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LC-MS-based lipid profile in colorectal cancer patients: TAGs are the main disturbed lipid markers of colorectal cancer progression

  • Tong Liu
  • Feng Peng
  • Jing Yu
  • Zhirong TanEmail author
  • Tai Rao
  • Yao Chen
  • Yicheng Wang
  • Zhaoqian Liu
  • Honghao Zhou
  • Jingbo PengEmail author
Research Paper

Abstract

Colorectal cancer (CRC) is one of the most common causes of cancer-related death worldwide. Emerging evidence has shown that lipid metabolism plays important roles in the occurrence and progression of CRC. The identification of potential biomarkers for CRC progression is critical for precise diagnosis and treatment. Therefore, the aim of this study is to explore the potential lipid markers in relation to CRC progression. The plasma of patients with stage I/II CRC (n = 20) and stage III/IV CRC (n = 20) was collected. Lipidomic screening was performed by ultrahigh-performance liquid chromatography–mass spectrometry. After multivariate data analysis, including orthogonal partial least squares discriminant analysis, determination of the fold change, and the Mann–Whitney U test, eight lipid species with altered levels with p < 0.05 and fold change greater than 2 were selected as potential lipid biomarkers. Compared with patients with early-stage CRC, patients with advanced-stage CRC showed significantly higher levels of cholesteryl ester (20:4) and some triglycerides with a saturated fatty acid chain and a lower level of fatty acid ester of hydroxy fatty acid 27:1 (9:0-18:1) in plasma. Furthermore, the receiver operating characteristic including these potential lipid biomarkers yielded a sensitivity of 85% and specificity of 80% for separation of early-stage CRC patients from advanced-stage CRC patients. In all, this is the first report showing that the levels of triglycerides, the major contents of lipid droplets, increase in plasma of advanced-stage CRC patients compared with early-stage CRC patients. These data indicate that lipid droplets may be target organelles for the study of CRC progression and treatment.

Graphical abstract

Keywords

Colorectal cancer Lipid profile Triglyceride lipids Ultrahigh-performance liquid chromatography–mass spectrometry Biomarkers 

Abbreviations

ACAT

Acylcoenzyme A:cholesterol acyltransferase

ATGL

Adipose triglyceride lipase

CE

Cholesteryl ester

CRC

Colorectal cancer

DGAT

Diacylglycerol acyltransferase

ESI

Electrospray ionization

FAHFA

Fatty acid ester of hydroxy fatty acid

FFA

Free fatty acid

HPLC

High-performance liquid chromatography

LPC

Lysophosphatidylcholine

LPE

Lysophosphatidylethanolamine

MS

Mass spectrometry

OPLS-DA

Orthogonal partial least squares discriminant analysis

PC

Phosphatidylcholine

PE

Phosphatidylethanolamine

PI

Phosphatidylinositol

QC

Quality control

TAG

Triacylglycerol

TOF

Time of flight

UHPLC

Ultrahigh-performance liquid chromatography

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (no. 81403086), the Fundamental Research Funds for the Central Universities of Central South University (no. 2018zzts901), and the Natural Science Foundation of Hunan Province, China (no. 2018JJ4020).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

Supplementary material

216_2019_1872_MOESM1_ESM.pdf (418 kb)
ESM 1 (PDF 417 kb)

