Network pharmacological approach predicts potential therapeutic targets for chronic myeloid leukemia

Cancer is an extremely complicated, multifaceted, organ-specific, and resilient illness. Chronic myeloid leukemia (CML), one of the most studied human diseases, has been associated with the Philadelphia (Ph) chromosome, a balanced, reciprocal translocation involving the long arms of chromosomes 9 and 22, for a number of reasons. Chronic phase (CP), accelerated phase (AP), and blast crisis (BC) are the clinical stages of CML, and each phase has a different kind of ab-normality. We selected the CML gene expression dataset for this study. To identify differentially expressed genes (DEGs), we employed a gene expression dataset. Using the DEGs, we also discovered significant KEGG pathways to better understand the signaling cascades underpinning BC development. The most down-regulated genes were PRKY, TREX2, SRD5A1P1, CD40LG, RAP2C-AS1, APLN, H2BW3P, TMSB15A, ARMCX2, and TERF1P7, in addition to MAP1A, CDKN1A, SERPINE1, SLFN14, SYT11, HNRNPA1, ECM1, CCDC92, CASS4, CENPI, TREML2, UTP25, JDP2, APO-BEC3H, CDKN1A, SLFN14, SYT11, HNRNPA1, ECM1, CCDC92, CASS4, CENPI, TREML2, APO-BEC3H, and MMP2. The DEGs with the strongest linkages across the whole DEG network are NTRK1, FBL, APEX1, HSP90AB1, SSRP1, IMPDH2, EIF3A, DKC1, NAT10, HNRN-PA1, SYNCRIP, PES1, EXOSC5, MYBBP1A, and IMP4. We can therefore conclude that these DEGs may be significant and the cause of changes in biological processes and gene expression. Furthermore, we observe that a number of potential signaling pathways, including as p53, PI3K-Akt, calcium signaling, ECM, Wnt, FoxO, cell cycle, and JAK-Stat signaling, were significantly enriched. We concluded that there was little chance that either drug would bind to MAP1A. Lastly, we conclude that Diosmin has a higher affinity for Apigenin based on the drug-target predictions. The top-ranked clustered proteins and the inferred proteins of the up-regulated genes did not bind the two medications in the same way as the inferred proteins of the top-ranked down-regulated genes. The drug that had the strongest affinity for both drugs was TREX2.

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Publication Details

Journal
Global Journal of Basic Science
Published
2025-06-15
DOI
https://doi.org/10.63454/jbs20000036
Primary Topic
Kruppel-like factors research
Type
article
Field-Weighted Citation Impact
0.00

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article

Network pharmacological approach predicts potential therapeutic targets for chronic myeloid leukemia

Rehab Al-Massabi
Global Journal of Basic Science
Kruppel-like factors research
article

Network pharmacological approach predicts potential therapeutic targets for chronic myeloid leukemia

Rehab Al-Massabi
article en

Abstract

Cancer is an extremely complicated, multifaceted, organ-specific, and resilient illness. Chronic myeloid leukemia (CML), one of the most studied human diseases, has been associated with the Philadelphia (Ph) chromosome, a balanced, reciprocal translocation involving the long arms of chromosomes 9 and 22, for a number of reasons. Chronic phase (CP), accelerated phase (AP), and blast crisis (BC) are the clinical stages of CML, and each phase has a different kind of ab-normality. We selected the CML gene expression dataset for this study. To identify differentially expressed genes (DEGs), we employed a gene expression dataset. Using the DEGs, we also discovered significant KEGG pathways to better understand the signaling cascades underpinning BC development. The most down-regulated genes were PRKY, TREX2, SRD5A1P1, CD40LG, RAP2C-AS1, APLN, H2BW3P, TMSB15A, ARMCX2, and TERF1P7, in addition to MAP1A, CDKN1A, SERPINE1, SLFN14, SYT11, HNRNPA1, ECM1, CCDC92, CASS4, CENPI, TREML2, UTP25, JDP2, APO-BEC3H, CDKN1A, SLFN14, SYT11, HNRNPA1, ECM1, CCDC92, CASS4, CENPI, TREML2, APO-BEC3H, and MMP2. The DEGs with the strongest linkages across the whole DEG network are NTRK1, FBL, APEX1, HSP90AB1, SSRP1, IMPDH2, EIF3A, DKC1, NAT10, HNRN-PA1, SYNCRIP, PES1, EXOSC5, MYBBP1A, and IMP4. We can therefore conclude that these DEGs may be significant and the cause of changes in biological processes and gene expression. Furthermore, we observe that a number of potential signaling pathways, including as p53, PI3K-Akt, calcium signaling, ECM, Wnt, FoxO, cell cycle, and JAK-Stat signaling, were significantly enriched. We concluded that there was little chance that either drug would bind to MAP1A. Lastly, we conclude that Diosmin has a higher affinity for Apigenin based on the drug-target predictions. The top-ranked clustered proteins and the inferred proteins of the up-regulated genes did not bind the two medications in the same way as the inferred proteins of the top-ranked down-regulated genes. The drug that had the strongest affinity for both drugs was TREX2.

Global Journal of Basic ScienceVol. 1(8)
University of Tabuk
Openalex Percentile: Top 78%
Kruppel-like factors research
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Network pharmacological approach predicts potential therapeutic targets for chronic myeloid leukemia — Rehab Al-Massabi · Global Journal of Basic Science (2025) | TGRS Research Map | TGRS