LinkedIn

 آمار

تعداد نشریات20
تعداد شماره‌ها1,157
تعداد مقالات10,573
تعداد مشاهده مقاله45,916,112
تعداد دریافت فایل اصل مقاله11,583,649
Sharafshah, Alireza, Motovali-Bashi, Majid, Keshavarz, Parvaneh. (1403). Pharmacogenomics-Based Detection of Variants Involved in Pain, Anti-inflammatory and Immunomodulating Agents Pathways by Whole Exome Sequencing and Deep in Silico Investigations Revealed Novel Chemical Carcinogenesis and Cancer Risks. سامانه مدیریت نشریات علمی, (), -. doi: 10.30476/ijms.2024.101852.3450
Alireza Sharafshah; Majid Motovali-Bashi; Parvaneh Keshavarz. "Pharmacogenomics-Based Detection of Variants Involved in Pain, Anti-inflammatory and Immunomodulating Agents Pathways by Whole Exome Sequencing and Deep in Silico Investigations Revealed Novel Chemical Carcinogenesis and Cancer Risks". سامانه مدیریت نشریات علمی, , , 1403, -. doi: 10.30476/ijms.2024.101852.3450
Sharafshah, Alireza, Motovali-Bashi, Majid, Keshavarz, Parvaneh. (1403). 'Pharmacogenomics-Based Detection of Variants Involved in Pain, Anti-inflammatory and Immunomodulating Agents Pathways by Whole Exome Sequencing and Deep in Silico Investigations Revealed Novel Chemical Carcinogenesis and Cancer Risks', سامانه مدیریت نشریات علمی, (), pp. -. doi: 10.30476/ijms.2024.101852.3450
Sharafshah, Alireza, Motovali-Bashi, Majid, Keshavarz, Parvaneh. Pharmacogenomics-Based Detection of Variants Involved in Pain, Anti-inflammatory and Immunomodulating Agents Pathways by Whole Exome Sequencing and Deep in Silico Investigations Revealed Novel Chemical Carcinogenesis and Cancer Risks. سامانه مدیریت نشریات علمی, 1403; (): -. doi: 10.30476/ijms.2024.101852.3450

Pharmacogenomics-Based Detection of Variants Involved in Pain, Anti-inflammatory and Immunomodulating Agents Pathways by Whole Exome Sequencing and Deep in Silico Investigations Revealed Novel Chemical Carcinogenesis and Cancer Risks

