Skip to content
2000
image of Cassia-Derived Natural Flavonoids as Multi-Target Candidates for Lung Cancer Therapy: A Network Pharmacology and Molecular Modeling Study

Abstract

Introduction

Lung cancer remains a major global health burden with high mortality rates and limited therapeutic options. Natural flavonoids, particularly those derived from Cassia species, have shown immunomodulatory and anticancer potential. This study investigates the therapeutic promise of selected Cassia-derived flavonoids targeting key lung cancer-associated proteins: Prostaglandin-endoperoxide synthase 2 (PTGS2), Mast/stem cell growth factor receptor (KIT), and Xanthine dehydrogenase (XDH).

Methodology

Eight flavonoids were selected based on literature and database-reported bioactivity. Target prediction was performed using SwissTargetPrediction and STITCH, followed by pathway enrichment STRING and KEGG databases. Molecular docking was conducted using AutoDock Vina against PTGS2 (PDB: 5IKQ), KIT (1N5X), and XDH (4U0I). Top-ranked complexes underwent 100 ns molecular dynamics (MD) simulations with GROMACS to assess binding stability, RMSD, and conformational behavior. Drug-likeness, ADME, and toxicity profiles were evaluated using SwissADME and ProTox-II. Standard drugs (Trametinib, Nivolumab, Erlotinib) were used for comparison.

Results

Epicatechin and Hispidulin showed the strongest binding affinities with PTGS2 (−9.04 kcal/mol) and XDH (−8.22 kcal/mol), respectively, with stable RMSD profiles. Chrysoeriol demonstrated the highest binding to KIT (−8.68 kcal/mol), outperforming Nivolumab (−6.03 kcal/mol). All selected flavonoids displayed acceptable pharmacokinetic profiles and low predicted toxicity. MD simulations confirmed the dynamic stability of key complexes.

Conclusion

Cassia-derived flavonoids represent promising multi-target candidates for lung cancer therapy, particularly through modulation of PTGS2, KIT, and XDH. Their favorable interaction profiles and safety predictions warrant further experimental and validation.

© 2026 Bentham Science Publishers
Loading

Article metrics loading...

