Generic placeholder image

Anti-Cancer Agents in Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1871-5206
ISSN (Online): 1875-5992

Research Article

Targeting Breast Cancer with N-Acetyl-D-Glucosamine: Integrating Machine Learning and Cellular Assays for Promising Results

Author(s): Ömür Baysal*, Deniz Genç, Ragıp Soner Silme, Kevser Kübra Kırboğa, Dilek Çoban, Naeem Abdul Ghafoor, Leyla Tekin and Osman Bulut

Volume 24, Issue 5, 2024

Published on: 05 January, 2024

Page: [334 - 347] Pages: 14

DOI: 10.2174/0118715206270568231129054853

Price: $65

Open Access Journals Promotions 2
Abstract

Background: Breast cancer is a common cancer with high mortality rates. Early diagnosis is crucial for reducing the prognosis and mortality rates. Therefore, the development of alternative treatment options is necessary.

Objective: This study aimed to investigate the inhibitory effect of N-acetyl-D-glucosamine (D-GlcNAc) on breast cancer using a machine learning method. The findings were further confirmed through assays on breast cancer cell lines.

Methods: MCF-7 and 4T1 cell lines (ATCC) were cultured in the presence and absence of varying concentrations of D-GlcNAc (0.5 mM, 1 mM, 2 mM, and 4 mM) for 72 hours. A xenograft mouse model for breast cancer was established by injecting 4T1 cells into mammary glands. D-GlcNAc (2 mM) was administered intraperitoneally to mice daily for 28 days, and histopathological effects were evaluated at pre-tumoral and post-tumoral stages.

Results: Treatment with 2 mM and 4 mM D-GlcNAc significantly decreased cell proliferation rates in MCF-7 and 4T1 cell lines and increased Fas expression. The number of apoptotic cells was significantly higher than untreated cell cultures (p < 0.01 - p < 0.0001). D-GlcNAc administration also considerably reduced tumour size, mitosis, and angiogenesis in the post-treatment group compared to the control breast cancer group (p < 0.01 - p < 0.0001). Additionally, molecular docking/dynamic analysis revealed a high binding affinity of D-GlcNAc to the marker protein HER2, which is involved in tumour progression and cell signalling.

Conclusion: Our study demonstrated the positive effect of D-GlcNAc administration on breast cancer cells, leading to increased apoptosis and Fas expression in the malignant phenotype. The binding affinity of D-GlcNAc to HER2 suggests a potential mechanism of action. These findings contribute to understanding D-GlcNAc as a potential anti-tumour agent for breast cancer treatment.

Keywords: Anti-tumour agent, apoptosis, breast cancer, fas expression, molecular docking, N-acetyl-D-glucosamine.

