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2000
Volume 30, Issue 33
  • ISSN: 1381-6128
  • E-ISSN: 1873-4286

Abstract

Background

The burden of malignant lymphoma in China is greater than the global equivalent. The randomized controlled trials provide medical evidence that TCM can improve the response and survival in patients with lymphoma. However, the mechanisms underlying remain undefined.

Objective

Evidence-based data mining for traditional Chinese medicine (TCM) on improving response and survival in malignant lymphoma treatment was performed in this study. In addition, the mechanisms of TCM through network pharmacology and molecular docking were explored.

Methods

The China national knowledge infrastructure, Wanfang Data, China Science and Technology Journal Database, PubMed, and Web of Science databases were searched to select TCM formulas with response and survival benefits in the treatment of malignant lymphomas. We then analyzed and visualized the tropism of taste, frequency of drug use, dosage, clustering, association rules mining (minimum support threshold as 0.20, the minimum confidence threshold as 0.80 and lift >1), and complex networks for potential core herb compositions using Excel, IBM SPSS Statistics 26, and IBM SPSS Modeler 18. TCM systems pharmacology, GeneCards, Online Mendelian Inheritance in Man, and other databases were used to screen potential core active ingredients and malignant lymphoma-related targets. The intersection targets were used to construct a protein interaction network using Cytoscape to obtain the key targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment were used to analyze the core target, and molecular docking of key components and targets was performed using CB-Dock2.

Results

Twenty-four Chinese herbal formulae were included, encompassing 107 herbs with mainly cold and warm properties and bitter and sweet flavors. They were associated with the yin meridians of the liver, spleen, and lungs. The TCMs underwent association rule analysis, identified 27 association rules, including 12 herb pairs and 13 angle medicine, and clustered into eight classes by clustering analysis. Combined with the results from mining analysis, Pinelliae (Ban-xia), Poria (Fu-ling), Atractylodis macrocephalae (Bai-zhu), Curcumae (E-zhu), and Sparganii (San-leng) were the potential core herbs According to network pharmacology and molecular docking, the main core components of the potential core drugs are hederagenin, cerevisterol, 14-acetyl-12-senecioyl-2E,8E,10E-atractylentriol, 12,13-epoxy-9-hydroxynonadeca-7,10-dienoic acid, cavidine, and baicalein. These core drugs are mainly involved in the pathways of EGFR tyrosine kinase inhibitor resistance, PD-1/L1, natural killer cell-mediated cytotoxicity, NF-κB, epithelial cell signaling in H. pylori infections, and Th17 cell differentiation. They aid in regulating the transmembrane receptor protein tyrosine kinase signaling pathway, ERBB signaling pathway, PI3K signaling pathway, and phosphorylation process. Ten key components and eight key targets, including baicalein and hederagenin, demonstrated strong binding activity.

Conclusion

Collectively, some core herbs exerted anti-tumor effects through immune and inflammatory pathway modulation, inhibition of immune escape, and induction of cell apoptosis. These findings support future evidence-based research on malignant lymphoma treatment using TCM.

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2024-07-30
2024-11-14
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References

