References
1. Araghi M, et al. Global trends in colorectal cancer mortality: projections to the year 2035. J. Cancer. 2019; 144: 2992-3000.
2. Lin, J.S.; Piper, M.A.; Perdue, L.A.; Rutter, C.M.; Webber, E.M.; O’Connor, E.; Smith, N.; Whitlock, E.P. Screening for Colorectal Cancer: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. Am. Med. Assoc. 2016; 315: 2576–2594.
3. Bray F, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer. Clin. 2018; 68: 394-424.
4. Guren MG. The global challenge of colorectal cancer. Lancet Gastroenterol. Hepatol. 2019; 4: 894-895.
5. Morano F, Sclafani F. Duration of first-line treatment for metastatic colorectal cancer: Translating the available evidence into general recommendations for routine practice. Rev. Oncol. Hematol. 2018; 131: 53-65.
6. Illiano P, et al. The mutual interplay of gut microbiota, diet and human disease. FEBS J. 2020; 287: 833-855.
7. Das V, et al. Predictive and prognostic biomarkers in colorectal cancer: A systematic review of recent advances and challenges. Pharmacother. 2017; 87: 8-19.
8. Cheung AH, et al. Latest development of liquid biopsy. Thorac. Dis. 2018; 10: S1645-S1651.
9. Maierthaler M, et al. Plasma miR-122 and miR-200 family are prognostic markers in colorectal cancer. J. Cancer. 2017; 140: 176-187.
10. Galamb O, et al. Diagnostic and prognostic potential of tissue and circulating long non-coding RNAs in colorectal tumors. World Gastroenterol. 2019; 25: 5026-5048.
11. Wishart, D. S. Emerging applications of metabolomics in drug discovery and precision medicine. Rev. Drug Discov. 2016; 15(7): 473-484.
12. Vignoli, A. et al. High-Throughput Metabolomics by 1D NMR. Chem., Int. Ed. 2019; 58(4): 968-994.
13. Takis, P.G. et al. Uniqueness of the NMR Approach to Metabolomics. Trac-Trends Anal. Chem. 2019; 120: 115300.
14. Gu J, et al. Metabolomics analysis in serum from patients with colorectal polyp and colorectal cancer by 1H-NMR spectrometry. Markers. 2019; 3491852.
15. Zamani Z, et al. A metabolic study on colon cancer using 1H nuclear magnetic resonance spectroscopy. Res. Int. 2014; 2014: 1-7.
16. Hu R, et al. NMR-based metabolomics in cancer research. Springer; 2021: 201-218.
17. Jiménez B, et al. 1H HR-MAS NMR spectroscopy of tumor-induced local metabolic “field-effects” enables colorectal cancer staging and prognostication. Proteome Res. 2013;12(2): 959-968.
18. Monleón D, et al. Metabolite profiling of fecal water extracts from human colorectal cancer. NMR Biomed. 2009; 22(3): 342-348.
19. Bezabeh, T. et al. Detecting colorectal cancer by 1H magnetic resonance spectroscopy of fecal extracts. NMR Biomed. 2009, 22, 593−600.
20. Brezmes, J. et al. Urine NMR Metabolomics for Precision Oncology in Colorectal Cancer. J. Mol. Sci. 2022; 23(19): 11171.
21. Wang, Z. et al. J. NMR-Based Metabolomic Techniques Identify Potential Urinary Biomarkers for Early Colorectal Cancer Detection. Oncotarget 2017; 8: 105819–10583.
22. Kim, E.R. et al. Urine-NMR Metabolomics for Screening of Advanced Colorectal Adenoma and Early Stage Colorectal Cancer. Rep. 2019; 9: 4786.
23. Eisner, R. et al. Machine-Learned Predictor of Colonic Polyps Based on Urinary Metabolomics. Res. Int. 2013; 2013: 303982.
24. Liesenfeld, D.B. et al. Changes in Urinary Metabolic Profiles of Colorectal Cancer Patients Enrolled in a Prospective Cohort Study (ColoCare). Metabolomics 2015; 11: 998–1012.
25. Vahabi F, et al. Staging of colorectal cancer using serum metabolomics with 1H NMR spectroscopy. Iran J. Basic Med. Sci. 2017; 20(7): 835-840.
26. Martín-Blázquez A, et al. Untargeted LC-HRMS-based metabolomics to identify novel biomarkers of metastatic colorectal cancer. Rep. 2019; 9(1): 20198.
27. Tristán, AI. et al. Serum nuclear magnetic resonance metabolomics analysis of human metastatic colorectal cancer: Biomarkers and pathway analysis. NMR Biomed. 2023, e4935, 1-17.
28. Salmerón AM. et al. Serum colorectal cancer biomarkers unraveled by NMR metabolomics: past, present, and future. Anal Chem. 2022; 9(1): 417-430.
29. Rath, C. M. & Dorrestein, P. C. The bacterial chemical repertoire mediates metabolic exchange within gut microbiomes. Microbiol. 2012; 15: 147–154.
30. Rinninella, E. et al. What is the Healthy Gut Microbiota Composition? A Changing Ecosystem across Age, Environment, Diet, and Diseases. Microorganisms 2019; 7: 14.
31. Valdes, A. M. et al. Role of the gut microbiota in nutrition and health. BMJ 2018, 361: k2179.
32. Dalal, N. et al. Gut microbiota-derived metabolites in CRC progression and causation. Cancer Res. Clin. Oncol. 2021; 147, 3141–3155.
33. Feng, Q. et al. Gut Microbiota: An Integral Moderator in Health and Disease. Microbiol. 2018; 9, 151.
34. Sinha A. et al. Systematic Review and Meta-Analysis: Taurine and Its Association With Colorectal Carcinoma. Cancer Med. 2024; 13: e70424.
35. Baidoun, F. et al. Colorectal Cancer Epidemiology: Recent Trends and Impact on Outcomes. Curr. Drug Targets 2021; 22: 998–1009.
36. Siegel, R. L. et al. Colorectal cancer statistics, 2020. CA. Cancer J. Clin. 2020; 70: 145–164.
37. Hultcrantz, R. Aspects of colorectal cancer screening, methods, age and gender. Intern. Med.; 2021, 289: 493–507.
38. Beckonert O. et al. Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Protoc. 2007; 2(11): 2692-2703.
39. Tristán, AI. et al. Metabolomic profiling of COVID-19 using serum and urine samples in intensive care and medical ward cohorts, Rep. 2024; 14: 23713.
40. Abreu, AC. et al. NMR-based Metabolomics and Fatty Acid Profiles to Unravel Biomarkers in Preclinical Animal Models of Compulsive Behavior. Proteome Res. 2022; 21: 612–622.
41. Salmerón AM. et al. Urinary metabolic biomarkers of attentional control in children with Attention-Deficit/Hyperactivity Disorder: a dimensional approach through 1H NMR-based metabolomics. NMR Biomed. 2025, submitted.
42. Ruiz-Sobremazas, D. et al. From Nutritional Patterns to Behavior: High-Fat Diet Influences on Inhibitory Control, Brain Gene Expression, and Metabolomics in Rats. ACS Chem. Neurosci. 2024; 15: 4369−4382.
43. Salmerón, AM. et al. Exploring microbiota-gut-brain axis biomarkers linked to autism spectrum disorder in prenatally chlorpyrifos-exposed Fmr1 knock-out and wild-type male rats. Toxicology 2024; 506: 153871.
44. Salmerón, AM. et al. Solution NMR in human embryo culture media as an option for assessment of embryo implantation potential. NMR Biomed. 2021; 34: e4536.