Main Article Content
Abstract
Purpose: This study examines the transformative potential of precision medicine in oncology, highlighting advancements in targeted therapies and immunotherapies and addressing both practical and theoretical challenges in clinical implementation.
Research Design and Methodology: This study employs a mixed-methods design, integrating quantitative data from a cross-sectional survey of oncologists with qualitative insights from in-depth interviews with key stakeholders. Advanced bioinformatics tools and multi-omics data, including genomics, proteomics, and transcriptomics, are analyzed to identify novel therapeutic targets and biomarkers.
Findings and Discussion: The findings demonstrate that precision medicine enhances patient outcomes by tailoring treatments to the genetic and molecular profiles of tumors. Targeted therapies, such as tyrosine kinase and epidermal growth factor receptor inhibitors, exhibit enhanced efficacy and reduced toxicity. Immunotherapy, remarkably immune checkpoint inhibitors, demonstrates significant promise but shows variability in patient responses, underscoring the need for predictive biomarkers. Integrating multi-omics data provides a comprehensive understanding of cancer biology and new therapeutic targets. Challenges include high costs, the need for robust bioinformatics infrastructure, and ethical considerations.
Implications: This study highlights the importance of investing in bioinformatics infrastructure, establishing standardized guidelines, and providing training for healthcare providers. Policymakers should develop strategies to reduce the costs of genetic testing and ensure equitable access to precision medicine. Future research should focus on cost-effective genomic testing methods, combination therapies to overcome resistance, and expanding studies to diverse populations to enhance the applicability and accessibility of precision medicine benefits.
Keywords
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This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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References
Ali, H. R., Chlon, L., Pharoah, P. D., & Markowetz, F. (2016). Patterns of immune infiltration in breast cancer and their clinical implications: A gene-expression-based retrospective study. PLOS Medicine, 13(12), e1002194. https://doi.org/10.1371/journal.pmed.1002194
Allison, J. P. (2015). Immune checkpoint blockade in cancer therapy: The 2015 Lasker-DeBakey Clinical Medical Research Award. JAMA, 314(11), 1113-1114. https://doi.org/10.1001/jama.2015.11660
Ashley, E. A. (2016). The precision medicine initiative: A new national effort. JAMA, 313(21), 2119-2120. https://doi.org/10.1001/jama.2015.3595
Ashley, E. A. (2016). Towards precision medicine. Nature Reviews Genetics, 17(9), 507-522. https://doi.org/10.1038/nrg.2016.86
Burke, W., Korngiebel, D. M., Fullerton, S. M., & Edwards, K. (2016). Clinical translation in genomic medicine: barriers and solutions. Current Genetic Medicine Reports, 4(4), 209-214. https://doi.org/10.1007/s40142-016-0107-8
Campbell, P. J., Getz, G., Korbel, J. O., Stuart, J. M., Jennings, J. L., Stein, L. D., ... & PCAWG Consortium. (2020). Pan-cancer analysis of whole genomes. Nature, 578(7793), 82-93. https://doi.org/10.1038/s41586-020-1969-6
Cancer Genome Atlas Research Network. (2014). Comprehensive molecular characterization of urothelial bladder carcinoma. Nature, 507(7492), 315-322. https://doi.org/10.1038/nature12965