  1. LiuW. LiuJ. SongY. Burden of lymphoma in China, 1990-2019: An analysis of the global burden of diseases, injuries, and risk factors study 2019.Aging20221473175319010.18632/aging.204006 35398840
    [Google Scholar]
  2. LiuW. JiX. SongY. Improving survival of 3760 patients with lymphoma: Experience of an academic center over two decades.Cancer Med.20209113765377410.1002/cam4.3037 32281275
    [Google Scholar]
  3. AllemaniC. MatsudaT. Di CarloV. Global surveillance of trends in cancer survival 2000–14 (CONCORD-3): Analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries.Lancet2018391101251023107510.1016/S0140‑6736(17)33326‑3 29395269
    [Google Scholar]
  4. HB. Research hotspots and trends of lymphoma in the field of traditional Chinese medicine based on cite space visualization.Guid J Trad Chin Med Pharm202228164173
    [Google Scholar]
  5. ChoudharyN. SinghV. A census of P. longum’s phytochemicals and their network pharmacological evaluation for identifying novel drug-like molecules against various diseases, with a special focus on neurological disorders.PLoS One2018131e019100610.1371/journal.pone.0191006 29320554
    [Google Scholar]
  6. HuangQ. LinJ. HuangS. ShenJ. Impact of qi-invigorating traditional chinese medicines on diffuse large B cell lymphoma based on network pharmacology and experimental validation.Front. Pharmacol.20211278781610.3389/fphar.2021.787816 34955857
    [Google Scholar]
  7. Agrawal RakeshS.R. Mining sequential patterns.Proceedings of the Eleventh International Conference on Data Engineering.31410.1109/ICDE.1995.380415
    [Google Scholar]
  8. RakeshA. Mining association rules between sets of items in large databases.Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data20716
    [Google Scholar]
  9. RakeshA. RamakrishnanS. Fast algorithms for mining association rules.Proceedings of the 20th VLDB Conference48799
    [Google Scholar]
  10. LuoW. DingR. GuoX. Clinical data mining reveals Gancao-Banxia as a potential herbal pair against moderate COVID‐19 by dual binding to IL-6/STAT3.Comput. Biol. Med.202214510545710.1016/j.compbiomed.2022.105457 35366469
    [Google Scholar]
  11. Lab of Systems Pharmacology Lab of Systems Pharmacology. 2012-2023Available from: https://www.tcmsp-e.com/#/home
  12. KimS. ChenJ. ChengT. PubChem 2023 update.Nucleic Acids Res.202351D1D1373D138010.1093/nar/gkac956 36305812
    [Google Scholar]
  13. GfellerD. MichielinO. ZoeteV. Shaping the interaction landscape of bioactive molecules.Bioinformatics201329233073307910.1093/bioinformatics/btt540 24048355
    [Google Scholar]
  14. WishartD.S. FeunangY.D. GuoA.C. DrugBank 5.0: A major update to the DrugBank database for 2018.Nucleic Acids Res.201846D1D1074D108210.1093/nar/gkx1037 29126136
    [Google Scholar]
  15. StelzerG RosenN PlaschkesI The GeneCards Suite: From gene data mining to disease genome sequence analyses.Curr Protoc Bioinformatics2016541.30.3131.30.33
    [Google Scholar]
  16. ZhouY. ZhangY. ZhaoD. TTD: Therapeutic target database describing target druggability information.Nucleic Acids Res.202352D1465D1477 37713619
    [Google Scholar]
  17. SzklarczykD. KirschR. KoutrouliM. The STRING database in 2023: Protein–protein association networks and functional enrichment analyses for any sequenced genome of interest.Nucleic Acids Res.202351D1D638D64610.1093/nar/gkac1000 36370105
    [Google Scholar]
  18. ZhouY. ZhouB. PacheL. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.Nat. Commun.2019101152310.1038/s41467‑019‑09234‑6 30944313
    [Google Scholar]
  19. RCSB Protein Data BankAvailable from: http://www.rcsb.org
