EMAN RESEARCH PUBLISHING | <p>Evolution of Genes and Transcripts Modifies Drug Sensitivity in Cancer Cell Lines

EMAN RESEARCH PUBLISHING | <p>Evolution of Genes and Transcripts Modifies Drug Sensitivity in Cancer Cell Lines - A Review</p>

Inflammation Cancer Angiogenesis Biology and Therapeutics | Impact 0.1 (CiteScore) | Online ISSN 2207-872X

REVIEWS (Open Access)

Previous Next Contents Vol 7 (2)

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

Krishna Sahu ¹, Urvashi Jain ²

+ Author Affiliations

Journal of Angiotherapy 7 (2) 1-5 https://doi.org/10.25163/angiotherapy.729397

Submitted: 03 November 2023 Revised: 03 December 2023 Published: 07 January 2024

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

References

Abaandou, L., Quan, D., & Shiloach, J. (2021). Affecting HEK293 cell growth and production performance by modifying the expression of specific genes. Cells, 10(7), 1667.

Aissa, A. F., Islam, A. B., Ariss, M. M., Go, C. C., Rader, A. E., Conrardy, R. D., ... & Benevolenskaya, E. V. (2021). Single-cell transcriptional changes associated with drug tolerance and response to combination therapies in cancer. Nature communications, 12(1), 1628.

Bailey, C., Shoura, M. J., Mischel, P. S., & Swanton, C. (2020). Extrachromosomal DNA—relieving heredity constraints, accelerating tumour evolution. Annals of Oncology, 31(7), 884-893.

Ben-David, U., Siranosian, B., Ha, G., Tang, H., Oren, Y., Hinohara, K., ... & Golub, T. R. (2018). Genetic and transcriptional evolution alters cancer cell line drug response. Nature, 560(7718), 325-330.

Boumahdi, S., & de Sauvage, F. J. (2020). The great escape: tumour cell plasticity in resistance to targeted therapy. Nature reviews Drug discovery, 19(1), 39-56.

Geeleher, P., Cox, N. J., & Huang, R. S. (2014). Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines. Genome biology, 15, 1-12.

Ghandi, M., Huang, F. W., Jané-Valbuena, J., Kryukov, G. V., Lo, C. C., McDonald III, E. R., ... & Sellers, W. R. (2019). Next-generation characterization of the cancer cell line encyclopedia. Nature, 569(7757), 503-508.

Gillet, J. P., Calcagno, A. M., Varma, S., Marino, M., Green, L. J., Vora, M. I., ... & Gottesman, M. M. (2011). Redefining the relevance of established cancer cell lines to the study of mechanisms of clinical anti-cancer drug resistance. Proceedings of the National Academy of Sciences, 108(46), 18708-18713.

Guièze, R., Liu, V. M., Rosebrock, D., Jourdain, A. A., Hernández-Sánchez, M., Zurita, A. M., ... & Wu, C. J. (2019). Mitochondrial reprogramming underlies resistance to BCL-2 inhibition in lymphoid malignancies. Cancer cell, 36(4), 369-384.

Guo, M., Peng, Y., Gao, A., Du, C., & Herman, J. G. (2019). Epigenetic heterogeneity in cancer. Biomarker research, 7(1), 1-19.

Haider, T., Pandey, V., Banjare, N., Gupta, P. N., & Soni, V. (2020). Drug resistance in cancer: mechanisms and tackling strategies. Pharmacological Reports, 72(5), 1125-1151.

Holohan, C., Van Schaeybroeck, S., Longley, D. B., & Johnston, P. G. (2013). Cancer drug resistance: an evolving paradigm. Nature Reviews Cancer, 13(10), 714-726.

Katti, A., Diaz, B. J., Caragine, C. M., Sanjana, N. E., & Dow, L. E. (2022). CRISPR in cancer biology and therapy. Nature Reviews Cancer, 22(5), 259-279.

Liu, C., Wei, D., Xiang, J., Ren, F., Huang, L., Lang, J., ... & Yang, J. (2020). An improved anticancer drug-response prediction based on an ensemble method integrating matrix completion and ridge regression. Molecular Therapy-Nucleic Acids, 21, 676-686.

Maleki Dana, P., Sadoughi, F., Asemi, Z., & Yousefi, B. (2022). The role of polyphenols in overcoming cancer drug resistance: A comprehensive review. Cellular & Molecular Biology Letters, 27(1), 1-26.

Marine, J. C., Dawson, S. J., & Dawson, M. A. (2020). Non-genetic mechanisms of therapeutic resistance in cancer. Nature Reviews Cancer, 20(12), 743-756.

Nusinow, D. P., Szpyt, J., Ghandi, M., Rose, C. M., McDonald III, E. R., Kalocsay, M., ... & Gygi, S. P. (2020). Quantitative proteomics of the cancer cell line encyclopedia. Cell, 180(2), 387-402.

Raoof, S., Mulford, I. J., Frisco-Cabanos, H., Nangia, V., Timonina, D., Labrot, E., ... & Hata, A. N. (2019). Targeting FGFR overcomes EMT-mediated resistance in EGFR mutant non-small cell lung cancer. Oncogene, 38(37), 6399-6413.

Shi, J., Li, Y., Jia, R., & Fan, X. (2020). The fidelity of cancer cells in PDX models: Characteristics, mechanism and clinical significance. International journal of cancer, 146(8), 2078-2088.

Shi, Y., Fan, S., Wu, M., Zuo, Z., Li, X., Jiang, L., ... & Chen, Y. (2019). YTHDF1 links hypoxia adaptation and non-small cell lung cancer progression. Nature communications, 10(1), 4892.

Shoshani, O., Brunner, S. F., Yaeger, R., Ly, P., Nechemia-Arbely, Y., Kim, D. H., ... & Cleveland, D. W. (2021). Chromothripsis drives the evolution of gene amplification in cancer. Nature, 591(7848), 137-141.

Si, W., Shen, J., Zheng, H., & Fan, W. (2019). The role and mechanisms of action of microRNAs in cancer drug resistance. Clinical epigenetics, 11(1), 1-24.

Smallegan, M. J., & Rinn, J. L. (2019). Linking long noncoding RNA to drug resistance. Proceedings of the National Academy of Sciences, 116(44), 21963-21965.

Su, Y., Ko, M. E., Cheng, H., Zhu, R., Xue, M., Wang, J., ... & Heath, J. R. (2020). Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line. Nature communications, 11(1), 2345.

Tlemsani, C., Pongor, L., Elloumi, F., Girard, L., Huffman, K. E., Roper, N., ... & Pommier, Y. (2020). SCLC-CellMiner: a resource for small cell lung cancer cell line genomics and pharmacology based on genomic signatures. Cell reports, 33(3).

Wang, X., Zhang, H., & Chen, X. (2019). Drug resistance and combating drug resistance in cancer. Cancer Drug Resistance, 2(2), 141.

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