Metabolomics for the diagnosis of bladder cancer: A systematic review
Herney Andrés García-Perdomoab*(),Angélica María Dávila-Raigozab,Fernando Korkesc
aDivision of Urology/Urooncology, Department of Surgery, School of Medicine, Universidad del Valle, Cali, Colombia bUROGIV Research Group, School of Medicine, Universidad del Valle, Cali, Colombia cUrologic Oncology, Division of Urology, ABC Medical School, Sao Paulo, Brazil
Objective: Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various variables (tissues, serum, blood, and urine). This study aimed to identify potential biomarkers for early BCa diagnosis.
Methods: A search strategy was designed to identify clinical trials, descriptive and analytical observational studies from databases such as Medline, Embase, Cochrane Central Register of Controlled Trials, and Latin American and Caribbean Literature in Health Sciences. Inclusion criteria comprised studies involving BCa tissue, serum, blood, or urine profiling using widely adopted metabolomics techniques like mass spectrometry and nuclear magnetic resonance. Primary outcomes included description of metabolites and metabolomics profiling in BCa patients and the association of metabolites and metabolomics profiling with BCa diagnosis compared to control patients. The risk of bias was assessed using the Quality Assessment of Studies of Diagnostic Accuracy.
Results: The search strategy yielded 2832 studies, of which 30 case-control studies were included. Urine was predominantly used as the primary sample for metabolite identification. Risk of bias was often unclear inpatient selection, blinding of the index test, and reference standard assessment, but no applicability concerns were observed. Metabolites and metabolomics profiles associated with BCa diagnosis were identified in glucose, amino acids, nucleotides, lipids, and aldehydes metabolism.
Conclusion: The identified metabolites in urine included citric acid, valine, tryptophan, taurine, aspartic acid, uridine, ribose, phosphocholine, and carnitine. Tissue samples exhibited elevated levels of lactic acid, amino acids, and lipids. Consistent findings across tissue, urine, and serum samples revealed downregulation of citric acid and upregulation of lactic acid, valine, tryptophan, taurine, glutamine, aspartic acid, uridine, ribose, and phosphocholine.
. [J]. Asian Journal of Urology, 2024, 11(2): 221-241.
Herney Andrés García-Perdomo, Angélica María Dávila-Raigoza, Fernando Korkes. Metabolomics for the diagnosis of bladder cancer: A systematic review. Asian Journal of Urology, 2024, 11(2): 221-241.
-High reproducibility, straightforward sample preparation, preservation of molecular integrity, potential sample reuse, cost-effectiveness, and greater ease of identification compared to MS [14]
-Lower detectable metabolites in urine sample and lower sensitivity compared to MS [14]
-Body fluids, in vivo and in situ studies [13]
GC-MS
-Higher specificity and sensitivity, available for comparison with a standard, and can be used for both targeted and nontargeted analyses compared to NMR spectroscopy [12]
-The manipulation of low volatile molecules can present difficulties [12]
-Heat stable, volatile, medium, and low polar molecules [14]
LC-MS
-Higher specificity and sensitivity, available for comparison with a standard, and can be used for both targeted and nontargeted analyses compared to NMR spectroscopy [12,14]
-Low retention for hydrophilic molecules and no complete database to compare with a standard [14]
-Most compounds, including those that exhibit heat-lability, nonvolatility, and resistance to derivatization [12]
Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2018; 68:394e424.
doi: 10.3322/caac.v68.6
[2]
Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin 2017; 67:7e30.
doi: 10.3322/caac.v67.1
[3]
Burger M, Catto JWF, Dalbagni G, Grossman HB, Herr H, Karakiewicz P, et al. Epidemiology and risk factors of urothelial bladder cancer. Eur Urol 2013; 63:234e41.
doi: 10.1016/j.eururo.2012.07.033
pmid: 22877502
[4]
Babjuk M, Burger M, Capoun O, Cohen D, Compérat EM, Dominguez Escrig JL, et al. European Association of Urology guidelines on non-muscle-invasive bladder cancer (Ta, T1 and carcinoma in situ). Eur Urol 2020 2022;81:75e94.
