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CLC number: R737.25

On-line Access: 2017-11-06

Received: 2016-10-04

Revision Accepted: 2017-01-15

Crosschecked: 2017-10-12

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 ORCID:

Jochen Neuhaus

http://orcid.org/0000-0003-2484-6994

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Journal of Zhejiang University SCIENCE B 2017 Vol.18 No.11 P.921-933

10.1631/jzus.B1600441


Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer


Author(s):  Bo Yang, Guo-qiang Liao, Xiao-fei Wen, Wei-hua Chen, Sheng Cheng, Jens-Uwe Stolzenburg, Roman Ganzer, Jochen Neuhaus

Affiliation(s):  Department of Urology, Zhoupu Hospital, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China; more

Corresponding email(s):   jochen.neuhaus@medizin.uni-leipzig.de

Key Words:  Prostate cancer, Metabolomics, Nuclear magnetic resonance (NMR), Biomarker


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Bo Yang, Guo-qiang Liao, Xiao-fei Wen, Wei-hua Chen, Sheng Cheng, Jens-Uwe Stolzenburg, Roman Ganzer, Jochen Neuhaus. Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer[J]. Journal of Zhejiang University Science B, 2017, 18(1): 921-933.

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author="Bo Yang, Guo-qiang Liao, Xiao-fei Wen, Wei-hua Chen, Sheng Cheng, Jens-Uwe Stolzenburg, Roman Ganzer, Jochen Neuhaus",
journal="Journal of Zhejiang University Science B",
volume="18",
number="11",
pages="921-933",
year="2017",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B1600441"
}

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%A Bo Yang
%A Guo-qiang Liao
%A Xiao-fei Wen
%A Wei-hua Chen
%A Sheng Cheng
%A Jens-Uwe Stolzenburg
%A Roman Ganzer
%A Jochen Neuhaus
%J Journal of Zhejiang University SCIENCE B
%V 18
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%P 921-933
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T1 - Nuclear magnetic resonance spectroscopy as a new approach for improvement of early diagnosis and risk stratification of prostate cancer
A1 - Bo Yang
A1 - Guo-qiang Liao
A1 - Xiao-fei Wen
A1 - Wei-hua Chen
A1 - Sheng Cheng
A1 - Jens-Uwe Stolzenburg
A1 - Roman Ganzer
A1 - Jochen Neuhaus
J0 - Journal of Zhejiang University Science B
VL - 18
IS - 11
SP - 921
EP - 933
%@ 1673-1581
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PB - Zhejiang University Press & Springer
ER -


Abstract: 
prostate cancer (PCa) is the second most common male cancer worldwide and the fifth leading cause of death from cancer in men. Early detection and risk stratification is the most effective way to improve the survival of PCa patients. Current PCa biomarkers lack sufficient sensitivity and specificity to cancer. Metabolite biomarkers are evolving as a new diagnostic tool. This review is aimed to evaluate the potential of metabolite biomarkers for early detection, risk assessment, and monitoring of PCa. Of the 154 identified publications, 27 and 38 were original papers on urine and serum metabolomics, respectively. nuclear magnetic resonance (NMR) is a promising method for measuring concentrations of metabolites in complex samples with good reproducibility, high sensitivity, and simple sample processing. Especially urine-based NMR metabolomics has the potential to be a cost-efficient method for the early detection of PCa, risk stratification, and monitoring treatment efficacy.

核磁共振波谱作为提高前列腺癌早期诊断和危险度分级的新方法

概要:前列腺癌(PCA)是全球第二个最常见的男性癌症,同时也是男性癌症死亡的第五大原因。早期发现和危险度分级是提高前列腺癌患者生存率最有效的方法。目前前列腺癌的生物标志物缺乏足够的敏感性和特异性,而代谢产物作为生物标志物可以作为一种新的提高早期诊断的工具。我们检索了154篇出版物,其中27篇和38篇是分别关于尿液和血清代谢组学分析的原研论文,提示了核磁共振波谱分析是一种很有前景的检测方法,可用于测量复杂的样本中代谢物的浓度,具有良好的重现性、高灵敏度和样本处理的便捷性。特别是基于核磁共振的代谢组学检测尿液已成为检测前列腺癌的早期潜在的危险度分级和监测治疗效果的有效的方法。
关键词:前列腺癌;代谢组学;核磁共振(NMR);生物标志物

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Armitage, E.G., Barbas, C., 2014. Metabolomics in cancer biomarker discovery: current trends and future perspectives. J. Pharm. Biomed. Anal., 87:1-11.

