Skip to main content
SpringerLink
Log in

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

  • Research Paper
  • Published:
Analytical and Bioanalytical Chemistry Aims and scope Submit manuscript

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

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

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

References

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

  5. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2017. CA Cancer J Clin. 2017;67(1):7–30.

    Article  PubMed  Google Scholar 

  6. Grunt TW. Interacting cancer machineries: cell signaling, lipid metabolism, and epigenetics. Trends Endocrinol Metab. 2018;29(2):86–98.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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. 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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  17. Bligh EG, Dyer WJ. A rapid method of total lipid extraction and purification. Can J Biochem Physiol. 1959;37(8):91–7.

    Article  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed Central  Google Scholar 

  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. 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.

    Article  CAS  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  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.

Download references

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).

Author information

Authors and Affiliations

  1. Department of Clinical Pharmacology, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China

    Tong Liu, Feng Peng, Jing Yu, Zhirong Tan, Tai Rao, Yao Chen, Yicheng Wang, Zhaoqian Liu, Honghao Zhou & Jingbo Peng

  2. Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, 111 Xiangya Road, Changsha, 410078, Hunan, China

    Tong Liu, Feng Peng, Jing Yu, Zhirong Tan, Tai Rao, Yao Chen, Yicheng Wang, Zhaoqian Liu, Honghao Zhou & Jingbo Peng

  3. Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, 111 Xiangya Road, Changsha, 410078, Hunan, China

    Tong Liu, Feng Peng, Jing Yu, Zhirong Tan, Tai Rao, Yao Chen, Yicheng Wang, Zhaoqian Liu, Honghao Zhou & Jingbo Peng

  4. National Clinical Research Center for Geriatric Disorders, 87 Xiangya Road, Changsha, 410008, Hunan, China

    Tong Liu, Feng Peng, Jing Yu, Zhirong Tan, Tai Rao, Yao Chen, Yicheng Wang, Zhaoqian Liu, Honghao Zhou & Jingbo Peng

Authors
  1. Tong Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Feng Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jing Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Zhirong Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tai Rao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yao Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yicheng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Zhaoqian Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Honghao Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jingbo Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Zhirong Tan or Jingbo Peng.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(PDF 417 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, T., Peng, F., Yu, J. et al. LC-MS-based lipid profile in colorectal cancer patients: TAGs are the main disturbed lipid markers of colorectal cancer progression. Anal Bioanal Chem 411, 5079–5088 (2019). https://doi.org/10.1007/s00216-019-01872-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00216-019-01872-5

Keywords

Search

Navigation