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  3. High-throughput single-cell metabolites profiling reveals metabolic reprogramming confers cisplatin resistance in lung cancer

High-throughput single-cell metabolites profiling reveals metabolic reprogramming confers cisplatin resistance in lung cancer

  • Talanta. 2025 Apr 1:285:127355. doi: 10.1016/j.talanta.2024.127355.
Changyi Liu 1,  Siyuan Pan 2,  Xingyu Pan 2,  Jinlei Yang 2,  Huan Yao 3,  Zhenli Yang 4,  Sijia Hao 4,  Yuqin Liu 4,  Peng Liu 5,  Sichun Zhang 6
Affiliations

Affiliations

  • 1 State Key Laboratory of Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Beijing, 100730, PR China.
  • 2 Department of Chemistry, Tsinghua University, Beijing, 100084, PR China.
  • 3 Division of Chemical Metrology and Analytical Science, National Institute of Metrology, Beijing, 100029, PR China.
  • 4 Cell Resource Center, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, 100730, PR China.
  • 5 State Key Laboratory of Complex, Severe, and Rare Diseases, Peking Union Medical College Hospital, Beijing, 100730, PR China. Electronic address: liupeng@pumch.cn.
  • 6 Department of Chemistry, Tsinghua University, Beijing, 100084, PR China. Electronic address: sczhang@mail.tsinghua.edu.cn.
PMID: 39673986 DOI: 10.1016/j.talanta.2024.127355
Abstract

Lung Cancer is the most common cause of cancer-related deaths worldwide. Platinum-containing two-drug regimens are the standard first-line chemotherapeutic regimen, but acquired resistance remains a major challenge. Cancer cells can evolve and adapt to therapeutic stress by reprogramming their metabolism and passing on drug resistance to neighboring drug-sensitive Cancer cells through cell-to-cell interactions. Here, we have developed a method to study the interactions between cells. Using human lung Cancer A549 cells, we constructed a drug-sensitive cell line expressing red fluorescent protein and a cisplatin-resistant cell line. Employing label-free mass cytometry, we acquired metabolites information at the single-cell level. Through pseudotime analysis, we identified two most important clusters of metabolites. We discovered that phosphatidylcholines are strongly associated with drug resistance. Through unsupervised learning, we observed that drug-sensitive cells in co-culture transform into a novel cell state after cisplatin treatment. This method offers a novel tool for investigating the mechanisms underlying the development of Cancer cell drug resistance.

Keywords

Cell-to-cell interaction; Cisplatin resistance; Lung cancer; Metabolic reprogramming; Single-cell analysis.

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