共查询到20条相似文献,搜索用时 46 毫秒
1.
Anna Lindahl Rainer Heuchel Jenny Forshed Janne Lehtiö Matthias Löhr Anders Nordström 《Metabolomics : Official journal of the Metabolomic Society》2017,13(5):61
Introduction
Pancreatic ductal adenocarcinoma (PDAC) is the fifth most common cause of cancer-related death in Europe with a 5-year survival rate of <5%. Chronic pancreatitis (CP) is a risk factor for PDAC development, but in the majority of cases malignancy is discovered too late for curative treatment. There is at present no reliable diagnostic marker for PDAC available.Objectives
The aim of the study was to identify single blood-based metabolites or a panel of metabolites discriminating PDAC and CP using liquid chromatography-mass spectrometry (LC-MS).Methods
A discovery cohort comprising PDAC (n?=?44) and CP (n?=?23) samples was analyzed by LC-MS followed by univariate (Student’s t test) and multivariate (orthogonal partial least squares-discriminant analysis (OPLS-DA)) statistics. Discriminative metabolite features were subject to raw data examination and identification to ensure high feature quality. Their discriminatory power was then confirmed in an independent validation cohort including PDAC (n?=?20) and CP (n?=?31) samples.Results
Glycocholic acid, N-palmitoyl glutamic acid and hexanoylcarnitine were identified as single markers discriminating PDAC and CP by univariate analysis. OPLS-DA resulted in a panel of five metabolites including the aforementioned three metabolites as well as phenylacetylglutamine (PAGN) and chenodeoxyglycocholate.Conclusion
Using LC-MS-based metabolomics we identified three single metabolites and a five-metabolite panel discriminating PDAC and CP in two independent cohorts. Although further study is needed in larger cohorts, the metabolites identified are potentially of use in PDAC diagnostics.2.
3.
Background
Chromophobe renal cell carcinoma (ChRCC) is the second common subtype of non-clear cell renal cell carcinoma (nccRCC), which accounting for 4–5% of renal cell carcinoma (RCC). However, there is no effective bio-marker to predict clinical outcomes of this malignant disease. Bioinformatic methods may provide a feasible potential to solve this problem.Methods
In this study, differentially expressed genes (DEGs) of ChRCC samples on The Cancer Genome Atlas database were filtered out to construct co-expression modules by weighted gene co-expression network analysis and the key module were identified by calculating module-trait correlations. Functional analysis was performed on the key module and candidate hub genes were screened out by co-expression and MCODE analysis. Afterwards, real hub genes were filter out in an independent dataset GSE15641 and validated by survival analysis.Results
Overall 2215 DEGs were screened out to construct eight co-expression modules. Brown module was identified as the key module for the highest correlations with pathologic stage, neoplasm status and survival status. 29 candidate hub genes were identified. GO and KEGG analysis demonstrated most candidate genes were enriched in mitotic cell cycle. Three real hub genes (SKA1, ERCC6L, GTSE-1) were selected out after mapping candidate genes to GSE15641 and two of them (SKA1, ERCC6L) were significantly related to overall survivals of ChRCC patients.Conclusions
In summary, our findings identified molecular markers correlated with progression and prognosis of ChRCC, which might provide new implications for improving risk evaluation, therapeutic intervention, and prognosis prediction in ChRCC patients.4.
Mohammad Reza Abbaszadegan Anali Riahi Mohammad Mahdi Forghanifard Meysam Moghbeli 《Cellular & molecular biology letters》2018,23(1):42
Background
Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer, with a poor prognosis. Deregulation of WNT and NOTCH signaling pathways is important in ESCC progression, which can be due to either malfunction of their components or crosstalk with other pathways. Therefore, identification of new crosstalk between such pathways may be effective to introduce new strategies for targeted therapy of cancer. A correlation study was performed to assess the probable interaction between growth factor receptors and WNT/NOTCH pathways via the epidermal growth factor receptor (EGFR) and Musashi1 (MSI1), respectively.Methods
Levels of MSI1/EGFR mRNA expression in tumor tissues from 48 ESCC patients were compared to their corresponding normal tissues using real-time polymerase chain reaction.Results
There was a significant correlation between EGFR and MSI1 expression (p?=?0.05). Moreover, there was a significant correlation between EGFR/MSI1 expression and grade of tumor differentiation (p?=?0.02).Conclusion
This study confirms a direct correlation between MSI1 and EGFR and may support the important role of MSI1 in activation of EGFR through NOTCH/WNT pathways in ESCC.5.
