Quantification of mouse pulmonary cancer models by microcomputed tomography imaging

Area of Science:

• Oncology
• Medical Imaging
• Preclinical Research

Background:

• Lung cancer remains a leading cause of cancer mortality, necessitating improved understanding and treatment strategies.
• Advances in preclinical cancer models, such as genetically engineered mouse models, offer opportunities to study cancer mechanisms relevant to human disease.
• Effective monitoring tools are crucial for evaluating therapeutic interventions in these models.

Purpose of the Study:

• To quantify tumor progression and assess drug efficacy in two distinct mouse lung cancer models.
• To validate the utility of microcomputed tomography (micro-CT) for non-invasive, real-time monitoring of lung cancer.
• To develop and utilize a more clinically relevant lung cancer model for preclinical evaluation.

Main Methods:

• Utilized two distinct mouse lung cancer models, including a K-ras(LSL-G12D)/p53(LSL-R270H) mutant mouse model.
• Employed microcomputed tomography (micro-CT) for imaging tumor development and progression.
• Combined micro-CT with bioluminescent imaging and histopathological analyses for comprehensive evaluation.
• Assessed the impact of anticancer drug treatment on tumor growth inhibition.

Main Results:

• Confirmed the utility of micro-CT for real-time, non-invasive monitoring of lung cancer progression.
• Successfully developed and utilized a K-ras(LSL-G12D)/p53(LSL-R270H) mutant mouse model, mimicking human lung cancer more closely.
• Demonstrated tumor growth inhibition in response to anticancer drug treatment using micro-CT imaging.
• Validated micro-CT findings with bioluminescent imaging and histopathology.

Conclusions:

• Micro-CT is a valuable tool for non-invasive, real-time monitoring of lung cancer progression in preclinical models.
• The K-ras(LSL-G12D)/p53(LSL-R270H) mutant mouse model represents a clinically relevant platform for lung cancer research.
• Imaging-guided evaluation of advanced preclinical models accelerates drug discovery and increases the likelihood of clinical success for lung cancer therapies.