Background Gut microbiota has been reported to be disrupted by cisplatin, as well as to modulate chemotherapy toxicity. However, the precise role of intestinal microbiota in the pathogenesis of cisplatin hepatotoxicity remains unknown. Methods We compared the composition and function of gut microbiota between mice treated with and without cisplatin using 16S rRNA gene sequencing and via metabolomic analysis. For understanding the causative relationship between gut dysbiosis and cisplatin hepatotoxicity, antibiotics were administered to deplete gut microbiota and faecal microbiota transplantation (FMT) was performed before cisplatin treatment. Results 16S rRNA gene sequencing and metabolomic analysis showed that cisplatin administration caused gut microbiota dysbiosis in mice. Gut microbiota ablation by antibiotic exposure protected against the hepatotoxicity induced by cisplatin. Interestingly, mice treated with antibiotics dampened the mitogen-activated protein kinase pathway activation and promoted nuclear factor erythroid 2-related factor 2 nuclear translocation, resulting in decreased levels of both inflammation and oxidative stress in the liver. FMT also confirmed the role of microbiota in individual susceptibility to cisplatin-induced hepatotoxicity. Conclusions This study elucidated the mechanism by which gut microbiota mediates cisplatin hepatotoxicity through enhanced inflammatory response and oxidative stress. This knowledge may help develop novel therapeutic approaches that involve targeting the composition and metabolites of microbiota.
Background Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV. Methods Based on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored. Results A prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8). Conclusion The present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.
Ovarian cancer (OC) is the most lethal gynecologic cancer, and the incidence of OC has risen steadily worldwide. Numerous microRNAs (miRNAs) have been found to be involved in the progression of OC. miR-204-5p is down-regulated and functions as a tumor suppressor in various types of human malignant tumors. However, the biological roles and molecular mechanisms of miR-204-5p in OC still remain unclear. In this study, the aberrant down-regulation of miR-204-5p was detected in OC tissues. We also observed that miR-204-5p overexpression represses OC cell proliferation. Ubiquitin-specific peptidase 47 (USP47) is verified as the functional target of miR-204-5p, through which it plays an important biological role in OC. Our results uncover new functions and mechanisms for miR-204-5p in the progression of OC, and provide a potential therapeutic target for the treatment of OC.
Polycystic ovary syndrome (PCOS) is a common disease in women, affecting women's menstruation and significantly impacting women's physical and mental health. Studies have shown that insulin resistance has an important relationship with polycystic ovary. It is of great significance to explore the changes of inflammatory factors, oxidative stress, glucose and lipid metabolism, and insulin resistance in patients with PCOS. In the study process, 642 polycystic ovary patients in the first half of 2019 were divided into insulin resistance (n=357) and non-insulin resistance (n=285) groups. Oxidative stress index, glucose, and lipid metabolism index, and inflammatory factors were detected during the study process. The results showed that the levels of hs-CRP, TNF- α, and IL-6 in the IR group were 5.9mg/L, 9.2μg/L, and 87.2ng /ml, while those in the non-IR group were 4.6mg/L, 6.3μg/L and 51.5ng/ml, respectively. Thus, IL-6 and insulin levels maintain a dynamic balance. Low levels of IL-6 can promote insulin secretion, while high levels can inhibit its secretion. The results of this study will provide a specific clinical reference value for the prevention and treatment of polycystic ovary syndrome.
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