Graphical Abstract
[1]
Lovrics, O.; Butt, J.; Lee, Y.; Lovrics, P.; Boudreau, V.; Anvari, M.; Hong, D.; Doumouras, A.G. The effect of bariatric surgery on breast cancer incidence and characteristics: A meta-analysis and systematic review. Am. J. Surg., 2021, 222(4), 715-722.
[http://dx.doi.org/10.1016/j.amjsurg.2021.03.016] [PMID: 33771341]
[2]
Maughan, K.L.; Lutterbie, M.A.; Ham, P.S. Treatment of breast cancer. Am. Fam. Physician, 2010, 81(11), 1339-1346.
[PMID: 20521754]
[3]
Bhushan, A.; Gonsalves, A.; Menon, J.U. Current state of breast cancer diagnosis, treatment, and theranostics. Pharmaceutics, 2021, 13(5), 723.
[http://dx.doi.org/10.3390/pharmaceutics13050723] [PMID: 34069059]
[4]
Liang, Y.; Xu, W.; Liu, S.; Chi, J.; Zhang, J.; Sui, A.; Wang, L.; Liang, Z.; Li, D.; Chen, Y.; Niu, H. N-acetyl-glucosamine sensitizes non-small cell lung cancer cells to trail-induced apoptosis by activating death receptor 5. Cell. Physiol. Biochem., 2018, 45(5), 2054-2070.
[http://dx.doi.org/10.1159/000488042] [PMID: 29533936]
[5]
Mattaveewong, T.; Wongkrasant, P.; Chanchai, S.; Pichyangkura, R.; Chatsudthipong, V.; Muanprasat, C. Chitosan oligosaccharide suppresses tumor progression in a mouse model of colitis-associated colorectal cancer through AMPK activation and suppression of NF-κB and mTOR signaling. Carbohydr. Polym., 2016, 145, 30-36.
[http://dx.doi.org/10.1016/j.carbpol.2016.02.077] [PMID: 27106148]
[6]
Medina, S.H.; Tekumalla, V.; Chevliakov, M.V.; Shewach, D.S.; Ensminger, W.D.; El-Sayed, M.E.H. N-acetylgalactosamine-functionalized dendrimers as hepatic cancer cell-targeted carriers. Biomaterials, 2011, 32(17), 4118-4129.
[http://dx.doi.org/10.1016/j.biomaterials.2010.11.068] [PMID: 21429574]
[7]
Stowell, S.R.; Ju, T.; Cummings, R.D. Protein glycosylation in cancer. Annu. Rev. Pathol., 2015, 10(1), 473-510.
[http://dx.doi.org/10.1146/annurev-pathol-012414-040438] [PMID: 25621663]
[8]
Varki, A.; Kannagi, R.; Toole, B.; Stanley, P. Glycosylation changes in cancer. In: Essentials of Glycobiology, 3rd ed.; Varki, A.; Cummings, R.D.; Esko, J.D.; Stanley, P.; Hart, G.W.; Aebi, M.; Darvill, A.G.; Kinoshita, T.; Packer, N.H.; Prestegard, J.H., Eds.; Cold Spring Harbor Laboratory Press: Cold Spring Harbor (NY), 2015; pp. 597-609.
[9]
Chou, T.Y.; Hart, G.W. O-linked N-acetylglucosamine and cancer: Messages from the glycosylation of c-Myc. Adv. Exp. Med. Biol., 2001, 491, 413-418.
[http://dx.doi.org/10.1007/978-1-4615-1267-7_26] [PMID: 14533811]
[10]
Baysal, Ö.; Silme, R.; Karaaslan, C. Genetic uniformity of a specific region in SARS-CoV-2 genome and in-silico target-oriented repurposing of N-Acetyl-D-Glucosamine Preprints, 2020, 2020050397.
[http://dx.doi.org/10.20944/preprints202005.0397.v1]
[11]
Baysal, Ö.; Silme, R.; Karaaslan, C.; Ignatov, A. Genetic uniformity of a specific region in SARS-CoV-2 genome and repurposing of N-acetyl-D-glucosamine. Fresenius Environ. Bull., 2021, 30, 2848-2857.
[12]
Baysal, Ö.; Abdul Ghafoor, N.; Silme, R.S.; Ignatov, A.N.; Kniazeva, V. Molecular dynamics analysis of N-acetyl-D-glucosamine against specific SARS-CoV-2’s pathogenicity factors. PLoS One, 2021, 16(5), e0252571.
[http://dx.doi.org/10.1371/journal.pone.0252571] [PMID: 34043733]
[13]
