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Hyperglycemia alters N-glycans on colon cancer cells through increased production of activated monosaccharides

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Abstract

Diabetes Mellitus (DM) is both, correlated and a known risk factor for colorectal cancer (CRC). Besides favoring the incidence of CRC, DM also accelerates its progression, worsening its prognosis. Previously, hyperglycemia, the DM hallmark, has been shown to lead to aberrant glycosylation of CRC cells, heightening their malignancy both in vivo and in vitro. Here we use mass spectrometry to elucidate the composition and putative structures of N-glycans expressed by MC38 cultured in normoglycemic (LG) and hyperglycemic-like conditions (HG). N-glycans, 67, were identified in MC38 cells cultured in LG and HG. The cells grown in HG showed a greater abundance of N-glycans when compared to LNG cells, without changes in the proportion of sialylated, fucosylated and mannosylated N-glycans. Among the identified N-glycans, 16 were differentially expressed, mostly mannosylated and fucosylated, with a minority of them being sialylated. Metabolomics analysis indicates that the alterations observed in the N-glycosylation may be mostly due to increase of the activated monosaccharides pool, through an increased glucose entrance into the cells. The alterations found here corroborate data from the literature regarding the progression of CRC, advocating for development or repositioning of effective treatments against CRC in diabetic patients.

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References

  1. Wild, S., et al.: Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 27(5), 1047–1053 (2004)

    Article  PubMed  Google Scholar 

  2. Vasconcelos-Dos-Santos, A., et al.: Hyperglycemia and aberrant O-GlcNAcylation: contributions to tumor progression. J Bioenerg Biomembr 50(3), 175–187 (2018)

    Article  CAS  PubMed  Google Scholar 

  3. Giovannucci, E., et al.: Diabetes and cancer: a consensus report. Diabetes Care 33(7), 1674–1685 (2010)

    Article  PubMed  PubMed Central  Google Scholar 

  4. Pearson-Stuttard, J., et al.: Trends in predominant causes of death in individuals with and without diabetes in England from 2001 to 2018: an epidemiological analysis of linked primary care records. Lancet Diabetes Endocrinol 9(3), 165–173 (2021)

    Article  PubMed  PubMed Central  Google Scholar 

  5. Song, M.: Cancer overtakes vascular disease as leading cause of excess death associated with diabetes. Lancet Diabetes Endocrinol 9(3), 131–133 (2021)

    Article  PubMed  Google Scholar 

  6. Lee, M.S., et al.: Type 2 diabetes increases and metformin reduces total, colorectal, liver and pancreatic cancer incidences in Taiwanese: a representative population prospective cohort study of 800,000 individuals. BMC Cancer 11, 20 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Wojciechowska, J., et al.: Diabetes and Cancer: a Review of Current Knowledge. Exp Clin Endocrinol Diabetes 124(5), 263–275 (2016)

    Article  CAS  PubMed  Google Scholar 

  8. Wu, L., et al.: Diabetes mellitus and the occurrence of colorectal cancer: an updated meta-analysis of cohort studies. Diabetes Technol Ther 15(5), 419–427 (2013)

    Article  PubMed  Google Scholar 

  9. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017.: Lancet 392(10159), 1789–1858 (2018)

  10. de Kort, S., et al.: Higher risk of colorectal cancer in patients with newly diagnosed diabetes mellitus before the age of colorectal cancer screening initiation. Sci Rep 7, 46527 (2017)

    Article  PubMed  PubMed Central  Google Scholar 

  11. Chang, S.C., Yang, W.V.: Hyperglycemia, tumorigenesis, and chronic inflammation. Crit Rev Oncol Hematol 108, 146–153 (2016)

    Article  PubMed  Google Scholar 

  12. Chen, H., et al.: Metabolic syndrome, metabolic comorbid conditions and risk of early-onset colorectal cancer. Gut 70(6), 1147–1154 (2021)

    Article  CAS  PubMed  Google Scholar 

  13. Erbach, M., Mehnert, H., Schnell, O.: Diabetes and the risk for colorectal cancer. J Diabetes Complications 26(1), 50–55 (2012)

    Article  PubMed  Google Scholar 

  14. Li, W., et al.: Effects of hyperglycemia on the progression of tumor diseases. J Exp Clin Cancer Res 38(1), 327 (2019)