Jie Yang Jianhua Cheng Bo Sun Haijing Li Shengming Wu Fangting Dong Xianzhong Yan 《Metabolomics : Official journal of the Metabolomic Society》2018,14(4):40
Introduction
Hypoxia commonly occurs in cancers and is highly related with the occurrence, development and metastasis of cancer. Treatment of triple negative breast cancer remains challenge. Knowledge about the metabolic status of triple negative breast cancer cell lines in hypoxia is valuable for the understanding of molecular mechanisms of this tumor subtype to develop effective therapeutics.Objectives
Comprehensively characterize the metabolic profiles of triple negative breast cancer cell line MDA-MB-231 in normoxia and hypoxia and the pathways involved in metabolic changes in hypoxia.Methods
Differences in metabolic profiles affected pathways of MDA-MB-231 cells in normoxia and hypoxia were characterized using GC–MS based untargeted and stable isotope assisted metabolomic techniques.Results
Thirty-three metabolites were significantly changed in hypoxia and nine pathways were involved. Hypoxia increased glycolysis, inhibited TCA cycle, pentose phosphate pathway and pyruvate carboxylation, while increased glutaminolysis in MDA-MB-231 cells.Conclusion
The current results provide metabolic differences of MDA-MB-231 cells in normoxia and hypoxia conditions as well as the involved metabolic pathways, demonstrating the power of combined use of untargeted and stable isotope-assisted metabolomic methods in comprehensive metabolomic analysis.6.
7.
Antonella Del-Corso Mario Cappiello Roberta Moschini Francesco Balestri Umberto Mura 《Metabolomics : Official journal of the Metabolomic Society》2018,14(1):2
Introduction
While the evolutionary adaptation of enzymes to their own substrates is a well assessed and rationalized field, how molecules have been originally selected in order to initiate and assemble convenient metabolic pathways is a fascinating, but still debated argument.Objectives
Aim of the present study is to give a rationale for the preferential selection of specific molecules to generate metabolic pathways.Methods
The comparison of structural features of molecules, through an inductive methodological approach, offer a reading key to cautiously propose a determining factor for their metabolic recruitment.Results
Starting with some commonplaces occurring in the structural representation of relevant carbohydrates, such as glucose, fructose and ribose, arguments are presented in associating stable structural determinants of these molecules and their peculiar occurrence in metabolic pathways.Conclusions
Among other possible factors, the reliability of the structural asset of a molecule may be relevant or its selection among structurally and, a priori, functionally similar molecules.8.
