Evolution of Genes and Transcripts Modifies Drug Sensitivity in Cancer Cell Lines - A Review

Krishna Sahu ¹, Urvashi Jain ²

Dynamic genomic and transcriptomic evolutionary modeling guides cancer genetics, transforming treatment by predicting drug sensitivity in genomics.

Abstract

Understanding the genes and transcripts evolving within cancer cell lines is crucial in cancer research and therapy, providing insights into drug sensitivity dynamics. Precision medicine methods need to grasp how genetic changes impact medication responses, considering the challenges of dynamic changes, cancer's heterogeneity, and evolving genomic landscapes. This review introduces a method called dynamic genomic and transcriptomic evolutionary modeling (DG-TEM), systematically profiling cancer cell lines' genomic and transcriptomic landscapes over time. DG-TEM combines experimental data with hypothetical scenarios, creating a framework to predict how genetic evolution may affect drug sensitivity in various clinical situations. This approach enables the identification of potential drug-resistant mutations or pathways before or during treatment. DG-TEM holds significant promise in unraveling the intricate connection between genetic evolution and medication sensitivity, offering implications for personalized cancer care by aiding doctors in selecting medicines tailored to each patient's changing genetic profile. Simulation analysis can further evaluate and enhance the suggested method, providing insights into the potential outcomes of evolutionary dynamics on drug sensitivity. The integration of experimental data and computational predictions has the potential to transform our understanding of cancer development and its impact on medication responses, ushering in a new era of precision oncology.

Keywords: Dynamic Genomic, Transcriptomic, Evolutionary Modeling, Genes, Drug Sensitivity, Cancer Cell Lines

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