    Article  PubMed  PubMed Central  Google Scholar 

  15. Wang, M., Yang, Y., Liao, Z.: Diabetes and cancer: Epidemiological and biological links. World J Diabetes 11(6), 227–238 (2020)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ferrer, C.M., Sodi, V.L., Reginato, M.J.: O-GlcNAcylation in Cancer Biology: Linking Metabolism and Signaling. J Mol Biol 428(16), 3282–3294 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Li, Z., Zhang, H.: Reprogramming of glucose, fatty acid and amino acid metabolism for cancer progression. Cell Mol Life Sci 73(2), 377–392 (2016)

    Article  CAS  PubMed  Google Scholar 

  18. Patra, K.C., Hay, N.: The pentose phosphate pathway and cancer. Trends Biochem Sci 39(8), 347–354 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Hakomori, S.: Glycosylation defining cancer malignancy: new wine in an old bottle. Proc Natl Acad Sci USA 99(16), 10231–10233 (2002)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Ichikawa, D., et al.: Molecular detection of disseminated cancer cells in the peripheral blood and expression of sialylated antigens in colon cancers. J Surg Oncol 75(2), 98–102 (2000)

    Article  CAS  PubMed  Google Scholar 

  21. Munkley, J., Elliott, D.J.: Hallmarks of glycosylation in cancer. Oncotarget 7(23), 35478–35489 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  22. Vajaria, B.N., Patel, P.S.: Glycosylation: a hallmark of cancer? Glycoconj J 34(2), 147–156 (2017)

    Article  CAS  PubMed  Google Scholar 

  23. Madigan, J.P., et al.: A role for ceramide glycosylation in resistance to oxaliplatin in colorectal cancer. Exp Cell Res 388(2), 111860 (2020)

  24. Very, N., Lefebvre, T., El Yazidi-Belkoura, I.: Drug resistance related to aberrant glycosylation in colorectal cancer. Oncotarget 9(1), 1380–1402 (2018)

    Article  PubMed  Google Scholar 

  25. Silsirivanit, A.: Glycosylation markers in cancer. Adv Clin Chem 89, 189–213 (2019)

    Article  CAS  PubMed  Google Scholar 

  26. Baldus, S.E., et al.: Comparative evaluation of the prognostic value of MUC1, MUC2, sialyl-Lewis(a) and sialyl-Lewis(x) antigens in colorectal adenocarcinoma. Histopathology 40(5), 440–449 (2002)

    Article  CAS  PubMed  Google Scholar 

  27. Hung, J.S., et al.: C1GALT1 overexpression promotes the invasive behavior of colon cancer cells through modifying O-glycosylation of FGFR2. Oncotarget 5(8), 2096–2106 (2014)

    Article  PubMed  PubMed Central  Google Scholar 

  28. Madunić, K., et al.: Colorectal cancer cell lines show striking diversity of their O-glycome reflecting the cellular differentiation phenotype. Cell Mol Life Sci 78(1), 337–350 (2021)

    Article  PubMed  CAS  Google Scholar 

  29. Balog, C.I., et al.: N-glycosylation of colorectal cancer tissues: a liquid chromatography and mass spectrometry-based investigation. Mol Cell Proteomics 11(9), 571–585 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Murata, K., et al.: Expression of N-acetylglucosaminyltransferase V in colorectal cancer correlates with metastasis and poor prognosis. Clin Cancer Res 6(5), 1772–1777 (2000)

    CAS  PubMed  Google Scholar 

  31. Vasconcelos-Dos-Santos, A., et al.: Hyperglycemia exacerbates colon cancer malignancy through hexosamine biosynthetic pathway. Oncogenesis 6(3), e306 (2017)

  32. Selman, M.H., et al.: Cotton HILIC SPE microtips for microscale purification and enrichment of glycans and glycopeptides. Anal Chem 83(7), 2492–2499 (2011)

    Article  CAS  PubMed  Google Scholar 

  33. Rodrigues Mantuano, N., et al.: Hyperglycemia Enhances Cancer Immune Evasion by Inducing Alternative Macrophage Polarization through Increased O-GlcNAcylation. Cancer Immunol Res 8(10), 1262–1272 (2020)

    Article  PubMed  Google Scholar 

  34. Ahn, E., et al.: Temporal fluxomics reveals oscillations in TCA cycle flux throughout the mammalian cell cycle. Mol Syst Biol 13(11), 953 (2017)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Wishart, D.S., et al.: HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res 46(D1), D608-d617 (2018)

  36. Pluskal, T., et al.: MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics 11, 395 (2010)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Myers, O.D., et al.: One Step Forward for Reducing False Positive and False Negative Compound Identifications from Mass Spectrometry Metabolomics Data: New Algorithms for Constructing Extracted Ion Chromatograms and Detecting Chromatographic Peaks. Anal Chem 89(17), 8696–8703 (2017)

