Integral role of metabolic profiling in patients with prostate cancer

Abstract

Prostate cancer is the most diagnosed malignant neoplasm among males worldwide. Over the past few years, there has been a need to find alternative methods for early diagnosis of prostate cancer. There is evidence that metabolic dysfunction is a characteristic feature of the carcinogenesis of prostate cancer, with various metabolites acting as biomarkers of tumor growth. Metabolomics is a young science that arose at the junction of molecular biology, biochemistry and genetics. The complete set of substrates and metabolic products is a metabolic profile, or metabolome. The metabolome of prostate cancer is formed by substances formed as a result of metabolic changes in response to the occurrence of a malignant process in the prostate. Unique data on metabolic changes have already been obtained, allowing us to rethink the carcinogenesis of prostate cancer. The study of the metabolome opens up new opportunities for early diagnosis, prognosis and treatment of prostate cancer.

References

[1] Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2021. CA Cancer J Clin. 2021;71(1):7–33. doi: 10.3322/caac.21654

[2] Siegel R.L., Miller K.D., Fuchs H.E., Jemal A. Cancer statistics, 2021 // CA Cancer J Clin. 2021. Vol. 71, N. 1. P. 7–33. doi: 10.3322/caac.21654

[3] Maggi M, Gentilucci A, Salciccia S, et al. Psychological impact of different primary treatments for prostate cancer: A critical analysis. Andrologia. 2019;51(1):e13157. doi: 10.1111/and.13157

[4] Maggi M., Gentilucci A., Salciccia S., et al. Psychological impact of different primary treatments for prostate cancer: A critical analysis // Andrologia. 2019. Vol. 51, N. 1. ID e13157. doi: 10.1111/and.13157

[5] Markozannes G, Tzoulaki I, Karli D, et al. Diet, body size, physical activity and risk of prostate cancer: An umbrella review of the evidence. Eur J Cancer. 2016;69:61–69. doi: 10.1016/j.ejca.2016.09.026

[6] Markozannes G., Tzoulaki I., Karli D., et al. Diet, body size, physical activity and risk of prostate cancer: An umbrella review of the evidence // Eur J Cancer. 2016. Vol. 69. P. 61–69. doi: 10.1016/j.ejca.2016.09.026

[7] Logozzi M, Angelini DF, Giuliani A, et al. Increased plasmatic levels of PSA-expressing exosomes distinguish prostate cancer patients from benign prostatic hyperplasia: A prospective study. Cancers (Basel). 2019;11(10):1449. doi: 10.3390/cancers11101449

[8] Logozzi M., Angelini D.F., Giuliani A., et al. Increased plasmatic levels of PSA-expressing exosomes distinguish prostate cancer patients from benign prostatic hyperplasia: A prospective study // Cancers (Basel). 2019. Vol. 11, N. 10. ID 1449. doi: 10.3390/cancers11101449

[9] Etzioni R, Gulati R, Cooperberg MR, et al. Limitations of basing screening policies on screening trials: The US preventive services task force and prostate cancer screening. Med Care. 2013;51(4):295–300. doi: 10.1097/MLR.0b013e31827da979

[10] Etzioni R., Gulati R., Cooperberg M.R., et al. Limitations of basing screening policies on screening trials: The US preventive services task force and prostate cancer screening // Med Care. 2013. Vol. 51, N. 4. P. 295–300. doi: 10.1097/MLR.0b013e31827da979

[11] Pavlova NN, Thompson CB. The emerging hallmarks of cancer metabolism. Cell Metab. 2016;23(1):27–47. doi: 10.1016/j.cmet.2015.12.006

[12] Pavlova N.N., Thompson C.B. The emerging hallmarks of cancer metabolism // Cell Metab. 2016. Vol. 23, N. 1. P. 27–47. doi: 10.1016/j.cmet.2015.12.006

[13] Kelly RS, Vander Heiden MG, Giovannucci E, Mucci LA. Metabolomic biomarkers of prostate cancer: prediction, diagnosis, progression, prognosis, and recurrence. Cancer Epidemiol Biomarkers Prev. 2016;25(6):887–906. doi: 10.1158/1055-9965.EPI-15-1223

[14] Kelly R.S., Vander Heiden M.G., Giovannucci E., Mucci L.A. Metabolomic biomarkers of prostate cancer: prediction, diagnosis, progression, prognosis, and recurrence // Cancer Epidemiol Biomarkers Prev. 2016. Vol. 25, N. 6. P. 887–906. doi: 10.1158/1055-9965.EPI-15-1223

[15] Zang X, Jones CM, Long TQ, et al. Feasibility of detecting prostate cancer by ultraperformance liquid chromatography-mass spectrometry serum metabolomics. J Proteome Res. 2014;13(7):3444–3454. doi: 10.1021/pr500409q

[16] Zang X., Jones C.M., Long T.Q., et al. Feasibility of detecting prostate cancer by ultraperformance liquid chromatography-mass spectrometry serum metabolomics // J Proteome Res. 2014. Vol. 13, N. 7. P. 3444–3454. doi: 10.1021/pr500409q

[17] Salciccia S, Capriotti AL, Laganà A, et al. Biomarkers in prostate cancer diagnosis: from current knowledge to the role of metabolomics and exosomes. Int J Mol Sci. 2021;22(9):4367. doi: 10.3390/ijms22094367

[18] Salciccia S., Capriotti A.L., Laganà A., et al. Biomarkers in prostate cancer diagnosis: from current knowledge to the role of metabolomics and exosomes // Int J Mol Sci. 2021. Vol. 22, N. 9. ID 4367. doi: 10.3390/ijms22094367

[19] Trock BJ. Application of metabolomics to prostate cancer. Urol Oncol. 2011;29(5):572–581. doi: 10.1016/j.urolonc.2011.08.002

[20] Trock B.J. Application of metabolomics to prostate cancer // Urol Oncol. 2011. Vol. 29, N. 5. P. 572–581. doi: 10.1016/j.urolonc.2011.08.002

[21] Steg A, Oczkowicz M, Smołucha G. Omics as a tool to help determine the effectiveness of supplements. Nutrients. 2022;14(24):5305. doi: 10.3390/nu14245305

[22] Steg A., Oczkowicz M., Smołucha G. Omics as a tool to help determine the effectiveness of supplements // Nutrients. 2022. Vol. 14, N. 24. ID 5305. doi: 10.3390/nu14245305

[23] Nagana Gowda GA, Raftery D. Biomarker discovery and translation in metabolomics. Curr Metabolomics. 2013;1(3):227–240. doi: 10.2174/2213235X113019990005

[24] Nagana Gowda G.A., Raftery D. Biomarker discovery and translation in metabolomics // Curr Metabolomics. 2013. Vol. 1, N. 3. P. 227–240. doi: 10.2174/2213235X113019990005

[25] Johnson CH, Ivanisevic J, Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol. 2016;17(7):451–459. doi: 10.1038/nrm.2016.25

[26] Johnson C.H., Ivanisevic J., Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms // Nat Rev Mol Cell Biol. 2016. Vol. 17, N. 7. P. 451–459. doi: 10.1038/nrm.2016.25

[27] Gates SC, Sweeley CC. Quantitative metabolic profiling based on gas chromatography. Clin Chem. 1978;24(10):1663–1673. doi: 10.1093/clinchem/24.10.1663

[28] Gates S.C., Sweeley C.C. Quantitative metabolic profiling based on gas chromatography // Clin Chem. 1978. Vol. 24, N. 10. P. 1663–1673. doi: 10.1093/clinchem/24.10.1663

[29] Novotny MV, Soini HA, Mechref Y. Biochemical individuality reflected in chromatographic, electrophoretic and mass-spectrometric profiles. J Chromatogr B. 2008;866(1-2):26–47. doi: 10.1016/j.jchromb.2007.10.007

[30] Novotny M.V., Soini H.A., Mechref Y. Biochemical individuality reflected in chromatographic, electrophoretic and mass-spectrometric profiles // J Chromatogr B. 2008. Vol. 866, N. 1–2. P. 26–47. doi: 10.1016/j.jchromb.2007.10.007

[31] Horning EC, Horning MG. Human metabolic profiles obtained by GC and GC/MS. J Chromatogr Sci. 1971;9(3):129–140. doi: 10.1093/chromsci/9.3.129

[32] Horning E.C., Horning M.G. Human metabolic profiles obtained by GC and GC/MS // J Chromatogr Sci. 1971. Vol. 9, N. 3. P. 129–140. doi: 10.1093/chromsci/9.3.129

