Journal of Microbiology and Biotechnology

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
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Reconstruction and Exploratory Analysis of mTORC1 Signaling Pathway and Its Applications to Various Diseases Using Network-Based Approach

  • Buddham, Richa (Centre for Computational Biology and Bioinformatics, Amity Institute of Biotechnology, Amity University) ;
  • Chauhan, Sweety (Centre for Computational Biology and Bioinformatics, Amity Institute of Biotechnology, Amity University) ;
  • Narad, Priyanka (Centre for Computational Biology and Bioinformatics, Amity Institute of Biotechnology, Amity University) ;
  • Mathur, Puniti (Centre for Computational Biology and Bioinformatics, Amity Institute of Biotechnology, Amity University)
  • Received : 2021.08.09
  • Accepted : 2022.01.06
  • Published : 2022.03.28
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Abstract

Mammalian target of rapamycin (mTOR) is a serine-threonine kinase member of the cellular phosphatidylinositol 3-kinase (PI3K) pathway, which is involved in multiple biological functions by transcriptional and translational control. mTOR is a downstream mediator in the PI3K/Akt signaling pathway and plays a critical role in cell survival. In cancer, this pathway can be activated by membrane receptors, including the HER (or ErbB) family of growth factor receptors, the insulin-like growth factor receptor, and the estrogen receptor. In the present work, we congregated an electronic network of mTORC1 built on an assembly of data using natural language processing, consisting of 470 edges (activations/interactions and/or inhibitions) and 206 nodes representing genes/proteins, using the Cytoscape 3.6.0 editor and its plugins for analysis. The experimental design included the extraction of gene expression data related to five distinct types of cancers, namely, pancreatic ductal adenocarcinoma, hepatic cirrhosis, cervical cancer, glioblastoma, and anaplastic thyroid cancer from Gene Expression Omnibus (NCBI GEO) followed by pre-processing and normalization of the data using R & Bioconductor. ExprEssence plugin was used for network condensation to identify differentially expressed genes across the gene expression samples. Gene Ontology (GO) analysis was performed to find out the over-represented GO terms in the network. In addition, pathway enrichment and functional module analysis of the protein-protein interaction (PPI) network were also conducted. Our results indicated NOTCH1, NOTCH3, FLCN, SOD1, SOD2, NF1, and TLR4 as upregulated proteins in different cancer types highlighting their role in cancer progression. The MCODE analysis identified gene clusters for each cancer type with MYC, PCNA, PARP1, IDH1, FGF10, PTEN, and CCND1 as hub genes with high connectivity. MYC for cervical cancer, IDH1 for hepatic cirrhosis, MGMT for glioblastoma and CCND1 for anaplastic thyroid cancer were identified as genes with prognostic importance using survival analysis.

Keywords

References

  1. Saxton RA, Sabatini DM. 2017. mTOR Signaling in growth, metabolism, and disease. Cell 168: 361-371. https://doi.org/10.1016/j.cell.2017.03.035
  2. Eng CP, Sehgal SN, Vezina C.1984. Activity of rapamycin (AY-22, 989) against transplanted tumors. J. Antibiot. (Tokyo) 37: 1231-1247. https://doi.org/10.7164/antibiotics.37.1231
  3. Kim DH, Sarbassov DD, Ali SM, King JE, Latek RR, Erdjument-Bromage H, et al. 2002. mTOR interacts with raptor to form a nutrient-sensitive complex that signals to the cell growth machinery. Cell 110: 163-175. https://doi.org/10.1016/S0092-8674(02)00808-5