Schultz, M.J.; Swindall, A.F.; Bellis, S.L. Regulation of the metastatic cell phenotype by sialylated glycans. Cancer Metastasis Rev., 2012, 31(3-4), 501-518.
[http://dx.doi.org/10.1007/s10555-012-9359-7] [PMID: 22699311]
[14]
Buehring, G.C.; Shen, H.M.; Jensen, H.M.; Jin, D.L.; Hudes, M.; Block, G. Exposure to bovine leukemia virus is associated with breast cancer: A case-control study. PLoS One, 2015, 10(9), e0134304.
[http://dx.doi.org/10.1371/journal.pone.0134304] [PMID: 26332838]
[15]
Melana, S.M.; Nepomnaschy, I.; Hasa, J.; Djougarian, A.; Djougarian, A.; Holland, J.F.; Pogo, B.G.T. Detection of human mammary tumor virus proteins in human breast cancer cells. J. Virol. Methods, 2010, 163(1), 157-161.
[http://dx.doi.org/10.1016/j.jviromet.2009.09.015] [PMID: 19781575]
[16]
Tsai, J.H.; Hsu, C.S.; Tsai, C.H.; Su, J.M.; Liu, Y.T.; Cheng, M.H.; Wei, J.C.C.; Chen, F.L.; Yang, C.C. Relationship between viral factors, axillary lymph node status and survival in breast cancer. J. Cancer Res. Clin. Oncol., 2006, 133(1), 13-21.
[http://dx.doi.org/10.1007/s00432-006-0141-5] [PMID: 16865407]
[17]
Joshi, D.; Quadri, M.; Gangane, N.; Joshi, R.; Gangane, N. Association of Epstein Barr virus infection (EBV) with breast cancer in rural Indian women. PLoS One, 2009, 4(12), e8180.
[http://dx.doi.org/10.1371/journal.pone.0008180] [PMID: 19997605]
[18]
Fawzy, S.; Sallam, M.; Mohammad, A. N. Detection of Epstein–Barr virus in breast carcinoma in Egyptian women. Clin. Biochem., 2008, 41(7-8), 486-492.
[http://dx.doi.org/10.1016/j.clinbiochem.2007.12.017] [PMID: 18258188]
[19]
Hachana, M.; Amara, K.; Ziadi, S.; Romdhane, E.; Gacem, R.B.; Trimeche, M. Investigation of Epstein–Barr virus in breast carcinomas in Tunisia. Pathol. Res. Pract., 2011, 207(11), 695-700.
[http://dx.doi.org/10.1016/j.prp.2011.09.007] [PMID: 22024152]
[20]
Harkins, L.E.; Matlaf, L.A.; Soroceanu, L.; Klemm, K.; Britt, W.J.; Wang, W.; Bland, K.I.; Cobbs, C.S. Detection of human cytomegalovirus in normal and neoplastic breast epithelium. Herpesviridae, 2010, 1(1), 8.
[http://dx.doi.org/10.1186/2042-4280-1-8] [PMID: 21429243]
[21]
Taher, C.; de Boniface, J.; Mohammad, A.A.; Religa, P.; Hartman, J.; Yaiw, K.C.; Frisell, J.; Rahbar, A.; Söderberg-Naucler, C. High prevalence of human cytomegalovirus proteins and nucleic acids in primary breast cancer and metastatic sentinel lymph nodes. PLoS One, 2013, 8(2), e56795.
[http://dx.doi.org/10.1371/journal.pone.0056795] [PMID: 23451089]
[22]
Costa, H.; Touma, J.; Davoudi, B.; Benard, M.; Sauer, T.; Geisler, J.; Vetvik, K.; Rahbar, A.; Söderberg-Naucler, C. Human cytomegalovirus infection is correlated with enhanced cyclooxygenase-2 and 5-lipoxygenase protein expression in breast cancer. J. Cancer Res. Clin. Oncol., 2019, 145(8), 2083-2095.
[http://dx.doi.org/10.1007/s00432-019-02946-8] [PMID: 31203442]
[23]
Yang, Z.; Tang, X.; Meng, G.; Benesch, M.; Mackova, M.; Belon, A.; Serrano-Lomelin, J.; Goping, I.; Brindley, D.; Hemmings, D. Latent cytomegalovirus infection in female mice increases breast cancer metastasis. Cancers, 2019, 11(4), 447.
[http://dx.doi.org/10.3390/cancers11040447] [PMID: 30934926]
[24]
Alibek, K.; Kakpenova, A.; Mussabekova, A.; Sypabekova, M.; Karatayeva, N. Role of viruses in the development of breast cancer. Infect. Agent. Cancer, 2013, 8(1), 32.