[2]Austdal, M., Tangerås, L.H., Skråstad, R.B., et al., 2015. First trimester urine and serum metabolomics for prediction of preeclampsia and gestational hypertension: a prospective screening study. Int. J. Mol. Sci., 16(9):21520-21538.

[3]Baade, P.D., Youlden, D.R., Cramb, S.M., et al., 2013. Epidemiology of prostate cancer in the Asia-Pacific region. Prostate Int., 1(2):47-58.

[4]Bansal, N., Gupta, A., Mitash, N., et al., 2013. Low- and high-grade bladder cancer determination via human serum-based metabolomics approach. J. Proteome Res., 12(12):5839-5850.

[5]Bansal, N., Gupta, A., Sankhwar, S.N., 2015. Proteometabolomics of bladder cancer: current and future prospects. Cancer Biomark., 15(4):339-348.

[6]Beger, R.D., 2013. A review of applications of metabolomics in cancer. Metabolites, 3(3):552-574.

[7]Behr, S.C., Aggarwal, R., Seo, Y., et al., 2016. A feasibility study showing [68Ga] citrate PET detects prostate cancer. Mol. Imaging Biol., 18(6):946-951.

[8]Bertini, I., Cacciatore, S., Jensen, B.V., et al., 2012. Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer. Cancer Res., 72(1):356-364.

[9]Brawley, O.W., 2012. Prostate cancer epidemiology in the United States. World J. Urol., 30(2):195-200.

[10]Carrola, J., Rocha, C.M., Barros, A.S., et al., 2011. Metabolic signatures of lung cancer in biofluids: NMR-based metabonomics of urine. J. Proteome Res., 10(1):221-230.

[11]Center, M.M., Jemal, A., Lortet-Tieulent, J., et al., 2012. International variation in prostate cancer incidence and mortality rates. Eur. Urol., 61(6):1079-1092.

[12]Chan, A.W., Mercier, P., Schiller, D., et al., 2016. 1H-NMR urinary metabolomic profiling for diagnosis of gastric cancer. Br. J. Cancer, 114(1):59-62.

[13]Chan, E.C., Pasikanti, K.K., Hong, Y., et al., 2015. Metabonomic profiling of bladder cancer. J. Proteome Res., 14(2):587-602.

[14]Chen, K.Y., Liu, X., Bu, P., et al., 2014. A metabolic signature of colon cancer initiating cells. The 36th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBC), Chicago, IL, USA. IEEE, p.4759-4762.

[15]Chen, W., Zheng, R., Baade, P.D., et al., 2016. Cancer statistics in China, 2015. CA Cancer J. Clin., 66(2):115-132.

[16]Coffey, D.S., 2001. New insights and methodologies are needed to solve the many epidemiologic enigmas of prostate cancer. Epidemiol. Rev., 23(1):1.

[17]Davis, V.W., Schiller, D.E., Eurich, D., et al., 2013. Pancreatic ductal adenocarcinoma is associated with a distinct urinary metabolomic signature. Ann. Surg. Oncol., 20(S3):S415-S423.

[18]DeSantis, C.E., Lin, C.C., Mariotto, A.B., et al., 2014. Cancer treatment and survivorship statistics, 2014. CA Cancer J. Clin., 64(4):252-271.

[19]Dona, A.C., Jimenez, B., Schafer, H., et al., 2014. Precision high-throughput proton NMR spectroscopy of human urine, serum, and plasma for large-scale metabolic phenotyping. Anal. Chem., 86(19):9887-9894.

[20]Doskocz, M., Marchewka, Z., Jeż, M., et al., 2015. Preliminary study on J-resolved NMR method usability for toxic Kidney’s injury assessment. Adv. Clin. Exp. Med., 24(4):629-635.

[21]Drake, R.R., Elschenbroich, S., Lopez-Perez, O., et al., 2010. In-depth proteomic analyses of direct expressed prostatic secretions. J. Proteome Res., 9(5):2109-2116.

[22]Duarte, I.F., Diaz, S.O., Gil, A.M., 2014. NMR metabolomics of human blood and urine in disease research. J. Pharm. Biomed. Anal., 93:17-26.