[33] Dalgliesh CE, Horning EC, Horning MG, et al. A gas-liquid-chromatographic procedure for separating a wide range of metabolites occuring in urine or tissue extracts. Biochem J. 1966;101(3):792–810. doi: 10.1042/bj1010792

[34] Dalgliesh C.E., Horning E.C., Horning M.G., et al. A gas-liquid-chromatographic procedure for separating a wide range of metabolites occuring in urine or tissue extracts // Biochem J. 1966. Vol. 101, N. 3. P. 792–810. doi: 10.1042/bj1010792

[35] Wishart DS, Guo AC, Oler E, et al. HMDB 5.0: the human metabolome database for 2022. Nucleic Acids Res. 2022;50(D1):D622–D631. doi: 10.1093/nar/gkab1062

[36] Wishart D.S., Guo A.C., Oler E., et al. HMDB 5.0: the human metabolome database for 2022 // Nucleic Acids Res. 2022. Vol. 50, N. D1. P. D622–D631. doi: 10.1093/nar/gkab1062

[37] Emwas A-H. The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research. In: Bjerrum J, editor. Metabonomics. Methods in Molecular Biology. Vol. 1277. New York: Humana Press, 2015. P. 161–193. doi: 10.1007/978-1-4939-2377-9_13

[38] Emwas A.-H. The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research. В кн.: Bjerrum J., editor. Metabonomics. Methods in Molecular Biology. Vol. 1277. New York: Humana Press, 2015. P. 161–193. doi: 10.1007/978-1-4939-2377-9_13

[39] Sciarra A, Panebianco V, Ciccariello M, et al. Magnetic resonance spectroscopic imaging (1H-MRSI) and dynamic contrast-enhanced magnetic resonance (DCE-MRI): pattern changes from inflammation to prostate cancer. Cancer Invest. 2010;28(4):424–432. doi: 10.3109/07357900903287048

[40] Sciarra A., Panebianco V., Ciccariello M., et al. Magnetic resonance spectroscopic imaging (1H-MRSI) and dynamic contrast-enhanced magnetic resonance (DCE-MRI): pattern changes from inflammation to prostate cancer // Cancer Invest. 2010. Vol. 28, N. 4. P. 424–432. doi: 10.3109/07357900903287048

[41] Costello LC, Franklin RB. The intermediary metabolism of the prostate: a key to understanding the pathogenesis and progression of prostate malignancy. Oncology. 2000;59(4):269–282. doi: 10.1159/000012183

[42] Costello L.C., Franklin R.B. The intermediary metabolism of the prostate: a key to understanding the pathogenesis and progression of prostate malignancy // Oncology. 2000. Vol. 59, N. 4. P. 269–282. doi: 10.1159/000012183

[43] Lima AR, de Lourders Bastos M, Carvalho M, de Pinho PG. Biomarker discovery in human prostate cancer: an update in metabolomics studies. Transl Oncol. 2016;9(4):357–370. doi: 10.1016/j.tranon.2016.05.004

[44] Lima A.R., de Lourders Bastos M., Carvalho M., de Pinho P.G. Biomarker discovery in human prostate cancer: an update in metabolomics studies // Transl Oncol. 2016. Vol. 9, N. 4. P. 357–370. doi: 10.1016/j.tranon.2016.05.004

[45] Lima AR, Pinto J, Amaro F, et al. Advances and perspectives in prostate cancer biomarker discovery in the last 5 years through tissue and urine metabolomics. Metabolites. 2021;11(3):181. doi: 10.3390/metabo11030181

[46] Lima A.R., Pinto J., Amaro F., et al. Advances and perspectives in prostate cancer biomarker discovery in the last 5 years through tissue and urine metabolomics // Metabolites. 2021. Vol. 11, N. 3. ID 181. doi: 10.3390/metabo11030181

[47] Zadra G, Loda M. Metabolic vulnerabilities of prostate cancer: Diagnostic and therapeutic opportunities. Cold Spring Harb Perspect Med. 2018;8(10):a030569. doi: 10.1101/cshperspect.a030569

[48] Zadra G., Loda M. Metabolic vulnerabilities of prostate cancer: Diagnostic and therapeutic opportunities // Cold Spring Harb Perspect Med. 2018. Vol. 8, N. 10. ID a030569. doi: 10.1101/cshperspect.a030569

[49] Saoi M, Britz-McKibbin P. New advances in tissue metabolomics: A review. Metabolites. 2021;11(10):672. doi: 10.3390/metabo11100672

