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image of Determination of FGFR1 Functions in Cytarabine Treatment of Acute Myeloid Leukemia Through Bioinformatics Analysis

Abstract

Aim

Among the most prevalent subtypes of acute leukemia is acute myeloid leukemia (LAML). Consequently, it is essential to understand the molecular causes of LAML and find its predictive and diagnostic biomarkers. The aim of this study is to determine the molecular functions of fibroblast growth factor receptor 1(FGFR1) involved in LAML pathogenesis and its potential therapeutic effect for AML treatment.

Methods

The molecular docking interaction of the Cytarabine with its target FGFR1 was examined. The Gene Expression Profiling Interactive Analysis, version 2 (GEPIA2), and UALCAN tools database were used to obtain the LAML gene expression datasets. Gene functional annotation was performed to investigate the DEGs' possible role. Using the Interactive Gene database retrieval tool (STRING) and a few chosen hub modules from the GeneMANIA database, the protein-protein interaction (PPI) network were constructed. A survival analysis was performed on the effects of hub genes on the overall survival of LAML patients.

Results

As a result of docking, a strong interaction was observed between cytarabine and FGFR1. It has been discovered that cytarabine can reverse FGFR1 expression. The survival study results showed an association between the prognosis of AML patients and one of the central genes, FGFR1.

Conclusion

The expression profile and functions of FGFR1 were determined in LAML patients. It has been shown that FGFR1 can be a viable therapeutic target for LAML and a possible biomarker for diagnosis.

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2024-10-09
2024-11-18
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References

