ArticleBiomolecules2022
Single-Cell FISH Analysis Reveals Distinct Shifts in PKM Isoform Populations during Drug Resistance Acquisition.
Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- [PKM1 Regulates the Expression of Autophagy and Neuroendocrine Markers in Small Cell Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2024Article
- Proteomic Profiling of Mouse Brain Pyruvate Kinase Binding Proteins: A Hint for Moonlighting Functions of PKM1?International journal of molecular sciences · 2023Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Warburg effect, i.e., the utilization of glycolysis under aerobic conditions, is recognized as a survival advantage of cancer cells. However, how the glycolytic activity is affected during drug resistance acquisition has not been explored at single-cell resolution. Because the relative ratio of the splicing isoform of pyruvate kinase M (PKM), PKM2/PKM1, can be used to estimate glycolytic activity, we utilized a single-molecule fluorescence in situ hybridization (SM-FISH) method to simultaneously quantify the mRNA levels of PKM1 and PKM2. Treatment of HCT116 cells with gefitinib (GE) resulted in two distinct populations of cells. However, as cells developed GE resistance, the GE-sensitive population with reduced PKM2 expression disappeared, and GE-resistant cells (Res) demonstrated enhanced PKM1 expression and a tightly regulated PKM2/PKM1 ratio. Our data suggest that maintaining an appropriate PKM2 level is important for cell survival upon GE treatment, whereas increased PKM1 expression becomes crucial in GE Res. This approach demonstrates the importance of single-cell-based analysis for our understanding of cancer cell metabolic responses to drugs, which could aid in the design of treatment strategies for drug-resistant cancers.
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