[50] Saoi M., Britz-McKibbin P. New advances in tissue metabolomics: A review // Metabolites. 2021. Vol. 11, N. 10. ID 672. doi: 10.3390/metabo11100672

[51] Huang J, Mondul AM, Weinstein SJ, et al. Prospective serum metabolomic profile of prostate cancer by size and extent of primary tumor. Oncotarget. 2017;8(28):45190–45199. doi: 10.18632/oncotarget.16775

[52] Huang J., Mondul A.M., Weinstein S.J., et al. Prospective serum metabolomic profile of prostate cancer by size and extent of primary tumor // Oncotarget. 2017. Vol. 8, N. 28. P. 45190–45199. doi: 10.18632/oncotarget.16775

[53] Kumar D, Gupta A, Mandhani A, Sankhvar SN. NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics. Prostate. 2016;76(12):1106–1119. doi: 10.1002/pros.23198

[54] Kumar D., Gupta A., Mandhani A., Sankhvar S.N. NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics // Prostate. 2016. Vol. 76, N. 12. P. 1106–1119. doi: 10.1002/pros.23198

[55] Averna TA, Kline EE, Smith AY, Sillerud LO. A decrease in 1H nuclear magnetic resonance spectroscopically determined citrate in human seminal fluid accompanies the development of prostate adenocarcinoma. J Urol. 2005;173(2):433–438. doi: 10.1097/01.ju.0000148949.72314.d7

[56] Averna T.A., Kline E.E., Smith A.Y., Sillerud L.O. A decrease in 1H nuclear magnetic resonance spectroscopically determined citrate in human seminal fluid accompanies the development of prostate adenocarcinoma // J Urol. 2005. Vol. 173, N. 2. P. 433–438. doi: 10.1097/01.ju.0000148949.72314.d7

[57] Eidelman E, Twum-Ampofo J, Ansari J, Siddiqui MM. The metabolic phenotype of prostate cancer. Front Oncol. 2017;7:131. doi: 10.3389/fonc.2017.00131

[58] Eidelman E., Twum-Ampofo J., Ansari J., Siddiqui M.M. The metabolic phenotype of prostate cancer // Front Oncol. 2017. Vol. 7. ID 131. doi: 10.3389/fonc.2017.00131

[59] Andersen MK, Giskeødegård GF, Tessem M-B. Metabolic alterations in tissues and biofluids of patients with prostate cancer. Curr Opin Endocr Metab Res. 2020;10:23–28. doi: 10.1016/j.coemr.2020.02.003

[60] Andersen M.K., Giskeødegård G.F., Tessem M.-B. Metabolic alterations in tissues and biofluids of patients with prostate cancer // Curr Opin Endocr Metab Res. 2020. Vol. 10. P. 23–28. doi: 10.1016/j.coemr.2020.02.003

[61] Gómez-Cebrián N, Rojas-Benedicto A, Albors-Vaquer A, et al. Metabolomics contributions to the discovery of prostate cancer biomarkers. Metabolites. 2019;9(3):48. doi: 10.3390/metabo9030048

[62] Gómez-Cebrián N., Rojas-Benedicto A., Albors-Vaquer A., et al. Metabolomics contributions to the discovery of prostate cancer biomarkers // Metabolites. 2019. Vol. 9, N. 3. ID 48. doi: 10.3390/metabo9030048

[63] van der Mijn JC, Kuiper MJ, Siegert CEH, et al. Lactic acidosis in prostate cancer: consider the Warburg effect. Case Rep Oncol. 2017;10(3):1085–1091. doi: 10.1159/000485242

[64] van der Mijn J.C., Kuiper M.J., Siegert C.E.H., et al. Lactic acidosis in prostate cancer: consider the Warburg effect // Case Rep Oncol. 2017. Vol. 10, N. 3. P. 1085–1091. doi: 10.1159/000485242

[65] Resurreccion EP, Fong K-W. The integration of metabolomics with other omics: Insights into understanding prostate cancer. Metabolites. 2022;12(6):488. doi: 10.3390/metabo12060488

[66] Resurreccion E.P., Fong K.-W. The integration of metabolomics with other omics: Insights into understanding prostate cancer // Metabolites. 2022. Vol. 12, N. 6. ID 488. doi: 10.3390/metabo12060488

