Relationship between 4-Hydroxynonenal (4-HNE) as Systemic Biomarker of Lipid Peroxidation and Metabolomic Profiling of Patients with Prostate Cancer
Abstract
1. Introduction
2. Materials and Methods
2.1. Chemicals and Reagents
2.2. Subjects and Sample Collection
2.3. Immunohistochemistry
2.4. HNE-ELISA
2.5. Sample Preparation and Metabolite Extraction
2.5.1. LC-MS Platform
2.5.2. GC-MS Platform
2.6. Preparation of Quality Control Samples (QCs)
2.7. Metabolomics Analysis
2.7.1. Fingerprinting by LC-ESI-QTOF-MS
2.7.2. Fingerprinting by GC-EI-Q-MS
2.8. Data Treatment
2.8.1. LC-MS Data Treatment
2.8.2. GC-MS Data Treatment
2.9. Statistical Analysis
3. Results
4. Discussion
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
- Rawla, P. Epidemiology of Prostate Cancer. World J. Oncol. 2019, 10, 63–89. [Google Scholar] [CrossRef] [PubMed]
- Netto, G.; Amin, M.; Kench, J.; Al, E. Tumours of the prostate. In WHO Classification of Tumours: Urinary and Male Genital Tumours; Srigley, J., Amin, M., Rubin, M., Tsuzuki, T., Eds.; International Agency for Research on Cancer: France, Lyon, 2022; p. 576. [Google Scholar]
- Ström, P.; Kartasalo, K.; Olsson, H.; Solorzano, L.; Delahunt, B.; Berney, D.M.; Bostwick, D.G.; Evans, A.J.; Grignon, D.J.; Humphrey, P.A.; et al. Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: A population-based, diagnostic study. Lancet. Oncol. 2020, 21, 222–232. [Google Scholar] [CrossRef] [PubMed]
- Jaganjac, M.; Poljak-Blazi, M.; Zarkovic, K.; Schaur, R.J.; Zarkovic, N. The involvement of granulocytes in spontaneous regression of Walker 256 carcinoma. Cancer Lett. 2008, 260, 180–186. [Google Scholar] [CrossRef] [PubMed]
- Žarković, N.; Jaganjac, M.; Žarković, K.; Gęgotek, A.; Skrzydlewska, E. Spontaneous Regression of Cancer: Revealing Granulocytes and Oxidative Stress as the Crucial Double-edge Sword. Front. Biosci. 2022, 27, 119. [Google Scholar] [CrossRef]
- Costanzo-Garvey, D.L.; Case, A.J.; Watson, G.F.; Alsamraae, M.; Chatterjee, A.; Oberley-Deegan, R.E.; Dutta, S.; Abdalla, M.Y.; Kielian, T.; Lindsey, M.L.; et al. Prostate cancer addiction to oxidative stress defines sensitivity to anti-tumor neutrophils. Clin. Exp. Metastasis 2022, 39, 641–659. [Google Scholar] [CrossRef]
- Jaganjac, M.; Cindrić, M.; Jakovčević, A.; Žarković, K.; Žarković, N. Lipid peroxidation in brain tumors. Neurochem. Int. 2021, 149, 105118. [Google Scholar] [CrossRef]
- Hacer, İ.A.; Zeynep, A.A.; Can, Ö.; Riza, K.A.; Dildar, K.; Tülay, A. The effect of prostate cancer and antianrogenic therapy on lipid peroxidation and antioxidant systems. Int. Urol. Nephrol. 2003, 36, 57–62. [Google Scholar] [CrossRef]
- Srivastava, D.S.L.; Mittal, R.D. Free radical injury and antioxidant status in patients with benign prostate hyperplasia and prostate cancer. Indian J. Clin. Biochem. 2005, 20, 162–165. [Google Scholar] [CrossRef]
- Custovic, Z.; Zarkovic, K.; Cindric, M.; Cipak, A.; Jurkovic, I.; Sonicki, Z.; Uchida, K.; Zarkovic, N. Lipid peroxidation product acrolein as a predictive biomarker of prostate carcinoma relapse after radical surgery. Free Radic. Res. 2010, 44, 497–504. [Google Scholar] [CrossRef]
- Jaganjac, M.; Milkovic, L.; Gegotek, A.; Cindric, M.; Zarkovic, K.; Skrzydlewska, E.; Zarkovic, N. The relevance of pathophysiological alterations in redox signaling of 4-hydroxynonenal for pharmacological therapies of major stress-associated diseases. Free Radic. Biol. Med. 2020, 157, 128–153. [Google Scholar] [CrossRef]
- Zarkovic, K.; Jakovcevic, A.; Zarkovic, N. Contribution of the HNE-immunohistochemistry to modern pathological concepts of major human diseases. Free Radic. Biol. Med. 2017, 111, 110–126. [Google Scholar] [CrossRef]
- Schaur, R.J.; Siems, W.; Bresgen, N.; Eckl, P.M. 4-Hydroxy-nonenal-A Bioactive Lipid Peroxidation Product. Biomolecules 2015, 5, 2247–2337. [Google Scholar] [CrossRef]
- Peiro, G.; Alary, J.; Cravedi, J.-P.; Rathahao, E.; Steghens, J.-P.; Guéraud, F. Dihydroxynonene mercapturic acid, a urinary metabolite of 4-hydroxynonenal, as a biomarker of lipid peroxidation. Biofactors 2005, 24, 89–96. [Google Scholar] [CrossRef]
- Pierre, F.; Peiro, G.; Taché, S.; Cross, A.J.; Bingham, S.A.; Gasc, N.; Gottardi, G.; Corpet, D.E.; Guéraud, F. New marker of colon cancer risk associated with heme intake: 1,4-dihydroxynonane mercapturic acid. Cancer Epidemiol. Biomark. Prev. 2006, 15, 2274–2279. [Google Scholar] [CrossRef]
- Cherkas, A.; Golota, S.; Guéraud, F.; Abrahamovych, O.; Pichler, C.; Nersesyan, A.; Krupak, V.; Bugiichyk, V.; Yatskevych, O.; Pliatsko, M.; et al. A Helicobacter pylori-associated insulin resistance in asymptomatic sedentary young men does not correlate with inflammatory markers and urine levels of 8-iso-PGF(2)-α or 1,4-dihydroxynonane mercapturic acid. Arch. Physiol. Biochem. 2018, 124, 275–285. [Google Scholar] [CrossRef]