/content/journals/cmc/10.2174/0109298673415885251023013748
2026-01-08
2026-02-24

  • From This Site

    /content/journals/cmc/10.2174/0109298673415885251023013748
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Thandra K.C. Barsouk A. Saginala K. Aluru J.S. Barsouk A. Epidemiology of lung cancer. Contemp. Oncol. 2021 25 1 45 52 10.5114/wo.2021.103829 33911981
    [Google Scholar]
  2. Barta J.A. Powell C.A. Wisnivesky J.P. Global epidemiology of lung cancer. Ann. Glob. Health 2019 85 1 8 10.5334/aogh.2419 30741509
    [Google Scholar]
  3. Schabath M.B. Cote M.L. Cancer progress and priorities: Lung cancer. Cancer Epidemiol. Biomarkers Prev. 2019 28 10 1563 1579 10.1158/1055‑9965.EPI‑19‑0221 31575553
    [Google Scholar]
  4. Deshpand R. Chandra M. Rauthan A. Evolving trends in lung cancer. Indian J. Cancer 2022 59 Suppl. 1 S90 S105 10.4103/ijc.IJC_52_21 35343194
    [Google Scholar]
  5. Guida F. Kidman R. Ferlay J. Schüz J. Soerjomataram I. Kithaka B. Ginsburg O. Mailhot Vega R.B. Galukande M. Parham G. Vaccarella S. Canfell K. Ilbawi A.M. Anderson B.O. Bray F. dos-Santos-Silva I. McCormack V. Global and regional estimates of orphans attributed to maternal cancer mortality in 2020. Nat. Med. 2022 28 12 2563 2572 10.1038/s41591‑022‑02109‑2 36404355
    [Google Scholar]
  6. Abou Khouzam R. Janji B. Thiery J. Zaarour R.F. Chamseddine A.N. Mayr H. Savagner P. Kieda C. Gad S. Buart S. Lehn J.M. Limani P. Chouaib S. Hypoxia as a potential inducer of immune tolerance, tumor plasticity and a driver of tumor mutational burden: Impact on cancer immunotherapy. Semin. Cancer Biol. 2023 Dec 97 104 123 10.1016/j.semcancer.2023.11.008 38029865
    [Google Scholar]
  7. Hirsch F.R. Scagliotti G.V. Mulshine J.L. Kwon R. Curran W.J. Jr Wu Y.L. Paz-Ares L. Lung cancer: Current therapies and new targeted treatments. Lancet 2017 389 10066 299 311 10.1016/S0140‑6736(16)30958‑8 27574741
    [Google Scholar]
  8. Scheff R.J. Schneider B.J. Non-small-cell lung cancer: Treatment of late stage disease: Chemotherapeutics and new frontiers. Semin. Intervent. Radiol. 2013 30 2 191 198 10.1055/s‑0033‑1342961 24436536
    [Google Scholar]
  9. Yang Z. Fu S. Li Y. Liang Y. Hao M. Guo R. Yu C. Hussain Z. Zhang J. Wang H. Exosome as non-invasive prognostic and diagnostic biomarker and nanovesicle for targeted therapy of non-small cell lung carcinoma. Chem. Eng. J. 2023 480 148160 10.1016/j.cej.2023.148160
    [Google Scholar]
  10. Leiter A. Veluswamy R.R. Wisnivesky J.P. The global burden of lung cancer: Current status and future trends. Nat. Rev. Clin. Oncol. 2023 20 9 624 639 10.1038/s41571‑023‑00798‑3 37479810
    [Google Scholar]
  11. Daylan A.E.C. Miao E. Tang K. Chiu G. Cheng H. Lung cancer in never smokers: Delving into epidemiology, genomic and immune landscape, prognosis, treatment, and screening. Lung 2023 201 6 521 529 10.1007/s00408‑023‑00661‑3 37973682
    [Google Scholar]
  12. Cani M. Turco F. Butticè S. Vogl U.M. Buttigliero C. Novello S. Capelletto E. How does environmental and occupational exposure contribute to carcinogenesis in genitourinary and lung cancers? Cancers 2023 15 10 2836 10.3390/cancers15102836 37345174
    [Google Scholar]
  13. Lahiri A. Maji A. Potdar P.D. Singh N. Parikh P. Bisht B. Mukherjee A. Paul M.K. Lung cancer immunotherapy: Progress, pitfalls, and promises. Mol. Cancer 2023 22 1 40 10.1186/s12943‑023‑01740‑y 36810079
    [Google Scholar]