  4. Sarbassov DD, Ali SM, Kim DH, Guertin DA, Latek RR, Erdjument-Bromage H, et al. 2004. Rictor, a novel binding partner of mTOR, defines a rapamycin-insensitive and raptor-independent pathway that regulates the cytoskeleton. Curr. Biol. 14: 1296-1302. https://doi.org/10.1016/j.cub.2004.06.054
  5. Hara K, Maruki Y, Long X, Yoshino K, Oshiro N, Hidayat S, et al. 2002. Raptor, a binding partner of target of rapamycin (TOR), mediates TOR action. Cell 110: 177-189. https://doi.org/10.1016/S0092-8674(02)00833-4
  6. Sancak Y, Thoreen CC, Peterson TR, Lindquist RA, Kang SA, Spooner E, et al. 2007. PRAS40 is an insulin-regulated inhibitor of the mTORC1 protein kinase. Mol. Cell. 25: 903-915. https://doi.org/10.1016/j.molcel.2007.03.003
  7. Holz MK, Ballif BA, Gygi SP, Blenis J. 2005. mTOR and S6K1 mediate assembly of the translation preinitiation complex through dynamic protein interchange and ordered phosphorylation events. Cell 123: 569- 580. https://doi.org/10.1016/j.cell.2005.10.024
  8. Gingras AC, Gygi SP, Raught B, Polakiewicz RD, Abraham RT, Hoekstra MF, et al. 1999. Regulation of 4E-BP1 phosphorylation: a novel two-step mechanism. Genes Dev. 13: 1422-1437. https://doi.org/10.1101/gad.13.11.1422
  9. Porstmann T, Santos CR, Griffiths B, Cully M, Wu M, Leevers S, et al. 2008. SREBP activity is regulated by mTORC1 and contributes to Akt-dependent cell growth. Cell Metab. 8: 224-236. https://doi.org/10.1016/j.cmet.2008.07.007
  10. Ben-Sahra I, Hoxhaj G, Ricoult SJH, Asara JM, Manning BD. 2016. mTORC1 induces purine synthesis through control of the mitochondrial tetrahydrofolate cycle. Science 351: 728-733. https://doi.org/10.1126/science.aad0489
  11. Inoki K, Li Y, Xu T, Guan KL. 2003. Rheb GTPase is a direct target of TSC2 GAP activity and regulates mTOR signaling. Genes Dev. 17: 1829-1834. https://doi.org/10.1101/gad.1110003
  12. Tee AR, Manning BD, Roux PP, Cantley LC, Blenis J. 2003. Tuberous sclerosis complex gene products, Tuberin and Hamartin, control mTOR signaling by acting as a GTPase-activating protein complex toward Rheb. Curr. Biol. 13: 1259-1268. https://doi.org/10.1016/S0960-9822(03)00506-2
  13. Long X, Lin Y, Ortiz-Vega S, Yonezawa K, Avruch J. 2005. Rheb binds and regulates the mTOR kinase. Curr. Biol. 15: 702-713. https://doi.org/10.1016/j.cub.2005.02.053
  14. Jewell JL, Kim YC, Russell RC, Yu FX, Park HW, Plouffe SW, et al. 2015. Differential regulation of mTORC1 by leucine and glutamine. Science 347: 194-198. https://doi.org/10.1126/science.1259472
  15. Bar-Peled L, Chantranupong L, Cherniack AD, Chen WW, Ottina KA, Grabiner BC, et al. 2013. A Tumor suppressor complex with GAP activity for the Rag GTPase that signal amino acid sufficiency to mTORC1. Science 340: 1100-1126. https://doi.org/10.1126/science.1232044
  16. Wolfson RL, Chantranupong L, Wyant GA, Gu X, Orozco JM, Shen K, et al. 2017. KICSTOR recruits GATOR1 to the lysosome and is necessary for nutrients to regulate mTORC1. Nature 543: 438-442. https://doi.org/10.1038/nature21423
  17. Jacinto E, Loewith R, Schmidt A, Lin S, Ruegg MA, Hall A, et al. 2004. Mammalian TOR complex 2 controls the actin cytoskeleton and is rapamycin insensitive. Nat. Cell Biol. 6: 1122-1128. https://doi.org/10.1038/ncb1183
  18. Gan X, Wang J, Wang C, Sommer E, Kozasa T, Srinivasula S, et al. 2012.PRR5L degradation promotes mTORC2-mediated PKC-δ phosphorylation and cell migration downstream of Gα12. Nat. Cell Biol. 14: 686-696. https://doi.org/10.1038/ncb2507