- Al-Menhali, A.S.; Anderson, C.; Gourine, A.V.; Abramov, A.Y.; D’Souza, A.; Jaganjac, M. Proteomic Analysis of Cardiac Adaptation to Exercise by High Resolution Mass Spectrometry. Front. Mol. Biosci. 2021, 8, 723858. [Google Scholar] [CrossRef]
- Gęgotek, A.; Domingues, P.; Wroński, A.; Ambrożewicz, E.; Skrzydlewska, E. The Proteomic Profile of Keratinocytes and Lymphocytes in Psoriatic Patients. Proteom. Clin. Appl. 2019, 13, e1800119. [Google Scholar] [CrossRef]
- Hauck, A.K.; Zhou, T.; Upadhyay, A.; Sun, Y.; O’connor, M.B.; Chen, Y.; Bernlohr, D.A. Histone carbonylation is a redox-regulated epigenomic mark that accumulates with obesity and aging. Antioxidants 2020, 9, 1210. [Google Scholar] [CrossRef]
- Wang, Y.; Jacobs, E.J.; Carter, B.D.; Gapstur, S.M.; Stevens, V.L. Plasma Metabolomic Profiles and Risk of Advanced and Fatal Prostate Cancer. Eur. Urol. Oncol. 2021, 4, 56–65. [Google Scholar] [CrossRef]
- Xu, B.; Chen, Y.; Chen, X.; Gan, L.; Zhang, Y.; Feng, J.; Yu, L. Metabolomics Profiling Discriminates Prostate Cancer From Benign Prostatic Hyperplasia Within the Prostate-Specific Antigen Gray Zone. Front. Oncol. 2021, 11, 730638. [Google Scholar] [CrossRef] [PubMed]
- Walz, S.; Wang, Q.; Zhao, X.; Hoene, M.; Häring, H.-U.; Hennenlotter, J.; Maas, M.; Peter, A.; Todenhöfer, T.; Stenzl, A.; et al. Comparison of the metabolome in urine prior and eight weeks after radical prostatectomy uncovers pathologic and molecular features of prostate cancer. J. Pharm. Biomed. Anal. 2021, 205, 114288. [Google Scholar] [CrossRef] [PubMed]
- Falegan, O.S.; Jarvi, K.; Vogel, H.J.; Hyndman, M.E. Seminal plasma metabolomics reveals lysine and serine dysregulation as unique features distinguishing between prostate cancer tumors of Gleason grades 6 and 7. Prostate 2021, 81, 713–720. [Google Scholar] [CrossRef] [PubMed]
- Zarkovic, K.; Juric, G.; Waeg, G.; Kolenc, D.; Zarkovic, N. Immunohistochemical appearance of HNE-protein conjugates in human astrocytomas. BioFactors 2005, 24, 33–40. [Google Scholar] [CrossRef] [PubMed]
- Weber, D.; Milkovic, L.; Bennett, S.J.; Griffiths, H.R.; Zarkovic, N.; Grune, T. Measurement of HNE-protein adducts in human plasma and serum by ELISA-Comparison of two primary antibodies. Redox Biol. 2013, 1, 226–233. [Google Scholar] [CrossRef]
- Perković, M.N.; Milković, L.; Uzun, S.; Mimica, N.; Pivac, N.; Waeg, G.; Žarković, N. Association of Lipid Peroxidation Product 4-Hydroxynonenal with Post-Traumatic Stress Disorder. Biomolecules 2021, 11, 1365. [Google Scholar] [CrossRef]
- Gil de la Fuente, A.; Godzien, J.; Fernández López, M.; Rupérez, F.J.; Barbas, C.; Otero, A. Knowledge-based metabolite annotation tool: CEU Mass Mediator. J. Pharm. Biomed. Anal. 2018, 154, 138–149. [Google Scholar] [CrossRef]
- Naz, S.; García, A.; Barbas, C. Multiplatform analytical methodology for metabolic fingerprinting of lung tissue. Anal. Chem. 2013, 85, 10941–10948. [Google Scholar] [CrossRef]
- Wishart, D.S.; Feunang, Y.D.; Marcu, A.; Guo, A.C.; Liang, K.; Vázquez-Fresno, R.; Sajed, T.; Johnson, D.; Li, C.; Karu, N.; et al. HMDB 4.0: The human metabolome database for 2018. Nucleic Acids Res. 2018, 46, D608–D617. [Google Scholar] [CrossRef]
- Smith, C.A.; O’Maille, G.; Want, E.J.; Qin, C.; Trauger, S.A.; Brandon, T.R.; Custodio, D.E.; Abagyan, R.; Siuzdak, G. METLIN: A metabolite mass spectral database. Ther. Drug Monit. 2005, 27, 747–751. [Google Scholar] [CrossRef]
- Kanehisa, M.; Goto, S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000, 28, 27–30. [Google Scholar] [CrossRef]
- Fahy, E.; Sud, M.; Cotter, D.; Subramaniam, S. LIPID MAPS online tools for lipid research. Nucleic Acids Res. 2007, 35, W606–W612. [Google Scholar] [CrossRef]
- Godzien, J.; Alonso-Herranz, V.; Barbas, C.; Armitage, E.G. Controlling the quality of metabolomics data: New strategies to get the best out of the QC sample. Metabolomics 2015, 11, 518–528. [Google Scholar] [CrossRef]
- Kuligowski, J.; Sánchez-Illana, Á.; Sanjuán-Herráez, D.; Vento, M.; Quintás, G. Intra-batch effect correction in liquid chromatography-mass spectrometry using quality control samples and support vector regression (QC-SVRC). Analyst 2015, 140, 7810–7817. [Google Scholar] [CrossRef]
- Chang, C.-C.; Lin, C.-J. LIBSVM: A library for support vector machines. ACM Trans. Intell. Syst. Technol. 2011, 2, 1–27. [Google Scholar] [CrossRef]
- De Livera, A.M.; Dias, D.A.; De Souza, D.; Rupasinghe, T.; Pyke, J.; Tull, D.; Roessner, U.; McConville, M.; Speed, T.P. Normalizing and integrating metabolomics data. Anal. Chem. 2012, 84, 10768–10776. [Google Scholar] [CrossRef]