  1. Fan H. Li Y. Liu C. Liu Y. Bai J. Li W. Circular RNA-100290 promotes cell proliferation and inhibits apoptosis in acute myeloid leukemia cells via sponging miR-203. Biochem. Biophys. Res. Commun. 2018 507 1-4 178 184 10.1016/j.bbrc.2018.11.002 30424877
    [Google Scholar]
  2. Wang Y. Guo X. Wang L. Xing L. Zhang X. Ren J. miR-342-3p Inhibits Acute Myeloid Leukemia Progression by Targeting SOX12. Oxid. Med. Cell. Longev. 2022 2022 1 10 10.1155/2022/1275141 36120594
    [Google Scholar]
  3. Wang H. He H. Yang C. Yang C. miR-342 suppresses the proliferation and invasion of acute myeloid leukemia by targeting Naa10p. Artif. Cells Nanomed. Biotechnol. 2019 47 1 3671 3676 10.1080/21691401.2019.1596930 31496296
    [Google Scholar]
  4. Misir S. Ozer Yaman S. Petrović N. Šami A. Akidan O. Hepokur C. Aliyazicioglu Y. Identification of a Novel hsa_circ_0058058/miR-324-5p Axis and Prognostic/Predictive Molecules for Acute Myeloid Leukemia Outcome by Bioinformatics-Based Analysis. Biology (Basel) 2024 13 7 487 10.3390/biology13070487 39056681
    [Google Scholar]
  5. Lu Y. Zhong L. Luo X. Liu C. Dan W. Chu X. Wan P. Zhang Z. Wang X. Liu Z. Liu B. MiRNA-301b-3p induces proliferation and inhibits apoptosis in AML cells by targeting FOXF2 and regulating Wnt/β-catenin axis. Mol. Cell. Probes 2022 63 101805 10.1016/j.mcp.2022.101805 35259424
    [Google Scholar]
  6. Elhamamsy A.R. El Sharkawy M.S. Zanaty A.F. Mahrous M.A. Mohamed A.E. Abushaaban E.A. Circulating miR-92a, miR-143 and miR-342 in Plasma are Novel Potential Biomarkers for Acute Myeloid Leukemia. Int. J. Mol. Cell. Med. 2017 6 2 77 86 28890884
    [Google Scholar]
  7. Hsu W.Y. Chiou S.S. Lin P.C. Liao Y.M. Yeh C.Y. Tseng Y.H. Prediction of miRNA‑mRNA network regulating the migration ability of cytarabine‑resistant HL60 cells. Biomed. Rep. 2023 20 2 20 10.3892/br.2023.1708 38170076
    [Google Scholar]
  8. Shahabadi N. Falsafi M. Maghsudi M. DNA-binding study of anticancer drug cytarabine by spectroscopic and molecular docking techniques. Nucleosides Nucleotides Nucleic Acids 2017 36 1 49 65 10.1080/15257770.2016.1218021 27759491
    [Google Scholar]
  9. Bhise N.S. Chauhan L. Shin M. Cao X. Pounds S. Lamba V. Lamba J.K. MicroRNA-mRNA pairs associated with outcome in AML: From in vitro cell-based studies to AML patients. Front. Pharmacol. 2016 6 324 10.3389/fphar.2015.00324 26858643
    [Google Scholar]
  10. Wang S.Y. Shih Y.H. Shieh T.M. Tseng Y.H. Proteasome inhibitors interrupt the activation of non-canonical nf-κb signaling pathway and induce cell apoptosis in cytarabine-resistant HL60 cells. Int. J. Mol. Sci. 2021 23 1 361 10.3390/ijms23010361 35008789
    [Google Scholar]
  11. Kontomanolis E.N. Koutras A. Syllaios A. Schizas D. Mastoraki A. Garmpis N. Diakosavvas M. Angelou K. Tsatsaris G. Pagkalos A. Ntounis T. Fasoulakis Z. Role of oncogenes and tumor-suppressor genes in carcinogenesis: A review. Anticancer Res. 2020 40 11 6009 6015 10.21873/anticanres.14622 33109539
    [Google Scholar]
  12. Folkman J. The role of angiogenesis in tumor growth. Semin. Cancer Biol. 1992 3 2 65 71 1378311
    [Google Scholar]
  13. Dias S. Hattori K. Heissig B. Zhu Z. Wu Y. Witte L. Hicklin D.J. Tateno M. Bohlen P. Moore M.A.S. Rafii S. Inhibition of both paracrine and autocrine VEGF/VEGFR-2 signaling pathways is essential to induce long-term remission of xenotransplanted human leukemias. Proc. Natl. Acad. Sci. USA 2001 98 19 10857 10862 10.1073/pnas.191117498 11553814