    Article  CAS  PubMed  Google Scholar 

  38. Blanas, A., et al.: Transcriptional activation of fucosyltransferase (FUT) genes using the CRISPR-dCas9-VPR technology reveals potent N-glycome alterations in colorectal cancer cells. Glycobiology 29(2), 137–150 (2019)

    Article  CAS  PubMed  Google Scholar 

  39. Damerell, D., et al.: The GlycanBuilder and GlycoWorkbench glycoinformatics tools: updates and new developments. Biol Chem 393(11), 1357–1362 (2012)

    Article  CAS  PubMed  Google Scholar 

  40. Ceroni, A., et al.: GlycoWorkbench: a tool for the computer-assisted annotation of mass spectra of glycans. J Proteome Res 7(4), 1650–1659 (2008)

    Article  CAS  PubMed  Google Scholar 

  41. Stanley, P., Taniguchi, M., Aebi, M.: N-Glycans, in Essentials of Glycobiology, A. Varki, et al., Editors. Cold Spring Harbor Laboratory Press (2015). Copyright 2015–2017 by The Consortium of Glycobiology Editors, La Jolla, California. All rights reserved.: Cold Spring Harbor (NY). p. 99–111

  42. Leng, J.X., et al.: Cell engineering for the production of hybrid-type N-glycans in HEK293 cells. J Biochem 170(1), 139–151 (2021)

    Article  CAS  PubMed  Google Scholar 

  43. Jin, Z.C., et al.: Genetic disruption of multiple α1,2-mannosidases generates mammalian cells producing recombinant proteins with high-mannose-type N-glycans. J Biol Chem 293(15), 5572–5584 (2018)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Lau, K.S., et al.: Complex N-glycan number and degree of branching cooperate to regulate cell proliferation and differentiation. Cell 129(1), 123–134 (2007)

    Article  CAS  PubMed  Google Scholar 

  45. Holst, S., Wuhrer, M., Rombouts, Y.: Glycosylation characteristics of colorectal cancer. Adv Cancer Res 126, 203–256 (2015)

    Article  PubMed  CAS  Google Scholar 

  46. Pinho, S.S., Reis, C.A.: Glycosylation in cancer: mechanisms and clinical implications. Nat Rev Cancer 15(9), 540–555 (2015)

    Article  CAS  PubMed  Google Scholar 

  47. Saldova, R., et al.: Core fucosylation and alpha2-3 sialylation in serum N-glycome is significantly increased in prostate cancer comparing to benign prostate hyperplasia. Glycobiology 21(2), 195–205 (2011)

    Article  CAS  PubMed  Google Scholar 

  48. Pan, J., et al.: Glycoproteomics-based signatures for tumor subtyping and clinical outcome prediction of high-grade serous ovarian cancer. Nat Commun 11(1), 6139 (2020)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Zhu, B., et al.: The relationship between diabetes and colorectal cancer prognosis: A meta-analysis based on the cohort studies. PLoS One 12(4), e0176068 (2017)

  50. Coura, M.M.A., et al.: Identification of Differential N-Glycan Compositions in the Serum and Tissue of Colon Cancer Patients by Mass Spectrometry. Biology (Basel). 10(4), (2021)

  51. Tabang, D.N., Ford, M., Li, L.: Recent Advances in Mass Spectrometry-Based Glycomic and Glycoproteomic Studies of Pancreatic Diseases. Front Chem 9, 707387 (2021)

  52. de Haan, N., Wuhrer, M., Ruhaak, L.R.: Mass spectrometry in clinical glycomics: The path from biomarker identification to clinical implementation. Clin Mass Spectrom 18, 1–12 (2020)

    Article  PubMed  PubMed Central  Google Scholar 

  53. Abdel Rahman, A.M., et al.: Golgi N-glycan branching N-acetylglucosaminyltransferases I, V and VI promote nutrient uptake and metabolism. Glycobiology 25(2), 225–240 (2015)

    Article  CAS  PubMed  Google Scholar 

  54. Demetriou, M., et al.: Reduced contact-inhibition and substratum adhesion in epithelial cells expressing GlcNAc-transferase V. J Cell Biol 130(2), 383–392 (1995)

    Article  CAS  PubMed  Google Scholar 

  55. Nagae, M., et al.: Structure and mechanism of cancer-associated N-acetylglucosaminyltransferase-V. Nat Commun 9(1), 3380 (2018)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Takahashi, M., et al.: Core fucose and bisecting GlcNAc, the direct modifiers of the N-glycan core: their functions and target proteins. Carbohydr Res 344(12), 1387–1390 (2009)

