Advertisement

Application of Urinary Volatile Organic Compounds (VOCs) for the Diagnosis of Prostate Cancer

Published:February 15, 2019DOI:https://doi.org/10.1016/j.clgc.2019.02.003

      Abstract

      Background

      Prostate cancer (PCa) screening using serum prostate-specific antigen (PSA) testing has caused unnecessary biopsies and overdiagnosis owing to its low accuracy and reliability. Therefore, there is an increased interest in identifying better PCa biomarkers. Studies showed that trained dogs can discriminate patients with PCa from unaffected men by sniffing urine. We hypothesized that urinary volatile organic compounds (VOCs) may be the source of that odor and could be used to develop urinary VOC PCa diagnosis models.

      Patients and Methods

      Urine samples from 55 and 53 biopsy proven PCa-positive and -negative patients respectively were initially obtained for diagnostic model development. Urinary metabolites were analyzed by gas chromatography-mass spectrometry. A PCa diagnosis model was developed and validated using innovative statistical machine-learning techniques. A second set of samples (53 PCa-positive and 22 PCa-negative patients) were used to evaluate the previously developed PCa diagnosis model.

      Results

      The analysis resulted in 254 and 282 VOCs for their significant association (P < .05) with either PCa-positive or -negative samples respectively. Regularized logistic regression analysis and the Firth method were then applied to predict PCa prevalence, resulting in a final model that contains 11 VOCs. Under cross-validation, the area under the receiver operating characteristic curve (AUC) for the final model was 0.92 (sensitivity, 0.96; specificity, 0.80). Further evaluation of the developed model using a testing cohort yielded an AUC of 0.86. As a comparison, the PSA-based diagnosis model only rendered an AUC of 0.54.

