Abstract
The ability to predict rodent lifetime tumor responses from short-term exposures and a scientific basis for rodent to human extrapolation are unmet needs in cancer risk assessment. To address these needs, quantitation of cancer driver mutations (CDMs) was integrated with an error-corrected, next generation sequencing (NGS) approach. The method developed, CarcSeq, involves performing multiple, high-fidelity PCR reactions to amplify hotspot CDM-containing target sequences, tagging amplicons with 9 base unique identifier sequences, and constructing libraries from the pooled amplicons. Single-strand consensus sequences were constructed for error correction. A metric of variability in CDM levels, median absolute deviation in mutant fraction (MAD), is being developed as a biomarker of clonal expansion. This study leveraged the sex-related difference in spontaneous lung tumor development in the rasH2-Tg mouse model to validate and refine the CarcSeq approach for assessing clonal expansion. Significantly greater MAD was observed in male as compared to female rasH2-Tg mice, along with more recurrent mutations and a higher proportion of mutations conferring a potentially selectable phenotype in males, consistent with the greater propensity for spontaneous lung tumorigenesis in males. In the analysis of MAD, use of a sex-specific median and classification of lung-specific drivers based on a COSMIC-reported mutation frequency ≥ 5% performed better than use of the overall median MF and classification based on COSMIC's top ranked lung neoplasia genes. Thus, this study provides further validation of the CarcSeq/MAD biomarker approach and technical insight into best practices in evaluating clonal expansion based on measurement of cancer driver gene mutations.