[23]Duijvesz, D., Luider, T., Bangma, C.H., et al., 2011. Exosomes as biomarker treasure chests for prostate cancer. Eur. Urol., 59(5):823-831.

[24]Dunn, W.B., Erban, A., Weber, R.J.M., et al., 2013. Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics. Metabolomics, 9(S1):44-66.

[25]Edmands, W.M., Beckonert, O.P., Stella, C., et al., 2011. Identification of human urinary biomarkers of cruciferous vegetable consumption by metabonomic profiling. J. Proteome Res., 10(10):4513-4521.

[26]Ellis, J.K., Athersuch, T.J., Thzmas, L.D., et al., 2012. Metabolic profiling detects early effects of environmental and lifestyle exposure to cadmium in a human population. BMC Med., 10:61.

[27]Emwas, A.H.M., Salek, R.M., Griffin, J.L., et al., 2013. NMR-based metabolomics in human disease diagnosis: applications, limitations, and recommendations. Metabolomics, 9(5):1048-1072.

[28]Emwas, A.H., Roy, R., McKay, R.T., et al., 2016. Recommendations and standardization of biomarker quantification using NMR-based metabolomics with particular focus on urinary analysis. J. Proteome Res., 15(2):360-373.

[29]Ervik, M., Lam, F., Ferlay, J., et al., 2016. Cancer Today. International Agency for Research on Cancer, Lyon, France. http://www.iarc.fr

[30]Felgueiras, J., Silva, J.V., Fardilha, M., 2014. Prostate cancer: the need for biomarkers and new therapeutic targets. J. Zhejiang Univ.-Sci. B (Biomed. & Biotechnol.), 15(1):16-42.

[31]Ferreiro-Vera, C., Priego-Capote, F., Luque de Castro, M.D., 2012. Comparison of sample preparation approaches for phospholipids profiling in human serum by liquid chromatography-tandem mass spectrometry. J. Chromatogr. A, 1240:21-28.

[32]Frantzi, M., Latosinska, A., Merseburger, A.S., et al., 2015. Recent progress in urinary proteome analysis for prostate cancer diagnosis and management. Expert Rev. Mol. Diagn., 15(12):1539-1554.

[33]Fukuhara, K., Ohno, A., Ota, Y., et al., 2013. NMR-based metabolomics of urine in a mouse model of Alzheimer’s disease: identification of oxidative stress biomarkers. J. Clin. Biochem. Nutr., 52(2):133-138.

[34]Giskeødegård, G.F., Davies, S.K., Revell, V.L., et al., 2015a. Diurnal rhythms in the human urine metabolome during sleep and total sleep deprivation. Sci. Rep., 5:14843.

[35]Giskeødegård, G.F., Hansen, A.F., Bertilsson, H., et al., 2015b. Metabolic markers in blood can separate prostate cancer from benign prostatic hyperplasia. Br. J. Cancer, 113(12):1712-1719.

[36]Gupta, A., Gupta, S., Mahdi, A.A., 2015. 1H NMR-derived serum metabolomics of leukoplakia and squamous cell carcinoma. Clin. Chim. Acta, 441:47-55.

[37]Huang, Z., Lin, L., Gao, Y., et al., 2011. Bladder cancer determination via two urinary metabolites: a biomarker pattern approach. Mol. Cell. Proteomics, 10:M111.007922.

[38]Ibrahim, B., Marsden, P., Smith, J.A., et al., 2013. Breath metabolomic profiling by nuclear magnetic resonance spectroscopy in asthma. Allergy, 68(8):1050-1056.

[39]Issaq, H.J., Nativ, O., Waybright, T., et al., 2008. Detection of bladder cancer in human urine by metabolomic profiling using high performance liquid chromatography/mass spectrometry. J. Urol., 179(6):2422-2426.

[40]Jahn, J.L., Giovannucci, E.L., Stampfer, M.J., 2015. The high prevalence of undiagnosed prostate cancer at autopsy: implications for epidemiology and treatment of prostate cancer in the Prostate-specific Antigen-era. Int. J. Cancer, 137(12):2795-2802.

[41]James, E.L., Parkinson, E.K., 2015. Serum metabolomics in animal models and human disease. Curr. Opin. Clin. Nutr. Metab. Care, 18(5):478-483.

[42]Jemal, A., Fedewa, S.A., Ma, J., et al., 2015. Prostate cancer incidence and PSA testing patterns in relation to USPSTF screening recommendations. JAMA, 314(19):2054-2061.