  14. Attili I. Del Re M. Guerini-Rocco E. Crucitta S. Pisapia P. Pepe F. Barberis M. Troncone G. Danesi R. de Marinis F. Malapelle U. Passaro A. The role of molecular heterogeneity targeting resistance mechanisms to lung cancer therapies. Expert Rev. Mol. Diagn. 2021 21 8 757 766 10.1080/14737159.2021.1943365 34278933
    [Google Scholar]
  15. Chen H. Cheng X. Tumor heterogeneity and resistance to EGFR-targeted therapy in advanced nonsmall cell lung cancer: Challenges and perspectives. OncoTargets Ther. 2014 7 1689 1704 10.2147/OTT.S66502 25285017
    [Google Scholar]
  16. Lim Z.F. Ma P.C. Emerging insights of tumor heterogeneity and drug resistance mechanisms in lung cancer targeted therapy. J. Hematol. Oncol. 2019 12 1 134 10.1186/s13045‑019‑0818‑2 31815659
    [Google Scholar]
  17. Wang D.C. Wang W. Zhu B. Wang X. Lung cancer heterogeneity and new strategies for drug therapy. Annu. Rev. Pharmacol. Toxicol. 2018 58 1 531 546 10.1146/annurev‑pharmtox‑010716‑104523 28977762
    [Google Scholar]
  18. Mwangi R.W. Macharia J.M. Wagara I.N. Bence R.L. The medicinal properties of Cassia fistula L: A review. Biomed. Pharmacother. 2021 144 112240 10.1016/j.biopha.2021.112240 34601194
    [Google Scholar]
  19. Fatmawati S. Yuliana Purnomo A.S. Abu Bakar M.F. Chemical constituents, usage and pharmacological activity of Cassia alata. Heliyon 2020 6 7 04396 10.1016/j.heliyon.2020.e04396 32685725
    [Google Scholar]
  20. Pawar H.A. D’mello P.M. Cassia tora Linn.: An overview. Int. J. Pharm. Sci. Res. 2011 2 9 2286 10.13040/IJPSR.0975‑8232.2(9).2286‑91
    [Google Scholar]
  21. Kaur G. Alam M.S. Jabbar Z. Javed K. Athar M. Evaluation of antioxidant activity of Cassia siamea flowers. J. Ethnopharmacol. 2006 108 3 340 348 10.1016/j.jep.2006.05.021 16846707
    [Google Scholar]
  22. Afu G. Laryea M.K. Borquaye L.S. Biological efficacy and toxicological evaluation of ethanolic extract of Cassia nodosa Buch.-Ham. (Leguminosae). J. Chem. 2020 2020 1 1 13 10.1155/2020/3983491
    [Google Scholar]
  23. Ahmed S.I. Hayat M.Q. Tahir M. Mansoor Q. Ismail M. Keck K. Bates R.B. Pharmacologically active flavonoids from the anticancer, antioxidant and antimicrobial extracts of Cassia angustifolia Vahl. BMC Complement. Altern. Med. 2016 16 1 460 10.1186/s12906‑016‑1443‑z 27835979
    [Google Scholar]
  24. Chittam K. Deore S. Cassia javanica Linn.: A review on its phytochemical and pharmacological profile. J. Biomed. Pharma. Res. 2013 2 1 33 35
    [Google Scholar]
  25. Yadav J.P. Arya V. Yadav S. Panghal M. Kumar S. Dhankhar S. Cassia occidentalis L.: A review on its ethnobotany, phytochemical and pharmacological profile. Fitoterapia 2010 81 4 223 230 10.1016/j.fitote.2009.09.008 19796670
    [Google Scholar]
  26. Zibaee E. Javadi B. Sobhani Z. Akaberi M. Farhadi F. Amiri M.S. Baharara H. Sahebkar A. Emami S.A. Cassia species: A review of traditional uses, phytochemistry and pharmacology. Pharmacol. Res. Mod. Chin. Med. 2023 9 100325 10.1016/j.prmcm.2023.100325
    [Google Scholar]
  27. Dar R.A. Shahnawaz M. Ahanger M.A. Majid I. Exploring the diverse bioactive compounds from medicinal plants: A review. J. Phytopharmacol. 2023 12 3 189 195 10.31254/phyto.2023.12307
    [Google Scholar]
  28. Kyene M.O. Droepenu E.K. Ayertey F. Yeboah G.N. Archer M-A. Kumadoh D. Mintah S.O. Gordon P.K. Appiah A.A. Synthesis and characterization of ZnO nanomaterial from Cassia sieberiana and determination of its anti-inflammatory, antioxidant and antimicrobial activities. Sci. Afr. 2023 19 01452 10.1016/j.sciaf.2022.e01452