[5]
Comploj E, Trenti E, Palermo S, Pycha A, Mian C. Urinary cytology in bladder cancer: why is it still relevant? Urologia 2015; 82:203e5.
doi: 10.5301/uro.5000129
pmid: 26219472
[6]
Garcia-Perdomo H, Vallejo F, Sanchez A. Metabolic profiling based on nuclear magnetic resonance spectroscopy and mass spectrometry as a tool for clinical application. Urol Sci 2019; 30:144e50.
doi: 10.4103/UROS.UROS_2_19
[7]
Issaq HJ, Nativ O, Waybright T, Luke B, Veenstra TD, Issaq EJ, et al. Detection of bladder cancer in human urine by metabolomic profiling using high performance liquid chromatography/mass spectrometry. J Urol 2008; 179:2422e6.
doi: 10.1016/j.juro.2008.01.084
pmid: 18433783
[8]
Roux A, Lison D, Junot C, Heilier JF. Applications of liquid chromatography coupled to mass spectrometry-based metabolomics in clinical chemistry and toxicology: a review. Clin Biochem 2011; 44:119e35.
doi: 10.1016/j.clinbiochem.2010.08.016
pmid: 20800591
[9]
Smolinska A, Blanchet L, Buydens LMC, Wijmenga SS. NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery: a review. Anal Chim Acta 2012; 750:82e97.
doi: 10.1016/j.aca.2012.05.049
pmid: 23062430
[10]
Gowda GAN, Zhang S, Gu H, Asiago V, Shanaiah N, Raftery D. Metabolomics-based methods for early disease diagnostics. Expert Rev Mol Diagn 2008; 8:617e33.
doi: 10.1586/14737159.8.5.617
pmid: 18785810
[11]
Nicholson J, Lindon J, Holmes E. “Metabonomics”: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 1999; 29: 1181e9.
doi: 10.1080/004982599238047
pmid: 10598751
Sethi S, Hayashi MA, Barbosa BS, Pontes JG, Tasic L, Brietzke E. Metabolomics:from fundamentals to clinical applications. In: Sussulini A, editor. Advances in Experimental Medicine and Biology, vol. 965. New York: Springer; 2017. https://doi.org/10.1007/978-3-319-47656-8.
[14]
Emwas AH. The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research. Methods Mol Biol 2015; 1277:161e93.
[15]
Ribbenstedt A, Ziarrusta H, Benskin JP. Development, characterization and comparisons of targeted and non-targeted metabolomics methods. PLoS One 2018; 13:1e18.
[16]
Roberts LD, Souza AL, Gerszten RE, Clish CB. Targeted metabolomics. Curr Protoc Mol Biol 2012; Chapter 30: Unit 30. 2.1e24. https://doi.org/10.1002/0471142727.mb3002s98.
[17]
Fiehn O. Metabolomics by gas chromatography-mass spectrometry: the combination of targeted and untargeted profiling. Curr Protoc Mol Biol 2016; 114:30e2.
[18]
Liberati A, Altman D, Tetzlaff J. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Ann Intern Med 2009; 151:W65e94. https://doi.org/10.7326/0003-4819-151-4-200908180-00136.
doi: 10.7326/0003-4819-151-4-200908180-00136
pmid: 19622512
[19]
Garcia-Perdomo HA, Dávila-Raigoza A, Korkes F. Metabolomics for the diagnosis of bladder cancer. A protocol for a systematic review. 2020. p. 1e4. https://doi.org/10.6084/m9.figshare.13271633.
[20]
Whiting PF, Rutjes AWS, Westwood ME, Mallet S, Deeks JJ, Reitsma JB, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011; 155:529e36.
doi: 10.7326/0003-4819-155-8-201110180-00009
pmid: 22007046
[21]
Srivastava S, Roy R, Singh S, Kumar P, Dalela D, Sankhwar SN, et al. Taurineda possible fingerprint biomarker in non-muscle invasive bladder cancer: a pilot study by 1H NMR spectroscopy. Cancer Biomark 2010; 6:11e20.
doi: 10.3233/CBM-2009-0115
pmid: 20164538
[22]
Pasikanti KK, Esuvaranathan K, Ho PC, Mahendran R, Kamaraj R, Wu QH, et al. Noninvasive urinary metabonomic diagnosis of human bladder cancer. J Proteome Res 2010; 9: 2988e95.
doi: 10.1021/pr901173v
pmid: 20337499
[23]
Kim JW, Lee G, Moon SM, Park MJ, Hong SK, Ahn YH, et al. Metabolomic screening and star pattern recognition by urinary amino acid profile analysis from bladder cancer patients. Metabolomics 2010; 6:202e6.
doi: 10.1007/s11306-010-0199-6
[24]
Putluri N, Shojaie A, Vasu VT, Vareed SK, Nalluri S, Putluri V, et al. Metabolomic profiling reveals potential markers and bioprocesses altered in bladder cancer progression. Cancer Res 2011; 71:7376e86.
doi: 10.1158/0008-5472.CAN-11-1154
pmid: 21990318
[25]
Huang Z, Lin L, Gao Y, Chen Y, Yan X, Xing J, et al. Bladder cancer determination via two urinary metabolites: a biomarker pattern approach. Mol Cell Proteomics 2011; 10: M111.007922. https://doi.org/10.1074/mcp.M111.007922.
