Altered gut metabolites and microbiota interactions are implicated in colorectal carcinogenesis and can be non-invasive diagnostic biomarkers
Tóm tắt
Gut microbiota contributes to colorectal cancer (CRC) pathogenesis through microbes and their metabolites. The importance of microbiota-associated metabolites in colorectal carcinogenesis highlights the need to investigate the gut metabolome along the adenoma-carcinoma sequence to determine their mechanistic implications in the pathogenesis of CRC. To date, how and which microbes and metabolites interactively promote early events of CRC development are still largely unclear. We aim to determine gut microbiota-associated metabolites and their linkage to colorectal carcinogenesis. We performed metabolomics and metagenomics profiling on fecal samples from 386 subjects including 118 CRC patients, 140 colorectal adenomas (CRA) patients and 128 healthy subjects as normal controls (NC). We identified differences in the gut metabolite profiles among NC, CRA and CRC groups by partial least squares-discriminant and principal component analyses. Among the altered metabolites, norvaline and myristic acid showed increasing trends from NC, through CRA, to CRC. CRC-associated metabolites were enriched in branched-chain amino acids, aromatic amino acids and aminoacyl-tRNA biosynthesis pathways. Moreover, metabolites marker signature (twenty metabolites) classified CRC from NC subjects with an area under the curve (AUC) of 0.80, and CRC from CRA with an AUC of 0.79. Integrative analyses of metabolomics and metagenomics profiles demonstrated that the relationships among CRC-associated metabolites and bacteria were altered across CRC stages; certain associations exhibited increasing or decreasing strengths while some were reversed from negative to positive or vice versa. Combinations of gut bacteria with the metabolite markers improved their diagnostic performances; CRC vs NC, AUC: 0.94; CRC vs CRA, AUC 0.92; and CRA vs NC, AUC: 0.86, indicating a potential for early diagnosis of colorectal neoplasia. This study underscores potential early-driver metabolites in stages of colorectal tumorigenesis. The Integrated metabolite and microbiome analysis demonstrates that gut metabolites and their association with gut microbiota are perturbed along colorectal carcinogenesis. Fecal metabolites can be utilized, in addition to bacteria, for non-invasive diagnosis of colorectal neoplasia.
Tài liệu tham khảo
Arthur JC, Jobin C. The struggle within: microbial influences on colorectal cancer: inflammatory bowel diseases. Inflamm Bowel Dis. 2011;17:396–409.
Hullar MAJ, Fu BC. Diet, the gut microbiome, and epigenetics. Cancer J. 2014;20:170–5.
Yang T, Owen JL, Lightfoot YL, Kladde MP, Mohamadzadeh M. Microbiota impact on the epigenetic regulation of colorectal cancer. Trends Mol Med. 2013;19:714–25.
Fraga MF, Ballestar E, Villar-Garea A, Boix-Chornet M, Espada J, Schotta G, et al. Loss of acetylation at Lys16 and trimethylation at Lys20 of histone H4 is a common hallmark of human cancer. Nat Genet. 2005;37:391–400.
Mima K, Nishihara R, Qian ZR, Cao Y, Sukawa Y, Nowak JA, et al. Fusobacterium nucleatum in colorectal carcinoma tissue and patient prognosis. Gut. 2016;65:1973–80.
Tetro JA. The human microbiome handbook. Lancaster: DEStech Publications, Inc; 2016.
Xu R, Wang Q, Li L. A genome-wide systems analysis reveals strong link between colorectal cancer and trimethylamine N-oxide (TMAO), a gut microbial metabolite of dietary meat and fat. BMC Genomics. 2015;16:S4.
Yazici C, Wolf PG, Kim H, Cross T-WL, Vermillion K, Carroll T, et al. Race-dependent association of sulfidogenic bacteria with colorectal cancer. Gut. 2017;66:1983–94.
Hale VL, Jeraldo P, Mundy M, Yao J, Keeney G, Scott N, et al. Synthesis of multi-omic data and community metabolic models reveals insights into the role of hydrogen sulfide in colon cancer. Methods. 2018;149:59–68.
Attene-Ramos MS, Wagner ED, Gaskins HR, Plewa MJ. Hydrogen sulfide induces direct radical-associated DNA damage. Mol Cancer Res. 2007;5:455–9.