Jialin Wang Tao Zhang Xiaotao Shen Jia Liu Deli Zhao Yawen Sun Lu Wang Yingjun Liu Xiaoyun Gong Yanxun Liu Zheng-Jiang Zhu Fuzhong Xue 《Metabolomics : Official journal of the Metabolomic Society》2016,12(7):116
Introduction
Previous metabolomics studies have revealed perturbed metabolic signatures in esophageal squamous cell carcinoma (ESCC) patients, however, most of these studies included mainly late-staged ESCC patients due to the difficulties of collecting the early-staged samples from asymptotic ESCC subjects.Objectives
This study aims to explore the early-staged ESCC metabolic signatures and potential of serum metabolomics to diagnose ESCC at early stages.Methods
Serum samples of 97 ESCC patients (stage 0, 39 cases; stage I, 17 cases; stage II, 11 cases, stage III, 30 cases) and 105 healthy controls (HC) were enrolled and randomly separated into training data (77 ESCCs, 84 HCs) and validation data (20 ESCCs, 21 HCs). Untargeted metabolomics was performed to identify ESCC-related metabolic signatures.Results
The global metabolomics profiles could clearly distinguish ESCC from HC in training data. 16 ascertained metabolites were found to be disturbed in the metabolic pathways characterized by dysregulated fatty acid biosynthesis, glycerophospholipid metabolism, choline metabolism in cancer and linoleic acid metabolism. The AUC value in validation data was 0.895, with sensitivity 85.0 % and specificity 90.5 %. Good diagnostic performances were also achieved for early stage ESCC, with the values of area under the curve (AUC) 0.881 for the ESCC patients in both stage 0 and I–II. In addition, six metabolites were found to discriminate ESCC stages. Among them, three biomarkers, dodecanoic acid, LysoPA(18:1), and LysoPC(14:0), exhibited clear trend for ESCC progression.Conclusion
These findings suggest serum metabolomics, performed in a minimally noninvasive and convenient manner, may possess great potential for early diagnosis of ESCC patients.9.
Ferran Casbas Pinto Srinivarao Ravipati David A. Barrett T. Charles Hodgman 《Metabolomics : Official journal of the Metabolomic Society》2017,13(7):81
Introduction
It is difficult to elucidate the metabolic and regulatory factors causing lipidome perturbations.Objectives
This work simplifies this process.Methods
A method has been developed to query an online holistic lipid metabolic network (of 7923 metabolites) to extract the pathways that connect the input list of lipids.Results
The output enables pathway visualisation and the querying of other databases to identify potential regulators. When used to a study a plasma lipidome dataset of polycystic ovary syndrome, 14 enzymes were identified, of which 3 are linked to ELAVL1—an mRNA stabiliser.Conclusion
This method provides a simplified approach to identifying potential regulators causing lipid-profile perturbations.10.
Andrei Prodan Sultan Imangaliyev Henk S. Brand Martijn N. A. Rosema Evgeni Levin Wim Crielaard Bart J. F. Keijser Enno C. I. Veerman 《Metabolomics : Official journal of the Metabolomic Society》2016,12(9):147
Introduction
Understanding the changes occurring in the oral ecosystem during development of gingivitis could help improve prevention and treatment strategies for oral health. Erythritol is a non-caloric polyol proposed to have beneficial effects on oral health.Objectives
To examine the effect of experimental gingivitis and the effect of erythritol on the salivary metabolome and salivary functional biochemistry.Methods
In a two-week experimental gingivitis challenge intervention study, non-targeted, mass spectrometry-based metabolomic profiling was performed on saliva samples from 61 healthy adults, collected at five time-points. The effect of erythritol was studied in a randomized, controlled trial setting. Fourteen salivary biochemistry variables were measured with antibody- or enzymatic activity-based assays.Results
Bacterial amino acid catabolites (cadaverine, N-acetylcadaverine, and α-hydroxyisovalerate) and end-products of bacterial alkali-producing pathways (N-α-acetylornithine and γ-aminobutyrate) increased significantly during the experimental gingivitis. Significant changes were found in a set of 13 salivary metabolite ratios composed of host cell membrane lipids involved in cell signaling, host responses to bacteria, and defense against free radicals. An increase in mevalonate was also observed. There were no significant effects of erythritol. No significant changes were found in functional salivary biochemistry.Conclusions
The findings underline a dynamic interaction between the host and the oral microbial biofilm during an experimental induction of gingivitis.11.