  20. LiuY. YangX. GanJ. ChenS. XiaoZ.X. CaoY. CB-Dock2: improved protein-ligand blind docking by integrating cavity detection, docking and homologous template fitting.Nucleic Acids Res.202250W1W159-6410.1093/nar/gkac394 35609983
    [Google Scholar]
  21. YangX. LiuY. GanJ. XiaoZ.X. CaoY. FitDock: Protein-ligand docking by template fitting.Brief. Bioinform.2022233bbac08710.1093/bib/bbac087 35289358
    [Google Scholar]
  22. SungH. FerlayJ. SiegelR.L. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J. Clin.202171320924910.3322/caac.21660 33538338
    [Google Scholar]
  23. ZongchaoL. ZhexuanL. YangZ. Interpretation on the report of global cancer statistics 2020.J Multidiscipl Can Manag2021702114
    [Google Scholar]
  24. LiuW. LiuJ. SongY. Burden of lymphoma in China, 2006–2016: An analysis of the global burden of disease study 2016.J. Hematol. Oncol.201912111510.1186/s13045‑019‑0785‑7 31744509
    [Google Scholar]
  25. GreenM.R. MontiS. RodigS.J. Integrative analysis reveals selective 9p24.1 amplification, increased PD-1 ligand expression, and further induction via JAK2 in nodular sclerosing Hodgkin lymphoma and primary mediastinal large B-cell lymphoma.Blood2010116173268327710.1182/blood‑2010‑05‑282780 20628145
    [Google Scholar]
  26. TwaD.D.W. ChanF.C. Ben-NeriahS. Genomic rearrangements involving programmed death ligands are recurrent in primary mediastinal large B-cell lymphoma.Blood2014123132062206510.1182/blood‑2013‑10‑535443 24497532
    [Google Scholar]
  27. Elenitoba-JohnsonK.S.J. LimM.S. New insights into lymphoma pathogenesis.Annu. Rev. Pathol.201813119321710.1146/annurev‑pathol‑020117‑043803 29140757
    [Google Scholar]
  28. CullyM. YouH. LevineA.J. MakT.W. Beyond PTEN mutations: The PI3K pathway as an integrator of multiple inputs during tumorigenesis.Nat. Rev. Cancer20066318419210.1038/nrc1819 16453012
    [Google Scholar]
  29. BorladoL.R. RedondoC. AlvarezB. Increased phosphoinositide 3-kinase activity induces a lymphoproliferative disorder and contributes to tumor generation in vivo.FASEB J.200014789590310.1096/fasebj.14.7.895 10783143
    [Google Scholar]
  30. NakamuraS. MatsumotoT. Helicobacter pylori and gastric mucosa-associated lymphoid tissue lymphoma: Recent progress in pathogenesis and management.World J. Gastroenterol.201319458181818710.3748/wjg.v19.i45.8181 24363507
    [Google Scholar]
  31. TuliH.S. AggarwalV. KaurJ. Baicalein: A metabolite with promising antineoplastic activity.Life Sci.202025911818310.1016/j.lfs.2020.118183 32781058
    [Google Scholar]
  32. PatwardhanR.S. Baicalein induces cell death in murine T cell lymphoma via inhibition of thioredoxin system.Int. J. Biochem. Cell Biol.2017914592
    [Google Scholar]
  33. YuX. LiH. ZhuM. Involvement of p53 acetylation in growth suppression of cutaneous T-cell lymphomas induced by HDAC inhibition.J. Invest. Dermatol.202014020092022
    [Google Scholar]
  34. OladimejiA.O. OladosuI.A. AliM.S. KhanS.A. YousufS. Cytotoxic effect of hederagenin on NCI-H460, human non-small lung cancer cells and its free radical scavenging activities.J Biol Activ Prod Nat201665-636537210.1080/22311866.2016.1269614
    [Google Scholar]
  35. TianK. SuY. DingJ. Hederagenin protects mice against ovariectomy-induced bone loss by inhibiting RANKL-induced osteoclastogenesis and bone resorption.Life Sci.202024411733610.1016/j.lfs.2020.117336 31972206
    [Google Scholar]
  36. LeeC.W. ParkS.M. ZhaoR. Hederagenin, a major component of Clematis mandshurica Ruprecht root, attenuates inflammatory responses in RAW 264.7 cells and in mice.Int. Immunopharmacol.201529252853710.1016/j.intimp.2015.10.002 26481049
