Plasma metabolites as possible biomarkers for diagnosis of breast cancer

Autoři: Jiwon Park aff001;  Yumi Shin aff002;  Tae Hyun Kim aff001;  Dong-Hyun Kim aff002;  Anbok Lee aff001
Působiště autorů: Department of Surgery, Busan Paik Hospital, College of medicine, Inje University, Busan, Korea aff001;  Department of Pharmacology, College of medicine, Inje University, Busan, Korea aff002
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article


Metabolomic approaches have been used to identify new diagnostic biomarkers for various types of cancers, including breast cancer. In this study, we aimed to identify potential biomarkers of breast cancer using plasma metabolic profiling. Furthermore, we analyzed whether these biomarkers had relationships with clinicopathological characteristics of breast cancer. Our study used two liquid chromatography-mass spectrometry sets: a discovery set (40 breast cancer patients and 30 healthy controls) and a validation set (30 breast cancer patients and 16 healthy controls). All breast cancer patients were randomly selected from among stage I–III patients who underwent surgery between 2011 and 2016. First, metabolites distinguishing cancer patients from healthy controls were identified in the discovery set. Then, consistent and reproducible metabolites were evaluated in terms of their utility as possible biomarkers of breast cancer. Receiver operating characteristic (ROC) analysis was applied to the discovery set, and ROC cut-off values for the identified metabolites derived therein were applied to the validation set to determine their diagnostic performance. Ultimately, four candidate biomarkers (L-octanoylcarnitine, 5-oxoproline, hypoxanthine, and docosahexaenoic acid) were identified. L-octanoylcarnitine showed the best diagnostic performance, with a 100.0% positive predictive value. Also, L-octanoylcarnitine levels differed according to tumor size and hormone receptor expression. The plasma metabolites identified in this study show potential as biomarkers allowing early diagnosis of breast cancer. However, the diagnostic performance of the metabolites needs to be confirmed in further studies with larger sample sizes.

Klíčová slova:

Biomarkers – Blood plasma – Breast cancer – Cancer detection and diagnosis – Fatty acids – Metabolites – Metabolomics – NMR spectroscopy


1. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin. 2012;62(1):10–29. doi: 10.3322/caac.20138 22237781.

2. society AC. cancer facts & figures 2015. 2015:1–52.

3. McGuire S. World Cancer Report 2014. Geneva, Switzerland: World Health Organization, International Agency for Research on Cancer, WHO Press, 2015. Adv Nutr. 2016;7(2):418–9. doi: 10.3945/an.116.012211 WOS:000372672300018. 26980827

4. Haghighi F, Naseh G, Mohammadifard M, Abdollahi N. Comparison of mammography and ultrasonography findings with pathology results in patients with breast cancer in Birjand, Iran. Electron Physician. 2017;9(10):5494–8. doi: 10.19082/5494 29238489; PubMed Central PMCID: PMC5718853.

5. Vander Heiden MG. Targeting cancer metabolism: a therapeutic window opens. Nat Rev Drug Discov. 2011;10(9):671–84. doi: 10.1038/nrd3504 21878982.

6. Zhang J, Bowers J, Liu L, Wei S, Gowda GA, Hammoud Z, et al. Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods. PLoS One. 2012;7(1):e30181. doi: 10.1371/journal.pone.0030181 22291914; PubMed Central PMCID: PMC3264576.

7. Emwas AH. The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research. Methods Mol Biol. 2015;1277:161–93. doi: 10.1007/978-1-4939-2377-9_13 25677154.

8. Sumner LW, Mendes P, Dixon RA. Plant metabolomics: large-scale phytochemistry in the functional genomics era. Phytochemistry. 2003;62(6):817–36. doi: 10.1016/s0031-9422(02)00708-2 WOS:000181400800002. 12590110

9. Gunther UL. Metabolomics Biomarkers for Breast Cancer. Pathobiology. 2015;82(3–4):153–65. doi: 10.1159/000430844 WOS:000360934500006. 26330356

10. Qiu YP, Zhou BS, Su MM, Baxter S, Zheng XJ, Zhao XQ, et al. Mass Spectrometry-Based Quantitative Metabolomics Revealed a Distinct Lipid Profile in Breast Cancer Patients. Int J Mol Sci. 2013;14(4):8047–61. doi: 10.3390/ijms14048047 WOS:000318017100079. 23584023

11. Johnson CH, Manna SK, Krausz KW, Bonzo JA, Divelbiss RD, Hollingshead MG, et al. Global metabolomics reveals urinary biomarkers of breast cancer in a mcf-7 xenograft mouse model. Metabolites. 2013;3(3):658–72. doi: 10.3390/metabo3030658 24958144; PubMed Central PMCID: PMC3901288.

