A novel, sensitive, quantitative method for detecting tumor burden in orthotopic mouse K-ras lung cancer models

1053 A number of investigators have developed models of lung cancer in mice that result from orthotopic activation of a mutated K-ras gene in pulmonary epithelial cells (Jackson et al., Genes and Development: 15:3243). Although these models have many advantages over injection of lung cancer cell lines, it has been difficult to quantify the amount of tumor within the lungs by using histologic examination. This is particularly limiting at time points early in the natural history of tumor formation or after therapeutic interventions associated with inflammation. We hypothesized that tumor burden could be measured by quantifying the amount of mRNA encoding for the specific K-ras mutations only expressed in tumor cells. Our approach takes advantage of commercially available kits that can detect single point mutations (Mutector Kits, Trimgen, Sparks, MD) in an ELISA format. A kit was ordered to detect the point mutation (G12D) in mouse K-ras that was engineered into the transgenic mouse strain studied. To test our approach, we used a lung cancer cell line derived from a tumor-bearing transgenic mouse carrying the K-rasG12D mutation (LKR cells). LKR cells were mixed with a mouse lung cancer cell line lacking a K-ras mutation (L1C2) at different ratios. Total RNA was isolated from the mixtures, reverse transcribed and followed by PCR amplification. RT/PCR products were then used for detection of K-ras mutation. The K-rasG12D mutation was clearly detected when as low as 0.5% of cells containing the mutation were present. We next measured K-rasG12D expression from frozen sections of mouse lung. Increasingly strong signals were detected in lung sections in mice with larger tumor loads. Interestingly, positive signals could be detected in mice with early lesions that were not visible by routine histology. In conclusion, application of the Mutector kit to detect mutant K-ras message provided a sensitive, accurate, and quantifiable method for evaluating tumor loads in mouse K-ras lung cancer model and could be applied to other transgenic models. This approach will be useful in monitoring prevention and treatment strategies.