References

  1. 1.
    Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.CrossRefGoogle Scholar
  2. 2.
    Arnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global patterns and trends in colorectal cancer incidence and mortality. Gut. 2017;66(4):683–91.CrossRefGoogle Scholar
  3. 3.
    Allison JE. The effect of fecal occult-blood screening on the incidence of colorectal cancer. N Engl J Med. 2001;344(13):1022–3.CrossRefGoogle Scholar
  4. 4.
    Taylor DP, Cannon-Albright LA, Sweeney C, Williams MS, Haug PJ, Mitchell JA, Burt RW. Comparison of compliance for colorectal cancer screening and surveillance by colonoscopy based on risk. Genet Med. 2011;13(8):737−43.Google Scholar
  5. 5.
    Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67(1):7–30.CrossRefGoogle Scholar
  6. 6.
    Grunt TW. Interacting cancer machineries: cell signaling, lipid metabolism, and epigenetics. Trends Endocrinol Metab. 2018;29(2):86–98.CrossRefGoogle Scholar
  7. 7.
    Wen YA, Xing X, Harris JW, Zaytseva YY, Mitov MI, Napier DL, et al. Adipocytes activate mitochondrial fatty acid oxidation and autophagy to promote tumor growth in colon cancer. Cell Death Dis. 2017;8(2):e2593.CrossRefGoogle Scholar
  8. 8.
    Rossin D, Calfapietra S, Sottero B, Poli G, Biasi F. HNE and cholesterol oxidation products in colorectal inflammation and carcinogenesis. Free Radic Biol Med. 2017.  https://doi.org/10.1016/j.freeradbiomed.2017.01.017.
  9. 9.
    Hussain A, Qazi AK, Mupparapu N, Guru SK, Kumar A, Sharma PR, et al. Modulation of glycolysis and lipogenesis by novel PI3K selective molecule represses tumor angiogenesis and decreases colorectal cancer growth. Cancer Lett. 2016;374(2):250–60.CrossRefGoogle Scholar
  10. 10.
    Li S, Guo B, Song JW, Deng XL, Cong YS, Li PF, et al. Plasma choline-containing phospholipids: potential biomarkers for colorectal cancer progression. Metabolomics. 2013;9(1):202–12.CrossRefGoogle Scholar
  11. 11.
    Zhao Z, Xiao Y, Elson P, Tan H, Plummer SJ, Berk M, et al. Plasma lysophosphatidylcholine levels: potential biomarkers for colorectal cancer. J Clin Oncol. 2007;25(19):2696–701.CrossRefGoogle Scholar
  12. 12.
    Mirnezami R, Spagou K, Vorkas PA, Lewis MR, Kinross J, Want E, et al. Chemical mapping of the colorectal cancer microenvironment via MALDI imaging mass spectrometry (MALDI-MSI) reveals novel cancer-associated field effects. Mol Oncol. 2014;8(1):39–49.CrossRefGoogle Scholar
  13. 13.
    Li F, Qin X, Chen H, Qiu L, Guo Y, Liu H, et al. Lipid profiling for early diagnosis and progression of colorectal cancer using direct-infusion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. Rapid Commun Mass Spectrom. 2013;27(1):24–34.CrossRefGoogle Scholar
  14. 14.
    Crotti S, Agnoletto E, Cancemi G, Di Marco V, Traldi P, Pucciarelli S, et al. Altered plasma levels of decanoic acid in colorectal cancer as a new diagnostic biomarker. Anal Bioanal Chem. 2016;408(23):6321–8.CrossRefGoogle Scholar
  15. 15.
    Triebl A, Trötzmüller M, Hartler J, Stojakovic T, Köfeler HC. Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples. J Chromatogr B. 2017;1053:72–80.CrossRefGoogle Scholar
  16. 16.
    Zhang Q, Xu H, Liu R, Gao P, Yang X, Jin W, et al. A Novel Strategy for Targeted Lipidomics Based on LC-tandem-MS parameters prediction, quantification, and multiple statistical data mining: evaluation of lysophosphatidylcholines as potential cancer biomarkers. Anal Chem. 2019;91(5):3389–96.CrossRefGoogle Scholar
  17. 17.
    Bligh EG, Dyer WJ. A rapid method of total lipid extraction and purification. Can J Biochem Physiol. 1959;37(8):91–7.CrossRefGoogle Scholar
  18. 18.
    Tsugawa H, Cajka T, Kind T, Ma Y, Higgins B, Ikeda K, et al. MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis. Nat Methods. 2015;12(6):523–6.CrossRefGoogle Scholar
  19. 19.
    Gika HG, Macpherson E, Theodoridis GA, Wilson ID. Evaluation of the repeatability of ultra-performance liquid chromatography-TOF-MS for global metabolic profiling of human urine samples. J Chromatogr B. 2008;871(2):299–305.CrossRefGoogle Scholar
  20. 20.
    Want EJ, Wilson ID, Gika H, Theodoridis G, Plumb RS, Shockcor J, et al. Global metabolic profiling procedures for urine using UPLC-MS. Nat Protoc. 2010;5(6):1005–18.CrossRefGoogle Scholar
  21. 21.
    Zhang J, Zhang L, Ye X, Chen L, Zhang L, Gao Y, et al. Characteristics of fatty acid distribution is associated with colorectal cancer prognosis. Prostaglandins Leukot Essent Fatty Acids. 2013;88(5):355–60.CrossRefGoogle Scholar