12. Jeong ES, Kim G, Shin HJ, Park S-M, Oh J-H, Kim Y-B, et al. Increased serum bile acid concentration following low-dose chronic administration of thioacetamide in rats, as evidenced by metabolomic analysis. 2015;288(2):213–22. doi: 10.1016/j.taap.2015.07.016 26222700

13. Sitter B, Bathen TF, Singstad TE, Fjosne HE, Lundgren S, Halgunset J, et al. Quantification of metabolites in breast cancer patients with different clinical prognosis using HR MAS MR spectroscopy. Nmr Biomed. 2010;23(4):424–31. doi: 10.1002/nbm.1478 WOS:000277525800012. 20101607

14. Asiago VM, Alvarado LZ, Shanaiah N, Gowda GAN, Owusu-Sarfo K, Ballas RA, et al. Early Detection of Recurrent Breast Cancer Using Metabolite Profiling. Cancer Res. 2010;70(21):8309–18. doi: 10.1158/0008-5472.CAN-10-1319 WOS:000283667300009. 20959483

15. Borgan E, Sitter B, Lingjaerde OC, Johnsen H, Lundgren S, Bathen TF, et al. Merging transcriptomics and metabolomics—advances in breast cancer profiling. Bmc Cancer. 2010;10. Artn 628 doi: 10.1186/1471-2407-10-628 WOS:000284874400002. 21080935

16. Asiago VM, Alvarado LZ, Shanaiah N, Gowda GN, Owusu-Sarfo K, Ballas RA, et al. Early detection of recurrent breast cancer using metabolite profiling. 2010;70(21):8309–18. doi: 10.1158/0008-5472.CAN-10-1319 20959483

17. Wei S, Liu L, Zhang J, Bowers J, Gowda GN, Seeger H, et al. Metabolomics approach for predicting response to neoadjuvant chemotherapy for breast cancer. 2013;7(3):297–307. doi: 10.1016/j.molonc.2012.10.003 23142658

18. Jobard E, Pontoizeau C, Blaise BJ, Bachelot T, Elena-Herrmann B, Trédan OJCl. A serum nuclear magnetic resonance-based metabolomic signature of advanced metastatic human breast cancer. 2014;343(1):33–41. doi: 10.1016/j.canlet.2013.09.011 24041867

19. Mikó E, Kovács T, Sebő É, Tóth J, Csonka T, Ujlaki G, et al. Microbiome—Microbial Metabolome—Cancer Cell Interactions in Breast Cancer—Familiar, but Unexplored. 2019;8(4):293.

20. Pietrzak I, Opala G. [The role of carnitine in human lipid metabolism]. Wiad Lek. 1998;51(1–2):71–5. 9608835.

21. Min HK, Kong G, Moon MH. Quantitative analysis of urinary phospholipids found in patients with breast cancer by nanoflow liquid chromatography-tandem mass spectrometry: II. Negative ion mode analysis of four phospholipid classes. Anal Bioanal Chem. 2010;396(3):1273–80. doi: 10.1007/s00216-009-3292-9 WOS:000273845200032. 19937430

22. Melone MAB, Valentino A, Margarucci S, Galderisi U, Giordano A, Peluso G. The carnitine system and cancer metabolic plasticity. Cell Death Dis. 2018;9. doi: ARTN 228 10.1038/s41419-018-0313-7. WOS:000427410000009.