- Gromski, P.S.; Xu, Y.; Hollywood, K.A.; Turner, M.L.; Goodacre, R. The influence of scaling metabolomics data on model classification accuracy. Metabolomics 2015, 11, 684–695. [Google Scholar] [CrossRef]
- Pang, Z.; Chong, J.; Zhou, G.; de Lima Morais, D.A.; Chang, L.; Barrette, M.; Gauthier, C.; Jacques, P.-É.; Li, S.; Xia, J. MetaboAnalyst 5.0: Narrowing the gap between raw spectra and functional insights. Nucleic Acids Res. 2021, 49, W388–W396. [Google Scholar] [CrossRef]
- Pang, Z.; Zhou, G.; Ewald, J.; Chang, L.; Hacariz, O.; Basu, N.; Xia, J. Using MetaboAnalyst 5.0 for LC–HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data. Nat. Protoc. 2022, 17, 1735–1761. [Google Scholar] [CrossRef]
- Živković, N.P.; Petrovečki, M.; Lončarić, Č.T.; Nikolić, I.; Waeg, G.; Jaganjac, M.; Žarković, K.; Žarković, N. Positron emission tomography-computed tomography and 4-hydroxynonenal-histidine immunohistochemistry reveal differential onset of lipid peroxidation in primary lung cancer and in pulmonary metastasis of remote malignancies. Redox Biol. 2017, 11, 600–605. [Google Scholar] [CrossRef]
- Zhong, H.; Xiao, M.; Zarkovic, K.; Zhu, M.; Sa, R.; Lu, J.; Tao, Y.; Chen, Q.; Xia, L.; Cheng, S.; et al. Mitochondrial control of apoptosis through modulation of cardiolipin oxidation in hepatocellular carcinoma: A novel link between oxidative stress and cancer. Free Radic. Biol. Med. 2017, 102, 67–76. [Google Scholar] [CrossRef] [PubMed]
- Gęgotek, A.; Nikliński, J.; Žarković, N.; Žarković, K.; Waeg, G.; Łuczaj, W.; Charkiewicz, R.; Skrzydlewska, E. Lipid mediators involved in the oxidative stress and antioxidant defence of human lung cancer cells. Redox Biol. 2016, 9, 210–219. [Google Scholar] [CrossRef] [PubMed]
- Bellezza, I.; Scarpelli, P.; Pizzo, S.V.; Grottelli, S.; Costanzi, E.; Minelli, A. ROS-independent Nrf2 activation in prostate cancer. Oncotarget 2017, 8, 67506–67518. [Google Scholar] [CrossRef] [PubMed]
- Pettazzoni, P.; Ciamporcero, E.; Medana, C.; Pizzimenti, S.; Dal Bello, F.; Minero, V.G.; Toaldo, C.; Minelli, R.; Uchida, K.; Dianzani, M.U.; et al. Nuclear factor erythroid 2-related factor-2 activity controls 4-hydroxynonenal metabolism and activity in prostate cancer cells. Free Radic. Biol. Med. 2011, 51, 1610–1618. [Google Scholar] [CrossRef] [PubMed]
- Sovic, A.; Borovic, S.; Loncaric, I.; Kreuzer, T.; Zarkovic, K.; Vukovic, T.; Wäg, G.; Hrascan, R.; Wintersteiger, R.; Klinger, R.; et al. The carcinostatic and proapoptotic potential of 4-hydroxynonenal in HeLa cells is associated with its conjugation to cellular proteins. Anticancer Res. 2001, 21, 1997–2004. [Google Scholar]
- Sunjic, S.B.; Gasparovic, A.C.; Jaganjac, M.; Rechberger, G.; Meinitzer, A.; Grune, T.; Kohlwein, S.D.; Mihaljevic, B.; Zarkovic, N. Sensitivity of Osteosarcoma Cells to Concentration-Dependent Bioactivities of Lipid Peroxidation Product 4-Hydroxynonenal Depend on Their Level of Differentiation. Cells 2021, 10, 269. [Google Scholar] [CrossRef]
- Sunjic, S.B.; Cipak, A.; Rabuzin, F.; Wildburger, R.; Zarkovic, N. The influence of 4-hydroxy-2-nonenal on proliferation, differentiation and apoptosis of human osteosarcoma cells. Biofactors 2005, 24, 141–148. [Google Scholar] [CrossRef]
- Tirumalai, R.; Rajesh Kumar, T.; Mai, K.H.; Biswal, S. Acrolein causes transcriptional induction of phase II genes by activation of Nrf2 in human lung type II epithelial (A549) cells. Toxicol. Lett. 2002, 132, 27–36. [Google Scholar] [CrossRef]
- Zarkovic, K.; Uchida, K.; Kolenc, D.; Hlupic, L.; Zarkovic, N. Tissue distribution of lipid peroxidation product acrolein in human colon carcinogenesis. Free Radic. Res. 2006, 40, 543–552. [Google Scholar] [CrossRef]
- Tabor, C.W.; Tabor, H.; Bachrach, U. Identification of the aminoaldehydes produced by the oxidation of spermine and spermidine with purified plasma amine oxidase. J. Biol. Chem. 1964, 239, 2194–2203. [Google Scholar] [CrossRef]
- Jaganjac, M.; Poljak-Blazi, M.; Schaur, R.J.; Zarkovic, K.; Borovic, S.; Cipak, A.; Cindric, M.; Uchida, K.; Waeg, G.; Zarkovic, N. Elevated neutrophil elastase and acrolein-protein adducts are associated with W256 regression. Clin. Exp. Immunol. 2012, 170, 178–185. [Google Scholar] [CrossRef]
- Jaganjac, M.; Matijevic Glavan, T.; Zarkovic, N. The Role of Acrolein and NADPH Oxidase in the Granulocyte-Mediated Growth-Inhibition of Tumor Cells. Cells 2019, 8, 292. [Google Scholar] [CrossRef]
- Bauer, G.; Zarkovic, N. Revealing mechanisms of selective, concentration-dependent potentials of 4-hydroxy-2-nonenal to induce apoptosis in cancer cells through inactivation of membrane-associated catalase. Free Radic. Biol. Med. 2015, 81, 128–144. [Google Scholar] [CrossRef]