    Article  CAS  PubMed  Google Scholar 

  57. Hanna, J., et al.: Protein Degradation and the Pathologic Basis of Disease. Am J Pathol 189(1), 94–103 (2019)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Zachara, N., Akimoto, Y., Hart, G.W.: The O-GlcNAc Modification, in Essentials of Glycobiology, A. Varki, et al., Editors. Cold Spring Harbor Laboratory Press (2015). Copyright 2015–2017 by The Consortium of Glycobiology Editors, La Jolla, California. All rights reserved.: Cold Spring Harbor (NY). 239–51

  59. Ramakrishnan, P., et al.: Activation of the transcriptional function of the NF-κB protein c-Rel by O-GlcNAc glycosylation. Sci Signal 6(290), ra75 (2013)

  60. Hanover, J.A., Krause, M.W., Love, D.C.: Bittersweet memories: linking metabolism to epigenetics through O-GlcNAcylation. Nat Rev Mol Cell Biol 13(5), 312–321 (2012)

    Article  CAS  PubMed  Google Scholar 

  61. Kuettel, S., et al.: The de novo and salvage pathways of GDP-mannose biosynthesis are both sufficient for the growth of bloodstream-form Trypanosoma brucei. Mol Microbiol 84(2), 340–351 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Yun, E.J., et al.: Biosynthetic Routes for Producing Various Fucosyl-Oligosaccharides. ACS Synth Biol 8(2), 415–424 (2019)

    Article  CAS  PubMed  Google Scholar 

  63. King, A., Selak, M.A., Gottlieb, E.: Succinate dehydrogenase and fumarate hydratase: linking mitochondrial dysfunction and cancer. Oncogene 25(34), 4675–4682 (2006)

    Article  CAS  PubMed  Google Scholar 

  64. Vasconcelos-Dos-Santos, A., et al.: Biosynthetic Machinery Involved in Aberrant Glycosylation: Promising Targets for Developing of Drugs Against Cancer. Front Oncol 5, 138 (2015)

    Article  PubMed  PubMed Central  Google Scholar 

  65. Ryan, D.G., et al.: Coupling Krebs cycle metabolites to signalling in immunity and cancer. Nat Metab 1, 16–33 (2019)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Mills, E.L., et al.: Itaconate is an anti-inflammatory metabolite that activates Nrf2 via alkylation of KEAP1. Nature 556(7699), 113–117 (2018)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Michelucci, A., et al.: Immune-responsive gene 1 protein links metabolism to immunity by catalyzing itaconic acid production. Proc Natl Acad Sci USA 110(19), 7820–7825 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Cheng, S.C., et al.: mTOR- and HIF-1α-mediated aerobic glycolysis as metabolic basis for trained immunity. Science 345(6204), 1250684 (2014)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Mak, P.A., et al.: A high-throughput screen to identify inhibitors of ATP homeostasis in non-replicating Mycobacterium tuberculosis. ACS Chem Biol 7(7), 1190–1197 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Frizzell, N., et al.: Succination of thiol groups in adipose tissue proteins in diabetes: succination inhibits polymerization and secretion of adiponectin. J Biol Chem 284(38), 25772–25781 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Nagai, R., et al.: Succination of protein thiols during adipocyte maturation: a biomarker of mitochondrial stress. J Biol Chem 282(47), 34219–34228 (2007)

    Article  CAS  PubMed  Google Scholar 

  72. Laukka, T., et al.: Fumarate and Succinate Regulate Expression of Hypoxia-inducible Genes via TET Enzymes. J Biol Chem 291(8), 4256–4265 (2016)

    Article  CAS  PubMed  Google Scholar 

  73. Kuo, C.Y., et al.: HIF-1-alpha links mitochondrial perturbation to the dynamic acquisition of breast cancer tumorigenicity. Oncotarget 7(23), 34052–34069 (2016)

    Article  PubMed  PubMed Central  Google Scholar 

  74. Sciacovelli, M., et al.: Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition. Nature 537(7621), 544–547 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Tsai, J.H., Yang, J.: Epithelial-mesenchymal plasticity in carcinoma metastasis. Genes Dev 27(20), 2192–2206 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Alisson-Silva, F., et al.: Increase of O-glycosylated oncofetal fibronectin in high glucose-induced epithelial-mesenchymal transition of cultured human epithelial cells. PLoS One 8(4). e60471 (2013)

  77. Mroueh, F.M., et al.: Unmasking the interplay between mTOR and Nox4: novel insights into the mechanism connecting diabetes and cancer. Faseb j 33(12), 14051–14066 (2019)

