Comparative Analysis of Acquired Resistance to Bortezomib in Prostate Cancer Cells Using Proteomic and Bioinformatic Tools

被引:0
|
作者
Seker, Semih [1 ]
Sahin, Betul [2 ]
Yerlikaya, Azmi [1 ]
机构
[1] Kutahya Hlth Sci Univ, Fac Med, Dept Med Biol, Kutahya, Turkiye
[2] Acibadem Labmed Clin Labs, Istanbul, Turkiye
关键词
bioinformatics; bortezomib; drug resistance; prostate cancer; proteomics; PROTEASOME ACTIVITY; DRUG-RESISTANCE; DEGRADATION; TRANSLATION; MECHANISMS; MUTATION; PATHWAY; SYSTEM; GENE;
D O I
10.1111/jcmm.70254
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Chemotherapy is a potent tool against cancer, but drug resistance remains a major obstacle. To combat this, understanding the molecular mechanisms behind resistance in cancer cells and the protein expression changes driving these mechanisms is crucial. Targeting the Ubiquitin-Proteasome System (UPS) has proven effective in treating multiple myeloma and shows promise for solid tumours. Despite initial success with the proteasome inhibitor bortezomib, acquired resistance soon after treatment poses a significant challenge to its efficacy. In this study, we explored proteins potentially involved in acquired resistance to bortezomib using label-free nLC-MS/MS proteomic analysis. The investigation revealed 299 proteins with notable differences in expression levels in the bortezomib-resistant PC3 prostate cancer cell line. Using bioinformatics tools, we illustrated the top 10 gene ontology (GO) processes [e.g., translational initiation (p = 5.964E-10), CRD-mediated mRNA stabilisation (p = 1.636E-5), and hydrogen ion transmembrane transport (p = 6.46E-5)] and the top 20 KEGG [e.g., metabolic pathways (p = 7.601E-13), biosynthesis of amino acids (p = 3.834E-12), and chemical carcinogenesis-reactive oxygen species (p = 1.891E-4)] and REACTOME [e.g., metabolism (p = 4.182E-21), translation (p = 9.484E-18), and Nonsense-Mediated Decay (NMD) (p = 1.829E-8)] pathways in the PC3-resistant cells. We further refined our results by comparing them with globally validated TCGA datasets. We correlated the 299 proteins identified through proteomic analysis with tumour aggressiveness and resistance by comparing them with the TCGA nodal metastasis N0 vs. N1 datasets using the UALCAN portal and identified 37 proteins consistent with our results. We believe that a combination of bortezomib with chemotherapeutics targeting these proteins could be effective in overcoming the resistance developed against bortezomib.
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页数:17
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