  19. Sarbassov DD, Guertin DA, Ali SM, Sabatini DM. 2005. Phosphorylation and regulation of Akt/PKB by the rictor-mTOR complex. Science 307: 1098-1101. https://doi.org/10.1126/science.1106148
  20. Garcia-Martinez JM, Alessi DR. 2008. mTOR complex 2 (mTORC2) controls hydrophobic motif phosphorylation and activation of serum- and glucocorticoid -induced protein kinase 1 (SGK1). Biochem. J. 416: 375-385. https://doi.org/10.1042/BJ20081668
  21. Lamming DW, Ye L, Katajisto P, Goncalves MD, Saitoh M, Stevens DM, et al. 2012. Rapamycin-induced insulin resistance is mediated by mTORC2 loss and uncoupled from longevity. Science 335: 1638-1643. https://doi.org/10.1126/science.1215135
  22. Grabiner BC, Nardi V, Birsoy K, Possemato R, Shen K, Sinha S, et al. 2014. A diverse array of cancer -associated MTOR mutations are hyperactivating and can predict rapamycin sensitivity. Cancer Discov. 4: 554-563. https://doi.org/10.1158/2159-8290.CD-13-0929
  23. Hietakangas V, Cohen SM. 2008. TOR complex 2 is needed for cell cycle progression and anchorage-independent growth of MCF7 and PC3 tumor cells. BMC Cancer 8: 282-289. https://doi.org/10.1186/1471-2407-8-282
  24. Popova NV, Jucker M. 2021.The Role of mTOR signaling as a therapeutic target in cancer. Int. J. Mol. Sci. 22: 1743-1760. https://doi.org/10.3390/ijms22041743
  25. Mao Z, Zhang W. 2018. Role of mTOR in glucose and lipid metabolism. Int. J. Mol. Sci. 19: 2043-2057. https://doi.org/10.3390/ijms19072043
  26. Michal Grzmil, Pier Morin Jr, Maria Maddalena Lino, Adrian Merlo, Stephan Frank, Yuhua Wang, et al. 2011. MAP kinase-interacting kinase 1 regulates SMAD2-dependent TGF-β signaling pathway in human glioblastoma. Cancer Res. 71: 2392-2402. https://doi.org/10.1158/0008-5472.CAN-10-3112
  27. Jaime Miguel Pita , Ines Filipa Figueiredo, Margarida Maria Moura, Valeriano Leite, Branca Maria Cavaco. 2014. Cell cycle deregulation and TP53 and RAS mutations are major events in poorly differentiated and undifferentiated thyroid carcinomas. J. Clin. Endocrinol. Metab. 99: E497-E507. https://doi.org/10.1210/jc.2013-1512
  28. McCall MN, Bolstad BM, Irizarry RA. 2010. Frozen robust multiarray analysis (fRMA). Biostatistics 11: 242-253. https://doi.org/10.1093/biostatistics/kxp059
  29. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13: 2498-2504. https://doi.org/10.1101/gr.1239303
  30. Gregor Warsow, Boris Greber, Steffi S I Falk, Clemens Harder, Marcin Siatkowski, Sandra Schordan, et al. 2010. ExprEssence - Revealing the essence of differential experimental data in the context of an interaction/regulation net-work. BMC Syst. Biol. 4: 164-182. https://doi.org/10.1186/1752-0509-4-164
  31. Maere S, Heymans K, Kuiper M. 2005. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21: 3448-3449. https://doi.org/10.1093/bioinformatics/bti551
  32. Winterhalter C, Widera P, Krasnogor N. 2014. JEPETTO: a Cytoscape plugin for gene set enrichment and topological analysis based on interaction networks. Bioinformatics 30: 1029-1037. https://doi.org/10.1093/bioinformatics/btt732
  33. Glaab E, Baudot A, Krasnogor N, Schneider R, Valencia A. 2012. Enrich Net: network-based gene set enrichment analysis. Bioinformatics 28: i451-i457. https://doi.org/10.1093/bioinformatics/btr678
  34. Glaab E, Baudot A, Krasnogor N, Valencia A. 2010. Extending pathways and processes using molecular interaction networks to analyze cancer genome data. BMC Bioinformatics 11: 597-607. https://doi.org/10.1186/1471-2105-11-597