[http://dx.doi.org/10.1186/1750-9378-8-32] [PMID: 24138789]
[25]
Richardson, A. Is breast cancer caused by late exposure to a common virus? Med. Hypotheses, 1997, 48(6), 491-497.
[http://dx.doi.org/10.1016/S0306-9877(97)90118-3] [PMID: 9247892]
[26]
Shamshirian, A.; Aref, A.R.; Yip, G.W.; Ebrahimi, W.M.; Heydari, K.; Razavi, B.S.; Hamzehgardeshi, Z.; Shamshirian, D.; Moosazadeh, M.; Alizadeh-Navaei, R. Diagnostic value of serum HER2 levels in breast cancer: A systematic review and meta-analysis. BMC Cancer, 2020, 20(1), 1049.
[http://dx.doi.org/10.1186/s12885-020-07545-2] [PMID: 33129287]
[27]
Pro, O. HER2 in Breast Cancer: ESMO biomarker factsheet. 2015. Available from: https://oncologypro.esmo.org/education-library/factsheets-on-biomarkers/her2-in-breast-cancer (Accessed on: 2023).
[28]
Borgquist, S.; Zhou, W.; Jirström, K.; Amini, R.M.; Sollie, T.; Sørlie, T.; Blomqvist, C.; Butt, S.; Wärnberg, F. The prognostic role of HER2 expression in ductal breast carcinoma in situ (DCIS); a population-based cohort study. BMC Cancer, 2015, 15(1), 468.
[http://dx.doi.org/10.1186/s12885-015-1479-3] [PMID: 26062614]
[29]
Ignatov, T.; Eggemann, H.; Burger, E.; Fettke, F.; Costa, S.D.; Ignatov, A. Moderate level of HER2 expression and its prognostic significance in breast cancer with intermediate grade. Breast Cancer Res. Treat., 2015, 151(2), 357-364.
[http://dx.doi.org/10.1007/s10549-015-3407-2] [PMID: 25926338]
[30]
Chiu, M.; Taurino, G.; Bianchi, M.G.; Kilberg, M.S.; Bussolati, O. Asparagine synthetase in cancer: Beyond acute lymphoblastic leukemia. Front. Oncol., 2020, 9, 1480.
[http://dx.doi.org/10.3389/fonc.2019.01480] [PMID: 31998641]
[31]
Shen, X.; Jain, A.; Aladelokun, O.; Yan, H.; Gilbride, A.; Ferrucci, L.M.; Lu, L.; Khan, S.A.; Johnson, C.H. Asparagine, colorectal cancer, and the role of sex, genes, microbes, and diet: A narrative review. Front. Mol. Biosci., 2022, 9, 958666.
[http://dx.doi.org/10.3389/fmolb.2022.958666] [PMID: 36090030]
[32]
Davidsen, K.; Sullivan, L.B. Free asparagine or die: Cancer cells require proteasomal protein breakdown to survive asparagine depletion. Cancer Discov., 2020, 10(11), 1632-1634.
[http://dx.doi.org/10.1158/2159-8290.CD-20-1251]
[33]
Gaulton, A.; Hersey, A.; Nowotka, M.; Bento, A.P.; Chambers, J.; Mendez, D.; Mutowo, P.; Atkinson, F.; Bellis, L.J.; Cibrián-Uhalte, E. The ChEMBL database in 2017. Nucleic Acids Res., 2017, 45(D1), D945-D954.
[http://dx.doi.org/10.1093/nar/gkw1074]
[34]
Jaeger, S.; Fulle, S.; Turk, S. Mol2vec: Unsupervised machine learning approach with chemical intuition. J. Chem. Inf. Model., 2018, 58(1), 27-35.
[http://dx.doi.org/10.1021/acs.jcim.7b00616] [PMID: 29268609]
[35]
Huang, K.; Fu, T.; Glass, L.M.; Zitnik, M.; Xiao, C.; Sun, J. DeepPurpose: A deep learning library for drug–target interaction prediction. Bioinformatics, 2021, 36(22-23), 5545-5547.
[http://dx.doi.org/10.1093/bioinformatics/btaa1005] [PMID: 33275143]
[36]
RDKit: Open-source cheminformatics 2022. Available from: https://www.rdkit.org/
[37]
Pedregosa, F.; Varoquaux, G.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M.; Prettenhofer, P.; Weiss, R.; Dubourg, V. Scikit-learn: Machine learning in python. J. Mach. Learn. Res., 2011, 12, 2825-2830.
