Exploring Cancer Drug Resistance Mechanisms through Cutting-Edge Computational Techniques and Data Analysis
DOI:
https://doi.org/10.31580/g4gwjc21Keywords:
Cancer, COSMIC, Drug resistance, EGFR, Genome Screening, KRAS, Mutation analysisAbstract
Background: Cancer drug resistance poses a significant challenge to precision medicine, as drug-resistant mutations continue to emerge. This study investigates the link between drug-resistant mutations and drug resistance through genome screening.
Methodology: By integrating data from previously identified drug-resistant mutations with information from the COSMIC database, we utilized Python and Linux methods to develop models for predicting cancer drug-resistance mutations.
Results: The findings of this study hold great significance as they enhance comprehension of the mechanisms that cause drug resistance in cancer. The identified genes and their variants, especially EGFR and KRAS, are known to be frequently mutated in various cancers and can function as potential objectives for the development of novel medications and therapies to combat drug resistance.
Conclusion: Accurate predictions of drug resistance mutations could significantly aid in the development of novel, personalized cancer treatment strategies. However, further data is required to fully understand drug resistance, particularly in clarifying the relationship between specific drugs and the mutations associated with resistance in cancer-related genes. Our innovative approach, which integrates genetic mutation data, has the potential to provide deeper insights into the underlying physiological mechanisms driving cancer drug resistance.
References
Duan C, Yu M, Xu J, Li BY, Zhao Y, Kankala RK. Overcoming Cancer Multi-drug Resistance (MDR): Reasons, mechanisms, nanotherapeutic solutions, and challenges. Biomedicine & Pharmacotherapy. 2023;162:114643.
Hu X, Zhang Z. Understanding the genetic mechanisms of cancer drug resistance using genomic approaches. Trends in Genetics. 2016;32(2):127-37.
Kuczynski EA, Sargent DJ, Grothey A, Kerbel RS. Drug rechallenge and treatment beyond progression—implications for drug resistance. Nature reviews Clinical oncology. 2013;10(10):571-87.
Vasan N, Baselga J, Hyman DM. A view on drug resistance in cancer. Nature. 2019 Nov 14;575(7782):299-309.
Garraway LA, Jänne PA. Circumventing cancer drug resistance in the era of personalized medicine. Cancer discovery. 2012;2(3):214-26.
Cheng F, Zhao J, Zhao Z. Advances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomes. Briefings in bioinformatics. 2016;17(4):642-56.
Tripathi SK, Pandey K, Rengasamy KR, Biswal BK. Recent updates on the resistance mechanisms to epidermal growth factor receptor tyrosine kinase inhibitors and resistance reversion strategies in lung cancer. Medicinal Research Reviews. 2020;40(6):2132-76.
Haider T, Pandey V, Banjare N, Gupta PN, Soni V. Drug resistance in cancer: mechanisms and tackling strategies. Pharmacological Reports. 2020;72(5):1125-51.
Tate JG, Bamford S, Jubb HC, Sondka Z, Beare DM, Bindal N, Boutselakis H, Cole CG, Creatore C, Dawson E, Fish P. COSMIC: the catalogue of somatic mutations in cancer. Nucleic acids research. 2019;47(D1):D941-7.
Sondka Z, Dhir NB, Carvalho-Silva D, Jupe S, Madhumita, McLaren K, Starkey M, Ward S, Wilding J, Ahmed M, Argasinska J. COSMIC: a curated database of somatic variants and clinical data for cancer. Nucleic Acids Research. 2024;52(D1):D1210-7.
Karagiannakos A, Adamaki M, Tsintarakis A, Vojtesek B, Fåhraeus R, Zoumpourlis V, Karakostis K. Targeting oncogenic pathways in the era of personalized oncology: a systemic analysis reveals highly mutated signaling pathways in cancer patients and potential therapeutic targets. Cancers. 2022;14(3):664.
Yang IS, Kim S. Isoform specific gene expression analysis of KRAS in the prognosis of lung adenocarcinoma patients. BMC bioinformatics. 2018;19:1-0.
Chalela R, Curull V, Enriquez C, Pijuan L, Bellosillo B, Gea J. Lung adenocarcinoma: from molecular basis to genome-guided therapy and immunotherapy. Journal of thoracic disease. 2017;9(7):2142.
Mascaux C, Iannino N, Martin B, Paesmans M, Berghmans T, Dusart M, Haller A, Lothaire P, Meert AP, Noel S, Lafitte JJ. The role of RAS oncogene in survival of patients with lung cancer: a systematic review of the literature with meta-analysis. British journal of cancer. 2005;92(1):131-9.
Forbes S, Beare D, Bindal N, Bamford S, Ward S, Cole CG, Jia M, Kok C, Boutselakis H, De T, Sondka Z. COSMIC: high‐resolution cancer genetics using the catalogue of somatic mutations in cancer. Current protocols in human genetics. 2016 Oct;91(1):10-1.
Yarden Y. The EGFR family and its ligands in human cancer: signalling mechanisms and therapeutic opportunities. European journal of cancer. 2001;37:3-8.
Lynch TJ, Bell DW, Sordella R, Gurubhagavatula S, Okimoto RA, Brannigan BW, Harris PL, Haserlat SM, Supko JG, Haluska FG, Louis DN. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non–small-cell lung cancer to gefitinib. New England Journal of Medicine. 2004;350(21):2129-39.
Bamford S, Dawson E, Forbes S, Clements J, Pettett R, Dogan A, Flanagan A, Teague J, Futreal PA, Stratton MR, Wooster R. The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website. British journal of cancer. 2004;91(2):355-8.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Pak-Euro Journal of Medical and Life Sciences
This work is licensed under a Creative Commons Attribution 4.0 International License.
