LC-MS/MS platform-based serum untargeted screening reveals the diagnostic biomarker panel and molecular mechanism of breast cancer.

BACKGROUND: Breast cancer (BC), the most common form of malignant cancer affecting women worldwide, was characterized by heterogeneous metabolic disorder and lack of effective biomarkers for diagnosis. The purpose of this study is to search for reliable metabolite biomarkers of BC as well as triple-negative breast cancer (TNBC) using serum metabolomics approach. METHODS: In this study, an untargeted metabolomics technique based on ultra-high performance liquid chromatography combined with mass spectrometry (UHPLC-MS) was utilized to investigate the differences in serum metabolic profile between the BC group (n = 53) and non-BC group (n = 57), as well as between TNBC patients (n = 23) and non-TNBC subjects (n = 30). The multivariate data analysis, determination of the fold change and the Mann-Whitney U test were used to screen out the differential metabolites. Additionally, machine learning methods including receiver operating curve analysis and logistic regression analysis were conducted to establish diagnostic biomarker panels. RESULTS: There were 36 metabolites found to be significantly different between BC and non-BC groups, and 12 metabolites discovered to be significantly different between TNBC and non-TNBC patients. Results also showed that four metabolites, including N-acetyl-D-tryptophan, 2-arachidonoylglycerol, pipecolic acid and oxoglutaric acid, were considered as vital biomarkers for the diagnosis of BC and non-BC with an area under the curve (AUC) of 0.995. Another two-metabolite panel of N-acetyl-D-tryptophan and 2-arachidonoylglycerol was discovered to discriminate TNBC from non-TNBC and produced an AUC of 0.965. CONCLUSION: This study demonstrated that serum metabolomics can be used to identify BC specifically and identified promising serum metabolic markers for TNBC diagnosis.

Resveratrol ameliorates myocardial fibrosis by regulating Sirt1/Smad3 deacetylation pathway in rat model with dilated cardiomyopathy.

BACKGROUND: The aim of this study was to investigate the effects of Resveratrol (RSV) in rats with dilated cardiomyopathy (DCM). METHODS: Porcine cardiac myosin was used to set up rat model with DCM. RSV (10 mg/kg in RSV-L group and 50 mg/kg in RSV-H group) or vehicle was administered to rats with DCM once daily from the 28th day till the 90th day after the first immunization. Cardiac function of rats was evaluated by echocardiographic analysis. The deposition of fibrous tissues in the hearts was evaluated by Masson and picrosirius red staining. The mRNA levels of collagen type I (Col I), collagen type III (Col III) and silence information regulator 1 (Sirt1) were measured by quantitative real-time polymerase chain reaction (qRT-PCR). The interaction of Sirt1 with Smad3 was revealed by coimmunoprecipitation. RESULTS: The heart weight, heart weight/body weight ratio, left ventricular end diastolic diameter (LVEDD) and left ventricular end systolic diameter (LVESD) were significantly increased in rats with DCM, and attenuated by RSV. RSV also positively decreased fibrosis, and the expression of Col I and Col III in the myocardium. The Sirt1 mRNA was significantly decreased in myosin-immunized hearts and was positively increased by RSV. The Sirt1 combined with Smad3 directly. Acetylation of Smad3 (Ac-Smad3) was significantly increased in DCM and was markedly decreased by RSV. CONCLUSION: RSV effectively ameliorated myocardial fibrosis and improved cardiac function by regulating Sirt1/Smad3 deacetylation pathway in rat model with DCM.