[67] Giskeødegård GF, Bertilsson H, Selnæs KM, et al. Spermine and citrate as metabolic biomarkers for assessing prostate cancer aggressiveness. PLoS One. 2013;8(4):e62375. doi: 10.1371/journal.pone.0062375

[68] Giskeødegård G.F., Bertilsson H., Selnæs K.M., et al. Spermine and citrate as metabolic biomarkers for assessing prostate cancer aggressiveness // PLoS One. 2013. Vol. 8, N. 4. ID e62375. doi: 10.1371/journal.pone.0062375

[69] Goodwin AC, Jadallah S, Toubaji A, et al. Increased spermine oxidase expression in human prostate cancer and prostatic intraepithelial neoplasia tissues. Prostate. 2008;68(7):766–772. doi: 10.1002/pros.20735

[70] Goodwin A.C., Jadallah S., Toubaji A., et al. Increased spermine oxidase expression in human prostate cancer and prostatic intraepithelial neoplasia tissues // Prostate. 2008. Vol. 68, N. 7. P. 766–772. doi: 10.1002/pros.20735

[71] Schmidt DR, Patel R, Kirsch DG, et al. Metabolomics in cancer research and emerging applications in clinical oncology. CA Cancer J Clin. 2021;71(4):333–358. doi: 10.3322/caac.21670

[72] Schmidt D.R., Patel R., Kirsch D.G., et al. Metabolomics in cancer research and emerging applications in clinical oncology // CA Cancer J Clin. 2021. Vol. 71, N. 4. P. 333–358. doi: 10.3322/caac.21670

[73] Ahmad F, Cherukuri MK, Choyke PL. Metabolic reprogramming in prostate cancer. Br J Cancer. 2021;125(9):1185–1196. doi: 10.1038/s41416-021-01435-5

[74] Ahmad F., Cherukuri M.K., Choyke P.L. Metabolic reprogramming in prostate cancer // Br J Cancer. 2021. Vol. 125, N. 9. P. 1185–1196. doi: 10.1038/s41416-021-01435-5

[75] Beyoğlu D, Idle JR. Metabolic rewiring and the characterization of oncometabolites. Cancers (Basel). 2021;13(12):2900. doi: 10.3390/cancers13122900

[76] Beyoğlu D., Idle J.R. Metabolic rewiring and the characterization of oncometabolites // Cancers (Basel). 2021. Vol. 13, N. 12. ID 2900. doi: 10.3390/cancers13122900

[77] Franko A, Shao Y, Heni M, et al. Human prostate cancer is characterized by an increase in urea cycle metabolites. Cancers (Basel). 2020;12(7):1814. doi: 10.3390/cancers12071814

[78] Franko A., Shao Y., Heni M., et al. Human prostate cancer is characterized by an increase in urea cycle metabolites // Cancers (Basel). 2020. Vol. 12, N. 7. ID 1814. doi: 10.3390/cancers12071814

[79] Vykoukal J, Fahrmann JF, Gregg JR, et al. Caveolin-1-mediated sphingolipid oncometabolism underlies a metabolic vulnerability of prostate cancer. Nat Commun. 2020;11(1):4279. doi: 10.1038/s41467-020-17645-z

[80] Vykoukal J., Fahrmann J.F., Gregg J.R., et al. Caveolin-1-mediated sphingolipid oncometabolism underlies a metabolic vulnerability of prostate cancer // Nat Commun. 2020. Vol. 11, N. 1. ID 4279. doi: 10.1038/s41467-020-17645-z

[81] Sreekumar A, Poisson LM, Rajendiran TM, et al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature. 2009;457(7231):910–914. doi: 10.1038/nature07762

[82] Sreekumar A., Poisson L.M., Rajendiran T.M., et al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression // Nature. 2009. Vol. 457, N. 7231. P. 910–914. doi: 10.1038/nature07762

[83] Jentzmik F, Stephan C, Miller K, et al. Sarcosine in urine after digital rectal examination fails as a marker in prostate cancer detection and identification of aggressive tumours. Eur Urol. 2010;58(1):12–18. doi: 10.1016/j.eururo.2010.01.035

[84] Jentzmik F., Stephan C., Miller K., et al. Sarcosine in urine after digital rectal examination fails as a marker in prostate cancer detection and identification of aggressive tumours // Eur Urol. 2010. Vol. 58, N. 1. P. 12–18. doi: 10.1016/j.eururo.2010.01.035