    [Google Scholar]
  29. Abood W.N. Immunomodulatory and anti-inflammatory effects of bioactive compounds of Cassia angustifolia Vahl. leaf extract. Plant Sci. Today 2024 11 2 10.14719/pst.3159
    [Google Scholar]
  30. Irshad M. Mehdi S.J. Al-Fatlawi A.A. Zafaryab M. Ali A. Ahmad I. Singh M. Rizvi M.M.A. Phytochemical composition of Cassia fistula fruit extracts and its anticancer activity against human cancer cell lines. J. Biol. Act. Prod. Nat. 2014 4 3 158 170 10.1080/22311866.2014.933084
    [Google Scholar]
  31. Batool S. Javed M.R. Aslam S. Noor F. Javed H.M.F. Seemab R. Rehman A. Aslam M.F. Paray B.A. Gulnaz A. Network pharmacology and bioinformatics approach reveals the multi-target pharmacological mechanism of Fumaria indica in the treatment of liver cancer. Pharmaceuticals 2022 15 6 654 10.3390/ph15060654 35745580
    [Google Scholar]
  32. Noor F. Tahir ul Qamar M. Ashfaq U.A. Albutti A. Alwashmi A.S.S. Aljasir M.A. Network pharmacology approach for medicinal plants: Review and assessment. Pharmaceuticals 2022 15 5 572 10.3390/ph15050572 35631398
    [Google Scholar]
  33. Malakar V. Dhanabal S.P. Justin A. Roy D. Kant K. Almeer R. Keremane K.S. Malakar C.C. Exploring the multi-target effects of Valeriana officinalis in Alzheimer’s disease: A network pharmacology approach. ChemistrySelect 2025 10 15 202403078 10.1002/slct.202403078
    [Google Scholar]
  34. Noor F. Rehman A. Ashfaq U.A. Saleem M.H. Okla M.K. Al-Hashimi A. AbdElgawad H. Aslam S. Integrating network pharmacology and molecular docking approaches to decipher the multi-target pharmacological mechanism of Abrus precatorius L. acting on diabetes. Pharmaceuticals 2022 15 4 414 10.3390/ph15040414 35455411
    [Google Scholar]
  35. Aloufi B. Alshabrmi F.M. Sreeharsha N. Rehman A. Exploring therapeutic targets and drug candidates for obesity: A combined network pharmacology, bioinformatics approach. J. Biomol. Struct. Dyn. 2024 42 21 11879 11900 10.1080/07391102.2023.2265491 37811763
    [Google Scholar]
  36. Rehman A. Noor F. Fatima I. Qasim M. Liao M. Identification of molecular mechanisms underlying the therapeutic effects of Celosia cristata on immunoglobulin nephropathy. Comput. Biol. Med. 2022 151 Pt A 106290 10.1016/j.compbiomed.2022.106290 36379189
    [Google Scholar]
  37. Rehman A. Fatima I. Wang Y. Tong J. Noor F. Qasim M. Peng Y. Liao M. Unveiling the multi-target compounds of Rhazya stricta: Discovery and inhibition of novel target genes for the treatment of clear cell renal cell carcinoma. Comput. Biol. Med. 2023 165 107424 10.1016/j.compbiomed.2023.107424 37717527
    [Google Scholar]
  38. Basavarajappa G.M. Rehman A. Shiroorkar P.N. Sreeharsha N. Anwer M.K. Aloufi B. Therapeutic effects of Crataegus monogyna inhibitors against breast cancer. Front. Pharmacol. 2023 14 1187079 10.3389/fphar.2023.1187079 37180727
    [Google Scholar]
  39. Vivek-Ananth R.P. Mohanraj K. Sahoo A.K. Samal A. IMPPAT 2.0: An enhanced and expanded phytochemical atlas of Indian medicinal plants. ACS Omega 2023 8 9 8827 8845 10.1021/acsomega.3c00156 36910986
    [Google Scholar]
  40. Nakamura Y. Mochamad Afendi F. Kawsar Parvin A. Ono N. Tanaka K. Hirai Morita A. Sato T. Sugiura T. Altaf-Ul-Amin M. Kanaya S. KNApSAcK Metabolite Activity Database for retrieving the relationships between metabolites and biological activities. Plant Cell Physiol. 2014 55 1 e7 e7 10.1093/pcp/pct176 24285751
    [Google Scholar]