    [Google Scholar]
  14. Zhu Z. Hattori K. Zhang H. Jimenez X. Ludwig D.L. Dias S. Kussie P. Koo H. Kim H.J. Lu D. Liu M. Tejada R. Friedrich M. Bohlen P. Witte L. Rafii S. Inhibition of human leukemia in an animal model with human antibodies directed against vascular endothelial growth factor receptor 2. Correlation between antibody affinity and biological activity. Leukemia 2003 17 3 604 611 10.1038/sj.leu.2402831 12646950
    [Google Scholar]
  15. Santos S.C.R. Dias S. Internal and external autocrine VEGF/KDR loops regulate survival of subsets of acute leukemia through distinct signaling pathways. Blood 2004 103 10 3883 3889 10.1182/blood‑2003‑05‑1634 14726393
    [Google Scholar]
  16. List A.F. Glinsmann-Gibson B. Stadheim C. Meuillet E.J. Bellamy W. Powis G. Vascular endothelial growth factor receptor-1 and receptor-2 initiate a phosphatidylinositide 3-kinase–dependent clonogenic response in acute myeloid leukemia cells. Exp. Hematol. 2004 32 6 526 535 10.1016/j.exphem.2004.03.005 15183893
    [Google Scholar]
  17. Zhang H. Li Y. Li H. Bassi R. Jimenez X. Witte L. Bohlen P. Hicklin D.J. Zhu Z. Inhibition of both the autocrine and the paracrine growth of human leukemia with a fully human antibody directed against vascular endothelial growth factor receptor 2. Leuk. Lymphoma 2004 45 9 1887 1897 10.1080/10428190410001712225 15223651
    [Google Scholar]
  18. Yang Y. Lu T. Li Z. Lu S. FGFR1 regulates proliferation and metastasis by targeting CCND1 in FGFR1 amplified lung cancer. Cell Adhes. Migr. 2020 14 1 82 95 10.1080/19336918.2020.1766308 32380883
    [Google Scholar]
  19. Farooq M. Khan A.W. Kim M.S. Choi S. The role of fibroblast growth factor (FGF) signaling in tissue repair and regeneration. Cells 2021 10 11 3242 10.3390/cells10113242 34831463
    [Google Scholar]
  20. Dorey K. Amaya E. FGF signalling: Diverse roles during early vertebrate embryogenesis. Development 2010 137 22 3731 3742 10.1242/dev.037689 20978071
    [Google Scholar]
  21. Cowell J.K. Qin H. Hu T. Wu Q. Bhole A. Ren M. Mutation in the FGFR1 tyrosine kinase domain or inactivation of PTEN is associated with acquired resistance to FGFR inhibitors in FGFR1‐driven leukemia/lymphomas. Int. J. Cancer 2017 141 9 1822 1829 10.1002/ijc.30848 28646488
    [Google Scholar]
  22. Karajannis M.A. Vincent L. DiRenzo R. Shmelkov S.V. Zhang F. Feldman E.J. Bohlen P. Zhu Z. Sun H. Kussie P. Rafii S. Activation of FGFR1β signaling pathway promotes survival, migration and resistance to chemotherapy in acute myeloid leukemia cells. Leukemia 2006 20 6 979 986 10.1038/sj.leu.2404203 16598308
    [Google Scholar]
  23. Yu S. Ye J. Wang Y. Lu T. Liu Y. Liu N. Zhang J. Lu F. Ma D. Gale R.P. Ji C. DNA damage to bone marrow stromal cells by antileukemia drugs induces chemoresistance in acute myeloid leukemia via paracrine FGF10–FGFR2 signaling. J. Biol. Chem. 2023 299 1 102787 10.1016/j.jbc.2022.102787 36509141
    [Google Scholar]
  24. Silva J. Chang C.S. Hu T. Qin H. Kitamura E. Hawthorn L. Ren M. Cowell J.K. Distinct signaling programs associated with progression of FGFR1 driven leukemia in a mouse model of stem cell leukemia lymphoma syndrome. Genomics 2019 111 6 1566 1573 10.1016/j.ygeno.2018.10.015 30439482
    [Google Scholar]