  35. Bader GD, Hogue CW. 2003. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4: 2849-2861.
  36. Clark TG, Bradburn MJ, Love SB, Altman DG. 2003. Survival analysis part I: basic concepts and first analyses. Br. J. Cancer 89: 232-238. https://doi.org/10.1038/sj.bjc.6601118
  37. Buller V, Carolyn L. 2010. Role of GLUT1 in the Mammalian target of rapamycin pathway: mechanisms of regulation. Mlibrary 34: 23-43.
  38. Greer EL, Brunet A. 2005. FOXO transcription factors at the interface between longevity and tumor suppression. Oncogene 24: 7410-7425. https://doi.org/10.1038/sj.onc.1209086
  39. Maryam S, Funda MB. 2019. Targeting AKT for cancer therapy. Expert. Opin. Investig. Drugs 28: 977-988. https://doi.org/10.1080/13543784.2019.1676726
  40. Mohammed Altaf, Janakiram NB, Madka Venkateshwar, et al. 2014. Eflornithine (DFMO) Prevents progression of pancreatic cancer by modulating ornithine decarboxylase signaling. Cancer Prev. Res. (Phila). 7: 1198-1209. https://doi.org/10.1158/1940-6207.CAPR-14-0176
  41. Hongxi Chen, Zhipeng Zhang, Yebin Lu, Kun Song, Xiwu Liu, Fada Xia, et al. 2017. Down-regulation of ULK1 by microRNA-372 inhibits the survival of human pancreatic adenocarcinoma cells. Cancer Sci. 108: 1811-1819. https://doi.org/10.1111/cas.13315
  42. Yang J, Nie J, Ma XL, Wei Y, Peng Y, Wei X. 2019. Targeting PI3K in cancer: mechanisms and advances in clinical trials. Mol. Cancer 18: 26. https://doi.org/10.1186/s12943-019-0954-x
  43. Huang Q, Li JH, Zheng J, and Wei A. 2019. The carcinogenic role of the notch signaling pathway in the development of hepatocellular carcinoma. J. Cancer 10: 1570-1579. https://doi.org/10.7150/jca.26847
  44. Bo Li, Zhang J, Su Y, Hou Y, Wang Z. 2019.Overexpression of PTEN may increase the effect of pemetrexed on A549 cells via inhibition of the PI3K/AKT/mTOR pathway and carbohydrate metabolism. Mol. Med. Rep. 20: 3793-3801.
  45. Ramirez Reyes JMJ, Cuesta R, Pause A. 2021. Folliculin: a regulator of transcription through AMPK and mTOR signaling pathways. Front. Cell Dev. Biol. 9: 667311-667333. https://doi.org/10.3389/fcell.2021.667311
  46. Guo Y, Xiao Z, Yang Li, Gao Y, Zhu QJ, Hu LJ. 2020. Hypoxia inducible factors in Hepatocellular carcinoma. Oncotarget 43: 3-15.
