4.7 Article

Label-Free Quantitative Proteomics Analysis of Adriamycin Selected Multidrug Resistant Human Lung Cancer Cells

期刊

BIOMOLECULES
卷 12, 期 10, 页码 -

出版社

MDPI
DOI: 10.3390/biom12101401

关键词

drug resistance; DLKP; label-free quantitative proteomics; lipid metabolism; ABC transporters; response to drug

资金

  1. SSPC
  2. SFI Research Centre for Pharmaceuticals
  3. European Regional Development Fund [12/RC/2275_P2]
  4. Science Foundation Ireland (SFI) [16/RI/3701]
  5. Science Foundation Ireland (SFI) [16/RI/3701] Funding Source: Science Foundation Ireland (SFI)

向作者/读者索取更多资源

The development of drug resistance in lung cancer is a significant clinical challenge. This study explores novel biomarkers of drug resistance in lung cancer cells and identifies the roles of ABC transporter proteins and lipid metabolism in drug resistance formation.
The development of drug resistance in lung cancer is a major clinical challenge, leading to a 5-year survival rate of only 18%. Therefore, unravelling the mechanisms of drug resistance and developing novel therapeutic strategies is of crucial importance. This study systematically explores the novel biomarkers of drug resistance using a lung cancer model (DLKP) with a series of drug-resistant variants. In-depth label-free quantitative mass spectrometry-based proteomics and gene ontology analysis shows that parental DLKP cells significantly differ from drug-resistant variants, and the cellular proteome changes even among the drug-resistant subpopulations. Overall, ABC transporter proteins and lipid metabolism were determined to play a significant role in the formation of drug resistance in DKLP cells. A series of membrane-related proteins such as HMOX1, TMB1, EPHX2 and NEU1 were identified to be correlated with levels of drug resistance in the DLKP subpopulations. The study also showed enrichment in biological processes and molecular functions such as drug metabolism, cellular response to the drug and drug binding. In gene ontology analysis, 18 proteins were determined to be positively or negatively correlated with resistance levels. Overall, 34 proteins which potentially have a therapeutic and diagnostic value were identified.

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