- Jaganjac, M.; Almuraikhy, S.; Al-Khelaifi, F.; Al-Jaber, M.; Bashah, M.; Mazloum, N.A.; Zarkovic, K.; Zarkovic, N.; Waeg, G.; Kafienah, W.; et al. Combined metformin and insulin treatment reverses metabolically impaired omental adipogenesis and accumulation of 4-hydroxynonenal in obese diabetic patients. Redox Biol. 2017, 12, 483–490. [Google Scholar] [CrossRef]
- Zarkovic, N.; Jakovcevic, A.; Mataic, A.; Jaganjac, M.; Vukovic, T.; Waeg, G.; Zarkovic, K. Post-mortem Findings of Inflammatory Cells and the Association of 4-Hydroxynonenal with Systemic Vascular and Oxidative Stress in Lethal COVID-19. Cells 2022, 11, 444. [Google Scholar] [CrossRef]
- Žarković, N.; Orehovec, B.; Baršić, B.; Tarle, M.; Kmet, M.; Lukšić, I.; Tatzber, F.; Wonisch, W.; Skrzydlewska, E.; Łuczaj, W. Lipidomics Revealed Plasma Phospholipid Profile Differences between Deceased and Recovered COVID-19 Patients. Biomolecules 2022, 12, 1488. [Google Scholar] [CrossRef]
- Kim, H.-Y.; Lee, K.-M.; Kim, S.-H.; Kwon, Y.-J.; Chun, Y.-J.; Choi, H.-K. Comparative metabolic and lipidomic profiling of human breast cancer cells with different metastatic potentials. Oncotarget 2016, 7, 67111–67128. [Google Scholar] [CrossRef]
- Ikeda, A.; Nishiumi, S.; Shinohara, M.; Yoshie, T.; Hatano, N.; Okuno, T.; Bamba, T.; Fukusaki, E.; Takenawa, T.; Azuma, T.; et al. Serum metabolomics as a novel diagnostic approach for gastrointestinal cancer. Biomed. Chromatogr. 2012, 26, 548–558. [Google Scholar] [CrossRef]
- Huang, J.; Mondul, A.M.; Weinstein, S.J.; Derkach, A.; Moore, S.C.; Sampson, J.N.; Albanes, D. Prospective serum metabolomic profiling of lethal prostate cancer. Int. J. Cancer 2019, 145, 3231–3243. [Google Scholar] [CrossRef]
- Nomura, D.K.; Lombardi, D.P.; Chang, J.W.; Niessen, S.; Ward, A.M.; Long, J.Z.; Hoover, H.H.; Cravatt, B.F. Monoacylglycerol Lipase Exerts Dual Control over Endocannabinoid and Fatty Acid Pathways to Support Prostate Cancer. Chem. Biol. 2011, 18, 846–856. [Google Scholar] [CrossRef]
- Crowe, F.L.; Allen, N.E.; Appleby, P.N.; Overvad, K.; Aardestrup, I.V.; Johnsen, N.F.; Tjønneland, A.; Linseisen, J.; Kaaks, R.; Boeing, H.; 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. [Google Scholar] [CrossRef] [PubMed]
- Leitzmann, M.F.; Stampfer, M.J.; Michaud, D.S.; Augustsson, K.; Colditz, G.C.; Willett, W.C.; Giovannucci, E.L. Dietary intake of n-3 and n-6 fatty acids and the risk of prostate cancer. Am. J. Clin. Nutr. 2004, 80, 204–216. [Google Scholar] [CrossRef] [PubMed]
- Augustsson, K.; Michaud, D.S.; Rimm, E.B.; Leitzmann, M.F.; Stampfer, M.J.; Willett, W.C.; Giovannucci, E. A prospective study of intake of fish and marine fatty acids and prostate cancer. Cancer Epidemiol. Biomark. Prev. 2003, 12, 64–67. [Google Scholar]
- Epstein, M.M.; Kasperzyk, J.L.; Mucci, L.A.; Giovannucci, E.; Price, A.; Wolk, A.; Håkansson, N.; Fall, K.; Andersson, S.-O.; Andrén, O. Dietary fatty acid intake and prostate cancer survival in Örebro County, Sweden. Am. J. Epidemiol. 2012, 176, 240–252. [Google Scholar] [CrossRef] [PubMed]
- Perez-Cornago, A.; Huybrechts, I.; Appleby, P.N.; Schmidt, J.A.; Crowe, F.L.; Overvad, K.; Tjønneland, A.; Kühn, T.; Katzke, V.; Trichopoulou, A.; et al. Intake of individual fatty acids and risk of prostate cancer in the European prospective investigation into cancer and nutrition. Int. J. Cancer 2020, 146, 44–57. [Google Scholar] [CrossRef]
- Wallström, P.; Bjartell, A.; Gullberg, B.; Olsson, H.; Wirfält, E. A prospective study on dietary fat and incidence of prostate cancer (Malmö, Sweden). Cancer Causes Control 2007, 18, 1107–1121. [Google Scholar] [CrossRef]
- Crowe, F.L.; Appleby, P.N.; Travis, R.C.; Barnett, M.; Brasky, T.M.; Bueno-de-Mesquita, H.B.; Chajes, V.; Chavarro, J.E.; Chirlaque, M.-D.; English, D.R.; et al. Circulating fatty acids and prostate cancer risk: Individual participant meta-analysis of prospective studies. J. Natl. Cancer Inst. 2014, 106, dju240. [Google Scholar] [CrossRef]
- Pelser, C.; Mondul, A.M.; Hollenbeck, A.R.; Park, Y. Dietary fat, fatty acids, and risk of prostate cancer in the NIH-AARP diet and health study. Cancer Epidemiol. Biomark. Prev. 2013, 22, 697–707. [Google Scholar] [CrossRef]
- Huang, J.; Zhao, B.; Weinstein, S.J.; Albanes, D.; Mondul, A.M. Metabolomic profile of prostate cancer-specific survival among 1812 Finnish men. BMC Med. 2022, 20, 362. [Google Scholar] [CrossRef]
- Kelavkar, U.P.; Nixon, J.B.; Cohen, C.; Dillehay, D.; Eling, T.E.; Badr, K.F. Overexpression of 15-lipoxygenase-1 in PC-3 human prostate cancer cells increases tumorigenesis. Carcinogenesis 2001, 22, 1765–1773. [Google Scholar] [CrossRef]
- Kelavkar, U.P.; Hutzley, J.; McHugh, K.; Allen, K.G.D.; Parwani, A. Prostate tumor growth can be modulated by dietarily targeting the 15-lipoxygenase-1 and cyclooxygenase-2 enzymes. Neoplasia 2009, 11, 692–699. [Google Scholar] [CrossRef]