  41. Daina A. Michielin O. Zoete V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 2017 7 1 42717 10.1038/srep42717 28256516
    [Google Scholar]
  42. Xiong G. Wu Z. Yi J. Fu L. Yang Z. Hsieh C. Yin M. Zeng X. Wu C. Lu A. Chen X. Hou T. Cao D. ADMETlab 2.0: An integrated online platform for accurate and comprehensive predictions of ADMET properties. Nucleic Acids Res. 2021 49 W1 W5 W14 10.1093/nar/gkab255 33893803
    [Google Scholar]
  43. Kim S. Chen J. Cheng T. Gindulyte A. He J. He S. Li Q. Shoemaker B.A. Thiessen P.A. Yu B. Zaslavsky L. Zhang J. Bolton E.E. PubChem 2019 update: Improved access to chemical data. Nucleic Acids Res. 2019 47 D1 D1102 D1109 10.1093/nar/gky1033 30371825
    [Google Scholar]
  44. Pence H.E. Williams A. ChemSpider: An online chemical information resource. J. Chem. Educ. 2010 87 11 1123 1124 10.1021/ed100697w
    [Google Scholar]
  45. Banerjee P. Eckert A.O. Schrey A.K. Preissner R. ProTox-II: A webserver for the prediction of toxicity of chemicals. Nucleic Acids Res. 2018 46 W1 W257 W263 10.1093/nar/gky318 29718510
    [Google Scholar]
  46. Kuhn M. Szklarczyk D. Franceschini A. Campillos M. von Mering C. Jensen L.J. Beyer A. Bork P. STITCH 2: An interaction network database for small molecules and proteins. Nucleic Acids Res. 2010 38 Database issue D552 D556 10.1093/nar/gkp937 19897548
    [Google Scholar]
  47. Gfeller D. Grosdidier A. Wirth M. Daina A. Michielin O. Zoete V. SwissTargetPrediction: A web server for target prediction of bioactive small molecules. Nucleic Acids Res. 2014 42 W1 W32 W38 10.1093/nar/gku293 24792161
    [Google Scholar]
  48. Clough E. Barrett T. The gene expression omnibus database. Methods Mol. Biol. 2016 1418 93 110 10.1007/978‑1‑4939‑3578‑9_5 27008011
    [Google Scholar]
  49. Ritchie M.E. Phipson B. Wu D. Hu Y. Law C.W. Shi W. Smyth G.K. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 2015 43 7 e47 e47 10.1093/nar/gkv007 25605792
    [Google Scholar]
  50. Dennis G. Jr Sherman B.T. Hosack D.A. Yang J. Gao W. Lane H.C. Lempicki R.A. DAVID: Database for annotation, visualization, and integrated discovery. Genome Biol. 2003 4 5 P3 10.1186/gb‑2003‑4‑5‑p3 12734009
    [Google Scholar]
  51. Mering C. Huynen M. Jaeggi D. Schmidt S. Bork P. Snel B. STRING: A database of predicted functional associations between proteins. Nucleic Acids Res. 2003 31 1 258 261 10.1093/nar/gkg034 12519996
    [Google Scholar]
  52. Kohl M. Wiese S. Warscheid B. Cytoscape: Software for visualization and analysis of biological networks. Methods Mol. Biol. 2011 696 291 303 10.1007/978‑1‑60761‑987‑1_18 21063955
    [Google Scholar]
  53. Tang Z. Kang B. Li C. Chen T. Zhang Z. GEPIA2: An enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Res. 2019 47 W1 W556 W560 10.1093/nar/gkz430 31114875
    [Google Scholar]
  54. Rose P.W. Prlić A. Altunkaya A. Bi C. Bradley A.R. Christie C.H. Costanzo L.D. Duarte J.M. Dutta S. Feng Z. Green R.K. Goodsell D.S. Hudson B. Kalro T. Lowe R. Peisach E. Randle C. Rose A.S. Shao C. Tao Y.P. Valasatava Y. Voigt M. Westbrook J.D. Woo J. Yang H. Young J.Y. Zardecki C. Berman H.M. Burley S.K. The RCSB protein data bank: Integrative view of protein, gene and 3D structural information. Nucleic Acids Res 2017 45 D1 D271 D281 10.1093/nar/gkw1000 27794042
    [Google Scholar]
  55. Pettersen E.F. Goddard T.D. Huang C.C. Couch G.S. Greenblatt D.M. Meng E.C. Ferrin T.E. UCSF Chimera—A visualization system for exploratory research and analysis. J. Comput. Chem. 2004 25 13 1605 1612 10.1002/jcc.20084 15264254
