#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Application of pharmacogenomics and bioinformatics to exemplify the utility of human ex vivo organoculture models in the field of precision medicine


Autoři: Karen Cowan aff001;  Graeme Macluskie aff001;  Michael Finch aff001;  Colin N. A. Palmer aff002;  Jane Hair aff003;  Max Bylesjo aff004;  Sarah Lynagh aff004;  Pamela Brankin aff005;  Marian McNeil aff006;  Carolyn Low aff006;  David Mallinson aff007;  Elaine M. Gourlay aff007;  Hannah Child aff006;  Linda Cheyne aff006;  David C. Bunton aff001
Působiště autorů: REPROCELL Europe Ltd, Thomson Pavilion, Glasgow, Scotland, United Kingdom aff001;  School of Medicine, University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland, United Kingdom aff002;  NHS Greater Glasgow & Clyde, Queen Elizabeth University Hospital, Glasgow, Scotland, United Kingdom aff003;  Fios Genomics Ltd, Nine Edinburgh Bioquarter, Edinburgh, Scotland, United Kingdom aff004;  Aridhia Informatics Ltd Teaching and Learning Building, Queen Elizabeth University Hospital, Glasgow, Scotland, United Kingdom aff005;  Stratified Medicines Scotland Innovation Centre, Teaching and Learning Building, Queen Elizabeth University Hospital, Glasgow, Scotland, United Kingdom aff006;  Sistemic Ltd, West of Scotland Science Park, Glasgow, Scotland, United Kingdom aff007
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0226564

Souhrn

Here we describe a collaboration between industry, the National Health Service (NHS) and academia that sought to demonstrate how early understanding of both pharmacology and genomics can improve strategies for the development of precision medicines. Diseased tissue ethically acquired from patients suffering from chronic obstructive pulmonary disease (COPD), was used to investigate inter-patient variability in drug efficacy using ex vivo organocultures of fresh lung tissue as the test system. The reduction in inflammatory cytokines in the presence of various test drugs was used as the measure of drug efficacy and the individual patient responses were then matched against genotype and microRNA profiles in an attempt to identify unique predictors of drug responsiveness. Our findings suggest that genetic variation in CYP2E1 and SMAD3 genes may partly explain the observed variation in drug response.

Klíčová slova:

Bioinformatics – Biopsy – Drug research and development – Genome-wide association studies – Chronic obstructive pulmonary disease – MicroRNAs – RNA extraction – Variant genotypes


Zdroje

1. Agyeman AA, Ofori-Asenso R. Perspective: Does personalized medicine hold the future for medicine? J Pharm Bioallied Sci. 7: 239–44. doi: 10.4103/0975-7406.160040 26229361

2. Chen Y, Guzauskas GF, Gu C, Wang BCM, Furnback WE, Xie G, et al. Precision Health Economics and Outcomes Research to Support Precision Medicine: Big Data Meets Patient Heterogeneity on the Road to Value. J Pers Med. 2016;6. doi: 10.3390/jpm6040020 27827859

3. Paul SM, Mytelka DS, Dunwiddie CT, Persinger CC, Munos BH, Lindborg SR, et al. How to improve RD productivity: The pharmaceutical industry’s grand challenge. Nature Reviews Drug Discovery. 2010. pp. 203–214. doi: 10.1038/nrd3078 20168317

4. Schork NJ. Personalized medicine: Time for one-person trials. Nature. Nature Publishing Group; 2015. pp. 609–611. doi: 10.1038/520609a 25925459

5. Trusheim MR, Burgess B, Hu SX, Long T, Averbuch SD, Flynn AA, et al. Quantifying factors for the success of stratified medicine. Nat Rev Drug Discov. 2011;10: 817–33. doi: 10.1038/nrd3557 22037040

6. Cook D, Brown D, Alexander R, March R, Morgan P, Satterthwaite G, et al. Lessons learned from the fate of AstraZeneca’s drug pipeline: a five-dimensional framework. Nat Rev Drug Discov. 2014;13: 419–31. doi: 10.1038/nrd4309 24833294

7. Biankin AV, Piantadosi S, Hollingsworth SJ. Patient-centric trials for therapeutic development in precision oncology. Nature. 2015;526: 361–70. doi: 10.1038/nature15819 26469047

8. Found in translation—European Pharmaceutical Review. [cited 30 Oct 2019]. https://www.europeanpharmaceuticalreview.com/article/16219/found-in-translation/

9. Asghar W, El Assal R, Shafiee H, Pitteri S, Paulmurugan R, Demirci U. Engineering cancer microenvironments for in vitro 3-D tumor models. Mater Today (Kidlington). 2015;18: 539–553. doi: 10.1016/j.mattod.2015.05.002 28458612

10. Zanoni M, Piccinini F, Arienti C, Zamagni A, Santi S, Polico R, et al. 3D tumor spheroid models for in vitro therapeutic screening: A systematic approach to enhance the biological relevance of data obtained. Sci Rep. 2016;6. doi: 10.1038/srep19103 26752500

11. Mandrekar SJ, Sargent DJ. All-Comers versus Enrichment Design Strategy in Phase II Trials. J Thorac Oncol. 2011.

12. Cilli A, Bal H, Gunen H. Efficacy and safety profile of roflumilast in a real-world experience. J Thorac Dis. 2019;11: 1100–1105. doi: 10.21037/jtd.2019.04.49 31179051

