Exploration on Biomarkers for Discrimination of Colorectal Adenoma and Cancer by UHPLC£­HRMS-based Serum Metabolomics

KeyWord:colorectal cancer  colorectal adenoma  ultrahigh-performance liquid chromatography£­tandem high-resolution mass spectrometry£¨UHPLC£­HRMS£©  serum metabolomics  biomarkers

Abstract:

      Colorectal cancer£¨CRC£© is one of the most vital causes of cancer-related death worldwide£¬while colorectal adenoma£¨CA£© is an important precancerous lesion of CRC. The development of a CA into a CRC is a relatively long and stealthy process£®However£¬there is still a lack of minimally invasive and reliable biomarkers to distinguish CA from CRC£®In this paper£¬an ultrahigh-performance liquid chromatography£­tandem high-resolution mass spectrometry£¨UHPLC£­HRMS£© combined with multivariate statistical analysis was used to analyze the untargeted metabolomics of serum samples from 64 CA patients and 84 CRC patients£®The acquired metabolomics data were analyzed by unsupervised segregation principal component analysis£¨PCA£© to visualize the grouping trends and detect outliers£®A supervised orthogonal partial least squares discriminant analysis£¨OPLS£­DA£© was subsequently utilized to maximize the discrimination between the groups£®The established OPLS£­DA model was validated by 200 times of permutation tests to confirm its rationality and reliability in data analysis£®Then the serum differential metabolites responsible for the discrimination between the groups were screened based on the criteria of P < 0.05 and fold change > 1.50 or < 0.67£¬and further identified using the mzCloud and HMDB databases£®The discriminative ability for differential metabolites was verified by receiver operating characteristic£¨ROC£© analysis£®Moreover£¬the pathway and enrichment analyses of differential metabolites using MetaboAnalyst were used to preliminarily explore the metabolic mechanism of CA cancerization£®Results showed that there were certain differences in serum metabolic profiles between the two groups£¬and 66 differential metabolites were screened and identified£¬including glycerophospholipids£¬fatty acids£¬sphingomyelins£¬steroids£¬amino acids£¬nucleosides and cholines£®These differential metabolites mainly involved in the biosynthesis of unsaturated fatty acids£¬purine metabolism and linoleic acid metabolism£¬suggesting that they may be closely related to the carcinogenesis of CA£®11 metabolic biomarkers including adenine£¬PC18¡Ã0£¬arachidonic acid£¬docosahexaenoic acid£¬PC 36¡Ã3£¬8£¬11£¬14-eicosatrienoic acid£¬PC 20¡Ã4£¬SM d36¡Ã2£¬5£¬8£¬11£¬14£¬17-eicosapentaenoic acid£¬sphingosine£¨d18¡Ã1£©£¬and ACar 20¡Ã1 showed good specificity and sensitivity with the area under the ROC curves greater than 0.80£¬which had the strong discriminant ability and high potential in clinical application to distinguish CA and CRC£®Especially£¬the area under the ROC curve of the marker panel including PC 36¡Ã3£¬adenine£¬sphingosine£¬PC 18¡Ã0£¬and PC 20¡Ã4 was 0.941£¬which presented an outstanding discriminant performance on the CA and CRC£®The marker panel discovered provides a valuable reference for the early prevention of CRC clinically.