Abstract 2286: Clonal sweep dynamics: A marker of tumor fitness and predictor of clinical outcomes

Abstract Cancer evolution is a complex process driven by cellular adaptations to environmental pressures. Understanding a tumor's evolutionary path is crucial for tailoring therapeutic strategies based on its genomic profile. We developed a method that estimates tumor 'fitness' (w) by analyzing the time of every clonal sweep. This is quantified by driver copy number or point mutations through analytical solutions derived from the branching process of tumor evolution. The method incorporates tumor size and growth rate, assessed through in-vivo BrdU staining, to determine the tumor's age, diversity, and aggressiveness. Using our method in the Yates et al. 2015 multi-region study, we analyzed 303 breast cancer tumors from 45 patients using whole-genome and exome sequencing (WES), focusing on ER+ (N=26) and ER- (N=19) subtypes. A negative correlation was observed between clonal cytoband alterations and fitness (ER+, R=-0. 41; P=0. 04; ER-, R=-0. 72; P0. 001). Expanding the analysis with the METABRIC study (Curtis et al. 2012), clonal cytoband alterations (CA) were linked to survival outcomes for both ER+ and ER- subtypes. Additionally, in the TRACERx NSCLC study (Jamal-Hanjani et al. 2017) of 327 tumors from 100 patients who underwent WES, the median tumor fitness was associated with a higher risk of recurrence or death. Survival analyses are detailed in Table 1 below. Multivariate analysis was adjusted for tumor size, nodal status, and CD8α expression in the breast cancer study, and according to the authors' methodology in the TRACERx study, respectively. The observed tumor growth rates in both studies align with known doubling times, demonstrating our method's accuracy. This approach successfully identifies tumor profiles linked to worse outcomes in breast and NSCLC cancers. Our findings suggest that analyzing clonal composition in tumors can improve patient stratification, particularly in infiltrated tumors, potentially enhancing immunotherapy response due to increased neoantigen exposure. Table 1 Survival Analysis Study and Endpoint Parameter Univariate HR (95% CI) Multivariate HR (95% CI) METABRIC: ER- (N=128) on RFS CA 3 (Ref: CA ≤ 3) 0. 61 (0. 40, 0. 93), P=0. 02 0. 49 (0. 32, 0. 75), P0. 001 METABRIC: ER- (N=128) on OS CA 3 (Ref: CA ≤ 3) 0. 68 (0. 47, 1), P=0. 05 0. 60 (0. 4, 0. 88), P=0. 01 METABRIC: ER+ (N=458) on RFS CA 3 (Ref: CA ≤ 3) 1. 61 (1. 33, 1. 94), P0. 001 1. 51 (1. 25, 1. 82), P0. 001 METABRIC: ER+ (N=458) on OS CA 3 (Ref: CA ≤3) 1. 44 (1. 23, 1. 68), P0. 001 1. 38 (1. 18, 1. 61), P0. 001 TRACERx NSCLC (N=43) on RFS Med. w 1. 031 (Ref: w ≤ 1. 031) 3. 24 (1. 38, 7. 62), P=0. 007 4. 11 (1. 12, 15. 1), P=0. 033 Citation Format: Luis E. Lara Gonzalez, Sherene Loi, Anthony T. Papenfuss, David L. Goode. Clonal sweep dynamics: A marker of tumor fitness and predictor of clinical outcomes abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 2286.