  25. Çakmak E. A Bioinformatics Approach to Identify Potential Biomarkers in Non-Small Cell Lung Cancer. Cumhur. Sci. J. 2022 43 1 6 13 10.17776/csj.976510
    [Google Scholar]
  26. Ferreira L. Dos Santos R. Oliva G. Andricopulo A. Molecular docking and structure-based drug design strategies. Molecules 2015 20 7 13384 13421 10.3390/molecules200713384 26205061
    [Google Scholar]
  27. Glide, Version 2. New York, NY, USA Schrodinger. LLC 2021
    [Google Scholar]
  28. LigPrep, Version 2. New York, NY, USA Schrodinger. LLC 2021
    [Google Scholar]
  29. MacroModel, Version 2. New York, NY, USA Schrodinger. LLC 2021
    [Google Scholar]
  30. Lin Q. Dai S. Qu L. Lin H. Guo M. Wei H. Chen Y. Chen X. Structural basis and selectivity of sulfatinib binding to FGFR and CSF-1R. Commun. Chem. 2024 7 1 3 10.1038/s42004‑023‑01084‑0 38172256
    [Google Scholar]
  31. Li T. Fan J. Wang B. Traugh N. Chen Q. Liu J.S. Li B. Liu X.S. TIMER: A web server for comprehensive analysis of tumor- infiltrating immune cells. Cancer Res. 2017 77 21 e108 e110 10.1158/0008‑5472.CAN‑17‑0307 29092952
    [Google Scholar]
  32. Li T. Fu J. Zeng Z. Cohen D. Li J. Chen Q. Li B. Liu X.S. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020 48 W1 W509 W514 10.1093/nar/gkaa407 32442275
    [Google Scholar]
  33. Tang Z. Li C. Kang B. Gao G. Li C. Zhang Z. GEPIA: A web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res. 2017 45 W1 W98 W102 10.1093/nar/gkx247 28407145
    [Google Scholar]
  34. Chandrashekar D.S. Bashel B. Balasubramanya S.A.H. Creighton C.J. Ponce-Rodriguez I. Chakravarthi B.V.S.K. Varambally S. UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses. Neoplasia 2017 19 8 649 658 10.1016/j.neo.2017.05.002 28732212
    [Google Scholar]
  35. Li C. Tang Z. Zhang W. Ye Z. Liu F. GEPIA2021: Integrating multiple deconvolution-based analysis into GEPIA. Nucleic Acids Res. 2021 49 W1 W242 W246 10.1093/nar/gkab418 34050758
    [Google Scholar]
  36. Szklarczyk D. Franceschini A. Kuhn M. Simonovic M. Roth A. Minguez P. Doerks T. Stark M. Muller J. Bork P. Jensen L.J. Mering C. The STRING database in 2011: Functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res. 2011 39 Database D561 D568 10.1093/nar/gkq973 21045058
    [Google Scholar]
  37. Warde-Farley D. Donaldson S.L. Comes O. Zuberi K. Badrawi R. Chao P. Franz M. Grouios C. Kazi F. Lopes C.T. Maitland A. Mostafavi S. Montojo J. Shao Q. Wright G. Bader G.D. Morris Q. The GeneMANIA prediction server: Biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010 38 W214 W220 10.1093/nar/gkq537 20576703
    [Google Scholar]
  38. Chandrashekar D.S. Karthikeyan S.K. Korla P.K. Patel H. Shovon A.R. Athar M. Netto G.J. Qin Z.S. Kumar S. Manne U. Creighton C.J. Varambally S. UALCAN: An update to the integrated cancer data analysis platform. Neoplasia 2022 25 18 27 10.1016/j.neo.2022.01.001 35078134
    [Google Scholar]
  39. Sircar A. Singh S. Xu-Monette Z.Y. Coyle K.M. Hilton L.K. Chavdoula E. Ranganathan P. Jain N. Hanel W. Tsichlis P. Alinari L. Peterson B.R. Tao J. Muthusamy N. Baiocchi R. Epperla N. Young K.H. Morin R. Sehgal L. Exploiting the fibroblast growth factor receptor-1 vulnerability to therapeutically restrict the MYC-EZH2-CDKN1C axis-driven proliferation in Mantle cell lymphoma. Leukemia 2023 37 10 2094 2106 10.1038/s41375‑023‑02006‑8 37598282
