Abstract
Cyclophosphamide (CP), an important alkylating agent which is used in the treatment therapy for chronic myeloid leukemia (CML). However, acquired drug resistance owing to the inactivation of its active metabolite aldophosphamide via tumoral-overexpressing aldehyde dehydrogenase (ALDH1A1) is one of the major issues with the CP therapy. However, the underlying mechanism of ALDH1A1 overexpression in cancer cells remains poorly defined. Therefore, the current study focused on analyzing the ALDH1A1-overexpressing microarray data for CP resistance and CP-sensitive CML cell lines. In this study, the microarray dataset was obtained from Gene Expression Omnibus GEO. The GEO2R tool was used to identify Differentially Expressing Genes (DEGs). Further, protein–protein interaction (PPI) network of DEGs were constructed using STRING database. Finally, Hub gene-miRNA-TFs interaction were constructed using miRNet tool. A total of 749 DEGs including 387 upregulated and 225 downregulated genes were identified from this pool of microarray data. The construction of DEGs network resulted in identification of three genes including ZEB2, EZH2, and MUC1 were found to be majorly responsible for ALDH1A1 overexpression. miRNA analysis identified that, hsa-mir-16-5p and hsa-mir-26a-5p as hub miRNA which are commonly interacting with maximum target genes. Additionally, drug-gene interaction analysis was performed to identify drugs which are responsible for ALDH1A1 expression. The entire study may provide a deeper understanding about ALDH1A1 regulatory genes responsible for its overexpression in CP resistance cancer. This understanding may be further explore for developing possible co-therapy to avoid the ALDH1A1-mediated CP resistance.
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This work was supported by the Indian Council of Medical Research (ICMR), New Delhi; under sanction No. ISRM/12(10)/2019.
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Narendra, G., Raju, B., Verma, H. et al. Identification of potential genes associated with ALDH1A1 overexpression and cyclophosphamide resistance in chronic myelogenous leukemia using network analysis. Med Oncol 38, 123 (2021). https://doi.org/10.1007/s12032-021-01569-9
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DOI: https://doi.org/10.1007/s12032-021-01569-9