Shih-Kuang Yang Yu-Chao Wang Chun-Cheih Chao Yung-Jen Chuang Chung-Yu Lan Bor-Sen Chen 《BMC medical genomics》2010,3(1):19
Background
Development in systems biology research has accelerated in recent years, and the reconstructions for molecular networks can provide a global view to enable in-depth investigation on numerous system properties in biology. However, we still lack a systematic approach to reconstruct the dynamic protein-protein association networks at different time stages from high-throughput data to further analyze the possible cross-talks among different signaling/regulatory pathways.Methods
In this study we integrated protein-protein interactions from different databases to construct the rough protein-protein association networks (PPANs) during TNFα-induced inflammation. Next, the gene expression profiles of TNFα-induced HUVEC and a stochastic dynamic model were used to rebuild the significant PPANs at different time stages, reflecting the development and progression of endothelium inflammatory responses. A new cross-talk ranking method was used to evaluate the potential core elements in the related signaling pathways of toll-like receptor 4 (TLR-4) as well as receptors for tumor necrosis factor (TNF-R) and interleukin-1 (IL-1R).Results
The highly ranked cross-talks which are functionally relevant to the TNFα pathway were identified. A bow-tie structure was extracted from these cross-talk pathways, suggesting the robustness of network structure, the coordination of signal transduction and feedback control for efficient inflammatory responses to different stimuli. Further, several characteristics of signal transduction and feedback control were analyzed.Conclusions
A systematic approach based on a stochastic dynamic model is proposed to generate insight into the underlying defense mechanisms of inflammation via the construction of corresponding signaling networks upon specific stimuli. In addition, this systematic approach can be applied to other signaling networks under different conditions in different species. The algorithm and method proposed in this study could expedite prospective systems biology research when better experimental techniques for protein expression detection and microarray data with multiple sampling points become available in the future.12.
Gunjal Garg Ali Yilmaz Praveen Kumar Onur Turkoglu David G. Mutch Matthew A. Powell Barry Rosen Ray O. Bahado-Singh Stewart F. Graham 《Metabolomics : Official journal of the Metabolomic Society》2018,14(12):154
Introduction
Epithelial ovarian cancer (EOC) remains the leading cause of death from gynecologic malignancies and has an alarming global fatality rate. Besides the differences in underlying pathogenesis, distinguishing between high grade (HG) and low grade (LG) EOC is imperative for the prediction of disease progression and responsiveness to chemotherapy.Objectives
The aim of this study was to investigate, the tissue metabolome associated with HG and LG serous epithelial ovarian cancer.Methods
A combination of one dimensional proton nuclear magnetic resonance (1D H NMR) spectroscopy and targeted mass spectrometry (MS) was employed to profile the tissue metabolome of HG, LG serous EOCs, and controls.Results
Using partial least squares-discriminant analysis, we observed significant separation between all groups (p?<?0.05) following cross validation. We identified which metabolites were significantly perturbed in each EOC grade as compared with controls and report the biochemical pathways which were perturbed due to the disease. Among these metabolic pathways, ascorbate and aldarate metabolism was identified, for the first time, as being significantly altered in both LG and HG serous cancers. Further, we have identified potential biomarkers of EOC and generated predictive algorithms with AUC (CI)?=?0.940 and 0.929 for HG and LG, respectively.Conclusion
These previously unreported biochemical changes provide a framework for future metabolomic studies for the development of EOC biomarkers. Finally, pharmacologic targeting of the key metabolic pathways identified herein could lead to novel and effective treatments of EOC.13.
Antonio Murgia Christine Hinz Sonia Liggi Jùlìa Denes Zoe Hall James West Maria Laura Santoru Cristina Piras Cristina Manis Paolo Usai Luigi Atzori Julian L. Griffin Pierluigi Caboni 《Metabolomics : Official journal of the Metabolomic Society》2018,14(10):140
Background
Inflammatory bowel disease is a group of pathologies characterised by chronic inflammation of the intestine and an unclear aetiology. Its main manifestations are Crohn’s disease and ulcerative colitis. Currently, biopsies are the most used diagnostic tests for these diseases and metabolomics could represent a less invasive approach to identify biomarkers of disease presence and progression.Objectives
The lipid and the polar metabolite profile of plasma samples of patients affected by inflammatory bowel disease have been compared with healthy individuals with the aim to find their metabolomic differences. Also, a selected sub-set of samples was analysed following solid phase extraction to further characterise differences between pathological samples.Methods
A total of 200 plasma samples were analysed using drift tube ion mobility coupled with time of flight mass spectrometry and liquid chromatography for the lipid metabolite profile analysis, while liquid chromatography coupled with triple quadrupole mass spectrometry was used for the polar metabolite profile analysis.Results
Variations in the lipid profile between inflammatory bowel disease and healthy individuals were highlighted. Phosphatidylcholines, lyso-phosphatidylcholines and fatty acids were significantly changed among pathological samples suggesting changes in phospholipase A2 and arachidonic acid metabolic pathways. Variations in the levels of cholesteryl esters and glycerophospholipids were also found. Furthermore, a decrease in amino acids levels suggests mucosal damage in inflammatory bowel disease.Conclusions
Given good statistical results and predictive power of the model produced in our study, metabolomics can be considered as a valid tool to investigate inflammatory bowel disease.14.