Iranian Journal of Medical Sciences
مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 28 مهر 1403    اصل مقاله (5.62 M)
نوع مقاله: Original Article(s)
شناسه دیجیتال (DOI): 10.30476/ijms.2024.101852.3450
نویسندگان
Alireza Sharafshah1، 2؛ Majid Motovali-Bashi* 1؛ Parvaneh Keshavarz2
1Division of Genetics, Department of Cell and Molecular Biology and Microbiology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran
2Cellular and Molecular Research Center, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran
چکیده
Background: Next-Generation Sequencing (NGS) methods specifically Whole-Exome Sequencing (WES) have demonstrated promising findings with a high accuracy of 91%-99% in Pharmacogenomics (PGx). A PGx-based panel can be utilized to minimize adverse drug reactions (ADRs) and maximize the treatment efficacy. Remarkably, Cancer Pain Management (CPM) is a cutting-edge concept in modern medicine. Thus, this study aimed to investigate the WES results by a PGx-based panel containing genes involved in Pain, Anti-inflammatory, and Immunomodulating agents (PAIma) signaling pathways. 
Methods: A total of 200 unrelated Iranians (100 western and 100 northern) were included. 100 WES results were analyzed through the PAIma panel. After DNA extraction, 100 samples were genotyped by Multiplex-Amplification-Refractory Mutation System (ARMS) PCR. A primary in silico investigation performed on 128 candidate genes through Protein-Protein Interactions (PPIs) and Gene-miRNA Interactions (GMIs) via the STRING database, and miRTargetLink2, respectively. Additionally, Enrichment Analysis (EA) was applied to find the unknown interplays among these three major pathways by Enrichr. 
Results: 55,590 annotations through 21 curated pathways were filtered, 900 variants were found, and 128 genes were refined. Finally, 54 candidate variants (48 non-synonymous single nucleotide variants (nsSNVs), 2 stop-gained, 1 frameshift, and 3 splicing) remained. 
Conclusion: Conclusively, six potentially actionable variants including rs1695 (GSTP1), rs628031 (SLC22A1), rs17863778 (UGT1A7), rs16947 (CYP2D6), rs2257401 (CYP3A7), and rs2515641 (CYP2E1) had the most deviations among Iranians, compared with the reference genome, which should be genotyped for drug prescribing. Remarkably, PPIs, GMIs, and EA revealed potential risks of carcinogenesis and cancer phenotypes resulting from PAIma pathways genes. 
کلیدواژه‌ها
Pharmacogenomics؛ Whole exome sequencing؛ Genetic variation؛ Cancer
مراجع
  1. Kalow W, Tang BK, Endrenyi L. Hypothesis: comparisons of inter- and intra-individual variations can substitute for twin studies in drug research. Pharmacogenetics. 1998;8:283-9. doi: 10.1097/00008571-199808000-00001. PubMed PMID: 9731714.
  2. Schildcrout JS, Denny JC, Bowton E, Gregg W, Pulley JM, Basford MA, et al. Optimizing drug outcomes through pharmacogenetics: a case for preemptive genotyping. Clin Pharmacol Ther. 2012;92:235-42. doi: 10.1038/clpt.2012.66. PubMed PMID: 22739144; PubMed Central PMCID: PMCPMC3785311.
  3. Pavlopoulos GA, Oulas A, Iacucci E, Sifrim A, Moreau Y, Schneider R, et al. Unraveling genomic variation from next generation sequencing data. BioData Min. 2013;6:13. doi: 10.1186/1756-0381-6-13. PubMed PMID: 23885890; PubMed Central PMCID: PMCPMC3726446.
  4. Hovelson DH, Xue Z, Zawistowski M, Ehm MG, Harris EC, Stocker SL, et al. Characterization of ADME gene variation in 21 populations by exome sequencing. Pharmacogenet Genomics. 2017;27:89-100. doi: 10.1097/FPC.0000000000000260. PubMed PMID: 27984508; PubMed Central PMCID: PMCPMC5287433.
  5. Boscolo Bielo L, Trapani D, Repetto M, Crimini E, Valenza C, Belli C, et al. Variant allele frequency: a decision-making tool in precision oncology? Trends Cancer. 2023;9:1058-68. doi: 10.1016/j.trecan.2023.08.011. PubMed PMID: 37704501.
  6. Rulten SL, Grose RP, Gatz SA, Jones JL, Cameron AJM. The Future of Precision Oncology. Int J Mol Sci. 2023;24. doi: 10.3390/ijms241612613. PubMed PMID: 37628794; PubMed Central PMCID: PMCPMC10454858.
  7. Raad M, Lopez WOC, Sharafshah A, Assefi M, Lewandrowski KU. Personalized Medicine in Cancer Pain Management. J Pers Med. 2023;13. doi: 10.3390/jpm13081201. PubMed PMID: 37623452; PubMed Central PMCID: PMCPMC10455778.
  8. van der Lee M, Allard WG, Bollen S, Santen GWE, Ruivenkamp CAL, Hoffer MJV, et al. Repurposing of Diagnostic Whole Exome Sequencing Data of 1,583 Individuals for Clinical Pharmacogenetics. Clin Pharmacol Ther. 2020;107:617-27. doi: 10.1002/cpt.1665. PubMed PMID: 31594036; PubMed Central PMCID: PMCPMC7027978.
