Patients with nonalcoholic fatty liver disease (NAFLD) have symptoms of a gut microbiota disorder with abnormal amino acid and glycolipid metabolism. This study was designed to analyze the characteristics of gut microbiota in patients with NAFLD, predict the gut microbiota phenotype, explore its role in the diagnosis of NAFLD, and establish its significance in disease progression. The characteristics of the gut microbiota in NAFLD patients (n = 28, 45.8 ± 14.2 years, male/female = 18/10) and healthy subjects (n = 20, 49.6 ± 4.8 years, male/female = 14/6) during March–May 2020 were analyzed using 16S rRNA sequencing technology and the phenotypes with large differences were predicted using the Tax4Fun method. The metabolites in the fecal samples of the patients were analyzed using mass spectrometry, and their correlation with different microorganisms was examined. The accuracy of the gut microbiota in diagnosing NAFLD was investigated by receiver operating characteristic curve analysis. We found that the microbial diversity and Bacteroides/Firmicutes (BF) ratio changed significantly ( P < .05) in the feces of NAFLD patients. Phenotypic prediction showed that there were significant differences in the phenotypes of amino acid, glucose, and lipid metabolism of gut microbiota in the NAFLD group ( P < .05). receiver operating characteristic curve analysis revealed that combination of Bacteroides and the BF ratio resulted in 88% and 100% sensitivity and specificity, respectively, when used for NAFLD diagnosis. Metabolomics and bioinformatics analysis revealed changes in the metabolism of nicotinate, nicotinamide, and pyrimidine; signaling pathways of calcium and oxytocin; pancreatic secretion with metabolites such as uracil, xanthine, and biliverdin; and enzymes such as xanthine dehydrogenase and xanthine oxidase ( P < .05). Therefore, the phenotypic changes may be a potential marker for NAFLD and we considered that a combined analysis of Bacteroides and BF ratio had good diagnostic accuracy for NAFLD.

Primary hepatocellular carcinoma (PHC) is a major health problem worldwide and is one of the 10 most commonly diagnosed cancers in China. Heat shock protein 27 (HSP27) were found to be overexpressed in a wide range of malignancies including PHC, however, post-translational modification of HSP27 still needs exploration in PHC. Recently, SUMOylation, an important post-translational modification associating with the development of many kinds of cancers has been intensively studied. In the current study, mRNA and protein level of HSP27 in archived tumor samples representing various pathological characteristics of PHC were examined, and modification of HSP27 by SUMO2/3 was investigated. HSP27 were expressed abundantly in patients' tumor tissues, and found to be associated with pathological progression. Besides, HSP27 was also elevated significantly in liver cancer cell lines Huh7 and HepG2 compared with human hepatocyte cells L02. Furthermore, knockdown of HSP27 was found to be associated with the decreased proliferation and invasion ability in Huh7 and HepG2 cells. Immunofluorescence assay showed that HSP27 and SUMO2/3 were co-localized in the subcellular, and co-immunoprecipitation verified the interaction between HSP27 and SUMO2/3. Overexpression of SUMO2/3 upregulated the HSP27 protein level and promotes Huh7 and HepG2 cell proliferation and invasion, and vice versa when the SUMO2/3 was knockdown. Taken together, increased protein level of HSP27 through SUMO2/3-mediated SUMOylation plays crucial roles in the progression of PHC, and this finding may shed light on developing potential therapeutic targets for PHC.

Common genetic variants (single-nucleotide polymorphisms [SNPs]) in microRNA genes may alter their maturation or expression, resulting in varied functional consequences. Several studies have evaluated the association between the SNP rs11614913 and cancer risk in diverse populations and in a range of cancers, with contradictory outcomes. In this study, we examined 114 paired samples (tumor and normal tissues) from breast cancer patients to study the genotype distribution and somatic mutation of the SNP in MIR 196A2 (rs11614913 C-T). In addition, we evaluated their influence on the mature MIR 196A2 expression. We found that 14% (16/114) of tumors underwent somatic mutation of the SNP rs11614913. Moreover, the CT heterozygous and the CC homozygous states of SNP rs11614913 were more prone to mutation, while the TT homozygous state appeared to be resistant. We further detected a significant increase (p = 0.002) in mature MIR 196A2 expression in breast cancer. In particular, we found a significant association between the occurrence of SNP rs11614913 mutation and high expression (p = 0.0002). In addition, the mature MIR 196A2 expression level was significantly associated with the higher tumor grade (p = 0.004). Taken together, our results seem to demonstrate that somatic mutation of SNP rs11614913 in MIR 196A2 can have an influence on its expression. In addition, it indicated that an unknown mechanism is responsible for both the mutation of SNP rs11614913 and the dysregulation of mature MIR 196A2 expression.

The importance of microRNAs (miRNAs) in cancer development has been widely recognized in recent decades. In the present study, the function and mechanism of miRNA-363-3p (miR-363-3p), formerly characterized as a tumor suppressor, in the hepatocarcinogenesis of liver cancer cells was investigated. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was applied to detect the expression of miR-363-3p in liver cancer tissues. Cell proliferation, survival and migration capacities were determined by MTT, colony formation and wound-healing assays, respectively. The targeting of high mobility group AT-hook 2 (HMGA2) mRNA by miR-363-3p was confirmed by bioinformatics analysis, and RT-qPCR, luciferase reporter and western blot assays. The correlation between the expression levels of HMGA2 and miR-363-3p was analyzed. The RT-qPCR results revealed that the levels of miR-363-3p were downregulated in liver cancer tissues. Cellular assays validated that miR-363-3p exerted tumor suppressing functions, including the inhibition of cell proliferation, survival and migration abilities in two liver cancer cell lines. Bioinformatics prediction and subsequent experiments demonstrated that HMGA2 was a direct target of miR-363-3p. Restoration of the expression of HMGA2 in miR-363-3p mimic-transfected cells reversed the tumor suppressing effects caused by miR-363-3p. Finally, there was a significant negative correlation between the expression levels of HMGA2 and miR-363-3p in liver cancer tissues. miR-363-3p was identified as an important tumor suppressor in liver cancer via targeting HMGA2, which may have potential benefits in liver cancer therapy.

Background/Aims: Obesity is increasingly becoming a major public health problem worldwide. Peripheral LKB1 inhibits white fat generation, but the effect of central LKB1 on diet-induced obesity (DIO) is unknown. Therefore, we examined whether LKB1 over-expression in the hypothalamus can inhibit the development of obesity. Methods: Adult male Sprague-Dawley rats were anesthetized and placed in a stereotaxic apparatus. LKB1-AAV-EGFP (2.0 × 10⁸ or 2.0 × 10¹⁰ vector genomes) or Control-AAV-EGFP (2.0 × 10⁸ vector genomes) was injected into the third ventricle. After administration, the rats were fed a high-fat diet (HFD) for 9 weeks to induce obesity. Rats fed a chow fat diet were used as normal controls. Results: LKB1 delivery decreased body weight, energy intake, fat mass, and serum lipid levels. LKB1 also improved HFD-induced hepatic fatty degeneration. Interestingly, LKB1 over-expression in the hypothalamus activated the AMPK-POMC neurons-sympathetic nervous system (SNS) axis, which can release epinephrine to promote white fat browning. Conversely, the elevated expression of MC3R/MC4R inhibited food intake. These two factors worked together to inhibit the development of obesity. Conclusions: LKB1 in the hypothalamus may have therapeutic potential for DIO through the activation of the AMPK-POMC neurons-SNS axis.