Metabolic Phenotyping to Monitor Chronic Enteritis Canceration

Overview

Journal Metabolomics

Publisher Springer

Specialty Endocrinology

Date 2020 Feb 26

PMID 32095917

Citations 1

Authors

Fan Zhang

ChunBo Li

Kui Deng

Zhuozhong Wang

Weiwei Zhao

Kai Yang

Chunyan Yang

Zhiwei Rong

Lei Cao

Yaxin Lu

Yue Huang

Peng Han

Kang Li

Affiliations

Soon will be listed here.

Abstract

Introduction: Colorectal cancer (CRC) remains an incurable disease. Previous metabolomic studies show that metabolic signatures in plasma distinguish CRC patients from healthy controls. Chronic enteritis (CE) represents a risk factor for CRC, with a 20 fold greater incidence than in healthy individuals. However, no studies have performed metabolomic profiling to investigate CRC biomarkers in CE.

Objective: Our aims were to identify metabolomic signatures in CRC and CE and to search for blood-derived metabolite biomarkers distinguishing CRC from CE, especially early-stage biomarkers.

Methods: In this case-control study, 612 subjects were prospectively recruited between May 2015 and May 2016, and including 539 CRC patients (stage I, 102 cases; stage II, 259 cases; stage III, 178 cases) and 73 CE patients. Untargeted metabolomics was performed to identify CRC-related metabolic signatures in CE.

Results: Five pathways were significantly enriched based on 153 differential metabolites between CRC and CE. 16 biomarkers were identified for diagnosis of CRC from CE and for guiding CRC staging. The AUC value for CRC diagnosis in the external validation set was 0.85. Good diagnostic performances were also achieved for early-stage CRC (stage I and stage II), with an AUC value of 0.84. The biomarker panel could also stage CRC patients, with an AUC of 0.72 distinguishing stage I from stage II CRC and AUC of 0.74 distinguishing stage II from stage III CRC.

Conclusions: The identified metabolic biomarkers exhibit promising properties for CRC monitoring in CE patients and are superior to commonly used clinical biomarkers (CEA and CA19-9).

Citing Articles

Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review.

Yu C, Farhat Z, Livinski A, Loftfield E, Zanetti K Cancer Epidemiol Biomarkers Prev. 2023; 32(9):1130-1145.

PMID: 37410086 PMC: 10472112. DOI: 10.1158/1055-9965.EPI-23-0045.

References

Smith C, Want E, OMaille G, Abagyan R, Siuzdak G . XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal Chem. 2006; 78(3):779-87. DOI: 10.1021/ac051437y. View

Meyerhardt J, Mayer R . Systemic therapy for colorectal cancer. N Engl J Med. 2005; 352(5):476-87. DOI: 10.1056/NEJMra040958. View

Phua L, Chue X, Koh P, Cheah P, Ho H, Chan E . Non-invasive fecal metabonomic detection of colorectal cancer. Cancer Biol Ther. 2014; 15(4):389-97. PMC: 3979816. DOI: 10.4161/cbt.27625. View

Platten M, Wick W, Van den Eynde B . Tryptophan catabolism in cancer: beyond IDO and tryptophan depletion. Cancer Res. 2012; 72(21):5435-40. DOI: 10.1158/0008-5472.CAN-12-0569. View

Edge S, Compton C . The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010; 17(6):1471-4. DOI: 10.1245/s10434-010-0985-4. View

Dowling P, Hughes D, Larkin A, Meiller J, Henry M, Meleady P . Elevated levels of 14-3-3 proteins, serotonin, gamma enolase and pyruvate kinase identified in clinical samples from patients diagnosed with colorectal cancer. Clin Chim Acta. 2014; 441:133-41. DOI: 10.1016/j.cca.2014.12.005. View

Cheng Y, Xie G, Chen T, Qiu Y, Zou X, Zheng M . Distinct urinary metabolic profile of human colorectal cancer. J Proteome Res. 2011; 11(2):1354-63. DOI: 10.1021/pr201001a. View

Ni Y, Xie G, Jia W . Metabonomics of human colorectal cancer: new approaches for early diagnosis and biomarker discovery. J Proteome Res. 2014; 13(9):3857-70. DOI: 10.1021/pr500443c. View

Liesenfeld D, Habermann N, Toth R, Owen R, Frei E, Staffa J . Changes in urinary metabolic profiles of colorectal cancer patients enrolled in a prospective cohort study (ColoCare). Metabolomics. 2017; 11(4):998-1012. PMC: 5730072. DOI: 10.1007/s11306-014-0758-3. View

10.

Jimenez B, Mirnezami R, Kinross J, Cloarec O, Keun H, Holmes E . 1H HR-MAS NMR spectroscopy of tumor-induced local metabolic "field-effects" enables colorectal cancer staging and prognostication. J Proteome Res. 2012; 12(2):959-68. DOI: 10.1021/pr3010106. View

11.

Derdak Z, Mark N, Beldi G, Robson S, Wands J, Baffy G . The mitochondrial uncoupling protein-2 promotes chemoresistance in cancer cells. Cancer Res. 2008; 68(8):2813-9. PMC: 2386271. DOI: 10.1158/0008-5472.CAN-08-0053. View

12.

Wang H, Tso V, Slupsky C, Fedorak R . Metabolomics and detection of colorectal cancer in humans: a systematic review. Future Oncol. 2010; 6(9):1395-406. DOI: 10.2217/fon.10.107. View

13.

Tan B, Qiu Y, Zou X, Chen T, Xie G, Cheng Y . Metabonomics identifies serum metabolite markers of colorectal cancer. J Proteome Res. 2013; 12(6):3000-9. PMC: 5902797. DOI: 10.1021/pr400337b. View

14.

Farshidfar F, Weljie A, Kopciuk K, Hilsden R, McGregor S, Buie W . A validated metabolomic signature for colorectal cancer: exploration of the clinical value of metabolomics. Br J Cancer. 2016; 115(7):848-57. PMC: 5046202. DOI: 10.1038/bjc.2016.243. View

15.

Chan E, Koh P, Mal M, Cheah P, Eu K, Backshall A . Metabolic profiling of human colorectal cancer using high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy and gas chromatography mass spectrometry (GC/MS). J Proteome Res. 2008; 8(1):352-61. DOI: 10.1021/pr8006232. View

16.

Ke C, Hou Y, Zhang H, Fan L, Ge T, Guo B . Large-scale profiling of metabolic dysregulation in ovarian cancer. Int J Cancer. 2014; 136(3):516-26. DOI: 10.1002/ijc.29010. View

17.

Nicholson J, Lindon J . Systems biology: Metabonomics. Nature. 2008; 455(7216):1054-6. DOI: 10.1038/4551054a. View

18.

Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M . Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2014; 136(5):E359-86. DOI: 10.1002/ijc.29210. View

19.

Li F, Qin X, Chen H, Qiu L, Guo Y, Liu H . 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. 2012; 27(1):24-34. DOI: 10.1002/rcm.6420. View

20.

Mayerle J, Kalthoff H, Reszka R, Kamlage B, Peter E, Schniewind B . Metabolic biomarker signature to differentiate pancreatic ductal adenocarcinoma from chronic pancreatitis. Gut. 2017; 67(1):128-137. PMC: 5754849. DOI: 10.1136/gutjnl-2016-312432. View