| Backgrounds:China is one of the countries with high incidence of esophageal cancer in the world,its morbidity and mortality are among the highest in the world,and more than 90%of them are esophageal squamous cell carcinoma.The Wenhe River Basin of Shandong Province is one of the high incidence areas of esophageal squamous cell carcinoma in China,especially in Feicheng City,where the incidence of esophageal squamous cell carcinoma is far above the provincial average level.The disease has no obvious symptoms in the early stage,it is mostly in the middle and late stages when it is discovered,with a poor prognosis and low 5-year survival rate.Esophageal cancer has caused a huge burden of disease and economic burden in high-incidence areas.Esophageal squamous cell carcinoma needs to go through a long process from normal to cancerous.If the stage of precancerous lesions can be identified and intervention measures are taken,it is likely to promote the reversal of the disease.Therefore,"early detection,early diagnosis,early treatment"is the key content of esophageal cancer prevention and treatment of esophageal cancer.Existing screening methods are difficult to be widely promoted due to technical and cost-effective limitations.Therefore,a cost-effective,non-invasive method with high sensitivity and specificity is urgently needed in practical application.Metabolomics can effectively identify biometric differences and contribute to the study of disease mechanism by qualitative and quantitative analysis of small molecular metabolites in biological samples.The carcinogenesis of esophageal squamous cell carcinoma is often accompanied by the changes of a variety of metabolites in the body,and metabolomics methods are widely used in the early screening and diagnosis of the disease.Previous metabolomic studies on ESCC involved multiple sample types of serum,plasma,urine and tissue,as well as various metabolomic detection techniques.But macroscopically,they were all based on traditional case-control studies of healthy controls and ESCC patients to find potential biomarkers for early diagnosis of ESCC,with little attention to different stages of the disease development process.At the same time,in other cancer research fields,the traditional two-group comparison method is still used to explore the differences of metabolic characteristics at different stages of cancer progression.Most studies have not used the hierarchical relationship of different stages in the evolution of cancer.In this study,our study population came from the esophageal cancer population screening and follow-up community cohort at the Feicheng City Demonstration Base for Early Diagnosis and Treatment of Esophageal Cancer.Metabolomic analysis and ordered multi-classification statistical analysis were used to screen the metabolites related to the progression of esophageal squamous epithelial lesions.Pathway analysis was used to explore the mechanism of metabolic disorders,and the metabolites found were used to establish discriminant model to study their ability to distinguish different stages.Methods:In this study,subjects covering all stages of esophageal squamous epithelial lesions progression were included.Ultra high performance liquid chromatography quadruple time-of-flight mass spectrometry(UPLC-QTOF/MS)were used for serum metabolomics detection to obtain corresponding metabolic fingerprints.Statistical analysis was carried out after preprocessing and quality evaluation of metabolomics data.First,unsupervised principal component analysis(PCA)and supervised partial least squares discriminant analysis(PLS-DA)were used to explore whether there was a classification trend among different groups of subjects,and combine the Wilcoxon rank sum test to screen differential metabolites,then check whether there are common differential metabolites.Then,the fuzzy c-means clustering method and ordinal logistic regression analysis were used to screen the metabolites associated with the progression of esophageal squamous epithelial lesions,and pathway analysis was performed.Finally,the selected metabolites were used to construct the multiple ordinal logistic discriminant model and binary logistic discriminant model,and the 5-fold cross validation method was used to verify the model.When constructing the multiple ordinal logistic discriminant model,the SMOTE method was used to deal with the problem of data imbalance in the training set.Results:1.A total of 653 subjects were enrolled in this study,including 305 healthy subjects,77 patients