Attene-Ramos MS, Nava GM, Muellner MG, Wagner ED, Plewa MJ, Gaskins HR. DNA damage and toxicogenomic analyses of hydrogen sulfide in human intestinal epithelial FHs 74 Int cells. Environ Mol Mutagen. 2010;51(4):304–14. https://doi.org/10.1002/em.20546.
Fung KYC, Cosgrove L, Lockett T, Head R, Topping DL. A review of the potential mechanisms for the lowering of colorectal oncogenesis by butyrate. Br J Nutr. 2012;108:820–31.
Smith PM, Howitt MR, Panikov N, Michaud M, Gallini CA, Bohlooly-Y M, et al. The microbial metabolites, short-chain fatty acids, regulate colonic treg cell homeostasis. Science. 2013;341:569–73.
Macfarlane GT, Macfarlane S. Fermentation in the human large intestine: its physiologic consequences and the potential contribution of prebiotics. J Clin Gastroenterol. 2011;45:S120–7.
Lightfoot YL, Yang T, Sahay B, Mohamadzadeh M. Targeting aberrant colon cancer-specific DNA methylation with lipoteichoic acid-deficient lactobacillus acidophilus. Gut Microbes. 2013;4:84–8.
Yachida S, Mizutani S, Shiroma H, Shiba S, Nakajima T, Sakamoto T, et al. Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer. Nat Med. 2019;25:968–76.
Weir TL, Manter DK, Sheflin AM, Barnett BA, Heuberger AL, Ryan EP. Stool microbiome and metabolome differences between colorectal Cancer patients and healthy adults. White BA, editor. PLoS One. 2013;8:e70803.
Sinha R, Ahn J, Sampson JN, Shi J, Yu G, Xiong X, et al. Fecal microbiota, fecal Metabolome, and colorectal Cancer interrelations. Cheah PY, editor. PLoS One. 2016;11:e0152126.
Wang X, Wang J, Rao B, Deng L. Gut flora profiling and fecal metabolite composition of colorectal cancer patients and healthy individuals. Exp Ther Med. 2017;13:2848–54.
Zhao L, Ni Y, Su M, Li H, Dong F, Chen W, et al. High throughput and quantitative measurement of microbial metabolome by gas chromatography/mass spectrometry using automated alkyl chloroformate derivatization. Anal Chem. 2017;89:5565–77.
Chong J, Wishart DS, Xia J. Using metaboanalyst 4.0 for comprehensive and integrative metabolomics data analysis. Curr Protoc Bioinformatics. 2019;68:e86 Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/cpbi.86. [cited 2020 Sep 3].
Rohart F, Gautier B, Singh A, Lê Cao K-A. mixOmics: an R package for ‘omics feature selection and multiple data integration. Schneidman D, editor. PLoS Comput Biol. 2017;13:e1005752.
Oksanen J, Blanchet FG, Friendly M, Kindt R. vegan: Community Ecology Package 2019. Available from: https://CRAN.R-project.org/package=vegan
Chong J, Yamamoto M, Xia J. Metabo analystR 2.0: from raw spectra to biological insights. Metabolites. 2019;9:57.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. 1995;57:289–300.
Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32:2847–9.
Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods. 2012;9:811–4.
Venables WN, Ripley BD, Venables WN. Modern applied statistics with S. 4th ed. New York: Springer; 2002.
Kuhn M. Building predictive models in R using the caret package. J Stat Soft. 2008;28(1):1–26 Available from: http://www.jstatsoft.org/v28/i05/. [cited 2020 Sep 3].
Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J-C, et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77.
Ternes D, Karta J, Tsenkova M, Wilmes P, Haan S, Letellier E. Microbiome in colorectal cancer: how to get from Meta-omics to mechanism? Trends Microbiol. 2020;28:401–23.
Wong SH, Kwong TNY, Chow T-C, Luk AKC, Dai RZW, Nakatsu G, et al. Quantitation of faecal Fusobacterium improves faecal immunochemical test in detecting advanced colorectal neoplasia. Gut. 2017;66:1441–8.