  47. Porta C, Amici MD, Quaglini S, Paglino C, Tagliani F, Boncimino A, et al. 2008. Circulating interleukin-6 as a tumor marker for Hepatocellular carcinoma. Ann. Oncol. 19: 353-358. https://doi.org/10.1093/annonc/mdm448
  48. Dietrich P, Gaza A, Wormser L. 2019. Neuroblastoma RAS viral oncogene homolog (NRAS) is a novel prognostic marker and contributes to sorafenib resistance in Hepatocellular Carcinoma. Neoplasia 21: 257-268. https://doi.org/10.1016/j.neo.2018.11.011
  49. Rodrigues C, Leanna R Joy, Sasikala P Sachithanandan, Sudhir Krishna. 2019. Notch signaling in cervical cancer. Exp. Cell Res. 385: 111682-111699. https://doi.org/10.1016/j.yexcr.2019.111682
  50. Wang HY, Lian P, Zheng PS. 2015. SOX9, a potential tumor suppressor in cervical cancer, transactivate p21WAF1/CIP1 and suppresses cervical tumor growth. Oncotarget. 6: 20711-20722. https://doi.org/10.18632/oncotarget.4133
  51. Peter WS. 2017. Therapeutic targeting of the pyruvate dehydrogenase complex/pyruvate dehydrogenase kinase (PDC/PDK) axis in cancer. J. Natl. Cancer Inst. 109: djx071-djx089.
  52. Fernandes Silva GA, Lima Nunes RA, Morale MG, Boccardo E, Aguayo F, Termini L, et al. 2018. Oxidative stress: therapeutic approaches for cervical cancer treatment. Clinics (Sao Paulo). 73: e548s-e558s. https://doi.org/10.6061/clinics/2018/e548s
  53. Atkinson GP, Nozell SE, Benveniste ET. 2010. NF-κB and STAT3 signaling in glioma: targets for future therapies. Expert Rev. Neurother. 10: 575-586. https://doi.org/10.1586/ern.10.21
  54. Justin TA, Ruowen Z, Rebecca JB.2021. GLI1: A therapeutic target for cancer. Front. Oncol. 11: 673154. https://doi.org/10.3389/fonc.2021.673154
  55. Joanne ES, Noon G. 2020. The impact of autophagy during the development and survival of glioblastoma. Open Biol. 10: 200184-200198. https://doi.org/10.1098/rsob.200184
  56. Cristina R, Rossella E. 2021. A narrative review of genetic alterations in primary thyroid epithelial cancer. Int. J. Mol. Sci. 22: 1726-1738. https://doi.org/10.3390/ijms22041726
  57. Cardamom GA, Gonzalez N, Maggio J, Lorenzano PM, Gomez DE. 2017. Rho GTPase as therapeutic targets in cancer. Int. J. Oncol. 51: 1025-1034. https://doi.org/10.3892/ijo.2017.4093
  58. Kremenevskaja N, Wasielewski RV, Rao AS, Schofl C, Andersson T, Brabant G. 2005. Wnt-5a has tumor suppressor activity in thyroid carcinoma. Oncogene. 24: 2144-2154. https://doi.org/10.1038/sj.onc.1208370
  59. Cheruku HR, Mohamedali A, Cantor DI, HweeTan S, Nice EC, Baker MS. 2015. Transforming growth factor-β, MAPK and Wnt signaling interactions in cancer. EuPA Open Proteomics. 8: 104-115. https://doi.org/10.1016/j.euprot.2015.06.004
  60. Sanders SS, De Simone FI, Thomas GM. 2019. mTORC1 signaling is palmitoylation-dependent in hippocampal neurons and nonneuronal cells and involves dynamic palmitoylation of LAMTOR1 and mTOR. Front. Cell Neurosci. 13: 115-130. https://doi.org/10.3389/fncel.2019.00115
  61. Magdalena K, Cynthia SS, Tasha M, Hong Wu, Elizabeth PH. 2008. mTOR is activated in the majority of malignant melanomas. J. Investig. Dermatol. 128: 980-987. https://doi.org/10.1038/sj.jid.5701074
  62. Abramowicz A, Gos M. 2014.Neurofibromin in neurofibromatosis type 1 - mutations in NF1gene as a cause of disease. Dev. Period Med. 18: 297-306.
  63. Peter Kovacs, Robert L Hanson, Yong-Ho Lee, Xiaolin Yang, Sayuko Kobes, Paska A Permana, et al. 2003. The role of insulin receptor substrate-1 Gene (IRS1) in type 2 diabetes in pima Indians. Diabetes 52: 3005-3009. https://doi.org/10.2337/diabetes.52.12.3005