Abstract 3385: Modeling evolutionary fitness in resistant cancers based on a common adaptability trait

Abstract Cancer is composed of a major subpopulation of proliferative cells and a minor subpopulation of highly adaptable cells. Although it is evident that cancer is an evolution like process driven by rare adaptable cancer cells that persist under various selection pressures, most of our knowledge about cancer comes from studying proliferative cancer cells. To overcome the hurdle in modeling adaptable cancer cell state that defeats all currently offered therapies, we are exploiting a linkage that exists between different adaptability substates such as metabolic, regulatory, and structural substates. Our studies, thus far carried out with aggressive triple-negative breast cancer and melanoma cell lines, suggest that it is feasible to apply severe metabolic challenges as realistic selection pressures/bottlenecks for modeling highly abnormal and highly adaptable cancer cells that drive cancer evolution and therapy resistance. The most significant aspect of our approach is an ability to model rare resistant cells (approximately 0. 01% of cells) that survive in reversible quiescence under selection pressures. Monitoring of cells under microscope for several weeks under a severe and prolonged metabolic challenge, for example, a lack of glutamine in culture medium, revealed perhaps most interesting and cancer-relevant cells that survive in quiescence for weeks and then advance to generate therapy-resistant cells. Such microscopic monitoring revealed a significant heterogeneity among surviving cells. As examples, 1) surviving cells differ in the depth of quiescence, some cells trying to proliferate sooner than others; 2) as cells progress from quiescence to proliferation, their fate is far from certain: cells may progress to yield few cells, tiny colony, or large colony and then stop proliferating and in most instances die (abortive attempts at evolution). Of significance, the cell lines derived inflammatory breast cancer (IBC), an aggressive subtype of breast cancer, possessed a higher evolutionary fitness than non-IBC cell lines. This approach also eliminates 99. 99% of cells that proliferate in cell culture but would not survive selection pressures in the body. The adaptable cells that survived the bottleneck and then proliferated indefinitely were highly resistant and metastatic. Molecular analyses of adaptable cells, including gene expression microarrays, CGH microarrays, and whole genome sequencing revealed mechanisms for their plasticity (exemplified by markers of high EMT), and for generating cellular diversity by altering epigenome (exemplified by low TET2) and by structural modifications in transcriptome (exemplified by high FTO). We conclude that the phenotype-based approach described here is good at modeling deep intrinsic resistance and may be useful in developing strategies for improving outcomes in resistant cancers. Supported by a State of Texas Grant for Rare and Aggressive Cancers. Citation Format: Balraj Singh, Vanessa N. Sarli, Anthony Lucci. Modeling evolutionary fitness in resistant cancers based on a common adaptability trait 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 3385.