[43]Jiang, T., Lin, Y., Yin, H., et al., 2015. Correlation analysis of urine metabolites and clinical staging in patients with ovarian cancer. Int. J. Clin. Exp. Med., 8(10):18165-18171.

[44]Jobard, E., Blanc, E., Négrier, S., et al., 2015. A serum metabolomic fingerprint of bevacizumab and temsirolimus combination as first-line treatment of metastatic renal cell carcinoma. Br. J. Cancer, 113(8):1148-1157.

[45]Jung, J., Jung, Y., Bang, E.J., et al., 2014. Noninvasive diagnosis and evaluation of curative surgery for gastric cancer by using NMR-based metabolomic profiling. Ann. Surg. Oncol., 21(S4):S736-S742.

[46]Kim, K.B., Yang, J.Y., Kwack, S.J., et al., 2010. Toxicometabolomics of urinary biomarkers for human gastric cancer in a mouse model. J. Toxicol. Environ. Health A, 73:1420-1430.

[47]Kim, K.B., Yang, J.Y., Kwack, S.J., et al., 2013. Potential metabolomic biomarkers for evaluation of adriamycin efficacy using a urinary 1H-NMR spectroscopy. J. Appl. Toxicol., 33(11):1251-1259.

[48]Kim, Y., Ignatchenko, V., Yao, C.Q., et al., 2012. Identification of differentially expressed proteins in direct expressed prostatic secretions of men with organ-confined versus extracapsular prostate cancer. Mol. Cell. Proteomics, 11(12):1870-1884.

[49]Kline, E.E., Treat, E.G., Averna, T.A., et al., 2006. Citrate concentrations in human seminal fluid and expressed prostatic fluid determined via 1H nuclear magnetic resonance spectroscopy outperform prostate specific antigen in prostate cancer detection. J. Urol., 176(5):2274-2279.

[50]Klotz, L., Vesprini, D., Sethukavalan, P., et al., 2015. Long-term follow-up of a large active surveillance cohort of patients with prostate cancer. J. Clin. Oncol., 33(3):272-277.

[51]Kumar, D., Gupta, A., Mandhani, A., et al., 2015. Metabolomics-derived prostate cancer biomarkers: fact or fiction. J. Proteome Res., 14(3):1455-1464.

[52]Kumar, D., Gupta, A., Nath, K., 2016a. NMR-based metabolomics of prostate cancer: a protagonist in clinical diagnostics. Expert Rev. Mol. Diagn., 16(6):651-661.

[53]Kumar, D., Gupta, A., Mandhani, A., et al., 2016b. NMR spectroscopy of filtered serum of prostate cancer: a new frontier in metabolomics. Prostate, 76(12):1106-1119.

[54]Lin, P.H., Aronson, W., Freedland, S.J., 2015. Nutrition, dietary interventions and prostate cancer: the latest evidence. BMC Med., 13:3.

[55]Lodi, A., Tiziani, S., Khanim, F.L., et al., 2013. Proton NMR-based metabolite analyses of archived serial paired serum and urine samples from myeloma patients at different stages of disease activity identifies acetylcarnitine as a novel marker of active disease. PLoS ONE, 8:e56422.

[56]Mathé, E.A., Patterson, A.D., Haznadar, M., et al., 2014. Noninvasive urinary metabolomic profiling identifies diagnostic and prognostic markers in lung cancer. Cancer Res., 74(12):3259-3270.

[57]McDunn, J.E., Li, Z., Adam, K.P., et al., 2013. Metabolomic signatures of aggressive prostate cancer. Prostate, 73(14):1547-1560.

[58]Moller, H., Roswall, N., van Hemelrijck, M., et al., 2015. Prostate cancer incidence, clinical stage and survival in relation to obesity: a prospective cohort study in Denmark. Int. J. Cancer, 136(8):1940-1947.

[59]Motegi, H., Tsuboi, Y., Saga, A., et al., 2015. Identification of reliable components in multivariate curve resolution-alternating least squares (MCR-ALS):a data-driven approach across metabolic processes. Sci. Rep., 5(1):15710.

[60]Motta, A., Paris, D., Melck, D., et al., 2012. Nuclear magnetic resonance-based metabolomics of exhaled breath condensate: methodological aspects. J. Eur. Respir., 39(2):498-500.