[38]
Pedregosa, F.; Varoquaux, G.e.; Gramfort, A.; Michel, V.; Thirion, B.; Grisel, O.; Blondel, M. Scikit-learn: Machine Learning in Python; Dataquest, 2018.
[39]
Cucina, A.; Proietti, S.; D’Anselmi, F.; Coluccia, P.; Dinicola, S.; Frati, L.; Bizzarri, M. Evidence for a biphasic apoptotic pathway induced by melatonin in MCF-7 breast cancer cells. J. Pineal Res., 2009, 46(2), 172-180.
[http://dx.doi.org/10.1111/j.1600-079X.2008.00645.x] [PMID: 19175854]
[40]
Matera, G.; Lupi, M.; Ubezio, P. Heterogeneous cell response to topotecan in a CFSE-based proliferation test. Cytometry A, 2004, 62A(2), 118-128.
[http://dx.doi.org/10.1002/cyto.a.20097] [PMID: 15536634]
[41]
Pulaski, B. A.; Ostrand-Rosenberg, S. Mouse 4T1 breast tumor model. Curr. Protocols Immunol., 2000, 39(1), 20.22.21-20.22.16.
[http://dx.doi.org/10.1002/0471142735.im2002s39]
[42]
Zheng, L.; Zhou, B.; Meng, X.; Zhu, W.; Zuo, A.; Wang, X.; Jiang, R.; Yu, S. A model of spontaneous mouse mammary tumor for human estrogen receptor- and progesterone receptor-negative breast cancer. Int. J. Oncol., 2014, 45(6), 2241-2249.
[http://dx.doi.org/10.3892/ijo.2014.2657] [PMID: 25230850]
[43]
Morris, G.M.; Huey, R.; Lindstrom, W.; Sanner, M.F.; Belew, R.K.; Goodsell, D.S.; Olson, A.J. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J. Comput. Chem., 2009, 30(16), 2785-2791.
[http://dx.doi.org/10.1002/jcc.21256] [PMID: 19399780]
[44]
Trott, O.; Olson, A.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem., 2010, 31(2), 455-461.
[http://dx.doi.org/10.1002/jcc.21334] [PMID: 19499576]
[45]
Grosdidier, A.; Zoete, V.; Michielin, O. SwissDock, a proteinsmall molecule docking web service based on EADock DSS. Nucleic Acids Res, 2011, 39(Web Server issue), W270-277.
[http://dx.doi.org/10.1093/nar/gkr366]
[46]
Phillips, J.C.; Hardy, D.J.; Maia, J.D.C.; Stone, J.E.; Ribeiro, J.V.; Bernardi, R.C.; Buch, R.; Fiorin, G.; Hénin, J.; Jiang, W.; McGreevy, R.; Melo, M.C.R.; Radak, B.K.; Skeel, R.D.; Singharoy, A.; Wang, Y.; Roux, B.; Aksimentiev, A.; Luthey-Schulten, Z.; Kalé, L.V.; Schulten, K.; Chipot, C.; Tajkhorshid, E. Scalable molecular dynamics on CPU and GPU architectures with NAMD. J. Chem. Phys., 2020, 153(4), 044130.
[http://dx.doi.org/10.1063/5.0014475] [PMID: 32752662]
[47]
Huang, J.; Rauscher, S.; Nawrocki, G.; Ran, T.; Feig, M.; de Groot, B.L.; Grubmüller, H.; MacKerell, A.D., Jr CHARMM36m: An improved force field for folded and intrinsically disordered proteins. Nat. Methods, 2017, 14(1), 71-73.
[http://dx.doi.org/10.1038/nmeth.4067] [PMID: 27819658]
[48]
Lee, J.; Cheng, X.; Swails, J.M.; Yeom, M.S.; Eastman, P.K.; Lemkul, J.A.; Wei, S.; Buckner, J.; Jeong, J.C.; Qi, Y.; Jo, S.; Pande, V.S.; Case, D.A.; Brooks, C.L., III; MacKerell, A.D., Jr; Klauda, J.B. Im, W. CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. J. Chem. Theory Comput., 2016, 12(1), 405-413.
[http://dx.doi.org/10.1021/acs.jctc.5b00935] [PMID: 26631602]
[49]
Comşa, Ş.; Cîmpean, A.M.; Raica, M. The story of MCF-7 breast cancer cell line: 40 years of experience in research. Anticancer Res., 2015, 35(6), 3147-3154.
[PMID: 26026074]
[50]