- Hada, M.; Edin, M.L.; Hartge, P.; Lih, F.B.; Wentzensen, N.; Zeldin, D.C.; Trabert, B. Prediagnostic Serum Levels of Fatty Acid Metabolites and Risk of Ovarian Cancer in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Cancer Epidemiol. Biomark. Prev. 2019, 28, 189–197. [Google Scholar] [CrossRef]
- Byberg, L.; Kilander, L.; Warensjö Lemming, E.; Michaëlsson, K.; Vessby, B. Cancer death is related to high palmitoleic acid in serum and to polymorphisms in the SCD-1 gene in healthy Swedish men. Am. J. Clin. Nutr. 2014, 99, 551–558. [Google Scholar] [CrossRef]
- Liotti, A.; Cosimato, V.; Mirra, P.; Calì, G.; Conza, D.; Secondo, A.; Luongo, G.; Terracciano, D.; Formisano, P.; Beguinot, F.; et al. Oleic acid promotes prostate cancer malignant phenotype via the G protein-coupled receptor FFA1/GPR40. J. Cell. Physiol. 2018, 233, 7367–7378. [Google Scholar] [CrossRef]
- Qiu, Y.; Cai, G.; Su, M.; Chen, T.; Zheng, X.; Xu, Y.; Ni, Y.; Zhao, A.; Xu, L.X.; Cai, S.; et al. Serum metabolite profiling of human colorectal cancer using GC-TOFMS and UPLC-QTOFMS. J. Proteome Res. 2009, 8, 4844–4850. [Google Scholar] [CrossRef]
- Nishiumi, S.; Kobayashi, T.; Ikeda, A.; Yoshie, T.; Kibi, M.; Izumi, Y.; Okuno, T.; Hayashi, N.; Kawano, S.; Takenawa, T.; et al. A novel serum metabolomics-based diagnostic approach for colorectal cancer. PLoS ONE 2012, 7, e40459. [Google Scholar] [CrossRef]
- Gall, W.E.; Beebe, K.; Lawton, K.A.; Adam, K.-P.; Mitchell, M.W.; Nakhle, P.J.; Ryals, J.A.; Milburn, M.V.; Nannipieri, M.; Camastra, S.; et al. Alpha-hydroxybutyrate is an early biomarker of insulin resistance and glucose intolerance in a nondiabetic population. PLoS ONE 2010, 5, e10883. [Google Scholar] [CrossRef]
- Goveia, J.; Pircher, A.; Conradi, L.-C.; Kalucka, J.; Lagani, V.; Dewerchin, M.; Eelen, G.; DeBerardinis, R.J.; Wilson, I.D.; Carmeliet, P. Meta-analysis of clinical metabolic profiling studies in cancer: Challenges and opportunities. EMBO Mol. Med. 2016, 8, 1134–1142. [Google Scholar] [CrossRef]
- Shukla, S.K.; Gebregiworgis, T.; Purohit, V.; Chaika, N.V.; Gunda, V.; Radhakrishnan, P.; Mehla, K.; Pipinos, I.I.; Powers, R.; Yu, F.; et al. Metabolic reprogramming induced by ketone bodies diminishes pancreatic cancer cachexia. Cancer Metab. 2014, 2, 18. [Google Scholar] [CrossRef]
- Schornack, P.A.; Gillies, R.J. Contributions of cell metabolism and H+ diffusion to the acidic pH of tumors. Neoplasia 2003, 5, 135–145. [Google Scholar] [CrossRef]
- Bensimon, L.; Yin, H.; Suissa, S.; Pollak, M.N.; Azoulay, L. Type 2 diabetes and the risk of mortality among patients with prostate cancer. Cancer Causes Control 2014, 25, 329–338. [Google Scholar] [CrossRef] [PubMed]
- Cai, H.; Xu, Z.; Xu, T.; Yu, B.; Zou, Q. Diabetes mellitus is associated with elevated risk of mortality amongst patients with prostate cancer: A meta-analysis of 11 cohort studies. Diabetes. Metab. Res. Rev. 2015, 31, 336–343. [Google Scholar] [CrossRef] [PubMed]
- Arthur, R.; Møller, H.; Garmo, H.; Häggström, C.; Holmberg, L.; Stattin, P.; Malmström, H.; Lambe, M.; Hammar, N.; Walldius, G.; et al. Serum glucose, triglycerides, and cholesterol in relation to prostate cancer death in the Swedish AMORIS study. Cancer Causes Control 2019, 30, 195–206. [Google Scholar] [CrossRef] [PubMed]
- Deng, Y.-L.; Liu, R.; Cai, Z.-D.; Han, Z.-D.; Feng, Y.-F.; Cai, S.-H.; Chen, Q.-B.; Zhu, J.-G.; Zhong, W.-D. Mannose inhibits the growth of prostate cancer through a mitochondrial mechanism. Asian J. Androl. 2022, 24, 540–548. [Google Scholar] [CrossRef] [PubMed]
- Conroy, L.R.; Stanback, A.E.; Young, L.E.A.; Clarke, H.A.; Austin, G.L.; Liu, J.; Allison, D.B.; Sun, R.C. In Situ Analysis of N-Linked Glycans as Potential Biomarkers of Clinical Course in Human Prostate Cancer. Mol. Cancer Res. 2021, 19, 1727–1738. [Google Scholar] [CrossRef]
- Platz, E.A.; Till, C.; Goodman, P.J.; Parnes, H.L.; Figg, W.D.; Albanes, D.; Neuhouser, M.L.; Klein, E.A.; Thompson, I.M.J.; Kristal, A.R. Men with low serum cholesterol have a lower risk of high-grade prostate cancer in the placebo arm of the prostate cancer prevention trial. Cancer Epidemiol. Biomark. Prev. 2009, 18, 2807–2813. [Google Scholar] [CrossRef]
- Mondul, A.M.; Clipp, S.L.; Helzlsouer, K.J.; Platz, E.A. Association between plasma total cholesterol concentration and incident prostate cancer in the CLUE II cohort. Cancer Causes Control 2010, 21, 61–68. [Google Scholar] [CrossRef]
- Van Hemelrijck, M.; Walldius, G.; Jungner, I.; Hammar, N.; Garmo, H.; Binda, E.; Hayday, A.; Lambe, M.; Holmberg, L. Low levels of apolipoprotein A-I and HDL are associated with risk of prostate cancer in the Swedish AMORIS study. Cancer Causes Control 2011, 22, 1011–1019. [Google Scholar] [CrossRef]