    Article  CAS  PubMed  Google Scholar 

  78. Moloughney, J.G., et al.: mTORC2 Responds to Glutamine Catabolite Levels to Modulate the Hexosamine Biosynthesis Enzyme GFAT1. Mol Cell 63(5), 811–826 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Gabbay, K.H.: The sorbitol pathway and the complications of diabetes. N Engl J Med 288(16), 831–836 (1973)

    Article  CAS  PubMed  Google Scholar 

  80. Hamada, Y., et al.: Rapid formation of advanced glycation end products by intermediate metabolites of glycolytic pathway and polyol pathway. Biochem Biophys Res Commun 228(2), 539–543 (1996)

    Article  CAS  PubMed  Google Scholar 

  81. Lorenzi, M.: The polyol pathway as a mechanism for diabetic retinopathy: attractive, elusive, and resilient. Exp Diabetes Res 2007, 61038 (2007)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

This work was supported by funding Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, to H.F. Loponte), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, to A.R. Todeschini and W.B. Dias), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ, to A.R. Todeschini, Mohana-Borges, F. Alisson-Silva and W.B. Dias), and Fundação do Câncer (to W.B. Dias). The authors thank the Centro de Espectrometria de Massas de Biomoléculas (CEMBIO) and Plataforma de Imuno-análise (PIA; UFRJ, Rio de Janeiro, Brazil).

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Authors and Affiliations

  1. Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, 21941-902, Rio de Janeiro, Brazil

    H. F. Loponte, I. A. Oliveira, R. Mohana-Borges, W. B. Dias & A. R. Todeschini

  2. Instituto de Biodiversidade e Sustentabilidade, Universidade Federal do Rio de Janeiro, 27965‑550, Macaé, Brazil

    B. C. Rodrigues & R. Nunes-da-Fonseca

  3. Instituto de Microbiologia Paulo de Goes, Universidade Federal do Rio de Janeiro, 21941-902, Rio de Janeiro, Brazil

    H. F. Loponte & F. Alisson-Silva

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  1. H. F. Loponte
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Contributions

H.F. Loponte was responsible for cell culture, sample preparation of N-glycans and metabolites, data analysis of N-glycomics and metabolomics, data interpretation and manuscript writing and reviewing. I.A. Oliveira assisted in sample preparation of metabolites, data acquisition in MS equipment, metabolomics data analysis, data interpretation and manuscript writing and reviewing. B.C. Rodrigues and R. Nunes-da-Fonseca were responsible for qRT-PCR essays and its data analysis. R. Mohana-Borges, F. Alisson-Silva and W.B. Dias assisted in data interpretation, manuscript reviewing and funding. A.R. Todeschini assisted in data interpretation, manuscript writing and reviewing and funding.

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10719_2022_10057_MOESM1_ESM.xlsx

Supplementary file1 (Fig. S1 Representative spectra from MC38 cells cultured in HG, first identified m/z and putative structures of purified N-glycans sample. (A). Average spectrum of GlycanPac AXR column LC retention time from 1-4 minutes containing solely non-sialylated N-glycans; (B). Average spectrum of GlycanPak LC retention time from 4-9 minutes containing solely monosialylated N-glycans; (C). Average spectrum of GlycanPak LC retention time from 12-16 mins (from m/z 800 to 1000, light blue) containing solely disialylated N-glycans and from 19-23 mins (from m/z 1000 to 1100, dark blue) containing solely disialylated N-glycans. In the structure, blue square: GlcNAc; green circle: mannose; yellow circle: galactose; red triangle: fucose; blank circle: hexose. XLSX 30 KB)

10719_2022_10057_MOESM2_ESM.xlsx

Supplementary file2 (Fig. S2 MC38 cells cultured in HG have different expression of N-glycans and can be differentiated solely by this feature, when compared to LG. (A). Bar graph comparing the 5 most differentially expressed hybrid N-glycans between HG and LG conditions. (B) Box-plot of the relative differential expression of the 20 significantly differentially expressed N-glycans. (C). Bar graph comparing the overall levels of Tri- and Tetra-Antennary complex N-glycans in MC38 cells cultured in LG and HG. n=3 (*p<0.05; **p<0.01; ***p<0.001). Mean ±SEM on bar graphs. XLSX 184 KB)

Supplementary file3 (PPTX 293 KB)

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Loponte, H.F., Oliveira, I.A., Rodrigues, B.C. et al. Hyperglycemia alters N-glycans on colon cancer cells through increased production of activated monosaccharides. Glycoconj J 39, 663–675 (2022). https://doi.org/10.1007/s10719-022-10057-9

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