Metabolomics Study On Evaluaiton Of Endocrine Therapy Response In Chinese Patients With Prostate Cancer

ObjectiveEarly evaluation of endocrine therapy response is an attractive strategy toimprove the prognosis of prostate cancer (PCa). But there are no perfect methods tomake a definite evaluation of endocrine therapy response. In this study, metabolomicapproach would be used to analyze tendency of metabolin in prostate cancer patientsunder endocrine thetapy to verify the results of prostate cancer animal models, andto establish an early, rapid and efficient strategy for evaluatuon of endocrine therapyresponse, and then to research some potential biomarkers related with the outcome.Methods80male subjects were divided into four groups (each of20cases). Controlgroup consisted of general population. PCa group consisted of patients initiallydiagnosed as advanced prostate cancer, who had not received endocrine therapy(Casodex+ZoLadex). Good response group consisted of advanced prostate cancerpatients under endocrine therapy and the time of transition to androgen-independentprostate cancer was more than2years, while the transition time of poor responsegroup was less than1year. The average age of the four groups was not statisticallysignificant (P>0.05). The mean value of initial prostate specific antigen (PSA) inPca, good and poor response group was not statistically significant (P>0.05).Approximate3ml vein blood was assembled from every subject of four groups, thenleft to clot for30minutes at room temperature. The serum was separated bycentrifugation at3000g for10min, and the aliquot was stored at80°C untilmetabonomic analysis. The samples collected time and manner from control andPCa group correspond with good and poor response group. After special pretreatments, serum samples were analyzed to acquire metabolicprofiles using rapidly-performance liquid chromatography-time of flight-massspectra (RPLC-Q-TOF-MS). Multivariate analysis (MVA), including partial leastsquares discriminant analysis(PLS-Da) and orthogonal single collection partialleast squares analysis (OPLS), were employed to visualize the changes in themetabolic profiles of sera from control, PCa, good and poor response subjects, thento display in score plot and loading plot, and discover potential biomarkers relatedwith the outcome.ResultsBased on RPLC-TOF-MS data, PLS-Da(negative model) allows a cleardiscrimination of the pathologic characteristics among subjects. The results frommetabolin identification have suggested there are markedly distinctions betweencontrol group and PCa, good response, poor response group. The results come fromorthogonal single collection partial least squares (OPLS) analysis between controlgroup and good and poor response group have suggest that there are48bio-markersin the negative model. The16biomarkers in the negative model would be verifiedwith Human Metabolome Database (http://metlin.scripps.edu) and Scripps Centerfor Mass Spectrometry (http://www.hmdb.ca).ConclusionsBased on RPLC-TOF-MS metabolomic approaches combined with patternrecognition permit the overall monitoring for the tendency of metabolin in prostatecancer patients under endocrine therapy, and allow accurate outcome evaluation ofendocrine therapy response in the early stage. The proposed approach hasadvantages of rapid, low-cost and efficiency, and is expected to be applied toprostate cancer patients in clinical.