[61]Moyer, V.A., 2012. Screening for prostate cancer: U.S. Preventive Services Task Force recommendation statement. Ann. Intern. Med., 157:120-134.

[62]Nagana Gowda, G.A., Raftery, D., 2015. Can NMR solve some significant challenges in metabolomics? J. Magn. Reson., 260:144-160.

[63]Neuhaus, J., Schiffer, E., von Wilcke, P., et al., 2013. Seminal plasma as a source of prostate cancer peptide biomarker candidates for detection of indolent and advanced disease. PLoS ONE, 8(6):e67514.

[64]Öman, T., Tessem, M.B., Bathen, T.F., et al., 2014. Identification of metabolites from 2D 1H-13C HSQC NMR using peak correlation plots. BMC Bioinformatics, 15:413.

[65]Pasikanti, K.K., Esuvaranathan, K., Hong, Y., et al., 2013. Urinary metabotyping of bladder cancer using two-dimensional gas chromatography time-of-flight mass spectrometry. J. Proteome Res., 12(9):3865-3873.

[66]Patel, S., Ahmed, S., 2015. Emerging field of metabolomics: big promise for cancer biomarker identification and drug discovery. J. Pharm. Biomed. Anal., 107:63-74.

[67]Prensner, J.R., Rubin, M.A., Wei, J.T., et al., 2012. Beyond PSA: the next generation of prostate cancer biomarkers. Sci. Transl. Med., 4(127):127rv3.

[68]Principe, S., Jones, E.E., Kim, Y., et al., 2013. In-depth proteomic analyses of exosomes isolated from expressed prostatic secretions in urine. Proteomics, 13:1667-1671.

[69]Roberts, M.J., Schirra, H.J., Lavin, M.F., et al., 2011. Metabolomics: a novel approach to early and noninvasive prostate cancer detection. Korean J. Urol., 52(2):79-89.

[70]Roine, A., Veskimäe, E., Tuokko, A., et al., 2014. Detection of prostate cancer by an electronic nose: a proof of principle study. J. Urol., 192(1):230-234.

[71]Ronquist, G., Brody, I., 1985. The prostasome: its secretion and function in man. Biochim. Biophys. Acta, 822(2):203-218.

[72]Salagierski, M., Schalken, J.A., 2012. Molecular diagnosis of prostate cancer: PCA3 and TMPRSS2:ERG gene fusion. J. Urol., 187(3):795-801.

[73]Salami, S.S., Schmidt, F., Laxman, B., et al., 2013. Combining urinary detection of TMPRSS2:ERG and PCA3 with serum PSA to predict diagnosis of prostate cancer. Urol. Oncol., 31(5):566-571.

[74]Schroder, F.H., Hugosson, J., Roobol, M.J., et al., 2012. Prostate-cancer mortality at 11 years of follow-up. N. Engl. J. Med., 366(11):981-990.

[75]Shipitsin, M., Small, C., Choudhury, S., et al., 2014. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error. Br. J. Cancer, 111(6):1201-1212.

[76]Siegel, R.L., Miller, K.D., Jemal, A., 2016. Cancer statistics, 2016. CA Cancer J. Clin., 66(1):7-30.

[77]Smolinska, A., Blanchet, L., Buydens, L.M., et al., 2012. NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery: a review. Anal. Chem. Acta, 750:82-97.

[78]Soininen, P., Kangas, A.J., Würtz, P., et al., 2015. Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics. Circ. Cardiovasc. Genet., 8(1):192-206.

[79]Sokolenko, S., McKay, R., Blondeel, E.J.M., et al., 2013. Understanding the variability of compound quantification from targeted profiling metabolomics of 1D-1H-NMR spectra in synthetic mixtures and urine with additional insights on choice of pulse sequences and robotic sampling. Metabolomics, 9(4):887-903.

[80]Srivastava, S., Roy, R., Singh, S., et al., 2010. Taurine—a possible fingerprint biomarker in non-muscle invasive bladder cancer: a pilot study by 1H NMR spectroscopy. Cancer Biomark., 6(1):11-20.

[81]Stephens, N.S., Siffledeen, J., Su, X., et al., 2013. Urinary NMR metabolomic profiles discriminate inflammatory bowel disease from healthy. J. Crohn’s Colitis, 7(1):e42-e48.

