Serum/Urinary Metabonomics Study Of Osteosarcoma

Objective:This study is designed to learn through the metabonomics test platform, analyze animalmodels with healthy control group urine specimens through the experiments, and clinicallyresearch into patients with osteosarcoma, benign bone tumors and healthy control serum /urine specimens. It was established a spectral mathematical model of osteosarcomarespectively by the application of the Partial least square-discriminate analysis (PLS-DA)method and other methods. Relevant analysis techniques and statistical methods were usedto analysis and comparison of animal experiment and clinical study of samples of the endproduct of metabolism. High resolution, reproducible osteosarcoma serum and urinemetabolism markers matter group were established to try to find osteosarcoma diagnosticmarkers by the body dynamic metabolic pathways .Methods:This study was divided into three parts.1. Experiments of animal models of osteosarcoma metabolic spectrum.The MG-63 (humanosteosarcoma cell line) of C3H mouse model and the healthy control group wereestablished , the use of ECF derivative by GC / MS technology platforms were observedin a rat model of tumor-bearing after 3, 5 and 7 weeks of endogenous small moleculemetabolic spectrum relative to the changes in the urine of healthy control group. usingthe principal of the component analysis (PCA) method determine the tumor-bearing miceat the same time point urine samples metabolic spectrum profile and trends.Through theanalysis of variable importance in projection (VIP) of PLS-DA model, we could identifythe differences in metabolites of the main ingredients.2. Experiments of the metabolic spectrum of clinical bone tumors (Benign /osteosarcoma).13 patients with osteosarcoma, 18 patients with benign bone tumor and 20healthy controls were divided into three groups. ECF derivative by GC / MS technologyplatform to analyze three groups of urine samples of metabolism;Synchronization basedon the use Trimethylsilyl (TMS) derivatives by gas chromatography time-of-flight massspectrometry (GC / TOF-MS) analysis method to study three groups of serum samples.This metabolite spectral changes of serum / urine samples, respectively. Then, by themethod of PCA and PLS-DA/OPLS-DA, we compared the bone tumor group and thehealthy control group and further distinguished between benign bone tumors and osteosarcoma group. Through the analysis of VIP, we could identify the differences inmetabolites of the main ingredients.3. Comprehensive analysis of osteosarcoma metabolism markers and metabolic pathway.The results of animal experiment and clinical study were combined analysis, to come tothe intersection of metabolites in the Metabolic Pathway and the KEGG (KyotoEncyclopedia of Genes and Genomes) database query of the metabolic pathway.Throughcomprehensive analysis, we can get into osteosarcoma in a more obvious metabolicchanges during the development of endogenous small molecule, presumably into the theosteosarcoma metabolic biomarkers, major metabolic pathways, as well as its metabolicpathway enzymes.Results:1. The result of Animal experiment showed that model in three weeks of the experimentbegan to offset the first five weeks have been initially apparent separation, the first sevenweeks can distinguish.The formation of 37-related differences in metabolite identified inthe PLS-DA model experiments with osteosarcoma, and using the NIST library and otherdatabases identified 10 metabolites.Hippuric acid, Urea, L-ornithine content in the tumorgroup than the healthy control group is lower;The content of putrescine, spermidine,isocitrate is higher.2. By the unsupervised PCA method, we got the metabolic spectrum separation trend of thehealthy controls and patients with bone tumors (Benign / osteosarcoma),We furtherused the orthogonal the partial least square-discriminant analysis (OPLS-DA) method toobserve clearly in the metabolic profile differences between the osteosarcoma, benignbone tumors and normal controls, and get the change of the metabolic pathways relatedto the clinical pathology of osteosarcoma.Serum metabonomics analysis: Ribitol,D-Fructose,2-Ketoglutaric acid,lactate,Butanal,Butanoic acid,Glycine,à-Aminoadipicacid,L-Ornithine,methylhistidine,L-Valine,Dodecanoic acid in the serum of patientswith osteosarcoma was significantly lower than in patients with benign bone tumors;Citrulline,L-Tyrosine,Urea,Galactopyranose,2-Deoxy-galactopyranose,Octadecanoicacid,α-Hydroxybutyric acid and other metabolites in the serum of patients withosteosarcoma were significantly higher than that of benign bone tumors. Urinemetabonomics analysis: glycine,leucine,lysine,homovanillate,lactate,citrate and othermetabolites in the urine of patients with osteosarcoma were significantly lower than in patients with benign bone tumors;hippurate,glutamate,histamine,Cystine,putresinein the urine of patients with osteosarcoma were significantly higher than in patients withbenign bone tumors3. We found abnormal osteosarcoma metabolites common pathway for tumor energymetabolism and ornithine cycle - polyamine metabolism abnormalities. Osteosarcomaurine metabonomics studies, citric acid, hippurate, putrescine, spermidine, ornithine maybecome the markers of the metabolic diagnosis, speculated that a key enzyme ornithinedecarboxylase (Ornithime decarboxylase ODC), S-transferases Gultathione (GST)isozyme of GSTM1, GSTT1.Into osteosarcoma serum metabonomics study results showthat malic acid, dodecanoic acid, Lanthionine may become the markers of the metabolicdiagnosis, speculated that a key enzyme responsible for the regulation of ornithine cycle /transit N-acetyl glutamate synthetase (NAGAS) and ornithine carbamyl transferase(OCT)。4. Metabolic differences: osteosarcoma not only affects the metabolism of carbohydrates,lipids and proteins in the three substances, and also have a significant impact on energymetabolism and ornithine cycle - polyamine metabolism and other physiologicalsystems,and may be a direct result of the metabolic pathways.Conclusion:1. Osteogenic sarcoma metabonomics experimental platform, based on ECF and TMSderivative by GC / MS study of the osteosarcoma animal models and clinicalmetabonomics into the blood / urine of patients with osteosarcoma, we can initially beenhealthy. malignant and healthy control population group separation of metabolicprofiling trends.This indicates that there is great potential in the early diagnosis ofosteosarcoma, based on chromatography / mass spectrometry method of urinemetabonomics.2. In this study, GC / TOF-MS-based serum Metabonomics also relatively stable, we canclearly divided into osteosarcoma, benign and normal serum metabolic profile.3. Model animal experiments and osteosarcoma clinical patient urine / serum metabonomicsconfirmed that the metabolic pathway for energy metabolism and ornithine cycle - andpolyamine metabolism obstruction occurred in osteosarcoma, the development ofpathological processes play an important role, and osteosarcoma formation, degradationand transfer to an important need to be follow-up verification.Contributions and innovations: 1. The first time we osteosarcoma metabonomics learn by GC / MS and GC / TOF-MSexperiment platform, not only can the healthy group and into the trend of metabolicprofiling of osteosarcoma group separation and can be further distinguishingbetween benign bone tumors with osteosarcoma metabolism mode.2. We exploratory results obtained in animal experiments and clinical studies tointegrate analysis, serum / urine samples metabonomics analysis results of crossvalidation can be relatively stable osteosarcoma metabolic markers. This mayinspire new ideas in the early diagnosis of osteosarcoma chromatography / massspectrometry-based metabonomics.3. We found that human and animals into osteosarcoma, a common metabolic pathwayfor energy metabolism and ornithine cycle - polyamine metabolic disorder led toimportant conclusions: the metabolic pathways of energy metabolism, ornithinecycle - and polyamine metabolism disorder may be osteogenic sarcoma,development, transfer pathological process of metabolism, for osteosarcomametabolic pathway in-depth studies provide important scientific evidence.