    [Google Scholar]
  56. Dundas J. Ouyang Z. Tseng J. Binkowski A. Turpaz Y. Liang J. CASTp: Computed atlas of surface topography of proteins with structural and topographical mapping of functionally annotated residues. Nucleic Acids Res. 2006 34 Web Server W116 W118 10.1093/nar/gkl282 16844972
    [Google Scholar]
  57. Dallakyan S. Olson A.J. Small-molecule library screening by docking with PyRx. Methods Mol. Biol. 2015 1263 243 250 10.1007/978‑1‑4939‑2269‑7_19 25618350
    [Google Scholar]
  58. Goddard T.D. Huang C.C. Meng E.C. Pettersen E.F. Couch G.S. Morris J.H. Ferrin T.E. UCSF ChimeraX: Meeting modern challenges in visualization and analysis. Protein Sci. 2018 27 1 14 25 10.1002/pro.3235 28710774
    [Google Scholar]
  59. Sharma S. Sharma A. Gupta U. Molecular docking studies on the anti-fungal activity of Allium sativum (Garlic) against Mucormycosis (black fungus) by BIOVIA discovery studio visualizer, 2021. 21.1. 0.0.
    [Google Scholar]
  60. Zhou B. Zang R. Zhang M. Song P. Liu L. Bie F. Peng Y. Bai G. Gao S. Worldwide burden and epidemiological trends of tracheal, bronchus, and lung cancer: A population-based study. EBioMedicine 2022 78 103951 10.1016/j.ebiom.2022.103951 35313216
    [Google Scholar]
  61. Li C. Lei S. Ding L. Xu Y. Wu X. Wang H. Zhang Z. Gao T. Zhang Y. Li L. Global burden and trends of lung cancer incidence and mortality. Chin. Med. J. 2023 136 13 1583 1590 10.1097/CM9.0000000000002529 37027426
    [Google Scholar]
  62. Megyesfalvi Z. Gay C.M. Popper H. Pirker R. Ostoros G. Heeke S. Lang C. Hoetzenecker K. Schwendenwein A. Boettiger K. Bunn P.A. Jr Renyi-Vamos F. Schelch K. Prosch H. Byers L.A. Hirsch F.R. Dome B. Clinical insights into small cell lung cancer: Tumor heterogeneity, diagnosis, therapy, and future directions. CA Cancer J. Clin. 2023 73 6 620 652 10.3322/caac.21785 37329269
    [Google Scholar]
  63. Tang F.H. Wong H.Y.T. Tsang P.S.W. Yau M. Tam S.Y. Law L. Yau K. Wong J. Farah F.H.M. Wong J. Recent advancements in lung cancer research: A narrative review. Transl. Lung Cancer Res. 2025 14 3 975 990 10.21037/tlcr‑24‑979 40248731
    [Google Scholar]
  64. Rejiya C.S. Cibin T.R. Abraham A. Leaves of Cassia tora as a novel cancer therapeutic – An in vitro study. Toxicol. In Vitro 2009 23 6 1034 1038 10.1016/j.tiv.2009.06.010 19540331
    [Google Scholar]
  65. Noor F. Asif M. Ashfaq U.A. Qasim M. Tahir ul Qamar M. Machine learning for synergistic network pharmacology: A comprehensive overview. Brief. Bioinform. 2023 24 3 bbad120 10.1093/bib/bbad120 37031957
    [Google Scholar]
  66. Hadi F. Noor F. Sardar H. Darwish H.W. Ashfaq U.A. Khan A.A. Daglia M. Khan H. Integrating in vitro, network pharmacology, and molecular docking approaches to uncover the antidiabetic potential of Tylophora hirsuta. Comput. Biol. Chem. 2025 119 108533 10.1016/j.compbiolchem.2025.108533 40516341
    [Google Scholar]
  67. Noor F. Shahid S. Fatima M. Haider S.Z. Al Shehri Z.S. Alshehri F.F. Rehman A. Bioinformatics and immunoinformatics approaches in the design of a multi-epitope vaccine targeting CTLA-4 for melanoma treatment. Mol. Divers. 2025 1 20 10.1007/s11030‑025‑11108‑7 39873886
    [Google Scholar]
  68. Hopkins A.L. Network pharmacology: The next paradigm in drug discovery. Nat. Chem. Biol. 2008 4 11 682 690 10.1038/nchembio.118 18936753
    [Google Scholar]