Lee, A. V.; Oesterreich, S.; Davidson, N. E. MCF-7 cells—changing the course of breast cancer research and care for 45 years. JNCI: J. Nation. Cancer Institute, 2015, 107(7), djv073.
[http://dx.doi.org/10.1093/jnci/djv073]
[51]
Ma, J.; Hart, G.W. O-GlcNAc profiling: From proteins to proteomes. Clin. Proteomics, 2014, 11(1), 8.
[http://dx.doi.org/10.1186/1559-0275-11-8] [PMID: 24593906]
[52]
Elola, M.; Fernandez, M.; Ferragut, F.; Vm, C.; Bracalente, C.; Bravo, I.; Cagnoni, A.; Nuñez, M.; Morosi, L.; Quintá, H. Glycosylation-dependent binding of galectin-8 to activated leukocyte cell adhesion molecule (ALCAM/CD166) promotes its surface segregation on breast cancer cells. Biochim. Biophys. Acta, 2016, 1860(10), 2255-2268.
[http://dx.doi.org/10.1016/j.bbagen.2016.04.019]
[53]
Peixoto, A.; Relvas-Santos, M.; Azevedo, R.; Santos, L.L.; Ferreira, J.A. Protein glycosylation and tumor microenvironment alterations driving cancer hallmarks. Front. Oncol., 2019, 9, 380.
[http://dx.doi.org/10.3389/fonc.2019.00380] [PMID: 31157165]
[54]
Kumar, P.; Tambe, P.; Paknikar, K.M.; Gajbhiye, V. Folate/N -acetyl glucosamine conjugated mesoporous silica nanoparticles for targeting breast cancer cells: A comparative study. Colloids Surf. B Biointerfaces, 2017, 156, 203-212.
[http://dx.doi.org/10.1016/j.colsurfb.2017.05.032] [PMID: 28531877]
[55]
Cheng, L.; Cao, L.; Wu, Y.; Xie, W.; Li, J.; Guan, F.; Tan, Z. Bisecting N-Acetylglucosamine on EGFR inhibits malignant phenotype of breast cancer via down-regulation of EGFR/Erk signaling. Front. Oncol., 2020, 10, 929.
[http://dx.doi.org/10.3389/fonc.2020.00929]
[56]
Mereiter, S.; Balmaña, M.; Campos, D.; Gomes, J.; Reis, C.A. Glycosylation in the era of cancer-targeted therapy: Where are we heading? Cancer Cell, 2019, 36(1), 6-16.
[http://dx.doi.org/10.1016/j.ccell.2019.06.006] [PMID: 31287993]
[57]
Xu, W.; Jiang, C.; Kong, X.; Liang, Y.; Rong, M.; Liu, W. Chitooligosaccharides and N-acetyl-D-glucosamine stimulate peripheral blood mononuclear cell-mediated antitumor immune responses. Mol. Med. Rep., 2012, 6(2), 385-390.
[http://dx.doi.org/10.3892/mmr.2012.918] [PMID: 22614871]
[58]
Quastel, J.H.; Cantero, A. Inhibition of tumour growth by D-glucosamine. Nature, 1953, 171(4345), 252-254.
[http://dx.doi.org/10.1038/171252a0] [PMID: 13036842]
[59]
Brasky, T.M.; Lampe, J.W.; Slatore, C.G.; White, E. Use of glucosamine and chondroitin and lung cancer risk in the VITamins And Lifestyle (VITAL) cohort. Cancer Causes Control, 2011, 22(9), 1333-1342.
[http://dx.doi.org/10.1007/s10552-011-9806-8] [PMID: 21706174]
[60]
Kantor, E.D.; Lampe, J.W.; Peters, U.; Shen, D.D.; Vaughan, T.L.; White, E. Use of glucosamine and chondroitin supplements and risk of colorectal cancer. Cancer Causes Control, 2013, 24(6), 1137-1146.
[http://dx.doi.org/10.1007/s10552-013-0192-2] [PMID: 23529472]
[61]
Kim, M.J.; Choi, M.Y.; Lee, D.H.; Roh, G.S.; Kim, H.J.; Kang, S.S.; Cho, G.J.; Kim, Y.S.; Choi, W.S. O-linked N-acetylglucosamine transferase enhances secretory clusterin expression via liver X receptors and sterol response element binding protein regulation in cervical cancer. Oncotarget, 2018, 9(4), 4625-4636.
[http://dx.doi.org/10.18632/oncotarget.23588] [PMID: 29435130]
[62]
Taniguchi, N.; Kizuka, Y. Glycans and cancer. Adv. Cancer Res., 2015, 126, 11-51.
