CD3ζ as a novel predictive biomarker of PD-1 inhibitor resistance in melanoma.


Journal

Molecular and cellular probes
ISSN: 1096-1194
Titre abrégé: Mol Cell Probes
Pays: England
ID NLM: 8709751

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 09 06 2023
revised: 27 07 2023
accepted: 08 08 2023
medline: 6 12 2023
pubmed: 12 8 2023
entrez: 11 8 2023
Statut: ppublish

Résumé

Malignant melanoma is the most lethal form of skin cancer, and its incidence rates are increasing in Europe, America, and Oceania countries. Despite immune checkpoint inhibitors, such as PD-1 inhibitors, have been shown to have significant therapeutic effects on malignant melanoma, many patients are unresponsive to these treatments, even emerged resistance. There is an urgent need to discover novel biomarkers that might distinguish resistant patients from responders. In this study, we used a series of bioinformatics analyses and experimental validation. The GSE65041 was used for differential expression analysis. Kaplan-Meier was used to assess the prognostic value. ESTIMATE, ssGSEA, EPIC, TIMER, quanTiseq and MCPcounter for estimation of immune infiltration in the tumor microenvironment. We eventually identified that CD3ζ was significantly down-regulated in IHC PD-L1(-) melanoma patients. Low level of CD3ζ expression possessed a poor prognosis. CD3ζ low expression population is significantly associated with lower immune infiltration. In vivo experiment, CD3ζ expression was significantly down-regulated in mice melanoma after intradermally injected with B16-F10R cells. Compared to their wildtype counterparts, melanoma resistant mice treated with nivolumab showed significant reductions in tumor volume and weight when adding CD3ζ. In vitro experiment, the addition of CD3ζ increased nivolumab effection on inhibiting B16-F10R cell viability. Our findings indicated that CD3ζ could be a novel predictive biomarker of PD-1 inhibitor resistance in melanoma.

Identifiants

pubmed: 37567322
pii: S0890-8508(23)00034-8
doi: 10.1016/j.mcp.2023.101925
pii:
doi:

Substances chimiques

Immune Checkpoint Inhibitors 0
Nivolumab 31YO63LBSN
Biomarkers, Tumor 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

101925

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they do not have any conflicts of interest.

Auteurs

Zhuo Zhang (Z)

Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China; Department of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, 50200, Thailand.

Duoli Zhang (D)

Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China.

Fang Wang (F)

Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China; Department of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, 50200, Thailand.

Jiao Liu (J)

Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China; Department of Pharmacy, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.

Xian Jiang (X)

Department of Anesthesiology, Luzhou People's Hospital, Luzhou, 646000, China.

Songyot Anuchapreeda (S)

Department of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, 50200, Thailand.

Singkome Tima (S)

Department of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, 50200, Thailand.

Zhangang Xiao (Z)

Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, 646000, China. Electronic address: zhangangxiao@swmu.edu.cn.

Suwit Duangmano (S)

Department of Medical Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, 50200, Thailand. Electronic address: suwit.du@cmu.ac.th.

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Classifications MeSH