with esophagitis,188 patients with mild ESD,40 patients with moderate ESD,15 patients with severe ESD,12 patients with carcinoma in situ,and 16 patients with ESCC.According to the characteristics of the disease,the subjects were divided into four groups:"normal","esophagitis","LGIN" and "HGIN/ESCC".Univariate ordinal logistic regression analysis showed that there were statistical differences in age,BMI,smoking and alcohol consumption between these groups(P<0.05).2.PCA score chart showed that the normal group and each disease group had a tendency of separation,but several disease groups almost completely overlap,indicating that the difference between disease groups was small.PLS-DA analysis showed that there were obvious classification trends between normal group and esophagitis group,LGIN group and HCIN/ESCC group.Combined with rank sum test analysis,57,69 and 58 different metabolites were screened,respectively.There are 40 different metabolites overlapping among the three results,including phospholipids and amino acids,but most of them are phospholipid metabolites.There are 6 non-phospholipid differential metabolites,including L-glutamine,L-histidine,L-tyrosine,L-tryptophan,L-leucine-L-proline and trans-vaccenic acid.The PLS-DA three-dimensional score chart showed that there was a classification trend between esophagitis and LGIN group,esophagitis and HGIN/ESCC group,LGIN and HGIN/ESCC group,but few differential metabolites were screened.3.All the identified metabolic characteristics were divided into 6 categories by FCM clustering analysis.The relative expression of metabolites in Cluster 1 and Cluster 2 has obvious decreasing and increasing trends from the normal group to the HGIN/ESCC group,respectively.Further analysis screened out 15 metabolites related to the progression of esophageal squamous lesion.L-histidine(OR=0.60),L-tryptophan(OR=0.73),dopamine(OR=0.70),5-hydroxyindoleacetate(OR=0.72)and some phospholipids such as PC(O-16:1/0:0)(OR=0.59)are associated with a reduced risk of progression of esophageal squamous epithelial lesions,and the relative expression levels of these metabolites showed a decreasing trend with the progression of esophageal squamous epithelial lesions.Glycochenodeoxycholate(OR=1.22),hypoxanthine(OR=1.37),carnitine(14:1)(OR=1.23),inosine(OR=1.35),and PC(P-18:0/18:3)(OR=1.21)are associated with an increased risk of esophageal squamous epithelial lesions progression,and the relative expression levels of these metabolites increased with the progression of esophageal squamous epithelial lesions.After multiple ordinal logistic regression analysis,L-histidine(OR=0.69),5-hydroxyindoleacetate(OR=0.79),dopamine(OR=0.81),glycochenodeoxycholate(OR=1.29),hypoxanthine(OR=1.44),inosine(OR=1.42)and PC(0-16:1/0:0)(OR=0.78)are still statistically significant(P<0.05),these metabolites are related to the occurrence and development of esophageal squamous epithelial lesions.4.Pathway analysis showed that the pathways of metabolic disorders with the development of esophageal squamous epithelial lesions mainly involved tryptophan metabolism,histidine metabolism and purine metabolism.5.When the subjects were divided into normal,esophagitis,LGIN and HGIN/ESCC groups,the quadratic weighted Kappa coefficients and the accuracy rates of the multiple ordinal logistic discriminant model were 0.53(0.47,0.59)and 0.50(0.46,0.54),respectively.When patients with esophagitis and above were used as case group to construct the binary logistic discriminant model,the AUC was 0.80(0.78,0.83),and the sensitivity and specificity were 0.75(0.61,0.83)and 0.76(0.66,0.88),respectively.Moreover,with the increase of disease severity,the ability of the model to distinguish them from normal group also increased.Conclusions:This study found that the expression levels of 15 metabolites such as L-histidine,L-tryptophan and hypoxanthine increased or decreased continuously during the development of normal esophageal epithelial tissue to ESCC.These metabolites are related to the progression of esophageal squamous epithelial lesions,mainly involving phospholipids and tryptophan metabolism,histidine metabolism and purine metabolism pathway disorders.The multiple ordinal logistic discriminant model and binary logistic discriminant model showed that these metabolites had the potential to distinguish esophageal squamous epithelial lesions at all stages and to be applied in esophageal squamous carcinoma screening,which is worth futher exploration. |
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