Erben V, Bhardwaj M, Schrotz-King P, Brenner H. Metabolomics biomarkers for detection of colorectal neoplasms: a systematic review. Cancers. 2018;10:246.
Vučetić M, Cormerais Y, Parks SK, Pouysségur J. The central role of amino acids in cancer redox homeostasis: vulnerability points of the cancer redox code. Front Oncol. 2017;7:319.
Vettore L, Westbrook RL, Tennant DA. New aspects of amino acid metabolism in cancer. Br J Cancer. 2020;122:150–6.
Lieu EL, Nguyen T, Rhyne S, Kim J. Amino acids in cancer. Exp Mol Med. 2020;52:15–30.
Choi B-H, Coloff JL. The diverse functions of non-essential amino acids in Cancer. Cancers. 2019;11:675.
Amelio I, Cutruzzolá F, Antonov A, Agostini M, Melino G. Serine and glycine metabolism in cancer. Trends Biochem Sci. 2014;39:191–8.
Burke L, Guterman I, Palacios Gallego R, Britton RG, Burschowsky D, Tufarelli C, et al. The Janus-like role of proline metabolism in cancer. Cell Death Discov. 2020;6:104.
Chang CI, Liao JC, Kuo L. Macrophage arginase promotes tumor cell growth and suppresses nitric oxide-mediated tumor cytotoxicity. Cancer Res. 2001;61:1100–6.
Ming X-F, Rajapakse AG, Carvas JM, Ruffieux J, Yang Z. Inhibition of S6K1 accounts partially for the anti-inflammatory effects of the arginase inhibitor L-norvaline. BMC Cardiovasc Disord. 2009;9:12.
Mamalakis G, Hatzis C, de Bree E, Sanidas E, Tsiftsis DD, Askoxylakis J, et al. Adipose tissue fatty acids in breast cancer patients versus healthy control women from Crete. Ann Nutr Metab. 2009;54:275–82.
Encarnação JC, Abrantes AM, Pires AS, Botelho MF. Revisit dietary fiber on colorectal cancer: butyrate and its role on prevention and treatment. Cancer Metastasis Rev. 2015;34:465–78.
Zhou Z, Sun B, Huang S, Yu D, Zhang X. Roles of aminoacyl-tRNA synthetase-interacting multi-functional proteins in physiology and cancer. Cell Death Dis. 2020;11:579.
Ananieva EA, Wilkinson AC. Branched-chain amino acid metabolism in cancer. Curr Opin Clin Nutr Metab Care. 2018;21:64–70.
Dodd D, Spitzer MH, Van Treuren W, Merrill BD, Hryckowian AJ, Higginbottom SK, et al. A gut bacterial pathway metabolizes aromatic amino acids into nine circulating metabolites. Nature. 2017;551:648–52.
Platten M, Nollen EAA, Röhrig UF, Fallarino F, Opitz CA. Tryptophan metabolism as a common therapeutic target in cancer, neurodegeneration and beyond. Nat Rev Drug Discov. 2019;18:379–401.
Wang H, Tso VK, Slupsky CM, Fedorak RN. Metabolomics and detection of colorectal cancer in humans: a systematic review. Future Oncol. 2010;6:1395–406.
Long X, Wong CC, Tong L, Chu ESH, Ho Szeto C, Go MYY, et al. Peptostreptococcus anaerobius promotes colorectal carcinogenesis and modulates tumour immunity. Nat Microbiol. 2019;4:2319–30.
Xie Y-H, Gao Q-Y, Cai G-X, Sun X-M, Zou T-H, Chen H-M, et al. Fecal clostridium symbiosum for noninvasive detection of early and advanced colorectal Cancer: test and validation studies. EBioMedicine. 2017;25:32–40.
Nicholson JK, Holmes E, Kinross J, Burcelin R, Gibson G, Jia W, et al. Host-gut microbiota metabolic interactions. Science. 2012;336(6086):1262–7. https://doi.org/10.1126/science.1223813.
Xie G, Wang L, Chen T, Zhou K, Zhang Z, Li J, et al. A metabolite Array technology for precision medicine. Anal Chem. 2021;93(14):5709–17. https://doi.org/10.1021/acs.analchem.0c04686 Epub 2021 Apr 2. PMID: 33797874.