  22. 22.
    Zhao Z, Xiao Y, Elson P, Tan H, Plummer SJ, Berk M, et al. Plasma lysophosphatidylcholine levels: potential biomarkers for colorectal cancer. J Clin Oncol. 2007;25(19):2696–701.CrossRefGoogle Scholar
  23. 23.
    Dobrzyńska I, Szachowicz-Petelska B, Sulkowski S, Figaszewski Z. Changes in electric charge and phospholipids composition in human colorectal cancer cells. Mol Cell Biochem. 2005;276(1-2):113–9.CrossRefGoogle Scholar
  24. 24.
    Hao B, Yu M, Sang C, Bi B, Chen J. Dyslipidemia and non-small cell lung cancer risk in Chinese population: a case-control study. Lipids Health Dis. 2018;17(1):278.CrossRefGoogle Scholar
  25. 25.
    Li Z, Guan M, Lin Y, Cui X, Zhang Y, Zhao Z, et al. Aberrant lipid metabolism in hepatocellular carcinoma revealed by liver lipidomics. Int J Mol Sci. 2017;18(12):2550.  https://doi.org/10.3390/ijms18122550.CrossRefGoogle Scholar
  26. 26.
    Di Leo L, Vegliante R, Ciccarone F, Salvatori I, Scimeca M, Bonanno E, et al. Forcing ATGL expression in hepatocarcinoma cells imposes glycolytic rewiring through PPAR-α/p300-mediated acetylation of p53. Oncogene. 2018.  https://doi.org/10.1038/s41388-018-0545-0.
  27. 27.
    Petan T, Jarc E, Jusović M. Lipid droplets in cancer: guardians of fat in a stressful world. Molecules. 2018;23(8):1941.  https://doi.org/10.3390/molecules23081941.CrossRefGoogle Scholar
  28. 28.
    Cotte AK, Aires V, Fredon M, Limagne E, Derangère V, Thibaudin M, et al. Lysophosphatidylcholine acyltransferase 2-mediated lipid droplet production supports colorectal cancer chemoresistance. Nat Commun. 2018;9(1):322.CrossRefGoogle Scholar
  29. 29.
    Mitra R, Le TT, Gorjala P, Goodman OB Jr. Positive regulation of prostate cancer cell growth by lipid droplet forming and processing enzymes DGAT1 and ABHD5. BMC Cancer. 2017;17(1):631.CrossRefGoogle Scholar
  30. 30.
    Zhang X, Saarinen AM, Hitosugi T, Wang Z, Wang L, Ho TH, et al. Inhibition of intracellular lipolysis promotes human cancer cell adaptation to hypoxia. Elife. 2017:001.  https://doi.org/10.7554/eLife.31132.
  31. 31.
    Yang D, Li Y, Xing L, Tan Y, Sun J, Zeng B, et al. Utilization of adipocyte-derived lipids and enhanced intracellular trafficking of fatty acids contribute to breast cancer progression. Cell Commun Signal. 2018;16(1):32.CrossRefGoogle Scholar
  32. 32.
    Chen G, Zhou G, Aras S, He Z, Lucas S, Podgorski I, et al. Loss of ABHD5 promotes the aggressiveness of prostate cancer cells. Sci Rep. 2017;7(1):13021.CrossRefGoogle Scholar
  33. 33.
    Ye K, Wu Y, Sun Y, Lin J, Xu J. TLR4 siRNA inhibits proliferation and invasion in colorectal cancer cells by downregulating ACAT1 expression. Life Sci. 2016.  https://doi.org/10.1016/j.lfs.2016.05.012.
  34. 34.
    Yue S, Li J, Lee SY, Lee HJ, Shao T, Song B, et al. Cholesteryl ester accumulation induced by PTEN loss and PI3K/AKT activation underlies human prostate cancer aggressiveness. Cell Metab. 2014;19(3):393–406.CrossRefGoogle Scholar
  35. 35.
    Yore MM, Syed I, Moraes-Vieira PM, Zhang T, Herman MA, Homan EA, et al. Discovery of a class of endogenous mammalian lipids with anti-diabetic and anti-inflammatory effects. Cell. 2014;159(2):318–32.CrossRefGoogle Scholar
  36. 36.
    Zhu QF, Yan JW, Gao Y, Zhang JW, Yuan BF, Feng YQ. Highly sensitive determination of fatty acid esters of hydroxyl fatty acids by liquid chromatography-mass spectrometry. J Chromatogr B. 2017.  https://doi.org/10.1016/j.jchromb.2017.06.045.

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Tong Liu
    • 1
    • 2
    • 3
    • 4
  • Feng Peng
    • 1
    • 2
    • 3
    • 4
  • Jing Yu
    • 1
    • 2
    • 3
    • 4
  • Zhirong Tan
    • 1
    • 2
    • 3
    • 4
    Email author
  • Tai Rao
    • 1
    • 2
    • 3
    • 4
  • Yao Chen
    • 1
    • 2
    • 3
    • 4
  • Yicheng Wang
    • 1
    • 2
    • 3
    • 4
  • Zhaoqian Liu
    • 1
    • 2
    • 3
    • 4
  • Honghao Zhou
    • 1
    • 2
    • 3
    • 4
  • Jingbo Peng
    • 1
    • 2
    • 3
    • 4
    Email author
  1. 1.Department of Clinical Pharmacology, Xiangya HospitalCentral South UniversityChangshaChina
  2. 2.Institute of Clinical Pharmacology, Hunan Key Laboratory of PharmacogeneticsCentral South UniversityChangshaChina
  3. 3.Engineering Research Center of Applied Technology of PharmacogenomicsMinistry of EducationChangshaChina
  4. 4.National Clinical Research Center for Geriatric DisordersChangshaChina

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