    [Google Scholar]
  40. Kommalapati A. Tella S.H. Borad M. Javle M. Mahipal A. Fgfr inhibitors in oncology: Insight on the management of toxicities in clinical practice. Cancers (Basel) 2021 13 12 2968 10.3390/cancers13122968 34199304
    [Google Scholar]
  41. Katoh M. FGFR inhibitors: Effects on cancer cells, tumor microenvironment and whole-body homeostasis (Review). Int. J. Mol. Med. 2016 38 1 3 15 10.3892/ijmm.2016.2620 27245147
    [Google Scholar]
  42. Ferguson H.R. Smith M.P. Francavilla C. Fibroblast growth factor receptors (FGFRS) and noncanonical partners in cancer signaling. Cells 2021 10 5 1201 10.3390/cells10051201 34068954
    [Google Scholar]
  43. Xie Y. Su N. Yang J. Tan Q. Huang S. Jin M. Ni Z. Zhang B. Zhang D. Luo F. Chen H. Sun X. Feng J.Q. Qi H. Chen L. FGF/FGFR signaling in health and disease. Signal Transduct. Target. Ther. 2020 5 1 181 10.1038/s41392‑020‑00222‑7 32879300
    [Google Scholar]
  44. Panneerselvam S. Yesudhas D. Durai P. Anwar M. Gosu V. Choi S. A combined molecular docking/dynamics approach to probe the binding mode of cancer drugs with cytochrome P450 3A4. Molecules 2015 20 8 14915 14935 10.3390/molecules200814915 26287147
    [Google Scholar]
  45. Dodson G.G. Lane D.P. Verma C.S. Molecular simulations of protein dynamics: new windows on mechanisms in biology. EMBO Rep. 2008 9 2 144 150 10.1038/sj.embor.7401160 18246106
    [Google Scholar]
  46. Agu P.C. Afiukwa C.A. Orji O.U. Ezeh E.M. Ofoke I.H. Ogbu C.O. Ugwuja E.I. Aja P.M. Molecular docking as a tool for the discovery of molecular targets of nutraceuticals in diseases management. Sci. Rep. 2023 13 1 13398 10.1038/s41598‑023‑40160‑2 37592012
    [Google Scholar]
  47. Gangadharan A.K. Kundil V.T. Jayanandan A. Computational Tools in Drug-Lead Identification and Development. Drugs from Nature: Targets, Assay Systems and Leads. Singapore Springer Nature Singapore 2024 89 119 10.1007/978‑981‑99‑9183‑9_4
    [Google Scholar]
  48. Zhang L. Yao Y. Zhang S. Liu Y. Guo H. Ahmed M. Bell T. Zhang H. Han G. Lorence E. Badillo M. Zhou S. Sun Y. Di Francesco M.E. Feng N. Haun R. Lan R. Mackintosh S.G. Mao X. Song X. Zhang J. Pham L.V. Lorenzi P.L. Marszalek J. Heffernan T. Draetta G. Jones P. Futreal A. Nomie K. Wang L. Wang M. Metabolic reprogramming toward oxidative phosphorylation identifies a therapeutic target for mantle cell lymphoma. Sci. Transl. Med. 2019 11 491 eaau1167 10.1126/scitranslmed.aau1167 31068440
    [Google Scholar]
  49. Krejci P. Faitova J. Laurell H. Hampl A. Dvorak P. FGF-2 expression and its action in human leukemia and lymphoma cell lines. Leukemia 2003 17 4 818 820 10.1038/sj.leu.2402861 12682649
    [Google Scholar]
  50. Wu Q. Bhole A. Qin H. Karp J. Malek S. Cowell J.K. Targeting FGFR1 to suppress leukemogenesis in syndromic and de novo AML in murine models. Oncotarget 2016 7 49733 49742 10.18632/oncotarget.10438
    [Google Scholar]
  51. Parish A. Schwaederle M. Daniels G. Piccioni D. Fanta P. Schwab R. Shimabukuro K. Parker B.A. Helsten T. Kurzrock R. Fibroblast growth factor family aberrations in cancers: Clinical and molecular characteristics. Cell Cycle 2015 14 13 2121 2128 10.1080/15384101.2015.1041691 25950492
    [Google Scholar]
