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RecruitingNCT03269474Updated Feb 13, 2024

Computational Drug Repurposing for All EBS Cases

An observational study in Epidermolysis Bullosa, Healthy and Genetic Skin Disease, sponsored by Joyce Teng. Recruiting at 1 site in United States. Open to participants aged 0 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2024-02-13.

Sponsored by Joyce Teng · Observational

Study type
Observational
Model
Cohort
Time perspective
Prospective
Enrollment
60
Ages
0 Years and older
Sex
All
01

Study summary

The study will compare gene expression differences between blistered and non-blistered skin from individuals with all subtypes of EB, as well as normal skin from non-EB subjects. State of the art computational analysis will be performed to help identify new drugs that might help all EB wound healing and reduce pain. Researchers will focus on drugs that have already been approved for treatment of other dermatologic or non-dermatologic diseases, and therefore be repurposed for treatment of EB. Drug development is a very expensive process taking decades for execution. Drug repurposing on the other hand, significantly reduces the cost and shortens the amount of time that is needed to bring effective treatments to clinical use. To date, there is no specific treatment targeting the physiology and immunologic response in EB patients during wound healing. Market availability of repurposed medications will provide all EB patients rapid access to treatments, thus improving their quality of life.

Read the detailed description

Although gene, cell, and protein-based therapies are in development for patients suffering from all subtypes of epidermolysis bullosa (EB), new pharmacological treatments are in dire need. Characterizing molecular changes in EB, including gene expression, can identify new therapeutic targets and drugs that modulate those targets. However, sifting through gene expression information to identify the most promising drug targets is a complex data challenge. The goal of the study will identify a computational approach to evaluate and identify existing drugs approved for other diseases that can be repurposed for EB patients. The study will perform an unprecedented characterization of gene expression changes in EB patients compared to healthy, non-EB individuals across multiple tissues. Using a validated computational drug discovery platform, researchers will analyze gene expression and drug data using unique algorithms. In the first year, a list of ten, safety drugs more probable to treat the EB disease state will be identified. The most promising drugs discovered will then be tested in the clinic setting.

02

Conditions studied

  • Epidermolysis Bullosa
  • Healthy
  • Genetic Skin Disease
  • Epidermolysis Bullosa Simplex
  • Epidermolysis Bullosa, Junctional
  • Epidermolysis Bullosa Dystrophica

Keywords

  • epidermolysis bullosa
  • genetic expression
  • drug repurposing
  • computational approaches
  • drug discovery
03

Who can participate

Ages eligible
0 Years and older
Sexes eligible
All
Accepts healthy volunteers
Yes
Sampling method
Probability sample

Study population

Subject of all ages with either 1) a diagnosis of EB subjects or 2) healthy, non-EB subjects

Inclusion criteria

  • Subjects of all ages
  • Diagnosis of all subtypes of EB subjects
  • Healthy, non-EB subjects
  • Ability to complete study visit to collect tissue and blood specimen

Exclusion criteria

Exclusion Criteria:

  • Pregnancy, breast feeding
  • Prior history of liver disease
  • Serious known concurrent medical illness or infection, which could potentially present a safety risk and/or prevent tissue collection from subjects
04

Study design

Observational model
Cohort
Time perspective
Prospective
Enrollment
60 participants (estimated)
Patient registry
No
Biospecimen retention
Samples with dna

Groups and cohorts

  • Experimental Group

    Blood and tissue specimen will be collected from subjects with an EB diagnosis. Tissue specimen will be collected from blistered and nonblistered skin.

    Procedure: Experimental Group

  • Control Group

    Blood and tissue specimen will be collected from healthy subjects with non-EB. Tissue specimen will be collected from an inconspicuous skin area.

    Procedure: Experimental Group

Interventions

  • ProcedureExperimental Group

    Subjects with EB diagnosis

05

What researchers measure

Primary outcomes

  1. Characterize gene expression changes in EB using RNA sequencing (RNA-seq) and Computational Profiling Potential Drug Targets

    Using bioinformatic algorithms to identify changes in gene expression and review of over 2000 FDA-approved drugs based on predicted modulation of gene expression changes using a computational evolutionary algorithm system.

    Time frame: Through the completion of study in 1 year.

06

Study locations

1 of 1 sites recruiting
  • Pediatric Dermatology Clinic at Stanford Children's Hospital
    Palo Alto, California 94304, United States
    Recruiting
07

