Identification of a novel peptide ligand for the cancer-specific receptor mutation EGFRvIII using high-throughput sequencing of phage-selected peptides.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
01 12 2022
Historique:
received: 03 01 2022
accepted: 28 11 2022
entrez: 1 12 2022
pubmed: 2 12 2022
medline: 6 12 2022
Statut: epublish

Résumé

We report here the selection and characterization of a novel peptide ligand using phage display targeted against the cancer-specific epidermal growth factor tyrosine kinase receptor mutation variant III (EGFRvIII). This receptor is expressed in several kinds of cancer: ovarian cancer, breast cancer and glioblastoma, but not in normal tissues. A 12-mer random peptide library was screened against EGFRvIII. Phage-selected peptides were sequenced in high-throughput by next generation sequencing (NGS), and their diversity was studied to identify highly abundant clones expected to bind with the highest affinities to EGFRvIII. The enriched peptides were characterized and their binding capacity towards stable cell lines expressing EGFRvIII, EGFR wild type (EGFR WT), or a low endogenous level of EGFR WT was confirmed by flow cytometry analysis. The best peptide candidate, VLGREEWSTSYW, was synthesized, and its binding specificity towards EGFRvIII was validated in vitro. Additionally, computational docking analysis suggested that the identified peptide binds selectively to EGFRvIII. The novel VLGREEWSTSYW peptide is thus a promising EGFRvIII-targeting agent for future applications in cancer diagnosis and therapy.

Identifiants

pubmed: 36456600
doi: 10.1038/s41598-022-25257-4
pii: 10.1038/s41598-022-25257-4
pmc: PMC9715707
doi:

Substances chimiques

epidermal growth factor receptor VIII 0
Ligands 0
ErbB Receptors EC 2.7.10.1
Peptides 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

20725

Informations de copyright

© 2022. The Author(s).

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Auteurs

Sourour Mansour (S)

Center for Protein Engineering and Drug Discovery, PMC Isochem SAS, 32, rue Lavoisier 91710, Vert-Le-Petit, France.

Indranil Adhya (I)

Center for Protein Engineering and Drug Discovery, PMC Isochem SAS, 32, rue Lavoisier 91710, Vert-Le-Petit, France.

Coralie Lebleu (C)

Center for Protein Engineering and Drug Discovery, PMC Isochem SAS, 32, rue Lavoisier 91710, Vert-Le-Petit, France.

Rama Dumpati (R)

Division of Computational Research, Chakrabarti Advanced Technology, Hyderabad, Telangana, India.

Ahmed Rehan (A)

Center for Protein Engineering and Drug Discovery, PMC Isochem SAS, 32, rue Lavoisier 91710, Vert-Le-Petit, France.

Santu Chall (S)

Division of Computational Research, Chakrabarti Advanced Technology, Hyderabad, Telangana, India.

Jingqi Dai (J)

Center for Protein Engineering and Drug Discovery, PMC Isochem SAS, 32, rue Lavoisier 91710, Vert-Le-Petit, France.

Gauthier Errasti (G)

Center for Protein Engineering and Drug Discovery, PMC Isochem SAS, 32, rue Lavoisier 91710, Vert-Le-Petit, France.

Thomas Delacroix (T)

Center for Protein Engineering and Drug Discovery, PMC Isochem SAS, 32, rue Lavoisier 91710, Vert-Le-Petit, France.

Raj Chakrabarti (R)

Center for Protein Engineering and Drug Discovery, PMC Isochem SAS, 32, rue Lavoisier 91710, Vert-Le-Petit, France. raj@pmc-group.com.
Division of Computational Research, Chakrabarti Advanced Technology, Hyderabad, Telangana, India. raj@pmc-group.com.
Chakrabarti Advanced Technology, LLC, PMC Group Building, 1288 Route 73, Ste 110, Mount Laurel, NJ, 08054, USA. raj@pmc-group.com.

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Classifications MeSH