  52. Gorringe K.L. Jacobs S. Thompson E.R. Sridhar A. Qiu W. Choong D.Y.H. Campbell I.G. High-resolution single nucleotide polymorphism array analysis of epithelial ovarian cancer reveals numerous microdeletions and amplifications. Clin. Cancer Res. 2007 13 16 4731 4739 10.1158/1078‑0432.CCR‑07‑0502 17699850
    [Google Scholar]
  53. Ross J.S. Wang K. Al-Rohil R.N. Nazeer T. Sheehan C.E. Otto G.A. He J. Palmer G. Yelensky R. Lipson D. Ali S. Balasubramanian S. Curran J.A. Garcia L. Mahoney K. Downing S.R. Hawryluk M. Miller V.A. Stephens P.J. Advanced urothelial carcinoma: Next-generation sequencing reveals diverse genomic alterations and targets of therapy. Mod. Pathol. 2014 27 2 271 280 10.1038/modpathol.2013.135 23887298
    [Google Scholar]
  54. Tsimafeyeu I. Demidov L. Stepanova E. Wynn N. Ta H. Overexpression of fibroblast growth factor receptors FGFR1 and FGFR2 in renal cell carcinoma. Scand. J. Urol. Nephrol. 2011 45 3 190 195 10.3109/00365599.2011.552436 21329481
    [Google Scholar]
  55. Yang F. Zhang Y. Ressler S.J. Ittmann M.M. Ayala G.E. Dang T.D. Wang F. Rowley D.R. FGFR1 is essential for prostate cancer progression and metastasis. Cancer Res. 2013 73 12 3716 3724 10.1158/0008‑5472.CAN‑12‑3274 23576558
    [Google Scholar]
  56. Kim H.S. Lee S.E. Bae Y.S. Kim D.J. Lee C.G. Hur J. Chung H. Park J.C. Jung D.H. Shin S.K. Lee S.K. Lee Y.C. Kim H.R. Moon Y.W. Kim J.H. Shim Y.M. Jewell S.S. Kim H. Choi Y.L. Cho B.C. Fibroblast growth factor receptor 1 gene amplification is associated with poor survival in patients with resected esophageal squamous cell carcinoma. Oncotarget 2015 6 4 2562 2572 10.18632/oncotarget.2944 25537505
    [Google Scholar]
  57. Schäfer M.H. Lingohr P. Sträßer A. Lehnen N.C. Braun M. Perner S. Höller T. Kristiansen G. Kalff J.C. Gütgemann I. Fibroblast growth factor receptor 1 gene amplification in gastric adenocarcinoma. Hum. Pathol. 2015 46 10 1488 1495 10.1016/j.humpath.2015.06.007 26239623
    [Google Scholar]
  58. Kawamata F. Patch A.M. Nones K. Bond C. McKeone D. Pearson S.A. Homma S. Liu C. Fennell L. Dumenil T. Hartel G. Kobayasi N. Yokoo H. Fukai M. Nishihara H. Kamiyama T. Burge M.E. Karapetis C.S. Taketomi A. Leggett B. Waddell N. Whitehall V. Copy number profiles of paired primary and metastatic colorectal cancers. Oncotarget 2018 9 3 3394 3405 10.18632/oncotarget.23277 29423054
    [Google Scholar]
  59. Guan Z. Lan H. Sun D. Wang X. Jin K. A potential novel therapy for FGFR1-amplified pancreatic cancer with bone metastasis, screened by next-generation sequencing and a patient-derived xenograft model. Oncol. Lett. 2019 17 2 2303 2307 30719110
    [Google Scholar]
  60. Giordano M. Decio A. Battistini C. Baronio M. Bianchi F. Villa A. Bertalot G. Freddi S. Lupia M. Jodice M.G. Ubezio P. Colombo N. Giavazzi R. Cavallaro U. L1CAM promotes ovarian cancer stemness and tumor initiation via FGFR1/SRC/STAT3 signaling. J. Exp. Clin. Cancer Res. 2021 40 1 319 10.1186/s13046‑021‑02117‑z 34645505
    [Google Scholar]
  61. Huang S. Liang S. Chen G. Chen J. You K. Ye H. Li Z. He S. Overexpression of glycosyltransferase 8 domain containing 2 confers ovarian cancer to CDDP resistance by activating FGFR/PI3K signalling axis. Oncogenesis 2021 10 7 55 10.1038/s41389‑021‑00343‑w 34294681
    [Google Scholar]
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  • Article Type:
    Research Article
Keywords: FGFR1 ; Acute myeloid leukemia ; cytarabine ; molecular docking
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