Intercellular communication between malignant cells and neighboring nonmalignant cells is involved in carcinogenesis. In the progression of carcinogenesis, exosomes are messengers for intercellular communication. Circular RNAs (circRNAs) are noncoding RNAs with functions that include regulation of the cell cycle and proliferation. However, the functions of exosomal circRNAs are not clear. The present research aimed to determine whether circRNAs secreted from arsenite-transformed human hepatic epithelial (L-02) cells are transferred into normal L-02 cells and become functionally active in the normal cells. The results showed that circRNA_100284 is involved in the malignant transformation of L-02 cells induced by arsenite. The medium from transformed L-02 cells induced upregulation of circRNA_100284, accelerated the cell cycle, and promoted proliferation of normal L-02 cells. Transformed cells transferred circRNA_100284 into normal L-02 cells via exosomes and led to the malignant transformation of the non-transformed cells. Knockdown of circRNA_100284, which reduced circRNA_100284 levels in exosomes derived from transformed L-02 cells, blocked the accelerated cell cycle and reduced proliferation and malignancy. In addition, in normal L-02 cells, exosomal circRNA_100284 derived from arsenite-transformed L-02 cells induced acceleration of the cell cycle and promoted proliferation via acting as a sponge of microRNA-217. Further, exosomal circRNA_100284 was upregulated in the sera of people exposed to arsenite. Thus, exosomes derived from transformed L-02 cells transferred circRNA_100284 to surrounding cells, which induced an accelerated cell cycle and promoted proliferation of normal liver cells and led to the malignant transformation of the non-transformed cells. The findings support the concept that exosomal circRNAs are involved in cell–cell communication during carcinogenesis induced by arsenite.

Arsenic and cadmium are important inorganic toxicants in the environment. Humans certainly have the potential to be exposed to the mixtures of arsenic and cadmium, but the toxicological interactions of these inorganic mixtures are poorly defined. A general population co-exposed to arsenic and cadmium, was selected in China. The total number of participants was 245, made up of 122 in the arsenic-cadmium polluted area, 123 in the non polluted area. Urinary arsenic (UAs) and cadmium (UCd) were determined by atomic absorption spectrometry as exposure biomarkers and beta2-microglobulin (Ubeta2MG), albumin (UALB), N-acetyl-beta2-glucosaminidase (UNAG) in urine were determined as effect biomarkers. The benchmark dose (BMD) and the lower confidence limit on the benchmark dose (LBMD) were calculated to estimate the critical concentration of UAs and UCd. UAs and UCd concentrations in the polluted area were significantly higher than those in the non polluted area (P < 0.01). The levels of Ubeta2MG, UALB and UNAG in the polluted area were significantly higher than those in the non polluted area (P < 0.01). The BMD/LBMD of UAs and UCd for a 10% level of risk above the background level were estimated as 121.91/102.11 microg/g creatinine and 1.05/0.88 microg/g creatinine. It was suggested that the lower confidence limit of population critical concentration of UAs and UCd for renal dysfunction for 10% excess risk level above the background, which is obtained from LBMD, may need to be kept below 102 and 0.88 microg/g creatinine in order to prevent renal damage in general population co-exposed to arsenic and cadmium. It is indicated that combined effect of arsenic and cadmium were additive effect and/or synergistic effect, and cadmium may potentiate arsenic nephrotoxicity during the long-term and co-exposure to arsenic and cadmium in humans.

Recent explosion of biological data brings a great challenge for the traditional methods. With increasing scale of large data sets, much advanced tools are required for the depth interpretation problems. As a rapid-developing technology, metabolomics can provide a useful method to discover the pathogenesis of diseases. This study was explored the dynamic changes of metabolic profiling in cells model and Balb/C nude-mouse model of prostate cancer, to clarify the therapeutic mechanism of berberine, as a case study. Here, we report the findings of comprehensive metabolomic investigation of berberine on prostate cancer by high-throughput ultra performance liquid chromatography-mass spectrometry coupled with pattern recognition methods and network pathway analysis. A total of 30 metabolite biomarkers in blood and 14 metabolites in prostate cancer cell were found from large-scale biological data sets (serum and cell metabolome), respectively. We have constructed a comprehensive metabolic characterization network of berberine to protect against prostate cancer. Furthermore, the results showed that berberine could provide satisfactory effects on prostate cancer via regulating the perturbed pathway. Overall, these findings illustrated the power of the ultra performance liquid chromatography-mass spectrometry with the pattern recognition analysis for large-scale biological data sets may be promising to yield a valuable tool that insight into the drug action mechanisms and drug discovery as well as help guide testable predictions.

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