the area under the receiver operating characteristic curve for the deep learning-based pathomics model in the test cohort was 0.860 (95% CI 0.752-0.969), with good agreement between the migration training cohort and the test cohort in predicting recurrence, and the predicted values matched well with the observed values, with p values of 0.667766 and 0.140233 for the Hosmer-Lemeshow test, respectively. The good clinical application was observed using a decision curve analysis method. We developed a deep learning-based pathomics model showed promising performance in predicting recurrence within one year in NMIBC patients. Including 10 state prediction NMIBC recurrence group pathology features be visualized, which may be used to facilitate personalized management of NMIBC patients to avoid ineffective or unnecessary treatment for the benefit of patients.

Tiron protects against UVB-induced senescence-like characteristics in human dermal fibroblasts by the inhibition of superoxide anion production and glutathione depletion.

BACKGROUND/OBJECTIVES: Free radicals and reactive oxygen species (ROS), which are generated by UV irradiation, may induce an irreversible growth arrest similar to senescence. Tiron, 4,5-dihydroxy-1,3-benzene disulfonic acid, is a widely used antioxidant to rescue ROS-evoked cell death. The aim of the article was to explore the effects of tiron on skin photoaging and associated mechanisms. METHODS: The effects of tiron on cell proliferation were determined using 3-(4,5-dimethylthiazol-2-Yl)-2,5-diphenyltetrazolium bromide. Senescent cells were determined by morphology and senescence-associated ß-galactosidase activity analysis. Intracellular hydrogen peroxide, superoxide anion and glutathione concentration were analysed by a fluorescent probe. The concomitant changes of protein expression were analysed with Western blot. RESULTS: Human dermal fibroblasts were induced to premature senescence by sub-cytotoxic doses of irradiated UVB. Strong senescence-associated ß-galactosidase activity and increased intracellular superoxide anion were observed in human dermal fibroblasts irradiated by UVB. Tiron blocks UVB-induced glutathione depletion and increase of superoxide anion and protects against UVB-induced senescence-like characteristics in human dermal fibroblasts. Compared with normal fibroblasts, UVB-irradiated human dermal fibroblasts showed a higher ratio of active (hypophosphorylated) to inactive (phosphorylated) forms of Rb and p38, upregulation of p53 or p16 and c-Myc and insulin-like growth factor 1 (IGF-1) downregulation. After treatment with tiron, p53, p16 c-Myc and IGF-1 as well as phosphorylation Rb and p38 could partially recover. CONCLUSION: These results indicate that tiron protects against UVB-induced senescence-like characteristics in human dermal fibroblasts via the inhibition of production of superoxide anion and glutathione depletion, and modulation of related senescence proteins.

Gene expression profiling of human kidneys undergoing laparoscopic donor nephrectomy.

BACKGROUND AND OBJECTIVES: The objective was to compare gene expression profiles of 6 kidneys from open donor nephrectomy with 6 kidneys removed after laparoscopic donor nephrectomy and several hours of carbon dioxide pneumoperitoneum with DNA microarrays and identify small-molecule drugs. METHODS: The gene expression profile GSE3297 was downloaded from the Gene Expression Omnibus database, and the differentially expressed genes were identified by a bioinformatics approach. First, Osprey software was used to construct a differentially expressed gene associated network. Then, DAVID (Database for Annotation, Visualization, and Integrated Discovery) and FuncAssociate were used to perform functional analyses. Finally, the Connectivity Map was used to screen for small-molecule drugs. RESULTS: A total of 285 differentially expressed genes were identified, including 148 down-regulated genes and 137 up-regulated genes. In addition, the differentially expressed genes in the most significant Gene Ontology term were CASP6, KRAS, SOCS1, ESR1, TSHB, COL1A1, and MMP14. Furthermore, several differentially expressed genes, including STAT1, STAT6, SOS2, and SOCS1, participated in the most remarkable Janus kinase-signal transducer and activator of transcription signaling pathway. Finally, luteolin--with the highest score (0.887)--was identified as the small-molecule drug. CONCLUSIONS: Our data show an altered renal transcriptome induced by several hours of carbon dioxide pneumoperitoneum and laparoscopic surgery characterized by up-regulation of genes associated with acute inflammation, apoptosis, and immune injury, which could potentially result in renal injury and an enhanced immune response in the recipient after transplant.

Identifying differentially expressed genes and small molecule drugs for prostate cancer by a bioinformatics strategy.

PURPOSE: Prostate cancer caused by the abnormal disorderly growth of prostatic acinar cells is the most prevalent cancer of men in western countries. We aimed to screen out differentially expressed genes (DEGs) and explore small molecule drugs for prostate cancer. MATERIALS AND METHODS: The GSE3824 gene expression profile of prostate cancer was downloaded from Gene Expression Omnibus database which including 21 normal samples and 18 prostate cancer cells. The DEGs were identified by Limma package in R language and gene ontology and pathway enrichment analyses were performed. In addition, potential regulatory microRNAs and the target sites of the transcription factors were screened out based on the molecular signature database. In addition, the DEGs were mapped to the connectivity map database to identify potential small molecule drugs. RESULTS: A total of 6,588 genes were filtered as DEGs between normal and prostate cancer samples. Examples such as ITGB6, ITGB3, ITGAV and ITGA2 may induce prostate cancer through actions on the focal adhesion pathway. Furthermore, the transcription factor, SP1, and its target genes ARHGAP26 and USF1 were identified. The most significant microRNA, MIR-506, was screened and found to regulate genes including ITGB1 and ITGB3. Additionally, small molecules MS-275, 8-azaguanine and pyrvinium were discovered to have the potential to repair the disordered metabolic pathways, abd furthermore to remedy prostate cancer. CONCLUSIONS: The results of our analysis bear on the mechanism of prostate cancer and allow screening for small molecular drugs for this cancer. The findings have the potential for future use in the clinic for treatment of prostate cancer.