15.
N. Cesbron A.-L. Royer Y. Guitton A. Sydor B. Le Bizec G. Dervilly-Pinel 《Metabolomics : Official journal of the Metabolomic Society》2017,13(8):99
Introduction
Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.Objectives
In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.Methods
The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.Results
A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.Conclusion
The workflow generated repeatable and informative fingerprints for robust metabolome characterization.16.
Sanaya Bamji-Stocke Victor van Berkel Donald M. Miller Hermann B. Frieboes 《Metabolomics : Official journal of the Metabolomic Society》2018,14(6):81
Introduction
Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection has proven essential to extend survival. Genomic and proteomic advances have provided impetus to the effort dedicated to detect and diagnose the disease at an earlier stage. Recently, the study of metabolites associated with tumor formation and progression has inaugurated the era of cancer metabolomics to aid in this effort.Objectives
This review summarizes recent work regarding novel metabolites with the potential to serve as biomarkers for early lung tumor detection, evaluation of disease progression, and prediction of patient outcomes.Method
We compare the metabolite profiling of cancer patients with that of healthy individuals, and the metabolites identified in tissue and biofluid samples and their usefulness as lung cancer biomarkers. We discuss metabolite alterations in tumor versus paired non-tumor lung tissues, as well as metabolite alterations in different stages of lung cancers and their usefulness as indicators of disease progression and overall survival. We evaluate metabolite dysregulation in different types of lung cancers, and those associated with lung cancer versus other lung diseases. We also examine metabolite differences between lung cancer patients and smokers/risk-factor individuals.Result
Although an extensive list of metabolites has been evaluated to distinguish between these cases, refinement of methods is further required for adequate patient diagnosis and treatment.Conclusion
We conclude that with technological advancement, metabolomics may be able to replace more invasive and costly diagnostic procedures while also providing the means to more effectively tailor treatment to patient-specific tumors.17.
Background
Cerebral infarction caused by different reasons seems differ in fibrinogen levels, so the current work intends to explore the relationship between the fibrinogen level and subtypes of the TOAST criteria in the acute stage of ischemic stroke.Methods
A total of 577 case research objects were treated acute ischemic stroke patients in our hospital from December 2008 to December 2010, and blood samples within 72 hours of the onset were processed with the fibrinogen (PT-der) measurement. Classification of selected patients according to the TOAST Criteria was conducted to study the distribution of fibrinogen levels in the stroke subtypes.Results
The distribution of fibrinogen levels in the subtypes was observed to be statistically insignificant.Conclusions
In the acute stage of ischemic stroke, fibrinogen level was not related to the subtypes of the TOAST criteria.18.
19.
Emily G. Armitage Andrew D. Southam 《Metabolomics : Official journal of the Metabolomic Society》2016,12(9):146
Introduction
Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics.Objectives
Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs.Methods
A literature search of the current relevant primary research was performed.Results
Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance.Conclusion
Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies.20.
M. M. Phelan E. Caamaño-Gutiérrez M. S. Gant R. X. Grosman J. Madine 《Metabolomics : Official journal of the Metabolomic Society》2017,13(12):151