[82]Struck-Lewicka, W., Kordalewska, M., Bujak, R., et al., 2015. Urine metabolic fingerprinting using LC-MS and GC-MS reveals metabolite changes in prostate cancer: a pilot study. J. Pharm. Biomed. Anal., 111:351-361.

[83]Thapar, R., Titus, M.A., 2014. Recent advances in metabolic profiling and imaging of prostate cancer. Curr. Metabolomics, 2(1):53-69.

[84]Trock, B.J., 2014. Circulating biomarkers for discriminating indolent from aggressive disease in prostate cancer active surveillance. Curr. Opin. Urol., 24(3):293-302.

[85]Trovato, F.M., Tognarelli, J.M., Crossey, M.M., et al., 2015. Challenges of liver cancer: future emerging tools in imaging and urinary biomarkers. World J. Hepatol., 7(26):2664-2675.

[86]Van, Q.N., Veenstra, T.D., Issaq, H.J., 2011. Metabolic profiling for the detection of bladder cancer. Curr. Urol. Rep., 12(1):34-40.

[87]Villaseñor, A., Kinross, J.M., Li, J.V., et al., 2014. 1H NMR global metabolic phenotyping of acute pancreatitis in the emergency unit. J. Proteome Res., 13(12):5362-5375.

[88]Wang, X., Zhang, A., Sun, H., 2013. Power of metabolomics in diagnosis and biomarker discovery of hepatocellular carcinoma. Hepatology, 57(5):2072-2077.

[89]Warburg, O., 1956. On the origin of cancer cells. Science, 123(3191):309-314.

[90]Ward, J.L., Baker, J.M., Miller, S.J., et al., 2010. An inter-laboratory comparison demonstrates that [1H]-NMR metabolite fingerprinting is a robust technique for collaborative plant metabolomic data collection. Metabolomics, 6(2):263-273.

[91]Wei, J.T., Feng, Z., Partin, A.W., et al., 2014. Can urinary PCA3 supplement PSA in the early detection of prostate cancer? J. Clin. Oncol., 32(36):4066-4072.

[92]Yang, M., Vousden, K.H., 2016. Serine and one-carbon metabolism in cancer. Nat. Rev. Cancer, 16(10):650-662.

[93]Yap, I.K., Angley, M., Veselkov, K.A., et al., 2010a. Urinary metabolic phenotyping differentiates children with autism from their unaffected siblings and age-matched controls. J. Proteome Res., 9(6):2996-3004.

[94]Yap, I.K., Brown, I.J., Chan, Q., et al., 2010b. Metabolome-wide association study identifies multiple biomarkers that discriminate north and south Chinese populations at differing risks of cardiovascular disease: INTERMAP study. J. Proteome Res., 9(12):6647-6654.

[95]Zhang, J., Wei, S., Liu, L., et al., 2012. NMR-based metabolomics study of canine bladder cancer. Biochim. Biophys. Acta, 1822(11):1807-1814.

[96]Zhang, X., Xu, L., Shen, J., et al., 2013. Metabolic signatures of esophageal cancer: NMR-based metabolomics and UHPLC-based focused metabolomics of blood serum. Biochim. Biophys. Acta, 1832(8):1207-1216.

[97]Zhao, W.X., Wang, B., Zhang, L.Y., et al., 2015. Analysis on the metabolite composition of serum samples from patients with papillary thyroid carcinoma using nuclear magnetic resonance. Int. J. Clin. Exp. Med., 8(10):18013-18022.

[98]Zhou, Y., Song, R., Zhang, Z., et al., 2016. The development of plasma pseudotargeted GC-MS metabolic profiling and its application in bladder cancer. Anal. Bioanal. Chem., 408(24):6741-6749.

[99]Zhu, Y., Wang, H.K., Qu, Y.Y., et al., 2015. Prostate cancer in East Asia: evolving trend over the last decade. Asian J. Androl., 17(1):48-57.

[100]Zijlstra, C., Stoorvogel, W., 2016. Prostasomes as a source of diagnostic biomarkers for prostate cancer. J. Clin. Invest., 126(4):1144-1151.

[101]Zou, X., Holmes, E., Nicholson, J.K., et al., 2016. Automatic spectroscopic data categorization by clustering analysis (ASCLAN):a data-driven approach for distinguishing discriminatory metabolites for phenotypic subclasses. Anal. Chem., 88(11):5670-5679.

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