[26]
Gamagedara S, Shi H, Ma Y. Quantitative determination of taurine and related biomarkers in urine by liquid chromatography-tandem mass spectrometry. Anal Bioanal Chem 2012; 402:763e70.
doi: 10.1007/s00216-011-5491-4
pmid: 22038588
[27]
Cao M, Zhao L, Chen H, Xue W, Lin D. NMR-based metabolomic analysis of human bladder cancer. Anal Sci 2012; 28:451e6.
pmid: 22687923
[28]
Lin L, Huang Z, Gao Y, Chen Y, Hang W, Xing J, et al. LC-MSbased serum metabolic profiling for genitourinary cancer classification and cancer type-specific biomarker discovery. Proteomics 2012; 12:2238e46.
doi: 10.1002/pmic.201200016
pmid: 22685041
[29]
Pasikanti KK, Esuvaranathan K, Hong Y, Ho PC, Mahendran R, Raman Nee Mani L, et al. Urinary metabotyping of bladder cancer using two-dimensional gas chromatography time-offlight mass spectrometry. J Proteome Res 2013; 12:3865e73.
doi: 10.1021/pr4000448
pmid: 23885889
[30]
Bansal N, Gupta A, Mitash N, Shakya PS, Mandhani A, Mahdi AA, et al. Low- and high-grade bladder cancer determination via human serum-based metabolomics approach. J Proteome Res 2013; 12:5839e50.
doi: 10.1021/pr400859w
pmid: 24219689
[31]
Huang Z, Chen Y, Hang W, Gao Y, Lin L, Li DY, et al. Holistic metabonomic profiling of urine affords potential early diagnosis for bladder and kidney cancers. Metabolomics 2013; 9: 119e29.
doi: 10.1007/s11306-012-0433-5
[32]
Jobu K, Sun C, Yoshioka S, Yokota J, Onogawa M, Kawada C, et al. Metabolomics study on the biochemical profiles of odor elements in urine of human with bladder cancer. Biol Pharm Bull 2012; 35:639e42.
pmid: 22466574
[33]
Jin X, Yun SJ, Jeong P, Kim IY, Kim WJ, Park S. Diagnosis of bladder cancer and prediction of survival by urinary metabolomics. Oncotarget 2014; 5:1635e45.
doi: 10.18632/oncotarget.1744
pmid: 24721970
[34]
Peng J, Chen YT, Chen CL, Li L. Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urinemetabolite- biomarker discovery. Anal Chem 2014; 86: 6540e7.
doi: 10.1021/ac5011684
pmid: 24877652
[35]
Tripathi P, Somashekar BS, Ponnusamy M, Gursky A, Dailey S, Kunju P, et al. HR-MAS NMR tissue metabolomic signatures cross-validated by mass spectrometry distinguish bladder cancer from benign disease. J Proteome Res 2013; 12: 3519e28.
doi: 10.1021/pr4004135
pmid: 23731241
[36]
Wittmann BM, Stirdivant SM, Mitchell MW, Wulff JE, McDunn JE, Li Z, et al. Bladder cancer biomarker discovery using global metabolomic profiling of urine. PLoS One 2014; 9: 1e19.
[37]
Shen C, Sun Z, Chen D, Su X, Jiang J, Li G, et al. Developing urinary metabolomic signatures as early bladder cancer diagnostic markers. Omi A J Integr Biol 2015; 19:1e11.
[38]
Zhou Y, Song R, Zhang Z, Lu X, Zeng Z, Hu C, et al. The development of plasma pseudotargeted GC-MS metabolic profiling and its application in bladder cancer. Anal Bioanal Chem 2016; 408:6741e9.
doi: 10.1007/s00216-016-9797-0
pmid: 27473428
[39]
Tan G, Wang H, Yuan J, Qin W, Dong X, Wu H, et al. Three serum metabolite signatures for diagnosing low-grade and high-grade bladder cancer. Sci Rep 2017; 7:1e11.
doi: 10.1038/s41598-016-0028-x
[40]
Shao CH, Chen CL, Lin JY, Chen CJ, Fu SH, Chen YT, et al. Metabolite marker discovery for the detection of bladder cancer by comparative metabolomics. Oncotarget 2017; 8: 38802e10.
doi: 10.18632/oncotarget.v8i24
[41]
Yumba Mpanga A, Siluk D, Jacyna J, Szerkus O, Wawrzyniak R, Markuszewski M, et al. Targeted metabolomics in bladder cancer: from analytical methods development and validation towards application to clinical samples. Anal Chim Acta 2018; 1037:188e99.
doi: S0003-2670(18)30160-0
pmid: 30292293
[42]
Cheng X, Liu X, Liu X, Guo Z, Sun H, Zhang M, et al. Metabolomics of non-muscle invasive bladder cancer: biomarkers for early detection of bladder cancer. Front Oncol 2018; 8:1e11.
doi: 10.3389/fonc.2018.00001
[43]
Jacyna J, Wawrzyniak R, Balayssac S, Gilard V, Malet-Martino M, Sawicka A, et al. Urinary metabolomic signature of muscle-invasive bladder cancer: a multiplatform approach. Talanta 2019; 202:572e9.
doi: S0039-9140(19)30523-5
pmid: 31171223
[44]
Wei Y, Wang M, Liu H, Niu Y, Wang S, Zhang F, et al. Simultaneous determination of seven endogenous aldehydes in human blood by headspace gas chromatography-mass spectrometry. J Chromatogr B Anal Technol Biomed Life Sci 2019; 1118e1119:85e92.
[45]
Loras A, Suárez-Cabrera C, Martínez-Bisbal MC, Quintás G, Paramio JM, Martínez-Má?ez R, et al. Integrative metabolomic and transcriptomic analysis for the study of bladder cancer. Cancers (Basel) 2019;11:686. https://doi.org/10.3390/cancers11050686.
[46]
Lin JY, Juo BR, Yeh YH, Fu SH, Chen YT, Chen CL, et al. Putative markers for the detection of early-stage bladder cancer selected by urine metabolomics. BMC Bioinformatics 2021; 22: 305. https://doi.org/10.1186/s12859-021-04235-z.
doi: 10.1186/s12859-021-04235-z
[47]
?uczykowski K, Warmuzińska N, Operacz S, Stryjak I, Bogusiewicz J, Jacyna J, et al. Metabolic evaluation of urine from patients diagnosed with high grade (HG) bladder cancer by SPME-LC-MS method. Molecules 2021;26:2194. https://doi.org/10.3390/molecules26082194.
[48]
Pinto J, Carapito ?, Amaro F, Lima AR, Carvalho-Maia C, Martins MC, et al. Discovery of volatile biomarkers for bladder cancer detection and staging through urine metabolomics. Metabolites 2021; 11:199. https://doi.org/10.3390/metabo11040199.
doi: 10.3390/metabo11040199
[49]
Li J, Cheng B, Xie H, Zhan C, Li S, Bai P. Bladder cancer biomarker screening based on non-targeted urine metabolomics. Int Urol Nephrol 2022; 54:23e9.
doi: 10.1007/s11255-021-03080-6
[50]
Jacyna J, Kordalewska M, Artymowicz M, Markuszewski M, Matuszewski M, Markuszewski MJ. Pre- and post-resection urine metabolic profiles of bladder cancer patients: results of preliminary studies on time series metabolomics analysis. Cancers (Basel) 2022; 14:1210. https://10.3390/cancers14051210.
doi: 10.3390/cancers14051210
Moffatt BA, Ashihara H. Purine and pyrimidine nucleotide synthesis and metabolism. Arab B 2002; 1:e0018. https://doi.org/10.1199/tab.0018.
[55]
O’Brien P, Siraki A, Shangari N. Aldehyde sources, metabolism, molecular toxicity mechanisms, and possible effects on human health. Crit Rev Toxicol 2005; 35:609e62.
doi: 10.1080/10408440591002183
pmid: 16417045
[56]
Toyokuni S, Okamoto K, Yodoi J, Hiai H. Persistent oxidative stress in cancer. FEBS Lett 1995;358:1e3.
[57]
Ashrafian H, Sounderajah V, Glen R, Ebbels T, Blaise BJ, Kalra D, et al. Metabolomics: the stethoscope for the twentyfirst century. Med Princ Pract 2021; 30:301e10.
doi: 10.1159/000513545
[58]
Spratlin JL, Serkova NJ, Eckhardt SG. Clinical applications of metabolomics in oncology: a review. Clin Cancer Res 2009; 15: 431e40.
doi: 10.1158/1078-0432.CCR-08-1059
pmid: 19147747
[59]
Inglese P, McKenzie JS, Mroz A, Kinross J, Veselkov K, Holmes E, et al. Deep learning and 3D-DESI imaging reveal the hidden metabolic heterogeneity of cancer. Chem Sci 2017; 8: 3500e11.
doi: 10.1039/c6sc03738k
pmid: 28507724
[60]
Tenori L, Oakman C, Claudino WM, Bernini P, Cappadona S, Nepi S, et al. Exploration of serum metabolomic profiles and outcomes in women with metastatic breast cancer: a pilot study. Mol Oncol 2012; 6:437e44.
doi: 10.1016/j.molonc.2012.05.003
pmid: 22687601
[61]
Mauri-Capdevila G, Jove M, Suarez-Luis I, Portero-Otin M, Purroy F. [Metabolomics in ischaemic stroke, new diagnostic and prognostic biomarkers]. Rev Neurol 2013; 57:29e36. [Article in Spanish].
pmid: 23799599
[62]
Wang TJ, Ngo D, Psychogios N, Dejam A, Larson MG, Vasan RS, et al. 2-Aminoadipic acid is a biomarker for diabetes risk. J Clin Invest 2013; 123:4309e17.
doi: 10.1172/JCI64801
pmid: 24091325
[63]
Kim WT, Yun SJ, Yan C, Jeong P, Kim YH, Lee IS, et al. Metabolic pathway signatures associated with urinary metabolite biomarkers differentiate bladder cancer patients from healthy controls. Yonsei Med J 2016; 57:865e71.
doi: 10.3349/ymj.2016.57.4.865
pmid: 27189278
[64]
Cheng Y, Yang X, Deng X, Zhang X, Li P, Tao J, et al. Metabolomics in bladder cancer: a systematic review. Int J Clin Exp Med 2015; 8:11052e63.
pmid: 26379905
[65]
Liberti MV, Locasale JW. The Warburg effect: how does it benefit cancer cells? Trends Biochem Sci 2016; 41:211e8.
doi: S0968-0004(15)00241-8
pmid: 26778478
[66]
Massari F, Ciccarese C, Santoni M, Iacovelli R, Mazzucchelli R, Piva F, et al. Metabolic phenotype of bladder cancer. Cancer Treat Rev 2016; 45:46e57.
doi: 10.1016/j.ctrv.2016.03.005
pmid: 26975021
[67]
Jin L, Alesi GN, Kang S. Glutaminolysis as a target for cancer therapy. Oncogene 2016; 35:3619e25.
doi: 10.1038/onc.2015.447
pmid: 26592449
[68]
Chung K, Gadupudi GS. Possible roles of excess tryptophan metabolites in cancer. Environ Mol Mutagen 2011; 52:81e104.
doi: 10.1002/em.v52.2
[69]
Lee SH, Mahendran R, Tham SM, Thamboo TP, Chionh BJ, Lim YX, et al. Tryptophan-kynurenine ratio as a biomarker of bladder cancer. BJU Int 2021; 127:445e53.
doi: 10.1111/bju.v127.4
[70]
Pilotte L, Larrieu P, Stroobant V, Colau D, Dolusic E, Frédérick R, et al. Reversal of tumoral immune resistance by inhibition of tryptophan 2,3-dioxygenase. Proc Natl Acad Sci U S A 2012;109:2497e502.
[71]
Long J, Zhang CJ, Zhu N, Du K, Yin YF, Tan X, et al. Lipid metabolism and carcinogenesis, cancer development. Am J Cancer Res 2018; 8:778e91.
pmid: 29888102
[72]
Wang G, Cao R, Ge Q, Xiao Y, Wang X. The role of lipids metabolism in bladder cancer. Cancer Res 2017; 77:2511. https://doi.org/10.1158/1538-7445.AM2017-2511.
doi: 10.1158/1538-7445.AM2017-2511
[73]
Serrano M, Gallego M, Silva M. Analysis of endogenous aldehydes in human urine by static headspace gas chromatographymass spectrometry. J Chromatogr A 2016; 1437:241e6.
doi: S0021-9673(16)30026-7
pmid: 26879451
[74]
Crowder SL, Playdon MC, Gudenkauf LM, Ose J, Gigic B, Greathouse L, et al. A molecular approach to understanding the role of diet in cancer-related fatigue: challenges and future opportunities. Nutrients 2022; 14: 1e14.
doi: 10.3390/nu14010001
[75]
Wang Y, Hodge RA, Stevens VL, Hartman TJ, McCullough ML. Identification and reproducibility of urinary metabolomic biomarkers of habitual food intake in a cross-sectional analysis of the cancer prevention study-3 diet assessment substudy. Metabolites 2021; 11:248. https://doi.org/10.3390/metabo11040248.
doi: 10.3390/metabo11040248