- Batty, G.D.; Kivimäki, M.; Clarke, R.; Davey Smith, G.; Shipley, M.J. Modifiable risk factors for prostate cancer mortality in London: Forty years of follow-up in the Whitehall study. Cancer Causes Control 2011, 22, 311–318. [Google Scholar] [CrossRef]
- Farwell, W.R.; D’Avolio, L.W.; Scranton, R.E.; Lawler, E.V.; Gaziano, J.M. Statins and prostate cancer diagnosis and grade in a veterans population. J. Natl. Cancer Inst. 2011, 103, 885–892. [Google Scholar] [CrossRef]
- Shafique, K.; McLoone, P.; Qureshi, K.; Leung, H.; Hart, C.; Morrison, D.S. Cholesterol and the risk of grade-specific prostate cancer incidence: Evidence from two large prospective cohort studies with up to 37 years’ follow up. BMC Cancer 2012, 12, 25. [Google Scholar] [CrossRef]
- Solomon, K.R.; Freeman, M.R. The complex interplay between cholesterol and prostate malignancy. Urol. Clin. North Am. 2011, 38, 243–259. [Google Scholar] [CrossRef]
- Pelton, K.; Freeman, M.R.; Solomon, K.R. Cholesterol and prostate cancer. Curr. Opin. Pharmacol. 2012, 12, 751–759. [Google Scholar] [CrossRef]
- Freeman, M.R.; Solomon, K.R. Cholesterol and benign prostate disease. Differentiation 2011, 82, 244–252. [Google Scholar] [CrossRef]
- Zhuang, L.; Lin, J.; Lu, M.L.; Solomon, K.R.; Freeman, M.R. Cholesterol-rich lipid rafts mediate akt-regulated survival in prostate cancer cells. Cancer Res. 2002, 62, 2227–2231. [Google Scholar]
- Locke, J.A.; Guns, E.S.; Lubik, A.A.; Adomat, H.H.; Hendy, S.C.; Wood, C.A.; Ettinger, S.L.; Gleave, M.E.; Nelson, C.C. Androgen levels increase by intratumoral de novo steroidogenesis during progression of castration-resistant prostate cancer. Cancer Res. 2008, 68, 6407–6415. [Google Scholar] [CrossRef]
- Montgomery, R.B.; Mostaghel, E.A.; Vessella, R.; Hess, D.L.; Kalhorn, T.F.; Higano, C.S.; True, L.D.; Nelson, P.S. Maintenance of intratumoral androgens in metastatic prostate cancer: A mechanism for castration-resistant tumor growth. Cancer Res. 2008, 68, 4447–4454. [Google Scholar] [CrossRef]
- Snaterse, G.; Visser, J.A.; Arlt, W.; Hofland, J. Circulating steroid hormone variations throughout different stages of prostate cancer. Endocr. Relat. Cancer 2017, 24, R403–R420. [Google Scholar] [CrossRef]
- Grigoryev, D.N.; Long, B.J.; Njar, V.C.O.; Brodie, A.H.M. Pregnenolone stimulates LNCaP prostate cancer cell growth via the mutated androgen receptor. J. Steroid Biochem. Mol. Biol. 2000, 75, 1–10. [Google Scholar] [CrossRef]
- Shih, D.M.; Shaposhnik, Z.; Meng, Y.; Rosales, M.; Wang, X.; Wu, J.; Ratiner, B.; Zadini, F.; Zadini, G.; Lusis, A.J. Hyodeoxycholic acid improves HDL function and inhibits atherosclerotic lesion formation in LDLR-knockout mice. FASEB J. Off. Publ. Fed. Am. Soc. Exp. Biol. 2013, 27, 3805–3817. [Google Scholar] [CrossRef]
- Režen, T.; Rozman, D.; Kovács, T.; Kovács, P.; Sipos, A.; Bai, P.; Mikó, E. The role of bile acids in carcinogenesis. Cell. Mol. Life Sci. 2022, 79, 243. [Google Scholar] [CrossRef] [PubMed]
- Fu, J.; Yu, M.; Xu, W.; Yu, S. Research Progress of Bile Acids in Cancer. Front. Oncol. 2021, 11, 778258. [Google Scholar] [CrossRef] [PubMed]
- Wei, Z.; Liu, X.; Cheng, C.; Yu, W.; Yi, P. Metabolism of Amino Acids in Cancer. Front. Cell Dev. Biol. 2020, 8, 603837. [Google Scholar] [CrossRef] [PubMed]
- Jajin, M.G.; Abooshahab, R.; Hooshmand, K.; Moradi, A.; Siadat, S.D.; Mirzazadeh, R.; Chegini, K.G.; Hedayati, M. Gas chromatography-mass spectrometry-based untargeted metabolomics reveals metabolic perturbations in medullary thyroid carcinoma. Sci. Rep. 2022, 12, 8397. [Google Scholar] [CrossRef] [PubMed]
- Capuano, G.; Rigamonti, N.; Grioni, M.; Freschi, M.; Bellone, M. Modulators of arginine metabolism support cancer immunosurveillance. BMC Immunol. 2009, 10, 1. [Google Scholar] [CrossRef]
- Wang, B.; Rong, X.; Palladino, E.N.D.; Wang, J.; Fogelman, A.M.; Martín, M.G.; Alrefai, W.A.; Ford, D.A.; Tontonoz, P. Phospholipid Remodeling and Cholesterol Availability Regulate Intestinal Stemness and Tumorigenesis. Cell Stem Cell 2018, 22, 206–220.e4. [Google Scholar] [CrossRef]
- Bronte, V.; Kasic, T.; Gri, G.; Gallana, K.; Borsellino, G.; Marigo, I.; Battistini, L.; Iafrate, M.; Prayer-Galetti, T.; Pagano, F.; et al. Boosting antitumor responses of T lymphocytes infiltrating human prostate cancers. J. Exp. Med. 2005, 201, 1257–1268. [Google Scholar] [CrossRef]
- Mumenthaler, S.M.; Yu, H.; Tze, S.; Cederbaum, S.D.; Pegg, A.E.; Seligson, D.B.; Grody, W.W. Expression of arginase II in prostate cancer. Int. J. Oncol. 2008, 32, 357–365. [Google Scholar] [CrossRef]
- Gannon, P.O.; Godin-Ethier, J.; Hassler, M.; Delvoye, N.; Aversa, M.; Poisson, A.O.; Péant, B.; Alam Fahmy, M.; Saad, F.; Lapointe, R.; et al. Androgen-regulated expression of arginase 1, arginase 2 and interleukin-8 in human prostate cancer. PLoS ONE 2010, 5, e12107. [Google Scholar] [CrossRef]
