Abstract LB228: Evolutionary trajectories of lung cancer in never smokers

Abstract

Abstract Purpose of the study Elucidating evolutionary trajectories of cancers allows us to understand the key events, and the order in which they occur, throughout their development. This can help us to find important associations with tumor progression and prognosis. Our aim was to perform de novo identification of the evolutionary trajectories within Sherlock-lung, with a dataset containing the largest collection of lung cancer in never smokers (LCINS) samples ever analyzed. Experimental procedures Our Plackett-Luce ordering model utilized copy number data from Battenberg and mutation cancer cell fraction (CCF) data from DPClust. Frequently-occurring copy number events and driver mutations are ordered within each sample using their copy number states and CCFs. An aggregate ordering is then calculated for a sample set. Mixture model analysis identifies subsets of samples displaying distinct orders of events, uncovering diverse evolutionary trajectories within a tumor set. Dataset The Sherlock-lung whole genome sequencing dataset (n=1217) was filtered to the samples that allowed us to identify subclonal expansions. Samples required at least 10 reads per chromosome copy and a minimum cellularity of 30%. This provided 458 LCINS samples of various histologies. 155 smoker samples were also analyzed for comparison. Results We identified two subsets of LCINS tumors following distinct evolutionary trajectories. The “loss-based” subset commonly saw whole genome duplication (WGD) combined with copy number losses occurring earlier, and at higher prevalence, than gains. Contrastingly, in the “gain-based” subset, WGD was relatively rare but ploidy increased via copy number gains, which were more prevalent than losses. Interestingly, these different trajectories converged on similar overall copy number states. The loss-based subset had a higher mutational burden and a higher proportion of the genome altered, and followed a more smoker-like trajectory than the gain-based subset. Considering these differences alongside the convergence in copy number states, it is intriguing that survival times were similar between the two subsets. Copy number events defined the difference between the two trajectories. However, driver mutations also played important roles in tumor evolution in LCINS. TP53 and EGFR mutations were associated with greater genomic instability. Conversely, KRAS mutations were associated with more stable genomes. Samples with early clonal mutations in TP53, ERBB2, and PIK3CA, as well as those with a copy number gain of ERBB2, exhibited shorter survival times. Conclusions Two distinct evolutionary trajectories of LCINS were identified by de novo Plackett-Luce event ordering analysis. The contrast between the subgroups was defined by different paths of copy number activity, but they ultimately converged on similar overall copy number states and outcomes. Key early driver mutations influenced genomic instability and survival times. Citation Format: Christopher Wirth, Tongwu Zhang, Wei Zhao, Phuc Hoang, Jian Sang, Nathaniel Rothman, Marcos Díaz-Gay, Ruxandra Teslo, Naser Ansari-Pour, Máire Ní Leathlobhair, Iliana Peneva, William Eagles, Lixing Yang, Ludmil Alexandrov, David C. Wedge, Maria Teresa Landi. Evolutionary trajectories of lung cancer in never smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB228.