RESUMO
Overconsumption of high-fat foods increases the risk of fatty liver disease (FLD) and liver cancer with long pathogenic cycles. It is also known that the intake of the chemical poison nitrosamine and its nanopreparations can promote the development of liver injuries, such as FLD, and hepatic fibrosis, and significantly shorten the formation time of the liver cancer cycle. The present work confirmed that the coexposure of a high-fat diet (HFD) and nano-diethylnitrosamine (nano-DEN) altered the tumor microenvironment and studied the effect of this coexposure on the progression of fatty liver malignant transformation into liver cancer. Gene transcriptomics and immunostaining were used to evaluate the tumor promotion effect of the coexposure in mice. After coexposure treatment, tumor nodules were obviously increased, and inflammation levels were elevated. The liver transcriptomics analysis showed that the expression levels of inflammatory, fatty, and fibrosis-related factors in the coexposed group were increased in comparison with the nano-DEN- and high-fat-alone groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that coexposure aggravated the high expression of genes related to the carcinomatous pathway and accelerated the formation of the tumor microenvironment. The immunohistochemical staining results showed that the coexposure significantly increased the abnormal changes in proteins related to inflammation, proliferation, aging, and hypoxia in mouse liver tissues. The coexposure of high fat and nano-DEN aggravated the process of steatosis and carcinogenesis. In conclusion, the habitual consumption of pickled foods containing nitrosamines in a daily HFD significantly increases the risk of liver pathology lesions progressing from FLD to liver cancer.
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Sinularin, a natural product that purified from soft coral, exhibits anti-tumor effects against various human cancers. However, the mechanisms are not well understood. In this study, we demonstrated that Sinularin inhibited the viability of human prostate cancer cells in a dose-dependent manner and displayed significant cytotoxicity only at high concentration against normal prostate epithelial cell RWPE-1. Flow cytometry assay demonstrated that Sinularin induced tumor cell apoptosis. Further investigations revealed that Sinularin exerted anti-tumor activity through intrinsic apoptotic pathway along with up-regulation of pro-apoptotic protein Bax and PUMA, inhibition of anti-apoptotic protein Bcl-2, mitochondrial membrane potential collapses, and release of mitochondrial proteins. Furthermore, we illustrated that Sinularin induced cell apoptosis via up-regulating PUMA through inhibition of FOXO3 degradation by the ubiquitin-proteasome pathway. To explore how Sinularin suppress FOXO3 ubiquitin-proteasome degradation, we tested two important protein kinases AKT and ERK that regulate FOXO3 stabilization. The results revealed that Sinularin stabilized and up-regulated FOXO3 via inhibition of AKT- and ERK1/2-mediated FOXO3 phosphorylation and subsequent ubiquitin-proteasome degradation. Our findings illustrated the potential mechanisms by which Sinularin induced cell apoptosis and Sinularin may be applied as a therapeutic agent for human prostate cancer.
Assuntos
Proteínas Reguladoras de Apoptose , Diterpenos , Compostos Heterocíclicos com 3 Anéis , Neoplasias da Próstata , Humanos , Masculino , Apoptose , Proteínas Reguladoras de Apoptose/metabolismo , Linhagem Celular Tumoral , Proteína Forkhead Box O3 , Próstata/metabolismo , Neoplasias da Próstata/tratamento farmacológico , Neoplasias da Próstata/metabolismo , Complexo de Endopeptidases do Proteassoma , Proteínas Proto-Oncogênicas c-akt/metabolismo , Ubiquitinas/metabolismoRESUMO
Gestational diabetes mellitus (GDM) refers to different degrees of glucose tolerance abnormalities that occur during pregnancy or are discovered for the first time, which can have a serious impact on the mother and the offspring. The screening of GDM mainly relies on the oral glucose tolerance test (OGTT) at 24-28 weeks of gestation. The early diagnosis and intervention of GDM can greatly improve adverse pregnancy outcomes. However, molecular markers for early prediction and diagnosis of GDM are currently lacking. Therefore, looking for GDM-specific early diagnostic markers has important clinical significance for the prevention and treatment of GDM and the management of subsequent maternal health. Circular RNA (circRNA) is a new type of non-coding RNA. Recent studies have found that circRNAs were involved in the occurrence and development of malignant tumors, metabolic diseases, cardiovascular and cerebrovascular diseases, etc., and could be used as the molecular marker for early diagnosis. Our previous research showed that circRNAs are differentially expressed in serum of GDM pregnant women in the second and third trimester, placental tissues during cesarean delivery, and cord blood. However, the mechanism of circular RNA in GDM still remains unclear. This article focuses on related circRNAs involved in insulin resistance and ß-cell dysfunction, speculating on the possible role of circRNAs in the pathophysiology of GDM under the current research context, and has the potential to serve as early molecular markers for the diagnosis of GDM.
RESUMO
PURPOSE: The purpose of this study is to explore the value of combining bpMRI and clinical indicators in the diagnosis of clinically significant prostate cancer (csPCa), and developing a prediction model and Nomogram to guide clinical decision-making. METHODS: We retrospectively analyzed 530 patients who underwent prostate biopsy due to elevated serum prostate specific antigen (PSA) levels and/or suspicious digital rectal examination (DRE). Enrolled patients were randomly assigned to the training group (n = 371, 70%) and validation group (n = 159, 30%). All patients underwent prostate bpMRI examination, and T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences were collected before biopsy and were scored, which were respectively named T2WI score and DWI score according to Prostate Imaging Reporting and Data System version 2 (PI-RADS v.2) scoring protocol, and then PI-RADS scoring was performed. We defined a new bpMRI-based parameter named Total score (Total score = T2WI score + DWI score). PI-RADS score and Total score were separately included in the multivariate analysis of the training group to determine independent predictors for csPCa and establish prediction models. Then, prediction models and clinical indicators were compared by analyzing the area under the curve (AUC) and decision curves. A Nomogram for predicting csPCa was established using data from the training group. RESULTS: In the training group, 160 (43.1%) patients had prostate cancer (PCa), including 128 (34.5%) with csPCa. Multivariate regression analysis showed that the PI-RADS score, Total score, f/tPSA, and PSA density (PSAD) were independent predictors of csPCa. The prediction model that was defined by Total score, f/tPSA, and PSAD had the highest discriminatory power of csPCa (AUC = 0.931), and the diagnostic sensitivity and specificity were 85.1% and 87.5%, respectively. Decision curve analysis (DCA) showed that the prediction model achieved an optimal overall net benefit in both the training group and the validation group. In addition, the Nomogram predicted csPCa revealed good estimation when compared with clinical indicators. CONCLUSION: The prediction model and Nomogram based on bpMRI and clinical indicators exhibit a satisfactory predictive value and improved risk stratification for csPCa, which could be used for clinical biopsy decision-making.