13. Rennard SI, Tashkin DP, McElhattan J, Goldman M, Ramachandran S, Martin UJ, et al. Efficacy and tolerability of budesonide/formoterol in one hydrofluoroalkane pressurized metered-dose inhaler in patients with chronic obstructive pulmonary disease: results from a 1-year randomized controlled clinical trial. Drugs. 2009;69: 549–65. doi: 10.2165/00003495-200969050-00004 19368417

14. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 2004;5: R80. doi: 10.1186/gb-2004-5-10-r80 15461798

15. Zheng X. Statistical Prediction of HLA Alleles and Relatedness Analysis in Genome-Wide Association Studies. 2013.

16. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: A tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81: 559–575. doi: 10.1086/519795 17701901

17. Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics. 2007;8: 118–127. doi: 10.1093/biostatistics/kxj037 16632515

18. Chou C-H, Chang N-W, Shrestha S, Hsu S-D, Lin Y-L, Lee W-H, et al. miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database. Nucleic Acids Res. 2016;44: D239–47. doi: 10.1093/nar/gkv1258 26590260

19. Edward Jackson J, York Chichester Brisbane Toronto N. A User’s Guide To Principal Components.

20. Arif E, Vibhuti A, Alam P, Deepak D, Singh B, Athar M, et al. Association of CYP2E1 and NAT2 gene polymorphisms with chronic obstructive pulmonary disease. Clin Chim Acta. 2007;382: 37–42. doi: 10.1016/j.cca.2007.03.013 17442289

21. Tilley AE, Harvey B-G, Heguy A, Hackett NR, Wang R, O’Connor TP, et al. Down-regulation of the notch pathway in human airway epithelium in association with smoking and chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2009;179: 457–66. doi: 10.1164/rccm.200705-795OC 19106307

22. Faura Tellez G, Vandepoele K, Brouwer U, Koning H, Elderman RM, Hackett T-L, et al. Protocadherin-1 binds to SMAD3 and suppresses TGF-β1-induced gene transcription. Am J Physiol Lung Cell Mol Physiol. 2015;309: L725–35. doi: 10.1152/ajplung.00346.2014 26209277

23. André PA, Prêle CM, Vierkotten S, Carnesecchi S, Donati Y, Chambers RC, et al. BARD1 mediates TGF-β signaling in pulmonary fibrosis. Respir Res. 2015;16. doi: 10.1186/s12931-015-0278-3 26415510

24. Chokas AL, Trivedi CM, Lu MM, Tucker PW, Li S, Epstein JA, et al. Foxp1/2/4-NuRD interactions regulate gene expression and epithelial injury response in the lung via regulation of interleukin-6. J Biol Chem. 2010;285: 13304–13. doi: 10.1074/jbc.M109.088468 20185820

25. Linhart K, Bartsch H, Seitz HK. The role of reactive oxygen species (ROS) and cytochrome P-450 2E1 in the generation of carcinogenic etheno-DNA adducts. Redox Biol. 2014;3: 56–62. doi: 10.1016/j.redox.2014.08.009 25462066

26. Yang T, Ying B, Song X, Zhang S, Fan H, Xu D, et al. Single-nucleotide polymorphisms in SMAD3 are associated with chronic obstructive pulmonary disease. Exp Biol Med (Maywood). 2010;235: 599–605. doi: 10.1258/ebm.2010.009268 20463300

27. Ezzie ME, Crawford M, Cho J-H, Orellana R, Zhang S, Gelinas R, et al. Gene expression networks in COPD: microRNA and mRNA regulation. Thorax. 2012;67: 122–31. doi: 10.1136/thoraxjnl-2011-200089 21940491

28. Yang H, Wang L, Zhao J, Chen Y, Lei Z, Liu X, et al. TGF-β-activated SMAD3/4 complex transcriptionally upregulates N-cadherin expression in non-small cell lung cancer. Lung Cancer. 2015;87: 249–57. doi: 10.1016/j.lungcan.2014.12.015 25595426

29. Yu J-R, Tai Y, Jin Y, Hammell MC, Wilkinson JE, Roe J-S, et al. TGF-β/Smad signaling through DOCK4 facilitates lung adenocarcinoma metastasis. Genes Dev. 2015;29: 250–61. doi: 10.1101/gad.248963.114 25644601

30. Milara J, Peiró T, Serrano A, Guijarro R, Zaragozá C, Tenor H, et al. Roflumilast N-oxide inhibits bronchial epithelial to mesenchymal transition induced by cigarette smoke in smokers with COPD. Pulm Pharmacol Ther. 2014;28: 138–48. doi: 10.1016/j.pupt.2014.02.001 24525294


Článek vyšel v časopise

PLOS One


2019 Číslo 12
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

KOST
Koncepce osteologické péče pro gynekology a praktické lékaře
nový kurz
Autoři: MUDr. František Šenk

Sekvenční léčba schizofrenie
Autoři: MUDr. Jana Hořínková

Hypertenze a hypercholesterolémie – synergický efekt léčby
Autoři: prof. MUDr. Hana Rosolová, DrSc.

Svět praktické medicíny 5/2023 (znalostní test z časopisu)

Imunopatologie? … a co my s tím???
Autoři: doc. MUDr. Helena Lahoda Brodská, Ph.D.

Všechny kurzy
Kurzy Podcasty Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#