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Metabolomics in urogenital cancer

    Renata Bujak

    Department of Toxicology, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, M Curie-Skłodowskiej 9, 85-094 Bydgoszcz, Poland

    ,
    Emilia Daghir

    Department of Toxicology, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, M Curie-Skłodowskiej 9, 85-094 Bydgoszcz, Poland

    ,
    Joanna Rybka

    Department of Biochemistry, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Bydgoszcz, Poland

    ,
    Piotr Koslinski

    Department of Toxicology, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, M Curie-Skłodowskiej 9, 85-094 Bydgoszcz, Poland

    &
    Michał Jan Markuszewski

    † Author for correspondence

    Department of Biopharmaceutics & Pharmacodynamics, Medical University of Gdańsk, Al. Gen. Hallera 107, 80-416 Gdańsk, Poland.

    Published Online:https://doi.org/10.4155/bio.11.43

    Although in recent decades the development of many drugs against cancer has been witnessed, the morbidity and mortality for the most prevalent urogenital cancer have not been significantly reduced. A key task in cancer medicine is to detect the disease as early as possible. In order to achieve this, many new technologies have been developed for cancer biomarker discovery. Monitoring fluctuations of certain metabolite levels in body fluids, such as urine, has become an important way to detect early stages in carcinogenesis. Moreover metabolomic approaches are likely to be used to screen for potential diagnostic and prognostic biomarkers of urogenital cancer. In future work, these potential biomarkers should be further validated with a large enough patient cohort to achieve earlier diagnosis not only of urogenital cancer, but also other malignancies. Moreover, the improvement of patient prognosis will be another aim of such investigations. This novel metabolomic approach has the potential to provide more information about the pathophysiological status of an organism and distinguish precancerous and cancerous stages.

    Papers of special note have been highlighted as: ▪ of interest ▪▪ of considerable interest

    Bibliography

    • Spratlin JL, Serkova NJ, Ekhardt SG. Clinical applications of metabolomics in oncology: a review. Clin. Cancer Res.15,431–440 (2009).▪▪ Comprehensive overview about clinical applications of metabolomics in oncology.
    • Van QV, Veenstra TD. How close is the bench to the bedside? Metabolic profiling in cancer research. Genome Medicine5,1–6 (2009).
    • Ma Y, Liu G, Du M et al. Recent development in the determination of urinary cancer biomarkers by capillary electrophoresis. Electrophoresis25,1473–1484 (2004).
    • Melichar B, Solichova D, Svobodova I et al. Neopterin in renal cell carcinoma inhalational administration of interleukin-2 is not accompanied by a rise of urinary neopterin. Luminescence20,310–314 (2005).
    • Seidel A, Brunner S, Seidel P et al. Modified nucleosides: an accurate tumor marker for clinical diagnosis of cancer, early detection therapy control. Br. J. Cancer.94,1726–1733 (2006).
    • Byun JA, Lee SH, Choi MH et al. Analysis of polyamines as carbamonyl derivaties in urine and serum by liquid chromatography-tandem mass spectrometry. Biomed. Chromatogr.22,73–80 (2008).
    • Szymańska E, Markuszewski MJ, Markuszewski M, Kaliszan R. Altered levels of nucleoside metabolite profiles in urogenital tract cancer measured by capillary electrophoresis J. Pharm. Biomed. Anal.53,1305–1312 (2010).
    • Denkart C, Budczeis J, Kind T et al. Mass spectrometry-based metabolic profiling reveals. Different metabolite patterns in invasiwe ovarian carcinomas and ovarian borderline tumors. Cancer Res.66,10795–10804 (2006).
    • Kind T, Tolstikov V, Fiehn O et al. A comprehensive urinary metabolomic approaches for identifying kidney. Cancer Anal. Biochem.363,185–195 (2007).
    • 10  Ramautar R, Somsen GW, de Jong GJ. CE–MS in metabolomics. Electrophoresis30(1),276–291 (2009).
    • 11  Monton MRN, Soga T. Metabolome analysis by capillary electrophoresis-mass spectrometry. J. Chromatogr. A1168(1–2),237–246 (2007).
    • 12  Lindon JC, Holmes E, Bollard ME, Stanley EG, Nicholson JK. Metabonomics technologies and their applications in physiological monitoring, and drug safety assessment and disease diagnosis. Biomarkers9(1),1–31 (2004).
    • 13  Shockcor JP, Holmes E. Metabonomic applications in toxicity screening and disease diagnosis. Curr. Top. Med. Chem.2(1),35–51 (2002).
    • 14  Lenz EM, Wilson ID. Analytical strategies in metabonomics. J. Proteome Res.6(2),443–458 (2007).▪▪ Excellent overview of NMR-based metabolomic applications.
    • 15  Coen M. A metabonomic approach for mechanistic exploration of pre-clinical toxicology. Toxicology278(3),326–340 (2010).▪ Excellent overview of calculation methods in metabolomics.
    • 16  Dunn WB, Bailey NJC, Johnson HE. Measuring the metabolome: current analytical technologies. Analyst130(5),606–625 (2005).
    • 17  Lindon JC, Holmes E, Nicholson JK. Metabonomics in pharmaceutical R & D. FEBS J.274(5),1140–1151 (2007).
    • 18  Nordstorm A, Lewensohn R. Metabolomics: moving to the clinic. J. Neuroimmune Pharmacol.5(1),4–17 (2010).
    • 19  Wen H, Yoo SS, Kang J et al. A new NMR-based metabolomics approach for the diagnosis of biliary tract cancer. Hepatol.52(2),228–233 (2010).
    • 20  Lewis IA, Schommer SC, Markley JL. rNMR: open source software for identifying and quantifying metabolites in NMR spectra. Magn. Reson. Chem.47(1),123–126 (2009).
    • 21  Giavalisco P, Kohl K, Hummel J, Bettina B, Willmitzer L. 13C isotope-labeled metabolomes allowing for improved compound annotation and relative quantification in liquid chromatography-mass spectrometry-based metabolomic research. Anal. Chem.81,6546–6551 (2009).
    • 22  Brennan L. Personalised nutrition. Metabolomic applications in nutritional research. Proc. Nutr. Soc.67(4),404–408 (2008).▪ Comprehensive overview of MS applications in metabolomics studies.
    • 23  Coen M, Holmes E, Lindon JC, Nicholson JK. NMR-based metabolic profiling and metabonomic approaches to problems in molecular toxicology. Chem. Res. Toxicol.21(1),9–27 (2008).
    • 24  Xiayan L, Legido-Quigley C. Advances in separation science applied to metabonomics. Electrophoresis29(18),3724–3736 (2008).
    • 25  Goodacre R, Vaidyanathan S, Dunn WB, Harrigan GG, Kell DB. Metabolomics by numbers:acquiring and understanding global metabolite data. Trends Biotechnol.22(5),245–252 (2004).
    • 26  Servais AC, Crommen J, Fillet M. Capillary electrophoresis-mass spectrometry, an attractive tool for drug bioanalysis and biomarker discovery. Electrophoresis27(13),2616–2629 (2006).
    • 27  Xie G, Su M, Li P et al. Analysis of urinary metabolites for metabolomic study by pressurized CEC. Electrophoresis28(23),4459–4468 (2007).
    • 28  O’Shaughnessy M, Konety B, Warlick C Prostate cancer screening: issues and controversies. Minn. Med.93(8),39–44 (2010).▪ Excellent overview of the role of metabolomic approach in diagnosis and prognosis of prostate cancer.
    • 29  Schorge JO, Modesitt SC, Coleman RL et al. SGO White Paper on ovarian cancer: etiology, screening and surveillance. Gynecol. Oncol.119(1),7–17 (2010).
    • 30  Jha AK, Jha J, Bista R et al. A scenario of cervical carcinoma in a cancer hospital. JNMAJ Nepal Med. Assoc.48(175),199–202 (2009).
    • 31  Arbyn M, Raifu AO, Weiderpass E, Bray F, Anttila A. Trends of cervical cancer mortality in the member states of the European Union. Eur. J. Cancer.45(15),2640–2648 (2009).
    • 32  Kakehi Y, Hirao Y, Kim W et al. Bladder Cancer Working Group report. Jpn. J. Clin. Oncol.40(Suppl. 1),57–64 (2010).
    • 33  Herman MP, Svatek RS, Lotan Y, Karakiewizc PI, Shariat SF. Urine-based biomarkers for the early detection and surveillance of non-muscle invasive bladder cancer. Minerva Urol. Nefrol.60(4),217–235 (2008).
    • 34  Naito S, Tomita Y, Rha SY et al. Kidney Cancer Working Group report. Jpn. J. Clin. Oncol.40(Suppl. 1),i51–i56 (2010).
    • 35  Osl M, Dreiseitl S, Pfeifer B et al. A new rule-based algorithm for identifying metabolic markers in prostate cancer using tandem mass spectrometry. Bioinformatics24(24),2908–2914 (2008).
    • 36  Goodacre R. Metabolomics of a superorganism. J. Nutr.137(Suppl. 1),259S–266S (2007).
    • 37  Griffin JL, Shockcor JP. Metabolic profiles of cancer cells. Nat. Rev. Cancer.4(7),551–561 (2004).
    • 38  Seidel A, Brunner S, Seidel P, Fritz GI, Herbarth O. Modified nucleosides: an accurate tumor marker for clinical diagnosis of cancer, early detection and therapy control. Br. J. Cancer94(11),1726–1733 (2006).
    • 39  Szymańska E, Markuszewski MJ, Bodzioch K, Kaliszan R. Development and validation of urinary nucleosides and creatinine assay by capillary electrophoresis with solid-phase extraction. J. Pharm. Biomed. Anal.44(5),1118–1126 (2007).
    • 40  Szymańska E, Markuszewski MJ, Markuszewski M, Kaliszan R. Altered levels of nucleoside metabolite profiles on urogenital tract cancer measured by capillary electrophoresis. J. Pharm. Biomed. Anal.53(5),1305–1312 (2010).
    • 41  Theodorescu D, Wittke S, Ross MM et al. Discovery and validation of new protein biomarkers for urothelial cancer: a prospective analysis. Lancet Oncol.7(3),230–240 (2006).▪▪ Comperhensive overview of metabolomic biomarkers in urothelial cancer.
    • 42  Odunsi K, Wollman RM, Ambrosone CB et al. Detection of epithelial ovarian cancer using 1H-NMR-based metabonomics. Int. J. Cancer.113(5),782–788 (2005).
    • 43  Jordan KW, Cheng LL. NMR-based metabolomics approach to target biomarkers for human prostate cancer. Expert Rev. Proteomics.4(3),389–400 (2007).
    • 44  Serkova NJ, Gamito EJ, Jones RH et al. The metabolites citrate, myo-inositol, and spermine are potential age-independent markers of prostate cancer in human expressed prostatic secretions. Prostate68(6),620–628 (2008).
    • 45  Mueller-Lisse UG, Scherr MK. Proton MR spectroscopy of the prostate. Eur. J. Radiol.63(3),351–360 (2007).
    • 46  Lyng H, Sitter B, Bathen TF et al. Metabolic mapping by use of high-resolution magic angle spinning 1H MR spectroscopy for assessment of apoptosis in cervical carcinomas. BMC Cancer7,11 (2007).
    • 47  Gao H, Dong B, Liu X et al. Metabonomic profiling of renal cell carcinoma: high resolution proton nuclear magnetic resonance spectroscopy of human serum with multivariate data analysis. Anal. Chim. Acta.624(2),269–277 (2008).
    • 48  Kim K, Aronov P, Zakharkin SO et al. Urine metabolomics analysis for kidney cancer detection and biomarker discovery. Mol. Cell Proteomics.8(3),558–570 (2009).
    • 49  Issaq HJ, Nativ O, Waybright T et al. Detection of bladder cancer in human urine by metabolomic profiling using high performance liquid chromatography/mass spectrometry. J. Urol.179(6),2422–2426 (2008).
    • 50  Guan W, Zhou M, Hampton CY et al. Ovarian cancer detection from metabolomic liquid chromatography/mass spectrometry data by support vector machines. BMC Bioinformatics10,259 (2009).
    • 51  Avril N, Sassen S, Schmalfeldt B et al. Prediction of response to neoadjuvant chemotherapy by sequential F-18-fluorodeoxyglucose positron emission tomography in patients with advanced-stage ovarian cancer. J. Clin. Oncol.23(30),7445–7453 (2005).
    • 52  Mutch D, Markman M. A case report demonstrating unambiguous clinical utility of PET/CT scanning in recurrent ovarian cancer. Case Rep. Oncol.2(2),121–124 (2009).
    • 53  Pucar D, Koutcher JA, Shah A et al. Preliminary assessment of magnetic resonance spectroscopic imaging in predicting treatment outcome in patients with prostate cancer at high risk for relapse. Clin. Prostate Cancer3(3),174–181 (2004).
    • 54  Nordström A, Lewensohn R. Metabolomics: moving to the clinic. J. Neuroimmune Pharmacol.5(1),4–17 (2009).
    • 55  Oldiges M, Lutz S, Pflug S et al. Metabolomics: current state and evolving methodologies and tools. Appl. Microbiol. Biotechnol.76,495–511 (2007).
    • 56  Boros LG, Lerner MR. D-glucose profiles of serum, liver, pancreas, and DMBA-induced pancreatic tumors of rats. Pancreas32,337–343 (2005).
    • 57  Weisberg E, Wright RD, Jiang J. Effects of PKC 412, nilotinib, and imatinib against GIST-associated PDGFRA mutants with differential imatinib sensitivity. Gastroenterology131,1734–1742 (2006).
    • 58  Serkova NJ, Niemann CU. Pattern recognition and biomarker validation using quantitative 1H-NMR-based metabolomics. Expert Rev. Mol. Diagn.6,717–731 (2006).