23. Liu Y. Fatty acid oxidation is a dominant bioenergetic pathway in prostate cancer. Prostate Cancer P D. 2006;9(3):230–4. doi: 10.1038/sj.pcan.4500879 WOS:000240144800014. 16683009

24. Nomura DK, Long JZ, Niessen S, Hoover HS, Ng SW, Cravatt BF. Monoacylglycerol Lipase Regulates a Fatty Acid Network that Promotes Cancer Pathogenesis. Cell. 2010;140(1):49–61. doi: 10.1016/j.cell.2009.11.027 WOS:000273391900014. 20079333

25. Kang KS, Wang P, Yamabe N, Fukui M, Jay T, Zhu BT. Docosahexaenoic Acid Induces Apoptosis in MCF-7 Cells In Vitro and In Vivo via Reactive Oxygen Species Formation and Caspase 8 Activation. Plos One. 2010;5(4). ARTN e10296 doi: 10.1371/journal.pone.0010296 WOS:000276952600013. 20421971

26. Cao WQ, Ma ZF, Rasenick MM, Yeh SY, Yu JZ. N-3 Poly-Unsaturated Fatty Acids Shift Estrogen Signaling to Inhibit Human Breast Cancer Cell Growth. Plos One. 2012;7(12). ARTN e52838 doi: 10.1371/journal.pone.0052838 WOS:000313051500068. 23285198

27. Xiong A, Yu W, Tiwary R, Sanders BG, Kline K. Distinct roles of different forms of vitamin E in DHA-induced apoptosis in triple-negative breast cancer cells. Mol Nutr Food Res. 2012;56(6):923–34. doi: 10.1002/mnfr.201200027 22707267.

28. Hwang S-y, Kim T-H, Lee H-H, Kim HY, Seo J. Effect of Docosahexaenoic Acid (DHA) on Breast Cancer Cells. Kosin Medical Journal. 2015;30(2):103–7. doi: 10.7180/kmj.2015.30.2.103

29. Thamer NA SR, Faek A, Abd-Alammer R. Detection of Xanthine Oxidase IN Breast Cancer. Iraqi Journal of Cancer and Medical Genetics. 2013;6(2):145–7.

30. Kondo M, Yamaoka T, Honda S, Miwa Y, Katashima R, Moritani M, et al. The rate of cell growth is regulated by purine biosynthesis via ATP production and G(1) to S phase transition. J Biochem. 2000;128(1):57–64. doi: 10.1093/oxfordjournals.jbchem.a022730 WOS:000088081600007. 10876158

31. Kumar A, Bachhawat AK. Pyroglutamic acid: throwing light on a lightly studied metabolite. Curr Sci India. 2012;102(2):288–97. WOS:000299857300022.

32. Budczies J, Pfitzner BM, Gyorffy B, Winzer KJ, Radke C, Dietel M, et al. Glutamate enrichment as new diagnostic opportunity in breast cancer. Int J Cancer. 2015;136(7):1619–28. doi: 10.1002/ijc.29152 WOS:000348443400015. 25155347

33. Budczies J, Brockmoller SF, Muller BM, Barupal DK, Richter-Ehrenstein C, Kleine-Tebbe A, et al. Comparative metabolomics of estrogen receptor positive and estrogen receptor negative breast cancer: alterations in glutamine and beta-alanine metabolism. J Proteomics. 2013;94:279–88. doi: 10.1016/j.jprot.2013.10.002 WOS:000330493400020. 24125731

34. Kumar V, Abbas AK, Aster JC. Robbins and Cotran pathologic basis of disease. Ninth edition. ed. Philadelphia, PA: Elsevier/Saunders; 2015. xvi, 1391 pages p.

35. Hadi NI, Jamal Q, Iqbal A, Shaikh F, Somroo S, Musharraf SG. Serum Metabolomic Profiles for Breast Cancer Diagnosis, Grading and Staging by Gas Chromatography-Mass Spectrometry. Sci Rep. 2017;7(1):1715. doi: 10.1038/s41598-017-01924-9 28496143; PubMed Central PMCID: PMC5431835.

36. Hart CD, Vignoli A, Tenori L, Uy GL, To TV, Adebamowo C, et al. Serum Metabolomic Profiles Identify ER-Positive Early Breast Cancer Patients at Increased Risk of Disease Recurrence in a Multicenter Population. Clin Cancer Res. 2017;23(6):1422–31. doi: 10.1158/1078-0432.CCR-16-1153 WOS:000397344800009. 28082280

Článek vyšel v časopise


2019 Číslo 12
Nejčtenější tento týden