Fei Sheng's research while affiliated with Nanjing Medical University and other places

With the rapid development of nanotechnology and nanoscience, nanosafety assessment has raised public concern. Although many studies have illustrated that nanomaterials could lead to genotoxicity, the early alterations of DNA methylation with nanomaterials under low-dose exposure have not been completely clear. In this study, we investigated the potential effect and molecular mechanism of AgNPs on the alternation of DNA methylation fingerprints in HEK293T cells under sublethal exposure. Intriguingly, silver nanoparticle treatment increased 5-mC level and changed methylation-related enzyme contents. Mechanistically, we scrutinized the changes in the molecular signaling and biological functions by means of MeDIP-Seq and RNA-seq. Our results revealed that AgNPs might undermine a number of vital regulatory networks including the metabolic processes, biological regulation and other cellular processes. More specifically at the DNA methylation fingerprints, there were 12 up-regulated and simultaneous hypomethylated genes, and 22 down-regulated and concomitant hypermethylated genes in HEK293T cells responding to AgNPs. Notably, these genes were primarily involved in lipid metabolism and ion metabolism. Together, these responsive genes might be used as early sensitive indicators for the variations of early epigenetic integrity through changing the DNA methylation fingerprints, as reflective of biological risk and toxicity of silver nanoparticles under realistic exposure scenarios.

Currently, almost all available cancer biomarkers are based on concentrations of compounds, often suffering from low sensitivity, poor specificity, and false positive or negative results. The stable isotopic composition of elements provides a different dimension from the concentration and has been widely used as a tracer in geochemistry. In health research, stable isotopic analysis has also shown potential as a new diagnostic/prognostic tool, which is still in the nascent stage. Here we discovered that bladder cancer (BCa) could induce a significant variation in the ratio of natural copper isotopes (65Cu/63Cu) in the blood of patients relative to benign and healthy controls. Such inherent copper isotopic signatures permitted new insights into molecular mechanisms of copper imbalance underlying the carcinogenic process. More importantly, to enhance the diagnostic capability, a machine learning model was developed to classify BCa and non-BCa subjects based on two-dimensional copper signatures (copper isotopic composition and concentration in plasma and red blood cells) with a high sensitivity, high true negative rate, and low false positive rate. Our results demonstrated the promise of blood copper signatures combined with machine learning as a versatile tool for cancer research and potential clinical application.

Hexavalent chromium (Cr (VI)), which is a recognized human carcinogen, is widely used in industrial production of raw materials. Evidence verifies that environmental contaminants in the urine can induce malignant transformation in the urinary bladder tract, and our data indicate that Cr (VI) could promote the proliferation and migration and inhibit the apoptosis of bladder cancer (BLCA) cells. However, the molecular mechanism remains ambiguous. We find that Filamin A (FLNA) is overexpressed in BLCA, and Cr (VI) promotes epithelial‐to‐mesenchymal transition by regulating FLNA in BLCA. Thus, inhibiting the expression of FLNA may be a prospective method for limiting the BLCA progression caused by Cr (VI) exposure.

Improved understanding of the molecular mechanisms and immunoregulation of muscle-invasive bladder cancer (MIBC) is essential to predict prognosis and develop new targets for therapies. In this study, we used the cancer genome atlas (TCGA) MIBC and GSE13507 datasets to explore the differential co-expression genes in MIBC comparing with adjacent non-carcinoma tissues. We firstly screened 106 signature genes by Weighted Gene Co-expression Network Analysis (WGCNA) and further identified 15 prognosis-related genes of MIBC using the univariate Cox progression analysis. Then we systematically analyzed the genetic alteration, molecular mechanism, and clinical relevance of these 15 genes. We found a different expression alteration of 15 genes in MIBC comparing with adjacent non-carcinoma tissues and normal tissues. Meanwhile, the biological functions and molecular mechanisms of them were also discrepant. Among these, we observed the ANLN was highly correlated with multiple cancer pathways, molecular function, and cell components, revealing ANLN may play a pivotal role in MIBC development. Next, we performed a consensus clustering of 15 prognosis-related genes; the results showed that the prognosis, immune infiltration status, stage, and grade of MIBC patients were significantly different in cluster1/2. We further identified eight-genes risk signatures using the least absolute shrinkage and selection operator (LASSO) regression analysis based on the expression values of 15 prognosis-related genes, and also found a significant difference in the prognosis, immune infiltration status, stage, grade, and age in high/low-risk cohort. Moreover, the expression of PD-1, PD-L1, and CTLA4 was significantly up-regulated in cluster1/high-risk-cohort than that in cluster2/low-risk-cohort. High normalized enrichment score of the Mitotic spindle, mTORC1, Complement, and Apical junction pathway suggested that they might be involved in the distinct tumor immune microenvironment (TIME) of cluster1/2 and high-/low-risk-cohort. Our study identified 15 prognosis-related genes of MIBC, provided a feasible stratification method to help for the future immunotherapy strategies of MIBC patients.

Background Dysfunction of primary cilia (PC), which could influence cell cycle and modulate cilia-related signaling transduction, has been reported in several cancers. However, there is no evidence of their function in bladder cancer (BLCA). This study was performed to investigate the presence of PC in BLCA and to explore the potential molecular mechanisms underlying the PC in BLCA. Patients and methods The presence of PC was assessed in BLCA and adjacent non-cancerous tissues. The gene expression dataset GSE52519 was employed to obtain differentially expressed genes (DEGs) associated with PC. The mRNA expression of the DEGs were confirmed by Gene Expression Profiling Interactive Analysis. The DEGs properties and pathways were analyzed by Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Genomatix software was used to predict putative transcription factor binding sites (TFBS) in the promoter region of DEGs, and the transcription factors were achieved according to the shared TFBS, which were supported by the ChIP-Sequence data. Results PC were found to be reduced in BLCA tissue samples in this study. Seven DEGs were observed to be associated with PC, and gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that these DEGs exhibited the properties and functions of PC, and that the Hedgehog signaling pathway probably participated in the pathogenesis and progression of BLCA. The mRNA expression of the seven DEGs in 404 BLCA and 28 normal tissue samples were analyzed, and five DEGs including CENPF, STIL, AURKA, STK39 and OSR1 were identified. Five TFBS including CREB, E2FF, EBOX, ETSF and HOXF in the promoter region of five DEGs were calculated and the transcription factors were obtained according to the shared TFBS. Conclusion PC were found to be reduced in BLCA, and the potential molecular mechanisms of PC in BLCA helped to provide novel diagnosis and therapeutic targets for BLCA.