Identification of chemoresistance targets in doxorubicin-resistant lung adenocarcinoma cells using LC-MS/MS-based proteomics

Abstract

Acquired chemoresistance remains a significant challenge in the clinics as most of the treated cancers eventually emerge as hard-to-treat phenotypes. Therefore, identifying chemoresistance targets is highly warranted to manage the disease better. In this study, we employed a label-free LC-MS/MS-based quantitative proteomics analysis to identify potential targets and signaling pathways underlying acquired chemoresistance in a sub-cell line (A549DR) derived from the parental lung adenocarcinoma cells (A549) treated with gradually increasing doses of doxorubicin (DOX). Our proteomics analysis identified 146 upregulated and 129 downregulated targets in A549DR cells. The KEGG pathway and Gene ontology (GO) analysis of differentially expressed upregulated and downregulated proteins showed that most abundant upregulated pathways were related to metabolic pathways, cellular senescence, cell cycle, and p53 signaling. Meanwhile, the downregulated pathways were related to spliceosome, nucleotide metabolism, DNA replication, nucleotide excision repair, and nuclear-cytoplasmic transport. Further, STRING analysis of upregulated biological processes showed a protein-protein interaction (PPI) between CDK1, AKT2, SRC, STAT1, HDAC1, FDXR, FDX1, NPC1, ALDH2, GPx1, CDK4, and B2M, proteins. The identified proteins in this study might be the potential therapeutic targets for mitigating DOX resistance.

Keywords:

• Chemoresistance
• doxorubicin
• KEGG pathway
• LC-MS/MS
• proteomics
• STRING

Acknowledgments

N. Bano and KM Kainat received a senior research fellowship from CSIR, India. Anjali Pal received her junior research fellowship from UGC, India. India. Mohammad Imran Ansari received his SRF from UGC, India. Sana Sarkar thanks the Indian Council of Medical Research, India, for providing her the fellowship to conduct the research. The authors acknowledge the institutional proteomics facility for the proteomics analysis. The authors are grateful to Ms. Deepshikha Srivastava, Technical Officer, LC-MS/MS Laboratory, CSIR-Indian Institute of Toxicology Research, Lucknow, India, for extending the operational support for LC-MS/MS analysis. The manuscript communication number is IITR/SEC/MS/2024/11.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Raw data files of this proteomics study have been submitted to CCMS-Mass spectrometry interactive virtual environment (MassIVE), and the allotted accession number is MassIVE MSV000094078.

Additional information

Funding

This work was supported by a grant (MLP003) from the Council of Scientific and Industrial Research (CSIR), India.