  69. Liu S. Li S. Dong Y. Qiao K. Zhao Y. Yu J. Hispidulin targets PTGS2 to improve cyclophosphamide-induced cystitis by suppressing NLRP3 inflammasome. Naunyn Schmiedebergs Arch. Pharmacol. 2024 397 8 5819 5830 10.1007/s00210‑024‑02987‑y 38321213
    [Google Scholar]
  70. Takemura H. Uchiyama H. Ohura T. Sakakibara H. Kuruto R. Amagai T. Shimoi K. A methoxyflavonoid, chrysoeriol, selectively inhibits the formation of a carcinogenic estrogen metabolite in MCF-7 breast cancer cells. J. Steroid Biochem. Mol. Biol. 2010 118 1-2 70 76 10.1016/j.jsbmb.2009.10.002 19833205
    [Google Scholar]
  71. Alsharairi N.A. Insights into the mechanisms of action of proanthocyanidins and anthocyanins in the treatment of nicotine-induced non-small cell lung cancer. Int. J. Mol. Sci. 2022 23 14 7905 10.3390/ijms23147905 35887251
    [Google Scholar]
  72. Rausch S.M. Gonzalez B.D. Clark M.M. Patten C. Felten S. Liu H. Li Y. Sloan J. Yang P. SNPs in PTGS2 and LTA predict pain and quality of life in long term lung cancer survivors. Lung Cancer 2012 77 1 217 223 10.1016/j.lungcan.2012.02.017 22464751
    [Google Scholar]
  73. Mattsson J.S.M. Bergman B. Grinberg M. Edlund K. Marincevic M. Jirström K. Pontén F. Hengstler J.G. Rahnenführer J. Karlsson M.G. Karlsson C. Helenius G. Botling J. Micke P. Gulyas M. Prognostic impact of COX-2 in non-small cell lung cancer: A comprehensive compartment-specific evaluation of tumor and stromal cell expression. Cancer Lett. 2015 356 2 837 845 10.1016/j.canlet.2014.10.032 25449785
    [Google Scholar]
  74. Lin X. Luo W. Wang H. Li R. Huang Y. Chen L. Wu X. The role of prostaglandin-endoperoxide synthase-2 in chemoresistance of non-small cell lung cancer. Front. Pharmacol. 2019 10 836 10.3389/fphar.2019.00836 31440159
    [Google Scholar]
  75. Jara-Gutiérrez Á. Baladrón V. The role of prostaglandins in different types of cancer. Cells 2021 10 6 1487 10.3390/cells10061487 34199169
    [Google Scholar]
  76. Finetti F. Travelli C. Ercoli J. Colombo G. Buoso E. Trabalzini L. Prostaglandin E2 and cancer: Insight into tumor progression and immunity. Biology 2020 9 12 434 10.3390/biology9120434 33271839
    [Google Scholar]
  77. Martey C.A. Pollock S.J. Turner C.K. O’Reilly K.M.A. Baglole C.J. Phipps R.P. Sime P.J. Cigarette smoke induces cyclooxygenase-2 and microsomal prostaglandin E2 synthase in human lung fibroblasts: Implications for lung inflammation and cancer. Am. J. Physiol. Lung Cell. Mol. Physiol. 2004 287 5 L981 L991 10.1152/ajplung.00239.2003 15234907
    [Google Scholar]
  78. Li F. Zheng Z. Chen W. Li D. Zhang H. Zhu Y. Mo Q. Zhao X. Fan Q. Deng F. Han C. Tan W. Regulation of cisplatin resistance in bladder cancer by epigenetic mechanisms. Drug Resist. Updat. 2023 68 100938 10.1016/j.drup.2023.100938 36774746
    [Google Scholar]
/content/journals/cmc/10.2174/0109298673415885251023013748
Loading
Cassia-Derived Natural Flavonoids as Multi-Target Candidates for Lung Cancer Therapy: A Network Pharmacology and Molecular Modeling Study
Bentham Science Publishers ; https://doi.org/10.2174/0109298673415885251023013748
/content/journals/cmc/10.2174/0109298673415885251023013748
/content/journals/cmc/10.2174/0109298673415885251023013748
Loading

Data & Media loading...

Supplements

Supplementary material is available on the publisher’s website along with the published article.

file format download Download

  • Article Type:     Research Article
Keywords: Lung cancer ; integrated medicine ; molecular docking, simulation ; network pharmacology ; flavonoids

Most Cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test