Chen, D. S., & Mellman, I. (2017). Elements of cancer immunity and the cancer–immune set point. Nature, 541(7637), 321-330. https://doi.org/10.1038/nature21349
Ciriello, G., Miller, M. L., Aksoy, B. A., Senbabaoglu, Y., Schultz, N., & Sander, C. (2013). Emerging landscape of oncogenic signatures across human cancers. Nature Genetics, 45(10), 1127-1133. https://doi.org/10.1038/ng.2762
Collins, F. S., & Varmus, H. (2015). A new initiative on precision medicine. New England Journal of Medicine, 372(9), 793-795. https://doi.org/10.1056/NEJMp1500523
Druker, B. J., Guilhot, F., O'Brien, S. G., Gathmann, I., Kantarjian, H., Gattermann, N., ... & Larson, R. A. (2006). Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia. New England Journal of Medicine, 355(23), 2408-2417. https://doi.org/10.1056/NEJMoa062867
Edsjö, A. (2023). Scalable molecular diagnostics and adaptive profiling strategies in precision oncology. Nature Reviews Drug Discovery, 22(2), 123-135. https://doi.org/10.1038/s41573-022-00142-5
Flaherty, K. T., Puzanov, I., Kim, K. B., Ribas, A., McArthur, G. A., Sosman, J. A., ... & Chapman, P. B. (2010). Inhibition of mutated, activated BRAF in metastatic melanoma. New England Journal of Medicine, 363(9), 809-819. https://doi.org/10.1056/NEJMoa1002011
pathway blockade in non-small cell lung cancer: A retrospective analysis. Clinical Cancer Research, 22(18), 4585-4593. https://doi.org/10.1158/1078-0432.CCR-15-3101
Gainor, J. F., Shaw, A. T., Sequist, L. V., Fu, X., Azzoli, C. G., Piotrowska, Z., ... & Engelman, J. A. (2016). EGFR mutations and ALK rearrangements are associated with low response rates to PD-1 pathway blockade in non-small cell lung cancer: A retrospective analysis. Clinical Cancer Research, 22(18), 4585-4593. https://doi.org/10.1158/1078-0432.CCR-15-3101
Gerlinger, M., Rowan, A. J., Horswell, S., Larkin, J., Endesfelder, D., Gronroos, E., ... & Swanton, C. (2012). Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. New England Journal of Medicine, 366(10), 883-892. https://doi.org/10.1056/NEJMoa1113205
Hellmann, M. D., Ciuleanu, T. E., Pluzanski, A., Lee, J. S., Otterson, G., Audigier-Valette, C., ... & Ready, N. (2018). Nivolumab plus ipilimumab in lung cancer with a high tumor mutational burden. New England Journal of Medicine, 378(22), 2093-2104. https://doi.org/10.1056/NEJMoa1801946
Honjo, T. (2017). Celebrating 25 years of the discovery of PD-1: A personal reflection on the history and future of PD-1 research. European Journal of Immunology, 47(10), 1781-1790. https://doi.org/10.1002/eji.201747947
Kandoth, C., Schultz, N., Cherniack, A. D., Akbani, R., Liu, Y., Shen, H., ... & Ding, L. (2013). Integrated genomic characterization of endometrial carcinoma. Nature, 497(7447), 67-73. https://doi.org/10.1038/nature12113
Kaye, J., Terry, S. F., Juengst, E., & Hudson, K. (2015). Including all voices in international data-sharing governance. Human Genetics, 134(6), 659-667. https://doi.org/10.1007/s00439-015-1554-3
Manolio, T. A., Chisholm, R. L., Ozenberger, B., Roden, D. M., Williams, M. S., Wilson, R., ... & Ginsburg, G. S. (2015). Implementing genomic medicine in the clinic: the future is here. Genetics in Medicine, 17(12), 956-964. https://doi.org/10.1038/gim.2015.47
Maude, S. L., Laetsch, T. W., Buechner, J., Rives, S., Boyer, M., Bittencourt, H., ... & Grupp, S. A. (2018). Tisagenlecleucel in children and young adults with B-cell lymphoblastic leukemia. New England Journal of Medicine, 378(5), 439-448. https://doi.org/10.1056/NEJMoa1709866
