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.
- 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: [email protected].
- 6. Department of Chemistry, Tsinghua University, Beijing, 100084, PR China. Electronic address: [email protected].
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.
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Research Areas: Cancer