[85] Cao D-L, Ye D-W, Zhu Y, et al. Efforts to resolve the contradictions in early diagnosis of prostate cancer: a comparison of different algorithms of sarcosine in urine. Prostate Cancer Prostatic Dis. 2011;14(2):166–172. doi: 10.1038/pcan.2011.2

[86] Cao D.-L., Ye D.-W., Zhu Y., et al. Efforts to resolve the contradictions in early diagnosis of prostate cancer: a comparison of different algorithms of sarcosine in urine // Prostate Cancer Prostatic Dis. 2011. Vol. 14, N. 2. P. 166–172. doi: 10.1038/pcan.2011.2

[87] Yang B, Zhang C, Cheng S, et al. Novel metabolic signatures of prostate cancer revealed by 1H-NMR metabolomics of urine. Diagnostics (Basel). 2021;11(2):149. doi: 10.3390/diagnostics11020149

[88] Yang B., Zhang C., Cheng S., et al. Novel metabolic signatures of prostate cancer revealed by 1H-NMR metabolomics of urine // Diagnostics (Basel). 2021. Vol. 11, N. 2. ID 149. doi: 10.3390/diagnostics11020149

[89] Yousefi M, Qujeq D, Shafi H, Tilaki KH. Serum and urine levels of sarcosine in benign prostatic hyperplasia and newly diagnosed prostate cancer patients. J Kermanshah Univ Med Sci. 2020;24(1):e97000. doi: 10.5812/jkums.97000

[90] Yousefi M., Qujeq D., Shafi H., Tilaki K.H. Serum and urine levels of sarcosine in benign prostatic hyperplasia and newly diagnosed prostate cancer patients // J Kermanshah Univ Med Sci. 2020. Vol. 24, N. 1. ID e97000. doi: 10.5812/jkums.97000

[91] Peppicelli S, Andreucci E, Ruzzolini J, et al. FDG uptake in cancer: a continuing debate. Theranostics. 2020;10(7):2944–2948. doi: 10.7150/thno.40599

[92] Peppicelli S., Andreucci E., Ruzzolini J., et al. FDG uptake in cancer: a continuing debate // Theranostics. 2020. Vol. 10, N. 7. P. 2944–2948. doi: 10.7150/thno.40599

[93] Lieu EL, Nguyen T, Rhyne S, Kim J. Amino acids in cancer. Exp Mol Med. 2020;52(1):15–30. doi: 10.1038/s12276-020-0375-3

[94] Lieu E.L., Nguyen T., Rhyne S., Kim J. Amino acids in cancer // Exp Mol Med. 2020. Vol. 52, N. 1. P. 15–30. doi: 10.1038/s12276-020-0375-3

[95] Dereziński P, Klupczynska A, Sawicki W, et al. Amino acid profiles of serum and urine in search for prostate cancer biomarkers: a pilot study. Int J Med Sci. 2017;14(1):1–12. doi: 10.7150/ijms.15783

[96] Dereziński P., Klupczynska A., Sawicki W., et al. Amino acid profiles of serum and urine in search for prostate cancer biomarkers: a pilot study // Int J Med Sci. 2017. Vol. 14, N. 1. P. 1–12. doi: 10.7150/ijms.15783

[97] Khodayari Moez E, Pyne S, Dinu I. Association between bivariate expression of key oncogenes and metabolic phenotypes of patients with prostate cancer. Comput Biol Med. 2018;103:55–63. doi: 10.1016/j.compbiomed.2018.09.017

[98] Khodayari Moez E., Pyne S., Dinu I. Association between bivariate expression of key oncogenes and metabolic phenotypes of patients with prostate cancer // Comput Biol Med. 2018. Vol. 103. P. 55–63. doi: 10.1016/j.compbiomed.2018.09.017

[99] Lee B, Mahmud I, Marchica J, et al. Integrated RNA and metabolite profiling of urine liquid biopsies for prostate cancer biomarker discovery. Sci Rep. 2020;10(1):3716. doi: 10.1038/s41598-020-60616-z

[100] Lee B., Mahmud I., Marchica J., et al. Integrated RNA and metabolite profiling of urine liquid biopsies for prostate cancer biomarker discovery // Sci Rep. 2020. Vol. 10, N. 1. ID 3716. doi: 10.1038/s41598-020-60616-z

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