Mizuno, H. (2022). Tissue-based and blood-based technologies in understanding tumor heterogeneity and treatment response in prostate cancer. Cancer Science, 113(8), 2525-2536. https://doi.org/10.1111/cas.15396
Mok, T. S., Wu, Y. L., Ahn, M. J., Garassino, M. C., Kim, H. R., Ramalingam, S. S., & Eichelbaum, M. (2017). Osimertinib or platinum–pemetrexed in EGFR T790M–positive lung cancer. New England Journal of Medicine, 376(7), 629-640. https://doi.org/10.1056/NEJMoa1612674
Ott, P. A., Hu, Z., Keskin, D. B., Shukla, S. A., Sun, J., Bozym, D. J., ... & Wu, C. J. (2017). An immunogenic personal neoantigen vaccine for patients with melanoma. Nature, 547(7662), 217-221. https://doi.org/10.1038/nature22991
Phillips, K. A., Deverka, P. A., Hooker, G. W., & Douglas, M. P. (2018). Genetic test availability and spending: where are we now? Where are we going? Health Affairs, 37(5), 710-716. https://doi.org/10.1377/hlthaff.2017.1427
Ribas, A., Puzanov, I., Dummer, R., Schadendorf, D., Hamid, O., Robert, C. & Hodi, F. S. (2019). Pembrolizumab versus investigator-choice chemotherapy for ipilimumab-refractory melanoma (KEYNOTE-002): A randomised, controlled, phase 2 trial. The Lancet Oncology, 16(8), 908-918. https://doi.org/10.1016/S1470-2045(15)00083-2
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015). limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Research, 43(7), e47. https://doi.org/10.1093/nar/gkv007
Roychowdhury, S., & Chinnaiyan, A. M. (2016). Translating cancer genomes and transcriptomes for precision oncology. CA: A Cancer Journal for Clinicians, 66(1), 75-88. https://doi.org/10.3322/caac.21322
Rulten, S. (2023). Ensuring global access to precision medicines in oncology. Lancet Oncology, 24(5), 601-612. https://doi.org/10.1016/S1470-2045(23)00089-5
Shaw, A. T., Kim, D. W., Mehra, R., Tan, D. S. W., Felip, E., Chow, L. Q., ... & Engelman, J. A. (2013). Ceritinib in ALK-rearranged non–small-cell lung cancer. New England Journal of Medicine, 368(25), 2385-2394. https://doi.org/10.1056/NEJMoa1214886
Soria, J. C., Ohe, Y., Vansteenkiste, J., Reungwetwattana, T., Chewaskulyong, B., Lee, K. H., ... & Ramalingam, S. S. (2018). Osimertinib in untreated EGFR-mutated advanced non-small-cell lung cancer. New England Journal of Medicine, 378(2), 113-125. https://doi.org/10.1056/NEJMoa1713137
Turajlic, S., Sottoriva, A., Graham, T., & Swanton, C. (2018). Resolving genetic heterogeneity in cancer. Nature Reviews Genetics, 20(7), 404-416. https://doi.org/10.1038/s41576-018-0007-6
Twyman-Saint Victor, C., Rech, A. J., Maity, A., Rengan, R., Pauken, K. E., Stelekati, E., ... & Wherry, E. J. (2015). Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer. Nature, 520(7547), 373-377. https://doi.org/10.1038/nature14292
Vogelstein, B., Papadopoulos, N., Velculescu, V. E., Zhou, S., Diaz, L. A., & Kinzler, K. W. (2013). Cancer genome landscapes. Science, 339(6127), 1546-1558. https://doi.org/10.1126/science.1235122
Wang, B., Mezlini, A. M., Demir, F., Fiume, M., Tu, Z., Brudno, M., ... & Goldenberg, A. (2014). Similarity network fusion for aggregating data types on a genomic scale. Nature Methods, 11(3), 333-337. https://doi.org/10.1038/nmeth.2810
Wang, L. (2022). The role of deep learning in precision oncology: Applications and future directions. Journal of Clinical Oncology, 40(18), 2012-2024. https://doi.org/10.1200/JCO.21.02423
Zhang, B., Wang, J., Wang, X., Zhu, J., Liu, Q., Shi, Z., ... & Snyder, M. (2019). Proteogenomic characterization of human colon and rectal cancer. Nature, 513(7518), 382-387. https://doi.org/10.1038/nature13438