[http://dx.doi.org/10.1016/bs.acr.2014.11.001] [PMID: 25727145]
[63]
Rivlin, M.; Navon, G. Glucosamine and N-acetyl glucosamine as new CEST MRI agents for molecular imaging of tumors. Sci. Rep., 2016, 6(1), 32648.
[http://dx.doi.org/10.1038/srep32648] [PMID: 27600054]
[64]
Ghosh, S. Sialic acids and sialoglycans in endocrinal disorders. In: Sialic Acids and Sialoglycoconjugates in the Biology of Life, Health and Disease; Ghosh, S., Ed.; Academic Press, 2020; pp. 247-268.
[http://dx.doi.org/10.1016/B978-0-12-816126-5.00009-3]
[65]
Wu, S.; Zhang, Q.; Zhang, F.; Meng, F.; Liu, S.; Zhou, R.; Wu, Q.; Li, X.; Shen, L.; Huang, J.; Qin, J.; Ouyang, S.; Xia, Z.; Song, H.; Feng, X.H.; Zou, J.; Xu, P. HER2 recruits AKT1 to disrupt STING signalling and suppress antiviral defence and antitumour immunity. Nat. Cell Biol., 2019, 21(8), 1027-1040.
[http://dx.doi.org/10.1038/s41556-019-0352-z] [PMID: 31332347]
[66]
Läubli, H.; Varki, A. Sialic acid–binding immunoglobulin-like lectins (Siglecs) detect self-associated molecular patterns to regulate immune responses. Cell. Mol. Life Sci., 2020, 77(4), 593-605.
[http://dx.doi.org/10.1007/s00018-019-03288-x] [PMID: 31485715]
[67]
Crocker, P.R.; Paulson, J.C.; Varki, A. Siglecs and their roles in the immune system. Nat. Rev. Immunol., 2007, 7(4), 255-266.
[http://dx.doi.org/10.1038/nri2056] [PMID: 17380156]
[68]
Macauley, M.S.; Crocker, P.R.; Paulson, J.C. Siglec-mediated regulation of immune cell function in disease. Nat. Rev. Immunol., 2014, 14(10), 653-666.
[http://dx.doi.org/10.1038/nri3737] [PMID: 25234143]
[69]
van de Wall, S.; Santegoets, K.C.M.; van Houtum, E.J.H.; Büll, C.; Adema, G.J. Sialoglycans and siglecs can shape the tumor immune microenvironment. Trends Immunol., 2020, 41(4), 274-285.
[http://dx.doi.org/10.1016/j.it.2020.02.001] [PMID: 32139317]
[70]
Hudak, J.E.; Canham, S.M.; Bertozzi, C.R. Glycocalyx engineering reveals a Siglec-based mechanism for NK cell immunoevasion. Nat. Chem. Biol., 2014, 10(1), 69-75.
[http://dx.doi.org/10.1038/nchembio.1388] [PMID: 24292068]
[71]
Daly, J.; Carlsten, M.; O’Dwyer, M. Sugar Free: Novel immunotherapeutic approaches targeting siglecs and sialic acids to enhance natural killer cell cytotoxicity against cancer. Front. Immunol., 2019, 10, 1047.
[http://dx.doi.org/10.3389/fimmu.2019.01047] [PMID: 31143186]
[72]
Bärenwaldt, A.; Läubli, H. The sialoglycan-Siglec glyco-immune checkpoint-a target for improving innate and adaptive anti-cancer immunity. Expert Opin. Ther. Targets, 2019, 23(10), 839-853.
[http://dx.doi.org/10.1080/14728222.2019.1667977] [PMID: 31524529]
[73]
Beatson, R.; Tajadura-Ortega, V.; Achkova, D.; Picco, G.; Tsourouktsoglou, T.D.; Klausing, S.; Hillier, M.; Maher, J.; Noll, T.; Crocker, P.R.; Taylor-Papadimitriou, J.; Burchell, J.M. The mucin MUC1 modulates the tumor immunological microenvironment through engagement of the lectin Siglec-9. Nat. Immunol., 2016, 17(11), 1273-1281.
[http://dx.doi.org/10.1038/ni.3552] [PMID: 27595232]
[74]
Rillahan, C.D.; Antonopoulos, A.; Lefort, C.T.; Sonon, R.; Azadi, P.; Ley, K.; Dell, A.; Haslam, S.M.; Paulson, J.C. Global metabolic inhibitors of sialyl- and fucosyltransferases remodel the glycome. Nat. Chem. Biol., 2012, 8(7), 661-668.