- Waeg, G.; Dimsity, G.; Esterbauer, H. Monoclonal antibodies for detection of 4-hydroxynonenal modified proteins. Free Radic. Res. 1996, 25, 149–159. [Google Scholar] [CrossRef]
- Tang, Y.; Li, R.; Lin, G.; Li, L. PEP search in MyCompoundID: Detection and identification of dipeptides and tripeptides using dimethyl labeling and hydrophilic interaction liquid chromatography tandem mass spectrometry. Anal. Chem. 2014, 86, 3568–3574. [Google Scholar] [CrossRef]
- Wegiel, B.; Gallo, D.; Csizmadia, E.; Harris, C.; Belcher, J.; Vercellotti, G.M.; Penacho, N.; Seth, P.; Sukhatme, V.; Ahmed, A.; et al. Carbon monoxide expedites metabolic exhaustion to inhibit tumor growth. Cancer Res. 2013, 73, 7009–7021. [Google Scholar] [CrossRef]
- Sunamura, M.; Duda, D.G.; Ghattas, M.H.; Lozonschi, L.; Motoi, F.; Yamauchi, J.-I.; Matsuno, S.; Shibahara, S.; Abraham, N.G. Heme oxygenase-1 accelerates tumor angiogenesis of human pancreatic cancer. Angiogenesis 2003, 6, 15–24. [Google Scholar] [CrossRef]
- Chen, G.G.; Liu, Z.M.; Vlantis, A.C.; Tse, G.M.K.; Leung, B.C.H.; van Hasselt, C.A. Heme oxygenase-1 protects against apoptosis induced by tumor necrosis factor-alpha and cycloheximide in papillary thyroid carcinoma cells. J. Cell. Biochem. 2004, 92, 1246–1256. [Google Scholar] [CrossRef]
- Was, H.; Cichon, T.; Smolarczyk, R.; Rudnicka, D.; Stopa, M.; Chevalier, C.; Leger, J.J.; Lackowska, B.; Grochot, A.; Bojkowska, K.; et al. Overexpression of heme oxygenase-1 in murine melanoma: Increased proliferation and viability of tumor cells, decreased survival of mice. Am. J. Pathol. 2006, 169, 2181–2198. [Google Scholar] [CrossRef]
- Matsumoto, T.; Mochizuki, W.; Nibe, Y.; Akiyama, S.; Matsumoto, Y.; Nozaki, K.; Fukuda, M.; Hayashi, A.; Mizutani, T.; Oshima, S.; et al. Retinol Promotes In Vitro Growth of Proximal Colon Organoids through a Retinoic Acid-Independent Mechanism. PLoS ONE 2016, 11, e0162049. [Google Scholar] [CrossRef]
- Mondul, A.M.; Watters, J.L.; Männistö, S.; Weinstein, S.J.; Snyder, K.; Virtamo, J.; Albanes, D. Serum retinol and risk of prostate cancer. Am. J. Epidemiol. 2011, 173, 813–821. [Google Scholar] [CrossRef]
- Frijhoff, J.; Winyard, P.G.; Zarkovic, N.; Davies, S.; Stocker, R.; Cheng, D.; Knight, A.; Taylor, E.L.; Oettrich, J.; Ruskovska, T.; et al. Clinical relevance of biomarkers of oxidative stress. Antioxid. Redox Signal. 2015, 23, 1144–1170. [Google Scholar] [CrossRef]
Category | Compound | RT | %Δ | FC | log2FC | pBH | VIP |
---|---|---|---|---|---|---|---|
Fatty Acyls | Caprylic acid (octanoic acid) | 9.79 | 41.43 | 1.41 | 0.50 | <0.0001 | 1.17 |
Caproic acid (hexanoic acid) | 7.06 | −68.94 | 0.31 | −1.69 | <0.0001 | 2.04 | |
Lauric acid (dodecanoic acid) | 14.75 | 69.22 | 1.69 | 0.76 | 0.002 | 1.00 | |
Palmitic acid (hexadecanoic acid) | 18.87 | 92.58 | 1.93 | 0.95 | <0.0001 | 1.06 | |
Stearic acid (octadecanoic acid) | 20.69 | 80.19 | 1.80 | 0.85 | 0.002 | 1.02 | |
Palmitoleic acid (hexadecenoic acid) | 18.68 | 181.07 | 2.81 | 1.49 | <0.0001 | 1.00 | |
Linoleic acid (octadecadienoic acid) | 20.41 | 140.74 | 2.41 | 1.27 | <0.0001 | 1.02 | |
Oleic acid (octadecenoic acid) | 20.46 | 177.32 | 2.77 | 1.47 | <0.0001 | 1.07 | |
Organic acids and derivatives | Lactic acid (2-hydroxypropanoic acid) | 6.85 | −56.24 | 0.44 | −1.19 | <0.0001 | 3.96 |
2-hydroxybutyric acid | 7.79 | 87.56 | 1.88 | 0.91 | <0.0001 | 1.09 | |
3-hydroxybutyric acid | 8.28 | 257.75 | 3.58 | 1.84 | <0.0001 | 1.58 | |
Pyruvic acid (2-oxopropanoic acid) | 6.70 | −65.78 | 0.34 | −1.55 | <0.0001 | 2.04 | |
2-ketoisocaproic acid (ketoleucine) | 8.54 | 33.61 | 1.34 | 0.42 | 0.049 | 1.03 | |
Carbohydrates and carbohydrate conjugates | Glycerol | 9.87 | 69.00 | 1.69 | 0.76 | <0.0001 | 1.08 |
Glyceric acid | 10.65 | 30.93 | 1.31 | 0.39 | 0.002 | 1.00 | |
Mannose | 17.22 | 19.80 | 1.20 | 0.26 | 0.002 | 1.02 | |
Galactose/glucose | 17.55 | 17.57 | 1.18 | 0.23 | 0.002 | 1.66 | |
Sterol Lipids | Cholesterol | 27.57 | 30.47 | 1.30 | 0.38 | 0.003 | 1.04 |
Category | Compound | ESI Mode | m/z | RT | %Δ | FC | log2FC | pBH | VIP |
---|---|---|---|---|---|---|---|---|---|
Fatty Acyls | Thapsic acid (hexadecanedioic acid) | - | 285.2072 | 16.30 | 138.00 | 2.38 | 1.25 | <0.0001 | 1.47 |
Methylhexadecenoic acid | + | 269.2461 | 18.70 | 86.68 | 1.87 | 0.90 | <0.0001 | 1.05 | |
Palmitoleic acid | - | 253.2176 | 27.60 | 88.09 | 1.88 | 0.91 | <0.0001 | 1.14 | |
Linolenic acid (octadecatrienoic acid) | - | 277.2174 | 25.90 | 91.04 | 1.91 | 0.93 | <0.0001 | 1.12 | |
Oleic acid | - | 281.2493 | 31.45 | 80.58 | 1.81 | 0.85 | <0.0001 | 1.03 | |