      Conclusion

      The study describes the development of a urinary VOC-based model for PCa detection.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Clinical Genitourinary Cancer
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Siegel R.L.
        • Miller K.D.
        • Jemal A.
        Cancer statistics, 2018.
        CA Cancer J Clin. 2018; 68: 7-30
        • Moyer V.A.
        • U.S. Preventive Services Task Force
        Screening for prostate cancer: U.S. Preventive Services Task Force recommendation statement.
        Ann Intern Med. 2012; 157: 120-134
        • Ekwueme D.U.
        • Stroud L.A.
        • Chen Y.
        Cost analysis of screening for, diagnosing, and staging prostate cancer based on a systematic review of published studies.
        Prev Chronic Dis. 2007; 4: A100
        • Aubry W.
        • Lieberthal R.
        • Willis A.
        • Bagley G.
        • Willis III, S.M.
        • Layton A.
        Budget impact model: epigenetic assay can help avoid unnecessary repeated prostate biopsies and reduce healthcare spending.
        Am Health Drug Benefits. 2013; 6: 15-24
        • Van Neste L.
        • Herman J.G.
        • Otto G.
        • Bigley J.W.
        • Epstein J.I.
        • Van Criekinge W.
        The epigenetic promise for prostate cancer diagnosis.
        Prostate. 2012; 72: 1248-1261
        • Simon H.B.
        What’s the downside to a biopsy? Prostate Knowledge, Harvard Medical School publications.
        (Available at:)
        • Hanahan D.
        • Weinberg R.A.
        Hallmarks of cancer: the next generation.
        Cell. 2011; 144: 646-674
        • Silva C.L.
        • Passos M.
        • Câmara J.S.
        Solid phase microextraction, mass spectrometry and metabolomic approaches for detection of potential urinary cancer biomarkers—a powerful strategy for breast cancer diagnosis.
        Talanta. 2012; 89: 360-368
        • Willis C.M.
        • Church S.M.
        • Guest C.M.
        • et al.
        Olfactory detection of human bladder cancer by dogs: proof of principle study.
        BMJ. 2004; 329: 712
        • Cornu J.-N.
        • Cancel-Tassin G.
        • Ondet V.
        • Girardet C.
        • Cussenot O.
        Olfactory detection of prostate cancer by dogs sniffing urine: a step forward in early diagnosis.
        Eur Urol. 2011; 59: 197-201
        • Taverna G.
        • Tidu L.
        • Grizzi F.
        • et al.
        Olfactory system of highly trained dogs detects prostate cancer in urine samples.
        J Urol. 2015; 193: 1382-1387
        • Sonoda H.
        • Kohnoe S.
        • Yamazato T.
        • et al.
        Colorectal cancer screening with odour material by canine scent detection.
        Gut. 2011; 60: 814-819
        • Matsumura K.
        • Opiekun M.
        • Oka H.
        • et al.
        Urinary volatile compounds as biomarkers for lung cancer: a proof of principle study using odor signatures in mouse models of lung cancer.
        PLoS One. 2010; 5: e8819
        • Amann A.
        • de Lacy Costello B.
        • Miekisch W.
        • et al.
        The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva.
        J Breath Res. 2014; 8: 034001
        • Amann A.
        • Smith D.
        Volatile Biomarkers: Non-invasive Diagnosis in Physiology and Medicine.
        Elsevier, Oxford2013
        • Nakhleh M.K.
        • Amal H.
        • Jeries R.
        • et al.
        Diagnosis and classification of 17 diseases from 1404 subjects via pattern analysis of exhaled molecules.
        ACS Nano. 2016; 11: 112-125
        • Khalid T.
        • Aggio R.
        • White P.
        • et al.
        Urinary volatile organic compounds for the detection of prostate cancer.
        PLoS One. 2015; 10: e0143283
        • Fan J.
        • Lv J.
        Sure independence screening for ultrahigh dimensional feature space.
        J R Stat Soc Series B Stat Methodol. 2008; 70: 849-911
        • Tibshirani R.
        Regression shrinkage and selection via the lasso.
        J R Stat Soc Series B Stat Methodol. 1996; 58: 267-288
        • Kleinbaum D.G.
        • Klein M.
        Logistic Regression, A Self-learning Text.
        3rd Edition. Springer, Berlin2010
        • Firth D.
        Bias reduction of maximum likelihood estimates.
        Biometrika. 1993; 80: 27-38
        • López-Ratón M.
        • Rodríguez-Álvarez M.X.
        • Cadarso-Suárez C.
        • Gude-Sampedro F.
        OptimalCutpoints: an R package for selecting optimal cutpoints in diagnostic tests.
        J Stat Softw. 2014; 61: 1-36
        • The R Development Core Team
        R: A Language and Environment for Statistical Computing.
        R Foundation for Statistical Computing, Vienna, Austria2017
        • Chistiakov D.A.
        • Myasoedova V.A.
        • Grechko A.V.
        • Melnichenko A.A.
        • Orekhov A.N.
        New biomarkers for diagnosis and prognosis of localized prostate cancer.
        Semin Cancer Biol. 2018; 52: 9-16
        • Parekh D.J.
        • Punnen S.
        • Sjoberg D.D.
        • et al.
        A multi-institutional prospective trial in the USA confirms that the 4Kscore accurately identifies men with high-grade prostate cancer.
