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Assessment of Resistance to Tyrosine Kinase Inhibitors by an Interrogation of Signal Transduction Pathways by Antibody Arrays
Published on: September 19, 2018
Branched-Chain Amino Acid Metabolic Reprogramming Orchestrates Drug Resistance to EGFR Tyrosine Kinase Inhibitors
Yuetong Wang1, Jian Zhang1, Shengxiang Ren2
1State Key Laboratory of Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; CAS Center for Excellence in Molecular Cell Science, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Innovation Center for Cell Signaling Network, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Abstract:
Drug resistance is a significant hindrance to effective cancer treatment. Although resistance mechanisms of epidermal growth factor receptor (EGFR) mutant cancer cells to lethal EGFR tyrosine kinase inhibitors (TKI) treatment have been investigated intensively, how cancer cells orchestrate adaptive response under sublethal drug challenge remains largely unknown. Here, we find that 2-h sublethal TKI treatment elicits a transient drug-tolerant state in EGFR mutant lung cancer cells. Continuous sublethal treatment reinforces this tolerance and eventually establishes long-term TKI resistance. This adaptive process involves H3K9 demethylation-mediated upregulation of branched-chain amino acid aminotransferase 1 (BCAT1) and subsequent metabolic reprogramming, which promotes TKI resistance through attenuating reactive oxygen species (ROS) accumulation. Combination treatment with TKI- and ROS-inducing reagents overcomes this drug resistance in preclinical mouse models. Clinical information analyses support the correlation of BCAT1 expression with the EGFR TKI response. Our findings reveal the importance of BCAT1-engaged metabolism reprogramming in TKI resistance in lung cancer.
Insights
Sublethal cancer drug treatment induces a drug-tolerant state in EGFR-mutant lung cancer cells. This tolerance is mediated by BCAT1, a metabolic enzyme, leading to drug resistance.
Area of Science:
- Oncology
- Molecular Biology
- Cancer Research
Background:
- Drug resistance remains a major challenge in cancer therapy.
- Mechanisms of resistance to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) in EGFR-mutant cancers are well-studied.
- Adaptive responses to sublethal drug exposure are less understood.
Purpose of the Study:
- To investigate how cancer cells adapt to sublethal drug challenges.
- To elucidate the mechanisms underlying the development of TKI resistance in EGFR-mutant lung cancer.
- To identify potential therapeutic strategies to overcome TKI resistance.
Main Methods:
- Exposure of EGFR-mutant lung cancer cells to sublethal TKI treatment.
- Analysis of cellular adaptive responses and development of drug tolerance.
- Investigation of the role of H3K9 demethylation and BCAT1 expression.
- Metabolic profiling and assessment of reactive oxygen species (ROS) levels.
- Preclinical mouse models for combination therapy evaluation.
- Clinical data analysis correlating BCAT1 expression with TKI response.
Main Results:
- Sublethal TKI treatment induces a transient drug-tolerant state in EGFR-mutant lung cancer cells.
- Continuous sublethal treatment leads to long-term TKI resistance.
- This resistance is mediated by H3K9 demethylation-induced upregulation of BCAT1 and metabolic reprogramming.
- BCAT1 attenuates ROS accumulation, promoting TKI resistance.
- Combination therapy with TKI and ROS-inducing agents overcomes resistance in preclinical models.
- BCAT1 expression correlates with EGFR TKI response in clinical data.
Conclusions:
- BCAT1-engaged metabolic reprogramming is crucial for TKI resistance in lung cancer.
- Targeting BCAT1 or modulating ROS levels may offer strategies to overcome EGFR TKI resistance.
- Understanding adaptive responses to sublethal drug concentrations is vital for improving cancer treatment outcomes.
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