    [Google Scholar]
  37. GaoY. HeC. BiW. WuG. AltmanE. Bioassay guided fractionation identified hederagenin as a major cytotoxic agent from] Cyclocarya paliurus leaves.Planta Med.2016821-2171179 26393939
    [Google Scholar]
  38. ParkH.J. KwonS.H. LeeJ.H. LeeK.H. MiyamotoK. LeeK.T. Kalopanaxsaponin A is a basic saponin structure for the anti-tumor activity of hederagenin monodesmosides.Planta Med.200167211812110.1055/s‑2001‑11516 11301855
    [Google Scholar]
  39. KimG.J. SongD. YooH. ChungK.H. LeeK. AnJ. Hederagenin supplementation alleviates the pro-inflammatory and apoptotic response to alcohol in rats.Nutrients2017914110.3390/nu9010041 28067819
    [Google Scholar]
  40. LiY. DongJ. ShangY. ZhaoQ. LiP. WuB. Anti-inflammatory effects of hederagenin on diabetic cardiomyopathy via inhibiting NF-κB and Smads signaling pathways in a type-2 diabetic mice model.RSC Advances2019945262382624710.1039/C9RA02043H 35531007
    [Google Scholar]
  41. AsatiN. YadavaR.N. Antibacterial activity of a triterpenoid saponin from the stems of Caesalpinia pulcherrima Linn.Nat. Prod. Res.201832549950710.1080/14786419.2017.1317772 28423926
    [Google Scholar]
  42. NdjateuF.S.T. TsafackR.B.N. NganouB.K. Antimicrobial and antioxidant activities of extracts and ten compounds from three Cameroonian medicinal plants: Dissotis perkinsiae (Melastomaceae), Adenocarpus mannii (Fabaceae) and Barteria fistulosa (Passifloraceae).S. Afr. J. Bot.201491374210.1016/j.sajb.2013.11.009
    [Google Scholar]
  43. LiangB.F. HuangF. WangH.T. Involvement of norepinephrine and serotonin system in antidepressant-like effects of hederagenin in the rat model of unpredictable chronic mild stress-induced depression.Pharm. Biol.201553336837710.3109/13880209.2014.922586 25471378
    [Google Scholar]
  44. LinR. LiuL. SilvaM. Hederagenin protects PC12 cells against corticosterone-induced injury by the activation of the PI3K/AKT pathway.Front. Pharmacol.20211271287610.3389/fphar.2021.712876 34721013
    [Google Scholar]
  45. XieW FangX li H, et al. Advances in the anti-tumor potential of hederagenin and its analogs.Eur. J. Pharmacol.202395917607310.1016/j.ejphar.2023.176073 37742813
    [Google Scholar]
  46. HuangW. WangY. XuS. Design, synthesis, and tumor drug resistance reversal activity of novel hederagenin derivatives modified by nitrogen-containing heterocycles.Eur. J. Med. Chem.202223211420710.1016/j.ejmech.2022.114207 35219948
    [Google Scholar]
  47. Rodríguez-HernándezD. DemunerA.J. BarbosaL.C.A. HellerL. CsukR. Novel hederagenin-triazolyl derivatives as potential anti-cancer agents.Eur. J. Med. Chem.201611525726710.1016/j.ejmech.2016.03.018 27017553
    [Google Scholar]
  48. JabbourE. OttmannO.G. DeiningerM. HochhausA. Targeting the phosphoinositide 3-kinase pathway in hematologic malignancies.Haematologica201499171810.3324/haematol.2013.087171 24425689
    [Google Scholar]
  49. PatilK. KuttikrishnanS. KhanA.Q. Molecular pathogenesis of cutaneous T cell lymphoma: Role of chemokines, cytokines, and dysregulated signaling pathways.Semin. Cancer Biol.202286Pt 338239910.1016/j.semcancer.2021.12.003 34906723
    [Google Scholar]
  50. AbrahamR.M. ZhangQ. OdumN. WasikM.A. The role of cytokine signaling in the pathogenesis of cutaneous T-cell lymphoma.Cancer Biol. Ther.201112121019102210.4161/cbt.12.12.18144 22236880
    [Google Scholar]
  51. LaurentC. CharmpiK. GravelleP. Several immune escape patterns in non-Hodgkin’s lymphomas.OncoImmunology201548e102653010.1080/2162402X.2015.1026530 26405585
    [Google Scholar]
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