        Eur Urol. 2015; 68: 464-470
        • Leyten G.H.
        • Hessels D.
        • Jannink S.A.
        • et al.
        Prospective multicentre evaluation of PCA3 and TMPRSS2-ERG gene fusions as diagnostic and prognostic urinary biomarkers for prostate cancer.
        Eur Urol. 2014; 65: 534-542
        • Chun F.K.
        • de la Taille A.
        • Van Poppel H.
        • et al.
        Prostate cancer gene 3 (PCA3): development and internal validation of a novel biopsy nomogram.
        Eur Urol. 2009; 56: 659-668
        • Loeb S.
        • Catalona W.J.
        The Prostate Health Index: a new test for the detection of prostate cancer.
        Ther Adv Urol. 2014; 6: 74-77
        • Wojno K.J.
        • Costa F.J.
        • Cornell R.J.
        • et al.
        Reduced rate of repeated prostate biopsies observed in ConfirmMDx clinical utility field study.
        Am Health Drug Benefits. 2014; 7: 129-134
        • Klein E.A.
        • Chait A.
        • Hafron J.M.
        • et al.
        The single-parameter, structure-based IsoPSA assay demonstrates improved diagnostic accuracy for detection of any prostate cancer and high-grade prostate cancer compared to a concentration-based assay of total prostate-specific antigen: a preliminary report.
        Eur Urol. 2017; 72: 942-949
        • Hessels D.
        • Smit F.P.
        • Verhaegh G.W.
        • Witjes J.A.
        • Cornel E.B.
        • Schalken J.A.
        Detection of TMPRSS2-ERG fusion transcripts and prostate cancer antigen 3 in urinary sediments may improve diagnosis of prostate cancer.
        Clin Cancer Res. 2007; 13: 5103-5108
        • Tomlins S.A.
        • Laxman B.
        • Varambally S.
        • et al.
        Role of the TMPRSS2-ERG gene fusion in prostate cancer.
        Neoplasia. 2008; 10: 177-188
        • Stewart G.D.
        • Van Neste L.
        • Delvenne P.
        • et al.
        Clinical utility of an epigenetic assay to detect occult prostate cancer in histopathologically negative biopsies: results of the MATLOC study.
        J Urol. 2013; 189: 1110-1116
        • Trock B.J.
        Application of metabolomics to prostate cancer.
        Urol Oncol. 2011; 29: 572-581
        • Corbin J.M.
        • Ruiz-Echevarría M.J.
        One-carbon metabolism in prostate cancer: the role of androgen signaling.
        Int J Mol Sci. 2016; 17: 1208
        • Menendez J.A.
        • Lupu R.
        Fatty acid synthase and the lipogenic phenotype in cancer pathogenesis.
        Nat Rev Cancer. 2007; 7: 763-777
        • Swinnen J.V.
        • Brusselmans K.
        • Verhoeven G.
        Increased lipogenesis in cancer cells: new players, novel targets.
        Curr Opin Clin Nutr Metab Care. 2006; 9: 358-365
        • Igal R.A.
        Stearoyl-CoA desaturase-1: a novel key player in the mechanisms of cell proliferation, programmed cell death and transformation to cancer.
        Carcinogenesis. 2010; 31: 1509-1515
        • Crowe F.L.
        • Allen N.E.
        • Appleby P.N.
        • et al.
        Fatty acid composition of plasma phospholipids and risk of prostate cancer in a case-control analysis nested within the European Prospective Investigation into Cancer and Nutrition.
        Am J Clin Nutr. 2008; 88: 1353-1363
        • Epstein M.M.
        • Kasperzyk J.L.
        • Mucci L.A.
        • et al.
        Dietary fatty acid intake and prostate cancer survival in Örebro County, Sweden.
        Am J Epidemiol. 2012; 176: 240-252
        • Kim S.
        • Yang X.
        • Li Q.
        • et al.
        Myristoylation of Src kinase mediates Src induced and high fat diet accelerated prostate tumor progression in mice.
        J Biol Chem. 2017; 292: 18422-18433
        • Nadler M.J.
        • Harrison M.L.
        • Ashendel C.L.
        • Cassady J.M.
        • Geahlen R.L.
        Treatment of T cells with 2-hydroxymyristic acid inhibits the myristoylation and alters the stability of p56lck.
        Biochemistry. 1993; 32: 9250-9255
        • Noguchi M.
        • Kobayashi K.
        • Suetsugu N.
        • et al.
        Induction of cellular and humoral immune responses to tumor cells and peptides in HLA-A24 positive hormone-refractory prostate cancer patients by peptide vaccination.
        Prostate. 2003; 57: 80-92
        • Harada M.
        • Noguchi M.
        • Itoh K.
        Target molecules in specific immunotherapy against prostate cancer.
        Int J Clin Oncol. 2003; 8: 193-199
      1. National Center for Biotechnology Information. PubChem Compound Database; CID=73219, Available at: https://pubchem.ncbi.nlm.nih.gov/compound/73219, Accessed March 4, 2019.

        • Zhong C.
        • Yang S.
        • Huang J.
        • Cohen M.B.
        • Roy-Burman P.
        Aberration in the expression of the retinoid receptor, RXRα, in prostate cancer.
        Cancer Biol Ther. 2003; 2: 179-184
        • Gann P.H.
        • Hennekens C.H.
        • Ma J.
        • Longcope C.
        • Stampfer M.J.
        Prospective study of sex hormone levels and risk of prostate cancer.
        J Natl Cancer Inst. 1996; 88: 1118-1126