  9. Roden DM, Van Driest SL, Mosley JD, Wells QS, Robinson JR, Denny JC, et al. Benefit of Preemptive Pharmacogenetic Information on Clinical Outcome. Clin Pharmacol Ther. 2018;103:787-94. doi: 10.1002/cpt.1035. PubMed PMID: 29377064; PubMed Central PMCID: PMCPMC6134843.
  10. Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 2010;38:e164. doi: 10.1093/nar/gkq603. PubMed PMID: 20601685; PubMed Central PMCID: PMCPMC2938201.
  11. Szklarczyk D, Kirsch R, Koutrouli M, Nastou K, Mehryary F, Hachilif R, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. 2023;51:D638-D46. doi: 10.1093/nar/gkac1000. PubMed PMID: 36370105; PubMed Central PMCID: PMCPMC9825434.
  12. Kern F, Aparicio-Puerta E, Li Y, Fehlmann T, Kehl T, Wagner V, et al. miRTargetLink 2.0-interactive miRNA target gene and target pathway networks. Nucleic Acids Res. 2021;49:W409-W16. doi: 10.1093/nar/gkab297. PubMed PMID: 34009375; PubMed Central PMCID: PMCPMC8262750.
  13. Xie Z, Bailey A, Kuleshov MV, Clarke DJB, Evangelista JE, Jenkins SL, et al. Gene Set Knowledge Discovery with Enrichr. Curr Protoc. 2021;1:e90. doi: 10.1002/cpz1.90. PubMed PMID: 33780170; PubMed Central PMCID: PMCPMC8152575.
  14. Mizzi C, Peters B, Mitropoulou C, Mitropoulos K, Katsila T, Agarwal MR, et al. Personalized pharmacogenomics profiling using whole-genome sequencing. Pharmacogenomics. 2014;15:1223-34. doi: 10.2217/pgs.14.102. PubMed PMID: 25141897.
  15. Yang W, Wu G, Broeckel U, Smith CA, Turner V, Haidar CE, et al. Comparison of genome sequencing and clinical genotyping for pharmacogenes. Clin Pharmacol Ther. 2016;100:380-8. doi: 10.1002/cpt.411. PubMed PMID: 27311679; PubMed Central PMCID: PMCPMC5684873.
  16. Yan C, Pattabiraman N, Goecks J, Lam P, Nayak A, Pan Y, et al. Impact of germline and somatic missense variations on drug binding sites. Pharmacogenomics J. 2017;17:128-36. doi: 10.1038/tpj.2015.97. PubMed PMID: 26810135; PubMed Central PMCID: PMCPMC5380835.
  17. Pandi MT, Williams MS, van der Spek P, Koromina M, Patrinos GP. Exome-Wide Analysis of the DiscovEHR Cohort Reveals Novel Candidate Pharmacogenomic Variants for Clinical Pharmacogenomics. Genes (Basel). 2020;11. doi: 10.3390/genes11050561. PubMed PMID: 32443490; PubMed Central PMCID: PMCPMC7290308.
  18. Han SM, Park J, Lee JH, Lee SS, Kim H, Han H, et al. Targeted Next-Generation Sequencing for Comprehensive Genetic Profiling of Pharmacogenes. Clin Pharmacol Ther. 2017;101:396-405. doi: 10.1002/cpt.532. PubMed PMID: 27727443.
  19. Gulilat M, Lamb T, Teft WA, Wang J, Dron JS, Robinson JF, et al. Targeted next generation sequencing as a tool for precision medicine. BMC Med Genomics. 2019;12:81. doi: 10.1186/s12920-019-0527-2. PubMed PMID: 31159795; PubMed Central PMCID: PMCPMC6547602.
  20. Sivadas A, Sharma P, Scaria V. Landscape of warfarin and clopidogrel pharmacogenetic variants in Qatari population from whole exome datasets. Pharmacogenomics. 2016;17:1891-901. doi: 10.2217/pgs-2016-0130. PubMed PMID: 27767380.
  21. Nagar SD, Conley AB, Jordan IK. Population structure and pharmacogenomic risk stratification in the United States. BMC Biol. 2020;18:140. doi: 10.1186/s12915-020-00875-4. PubMed PMID: 33050895; PubMed Central PMCID: PMCPMC7557099.
  22. Fassoulaki A, Melemeni A, Staikou C, Triga A, Sarantopoulos C. Acute postoperative pain predicts chronic pain and long-term analgesic requirements after breast surgery for cancer. Acta Anaesthesiol Belg. 2008;59:241-8. PubMed PMID: 19235522.
  23. Preux C, Bertin M, Tarot A, Authier N, Pinol N, Brugnon D, et al. Prevalence of Opioid Use Disorder among Patients with Cancer-Related Pain: A Systematic Review. J Clin Med. 2022;11. doi: 10.3390/jcm11061594. PubMed PMID: 35329919; PubMed Central PMCID: PMCPMC8954099.
  24. Check DK, Avecilla RAV, Mills C, Dinan MA, Kamal AH, Murphy B, et al. Opioid Prescribing and Use Among Cancer Survivors: A Mapping Review of Observational and Intervention Studies. J Pain Symptom Manage. 2022;63:e397-e417. doi: 10.1016/j.jpainsymman.2021.10.015. PubMed PMID: 34748896.
  25. Yang GS, Barnes NM, Lyon DE, Dorsey SG. Genetic Variants Associated with Cancer Pain and Response to Opioid Analgesics: Implications for Precision Pain Management. Semin Oncol Nurs. 2019;35:291-9. doi: 10.1016/j.soncn.2019.04.011. PubMed PMID: 31085105; PubMed Central PMCID: PMCPMC6688486.
  26. Sharma M, Kantorovich S, Lee C, Anand N, Blanchard J, Fung ET, et al. An observational study of the impact of genetic testing for pain perception in the clinical management of chronic non-cancer pain. J Psychiatr Res. 2017;89:65-72. doi: 10.1016/j.jpsychires.2017.01.015. PubMed PMID: 28182962.
آمار
تعداد مشاهده مقاله: 92
تعداد دریافت فایل اصل مقاله: 104


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب