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Published on: June 28, 2018
Mouse models of human non-small-cell lung cancer: raising the bar
C F B Kim1, E L Jackson, D G Kirsch
1Center for Cancer Research and Department of Biology, Massachusetts Institute of Technology, Cambridge, 02139, USA.
Abstract:
Lung cancer is a devastating disease that presents a challenge to basic research to provide new steps toward therapeutic advances. The cell-type-specific responses to oncogenic mutations that initiate and regulate lung cancer remain poorly defined. A better understanding of the relevant signaling pathways and mechanisms that control therapeutic outcome could also provide new insight. Improved conditional mouse models are now available as tools to improve the understanding of the cellular and molecular origins of adenocarcinoma. These models have already proven their utility in proof-of-principle experiments with new technologies including genomics and imaging. Integrated thinking to apply technological advances while using the appropriate mouse model is likely to facilitate discoveries that will significantly improve lung cancer detection and intervention.
Insights
Understanding lung cancer requires exploring cell-type-specific responses to mutations. New mouse models combined with advanced technologies like genomics and imaging are key to improving lung cancer detection and treatment.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Lung cancer remains a significant challenge for basic research and therapeutic development.
- Cell-type-specific responses to oncogenic mutations initiating lung cancer are not well understood.
- Identifying signaling pathways and mechanisms controlling therapeutic outcomes is crucial for advancing treatment.
Purpose of the Study:
- To highlight the utility of improved conditional mouse models for studying lung adenocarcinoma.
- To emphasize the integration of technological advances with appropriate models for discovery.
- To underscore the potential for improving lung cancer detection and intervention.
Main Methods:
- Utilizing improved conditional mouse models for lung adenocarcinoma research.
- Applying advanced technologies such as genomics and imaging.
- Integrating technological advances with suitable mouse models for experimental design.
Main Results:
- Conditional mouse models have demonstrated utility in proof-of-principle experiments.
- These models facilitate the study of cellular and molecular origins of lung adenocarcinoma.
- The integration of technology and models shows promise for future discoveries.
Conclusions:
- Advanced conditional mouse models are valuable tools for lung cancer research.
- Integrating genomics and imaging with mouse models can accelerate discoveries.
- This integrated approach is expected to significantly improve lung cancer detection and intervention strategies.
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