References and documents

Publications

  • McLaren PJ, Mayne M, Rosser S, Moffatt T, Becker KG, Plummer FA, Fowke KR. Antigen-specific gene expression profiles of peripheral blood mononuclear cells do not reflect those of T-lymphocyte subsets. Clin Diagn Lab Immunol. 2004 Sep;11(5):977-82. doi: 10.1128/CDLI.11.5.977-982.2004. PubMed 15358662 ↗
  • Sleasman JW, Leon BH, Aleixo LF, Rojas M, Goodenow MM. Immunomagnetic selection of purified monocyte and lymphocyte populations from peripheral blood mononuclear cells following cryopreservation. Clin Diagn Lab Immunol. 1997 Nov;4(6):653-8. doi: 10.1128/cdli.4.6.653-658.1997. PubMed 9384284 ↗
  • Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol. 2016 May;34(5):525-7. doi: 10.1038/nbt.3519. Epub 2016 Apr 4. Erratum In: Nat Biotechnol. 2016 Aug 9;34(8):888. doi: 10.1038/nbt0816-888d. PubMed 27043002 ↗
  • Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010 Jan 1;26(1):139-40. doi: 10.1093/bioinformatics/btp616. Epub 2009 Nov 11. PubMed 19910308 ↗
  • Law V, Knox C, Djoumbou Y, Jewison T, Guo AC, Liu Y, Maciejewski A, Arndt D, Wilson M, Neveu V, Tang A, Gabriel G, Ly C, Adamjee S, Dame ZT, Han B, Zhou Y, Wishart DS. DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res. 2014 Jan;42(Database issue):D1091-7. doi: 10.1093/nar/gkt1068. Epub 2013 Nov 6. PubMed 24203711 ↗
  • Sugaya N, Kanai S, Furuya T. Dr. PIAS 2.0: an update of a database of predicted druggable protein-protein interactions. Database (Oxford). 2012 Oct 10;2012:bas034. doi: 10.1093/database/bas034. Print 2012. PubMed 23060433 ↗
  • Subramanian A, Kuehn H, Gould J, Tamayo P, Mesirov JP. GSEA-P: a desktop application for Gene Set Enrichment Analysis. Bioinformatics. 2007 Dec 1;23(23):3251-3. doi: 10.1093/bioinformatics/btm369. Epub 2007 Jul 20. PubMed 17644558 ↗
  • Cohn HI, Teng JM. Advancement in management of epidermolysis bullosa. Curr Opin Pediatr. 2016 Aug;28(4):507-16. doi: 10.1097/MOP.0000000000000380. PubMed 27386970 ↗
  • Uitto J, Bruckner-Tuderman L, Christiano AM, McGrath JA, Has C, South AP, Kopelan B, Robinson EC. Progress toward Treatment and Cure of Epidermolysis Bullosa: Summary of the DEBRA International Research Symposium EB2015. J Invest Dermatol. 2016 Feb;136(2):352-358. doi: 10.1016/j.jid.2015.10.050. PubMed 26802230 ↗
  • Nystrom A, Thriene K, Mittapalli V, Kern JS, Kiritsi D, Dengjel J, Bruckner-Tuderman L. Losartan ameliorates dystrophic epidermolysis bullosa and uncovers new disease mechanisms. EMBO Mol Med. 2015 Sep;7(9):1211-28. doi: 10.15252/emmm.201505061. PubMed 26194911 ↗
  • Wally V, Kitzmueller S, Lagler F, Moder A, Hitzl W, Wolkersdorfer M, Hofbauer P, Felder TK, Dornauer M, Diem A, Eiler N, Bauer JW. Topical diacerein for epidermolysis bullosa: a randomized controlled pilot study. Orphanet J Rare Dis. 2013 May 7;8:69. doi: 10.1186/1750-1172-8-69. PubMed 23651789 ↗
  • Li J, Zheng S, Chen B, Butte AJ, Swamidass SJ, Lu Z. A survey of current trends in computational drug repositioning. Brief Bioinform. 2016 Jan;17(1):2-12. doi: 10.1093/bib/bbv020. Epub 2015 Mar 31. PubMed 25832646 ↗
  • Low YS, Daugherty AC, Schroeder EA, Chen W, Seto T, Weber S, Lim M, Hastie T, Mathur M, Desai M, Farrington C, Radin AA, Sirota M, Kenkare P, Thompson CA, Yu PP, Gomez SL, Sledge GW Jr, Kurian AW, Shah NH. Synergistic drug combinations from electronic health records and gene expression. J Am Med Inform Assoc. 2017 May 1;24(3):565-576. doi: 10.1093/jamia/ocw161. PubMed 27940607 ↗
  • Bchetnia M, Tremblay ML, Leclerc G, Duperee A, Powell J, McCuaig C, Morin C, Legendre-Guillemin V, Laprise C. Expression signature of epidermolysis bullosa simplex. Hum Genet. 2012 Mar;131(3):393-406. doi: 10.1007/s00439-011-1077-7. Epub 2011 Aug 30. PubMed 21877134 ↗
  • Roth W, Reuter U, Wohlenberg C, Bruckner-Tuderman L, Magin TM. Cytokines as genetic modifiers in K5-/- mice and in human epidermolysis bullosa simplex. Hum Mutat. 2009 May;30(5):832-41. doi: 10.1002/humu.20981. PubMed 19267394 ↗
  • Lee B, Geyfman M, Andersen B, Dai X. Analysis of gene expression in skin using laser capture microdissection. Methods Mol Biol. 2013;989:109-17. doi: 10.1007/978-1-62703-330-5_10. PubMed 23483391 ↗
  • Lovendorf MB, Mitsui H, Zibert JR, Ropke MA, Hafner M, Dyring-Andersen B, Bonefeld CM, Krueger JG, Skov L. Laser capture microdissection followed by next-generation sequencing identifies disease-related microRNAs in psoriatic skin that reflect systemic microRNA changes in psoriasis. Exp Dermatol. 2015 Mar;24(3):187-93. doi: 10.1111/exd.12604. PubMed 25431026 ↗

Individual participant data

Plan to share: No — As of now, there are no plans to share the data with other researchers. Once the outcome measures have been accomplished, the research team will publish results for the entire clinicaltrials.gov community and researchers for this vulnerable population study.

08

Registry details

Key details

Study ID
NCT03269474
Lead sponsor
Joyce Teng
Responsible party
Joyce Teng (Director of Pediatric Dermatology, Stanford University) — Sponsor-investigator
First posted
Aug 31, 2017
Start date
Nov 28, 2017
Primary completion
Dec 30, 2024 (estimated)
Completion
Dec 31, 2024 (estimated)
Last update
Feb 13, 2024

Study contacts

Monica Martin
Contact
momartin@stanford.edu
650-723-0636
Joyce M Teng, MD, PhD
principal investigator · Stanford University

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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