Eicosapentaenoic acid | + | 303.2313 | 25.54 | 252.02 | 3.52 | 1.82 | <0.0001 | 1.19 | |
Docosapentaenoic acid | - | 329.2488 | 28.63 | 103.96 | 2.04 | 1.03 | <0.0001 | 1.19 | |
Decadienal | + | 153.1267 | 12.45 | −30.21 | 0.70 | −0.52 | <0.0001 | 0.28 | |
Octadecadienal (9,12) | + | 265.2508 | 25.92 | 146.52 | 2.47 | 1.30 | <0.0001 | 2.78 | |
Tetradecenoylcarnitine | + | 370.2963 | 12.70 | 113.97 | 2.14 | 1.10 | <0.0001 | 1.01 | |
9-hydroxyoctadecadienoic acid (9-HODE) | - | 295.2278 | 18.71 | 388.27 | 4.88 | 2.29 | <0.0001 | 3.97 | |
Glycerolipids | MG(16:0) | + | 331.2855 | 27.69 | 246.30 | 3.46 | 1.79 | <0.0001 | 1.55 |
MG(18:0) | + | 359.3155 | 32.05 | 2966.39 | 30.66 | 4.94 | <0.0001 | 6.00 | |
MG(18:2(9,12)) | + | 355.2844 | 25.33 | 238.69 | 3.39 | 1.76 | <0.0001 | 1.23 | |
Organic acids and derivatives | Arginine | + | 175.1190 | 0.57 | 62.43 | 1.62 | 0.70 | <0.0001 | 1.37 |
Threonylhistidine | - | 255.1121 | 1.79 | 91.05 | 1.91 | 0.93 | <0.0001 | 1.57 | |
O-methoxycatechol-O-sulphate | - | 203.0025 | 1.51 | −71.64 | 0.28 | −1.82 | <0.0001 | 1.59 | |
Pyrocatechol sulfate | - | 188.9878 | 1.19 | −80.33 | 0.20 | −2.35 | <0.0001 | 3.47 | |
Organoheterocyclic compounds | Biliverdin | + | 583.2551 | 9.90 | 180.27 | 2.80 | 1.49 | <0.0001 | 1.10 |
Prenol Lipids | Retinal | + | 285.2222 | 25.55 | 754.02 | 8.54 | 3.09 | <0.0001 | 2.91 |
Sterol Lipids | Hyodeoxycholic acid | - | 391.2841 | 15.03 | −83.22 | 0.17 | −2.57 | <0.0001 | 3.60 |
Pregnenolone | + | 317.2472 | 25.56 | 653.97 | 7.54 | 2.91 | <0.0001 | 1.66 |
Healthy Controls | Prostate Cancer Patients | |||||
---|---|---|---|---|---|---|
Compound | r | 95% Confidence Interval | p | r | 95% Confidence Interval | p |
2-ketoisocaproic acid | 0.146 | −0.179 to 0.442 | 0.363 | 0.394 | 0.005 to 0.680 | 0.042 * |
9-HODE | −0.014 | −0.376 to 0.352 | 0.941 | 0.633 | 0.343 to 0.812 | 0.000 *** |
Caproic acid (hexanoic acid) | −0.312 | −0.571 to 0.005 | 0.047 * | 0.179 | −0.227 to 0.532 | 0.371 |
Eicosapentaenoic acid | 0.120 | −0.208 to 0.424 | 0.460 | 0.544 | 0.211 to 0.764 | 0.002 ** |
Hexadecanedioic acid | 0.169 | −0.160 to 0.464 | 0.297 | −0.421 | −0.684 to −0.060 | 0.021 * |
Lactic acid (2-hydroxypropanoic acid) | −0.149 | −0.444 to 0.176 | 0.353 | 0.316 | −0.085 to 0.628 | 0.109 |
Linoleic acid (octadecadienoic acid) | 0.357 | 0.042 to 0.608 | 0.024 * | −0.115 | −0.484 to 0.288 | 0.567 |
Methyl hexadecanoic acid | 0.127 | −0.312 to 0.522 | 0.562 | 0.597 | 0.261 to 0.804 | 0.001 ** |
MG(18:2(9,12)) | 0.124 | −0.204 to 0.427 | 0.446 | 0.554 | 0.231 to 0.767 | 0.002 ** |
Octadecadienal (9,12) | 0.189 | −0.244 to 0.559 | 0.378 | 0.523 | 0.175 to 0.755 | 0.004 ** |
Octadecenoic acid | 0.150 | −0.174 to 0.445 | 0.349 | −0.330 | −0.623 to 0.046 | 0.075 |
Palmitoleic acid (hexadecenoic acid) | 0.198 | −0.144 to 0.498 | 0.239 | −0.509 | −0.750 to −0.148 | 0.007 ** |
Pregnenolone | 0.280 | −0.044 to 0.551 | 0.080 | 0.629 | 0.330 to 0.813 | 0.000 *** |
Pyruvic acid (2-oxopropanoic acid) | −0.393 | −0.630 to −0.087 | 0.011 * | −0.183 | −0.535 to 0.223 | 0.361 |
Retinal | 0.333 | −0.057 to 0.635 | 0.083 | 0.553 | 0.207 to 0.776 | 0.003 ** |
Stearic acid (octadecanoic acid) | 0.466 | 0.168 to 0.687 | 0.003 ** | −0.106 | −0.476 to 0.297 | 0.601 |
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Perkovic, M.N.; Jaganjac, M.; Milkovic, L.; Horvat, T.; Rojo, D.; Zarkovic, K.; Ćorić, M.; Hudolin, T.; Waeg, G.; Orehovec, B.; et al. Relationship between 4-Hydroxynonenal (4-HNE) as Systemic Biomarker of Lipid Peroxidation and Metabolomic Profiling of Patients with Prostate Cancer. Biomolecules 2023, 13, 145. https://doi.org/10.3390/biom13010145
Perkovic MN, Jaganjac M, Milkovic L, Horvat T, Rojo D, Zarkovic K, Ćorić M, Hudolin T, Waeg G, Orehovec B, et al. Relationship between 4-Hydroxynonenal (4-HNE) as Systemic Biomarker of Lipid Peroxidation and Metabolomic Profiling of Patients with Prostate Cancer. Biomolecules. 2023; 13(1):145. https://doi.org/10.3390/biom13010145
Chicago/Turabian StylePerkovic, Matea Nikolac, Morana Jaganjac, Lidija Milkovic, Tea Horvat, David Rojo, Kamelija Zarkovic, Marijana Ćorić, Tvrtko Hudolin, Georg Waeg, Biserka Orehovec, and et al. 2023. "Relationship between 4-Hydroxynonenal (4-HNE) as Systemic Biomarker of Lipid Peroxidation and Metabolomic Profiling of Patients with Prostate Cancer" Biomolecules 13, no. 1: 145. https://doi.org/10.3390/biom13010145
APA StylePerkovic, M. N., Jaganjac, M., Milkovic, L., Horvat, T., Rojo, D., Zarkovic, K., Ćorić, M., Hudolin, T., Waeg, G., Orehovec, B., & Zarkovic, N. (2023). Relationship between 4-Hydroxynonenal (4-HNE) as Systemic Biomarker of Lipid Peroxidation and Metabolomic Profiling of Patients with Prostate Cancer. Biomolecules, 13(1), 145. https://doi.org/10.3390/biom13010145