Project description:BackgroundTo find potential serum biomarkers of microwave ablation (MWA) for treatment of human lung cancer by 1H nuclear magnetic resonance (NMR)-based metabolomics analysis.MethodsSerum specimens collected from 43 healthy individuals, 39 patients with advanced non-small cell lung cancer (NSCLC) and 38 NSCLC patients treated with MWA, were subjected to 1H NMR-based metabolomics analysis. Partial least squares discriminant analysis was used to analyze the data.ResultsCompared with healthy controls, NSCLC patients showed significantly elevated serum levels of lactate, alanine, glutamate, proline, glycoprotein, phenylalanine, tyrosine and tryptophan, and markedly decreased serum levels of glucose, taurine, glutamine, glycine, phosphocreatine and threonine (p < 0.05). MWA treatment reversed the metabolic profiles of NSCLC patients towards the control group.Conclusions1H NMR-based metabolomics analysis enhanced the current understanding of the mechanisms involved in NSCLC, and uncovered the therapeutic potential of MWA for treatment of NSCLC. The above disturbed serum metabolites were proposed to be the potential biomarkers that may help to predict NSCLC and to evaluate the efficacy of MWA in the treatment of NSCLC.
Project description:The naked mole-rat (NMR), Heterocephalus glaber, is a mouse-sized subterranean rodent native to East Africa. Research on NMRs is intensifying in an effort to gain leverage from their unusual physiology, long-life span and cancer resistance for the development of new theraputics. Few studies have attempted to explain the reasons behind the NMR’s cancer resistance, but most prominently Tian et al. reported that NMR cells produce high-molecular weight hyaluronan as a potential cause for the NMR’s cancer resistance. Tian et al. have shown that NMR cells are resistant to transformation by SV40 Large T Antigen (SV40LT) and oncogenic HRAS (HRASG12V), a combination of oncogenes sufficient to transform mouse and rat fibroblasts. We have developed a number of lentiviral vectors to deliver both these oncogenes and generated 106 different cell lines from five different tissues and eleven different NMRs, and report here that contrary to Tian et al.’s observation, NMR cells are susceptible to oncogenic transformation by SV40LT and HRASG12V. Our data thus point to a non-cell autonomous mechanism underlying the remarkable cancer resistance of NMRs. Identifying these non-cell autonomous mechanisms could have significant implications on our understanding of human cancer development.
Project description:BackgroundTrichinellosis, caused by a parasitic nematode of the genus Trichinella, is a zoonosis that affects people worldwide. After ingesting raw meat containing Trichinella spp. larvae, patients show signs of myalgia, headaches, and facial and periorbital edema, and severe cases may die from myocarditis and heart failure. The molecular mechanisms of trichinellosis are unclear, and the sensitivity of the diagnostic methods used for this disease are unsatisfactory. Metabolomics is an excellent tool for studying disease progression and biomarkers; however, it has never been applied to trichinellosis. We aimed to elucidate the impacts of Trichinella infection on the host body and identify potential biomarkers using metabolomics.Methodology/principal findingsMice were infected with T. spiralis larvae, and sera were collected before and 2, 4, and 8 weeks after infection. Metabolites in the sera were extracted and identified using untargeted mass spectrometry. Metabolomic data were annotated via the XCMS online platform and analyzed with Metaboanalyst version 5.0. A total of 10,221 metabolomic features were identified, and the levels of 566, 330, and 418 features were significantly changed at 2-, 4-, and 8-weeks post-infection, respectively. The altered metabolites were used for further pathway analysis and biomarker selection. A major pathway affected by Trichinella infection was glycerophospholipid metabolism, and glycerophospholipids comprised the main metabolite class identified. Receiver operating characteristic revealed 244 molecules with diagnostic power for trichinellosis, with phosphatidylserines (PS) being the primary lipid class. Some lipid molecules, e.g., PS (18:0/19:0)[U] and PA (O-16:0/21:0), were not present in metabolome databases of humans and mice, thus they may have been secreted by the parasites.Conclusions/significanceOur study highlighted glycerophospholipid metabolism as the major pathway affected by trichinellosis, hence glycerophospholipid species are potential markers of trichinellosis. The findings of this study represent the initial steps in biomarker discovery that may benefit future trichinellosis diagnosis.
Project description:Proteome profiles of THP-1 cells with or without pre-treatment with selected miRNA upon infection with L. pertussis were characterized and quantified using SILAC.
Project description:Haematological malignancies are a frequently diagnosed group of neoplasms and a significant cause of cancer deaths. The successful treatment of these diseases relies on early and accurate detection. Specific small molecular compounds released by malignant cells and the simultaneous response by the organism towards the pathological state may serve as diagnostic/prognostic biomarkers or as a tool with relevance for cancer therapy management. To identify the most important metabolites required for differentiation, an 1H NMR metabolomics approach was applied to selected haematological malignancies. This study utilized 116 methanol serum extract samples from AML (n= 38), nHL (n= 26), CLL (n= 21) and HC (n= 31). Multivariate and univariate data analyses were performed to identify the most abundant changes among the studied groups. Complex and detailed VIP-PLS-DA models were calculated to highlight possible changes in terms of biochemical pathways and discrimination ability. Chemometric model prediction properties were validated by receiver operating characteristic (ROC) curves and statistical analysis. Two sets of eight important metabolites in HC/AML/CLL/nHL comparisons and five in AML/CLL/nHL comparisons were selected to form complex models to represent the most significant changes that occurred.