Analysis of the Inhibitory Effect of hsa-miR-145-5p and hsa-miR-203a-5p on Imatinib-Resistant K562 Cells by GC/MS Metabolomics Method.
Priyanka SinghRadheshyam YadavMalkhey VermaRavindresh ChhabraPublished in: Journal of the American Society for Mass Spectrometry (2023)
Imatinib (IM) resistance is considered to be a significant challenge in the management of chronic myeloid leukemia (CML). Previous studies have reported that hsa-miR-145-5p and hsa-miR-203a-5p can overcome IM resistance and hsa-miR-203a-5p can alter glutathione metabolism in IM-resistant cells. The purpose of this study was to examine whether hsa-miR-145-5p or hsa-miR-203a-5p counters IM resistance by targeting the overall metabolic profile of IM-resistant K562 cells. The metablic profiling of cell lysates obtained from IM-sensitive, IM-resistant, and miR-transfected IM-resistant K562 cells was carried out using the GC-MS technique. Overall, 75 major metabolites were detected, of which 32 were present in all samples. The pathway analysis of MetaboAnalyst 5.0 revealed that the majorly enriched pathways included glucose metabolism, fatty acid biosynthesis, lipogenesis, and nucleotide metabolism. Eleven of identified metabolites, l-glutamine, l-glutamic acid, l-lactic acid, phosphoric acid, 9,12-octadecadienoic acid, 9-octadecenoic acid, myristic acid, palmitic acid, cholesterol, and β-alanine, appeared in enriched pathways. IM-resistant cells had comparatively higher concentrations of all of these metabolites. Notably, the introduction of hsa-miR-145-5p or hsa-miR-203a-5p into resistant cells resulted in a decrease in levels of these metabolites. The efficacy of miR-203a-5p was particularly remarkable in comparison with miR-145-5p, as evidenced by partial least-squares-discriminant analysis (PLS-DA), which showed a high level of similarity in metabolic profile between IM-sensitive K562 cells and IM-resistant cells transfected with hsa-miR-203a-5p. The results indicate that GC-MS-based metabolic profiling has the potential to distinguish between drug-resistant and -sensitive cells. This approach can also be used to routinely monitor therapeutic response in drug-resistant patients, thus, enabling personalized therapy.
Keyphrases
- induced apoptosis
- drug resistant
- cell cycle arrest
- endoplasmic reticulum stress
- cell death
- ms ms
- fatty acid
- metabolic syndrome
- bone marrow
- single cell
- long non coding rna
- chronic myeloid leukemia
- adipose tissue
- acinetobacter baumannii
- mesenchymal stem cells
- mass spectrometry
- climate change
- end stage renal disease
- long noncoding rna
- data analysis