[http://dx.doi.org/10.1038/nchembio.999] [PMID: 22683610]
[75]
Horstkorte, R.; Fuss, B. Cell adhesion molecules. In: Basic Neurochemistry, 8th ed; Brady, S.T.; Siegel, G.J.; Albers, R.W.; Price, D.L., Eds.; Academic Press, 2012; pp. 165-179.
[http://dx.doi.org/10.1016/B978-0-12-374947-5.00009-2]
[76]
Hart, G.W. Nutrient regulation of signaling and transcription. J. Biol. Chem., 2019, 294(7), 2211-2231.
[http://dx.doi.org/10.1074/jbc.AW119.003226] [PMID: 30626734]
[77]
Chugh, S.; Gnanapragassam, V.S.; Jain, M.; Rachagani, S.; Ponnusamy, M.P.; Batra, S.K. Pathobiological implications of mucin glycans in cancer: Sweet poison and novel targets. Biochim. Biophys. Acta Rev. Cancer, 2015, 1856(2), 211-225.
[http://dx.doi.org/10.1016/j.bbcan.2015.08.003] [PMID: 26318196]
[78]
Pietrobono, S.; Stecca, B. Aberrant sialylation in cancer: Biomarker and potential target for therapeutic intervention? Cancers, 2021, 13(9), 2014.
[http://dx.doi.org/10.3390/cancers13092014] [PMID: 33921986]
[79]
Akella, N.M.; Le Minh, G.; Ciraku, L.; Mukherjee, A.; Bacigalupa, Z.A.; Mukhopadhyay, D.; Sodi, V.L.; Reginato, M.J. O-GlcNAc transferase regulates cancer stem–like potential of breast cancer cells. Mol. Cancer Res., 2020, 18(4), 585-598.
[http://dx.doi.org/10.1158/1541-7786.MCR-19-0732] [PMID: 31974291]
[80]
Ma, Z.; Vosseller, K. Cancer metabolism and elevated O-GlcNAc in oncogenic signaling. J. Biol. Chem., 2014, 289(50), 34457-34465.
[http://dx.doi.org/10.1074/jbc.R114.577718] [PMID: 25336642]
[81]
Lam, C.; Low, J.Y.; Tran, P.T.; Wang, H. The hexosamine biosynthetic pathway and cancer: Current knowledge and future therapeutic strategies. Cancer Lett., 2021, 503, 11-18.
[http://dx.doi.org/10.1016/j.canlet.2021.01.010] [PMID: 33484754]
[82]
DeVito, S.R.; Ortiz-Riaño, E.; Martínez-Sobrido, L.; Munger, J. Cytomegalovirus-mediated activation of pyrimidine biosynthesis drives UDP–sugar synthesis to support viral protein glycosylation. Proc. Natl. Acad. Sci. USA, 2014, 111(50), 18019-18024.
[http://dx.doi.org/10.1073/pnas.1415864111] [PMID: 25472841]
[83]
Hulikova, K.; Benson, V.; Svoboda, J.; Sima, P.; Fiserova, A. N-Acetyl-D-glucosamine-coated polyamidoamine dendrimer modulates antibody formation via natural killer cell activation. Int. Immunopharmacol., 2009, 9(6), 792-799.
[http://dx.doi.org/10.1016/j.intimp.2009.03.007] [PMID: 19303462]
[84]
Han, T.; Kang, D.; Ji, D.; Wang, X.; Zhan, W.; Fu, M.; Xin, H.B.; Wang, J.B. How does cancer cell metabolism affect tumor migration and invasion? Cell Adhes. Migr., 2013, 7(5), 395-403.
[http://dx.doi.org/10.4161/cam.26345] [PMID: 24131935]
[85]
Denning, T.L.; Takaishi, H.; Crowe, S.E.; Boldogh, I.; Jevnikar, A.; Ernst, P.B. Oxidative stress induces the expression of Fas and Fas ligand and apoptosis in murine intestinal epithelial cells. Free Radic. Biol. Med., 2002, 33(12), 1641-1650.
[http://dx.doi.org/10.1016/S0891-5849(02)01141-3] [PMID: 12488132]
[86]
Brunk, U.T.; Svensson, I. Oxidative stress, growth factor starvation and Fas activation may all cause apoptosis through lysosomal leak. Redox Rep., 1999, 4(1-2), 3-11.
[http://dx.doi.org/10.1179/135100099101534675] [PMID: 10714269]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy