PD-L1 detection on circulating tumor-derived extracellular vesicles (T-EVs) from patients with lung cancer.

Programmed cell death ligand-1 (PD-L1) exosome extracellular vesicle (EV) lung cancer

Journal

Translational lung cancer research
ISSN: 2218-6751
Titre abrégé: Transl Lung Cancer Res
Pays: China
ID NLM: 101646875

Informations de publication

Date de publication:
Jun 2021
Historique:
received: 17 12 2020
accepted: 06 04 2021
entrez: 23 7 2021
pubmed: 24 7 2021
medline: 24 7 2021
Statut: ppublish

Résumé

Recent breakthroughs in therapies with immune checkpoint inhibitors (ICIs) have revolutionized the treatment of lung cancer. However, only 15-25% of patients respond to the ICIs therapy, and methods to identify those responsive patients are currently a hot research topic. PD-L1 expression measured on tumor tissues using immunohistochemistry (IHC) was approved as one of the companion diagnostic methods, but it is invasive and cannot be used to monitor dynamic changes in PD-L1 expression during treatments. In this study, we developed an Epcam-PD-L1 extracellular vesicle (EV) detection prototype using the Simoa platform. This assay detected PD-L1 expression levels on tumor-derived exosomes from the lung cancer cell lines A549 and SK-MES1. In addition, 35 plasma samples from patients with lung cancer were tested with this assay and the results were compared to the tissue PD-L1 expression levels represented by the tumor proportion score (TPS). PD-L1 TPS-positive patients (≥1% IHC TPS) had significantly higher Simoa Epcam-PD-L1 signals than TPS-negative patients (<1% IHC TPS, P=0.026). The Simoa Epcam-PD-L1 area under curve (AUC) reached 0.776, with a sensitivity of 92.86% and a specificity of 71.43%. When PD-L1 TPS-positive patients were defined as having an IHC TPS ≥10%, the greatest difference in Epcam-PD-L1 signals was observed between IHC TPS-positive and IHC TPS-negative groups (P=0.0024) and the Simoa Epcam-PD-L1 AUC reached 0.832. Finally, the Spearman's correlation coefficient showed a significant correlation between the TPS and Simoa Epcam-PD-L1 signals (0.428, P=0.0104). Based on our results, our Simoa Epcam-PD-L1 EV detection assay is a potential liquid biopsy method to predict the PD-L1 expression level in patients with lung cancer.

Sections du résumé

BACKGROUND BACKGROUND
Recent breakthroughs in therapies with immune checkpoint inhibitors (ICIs) have revolutionized the treatment of lung cancer. However, only 15-25% of patients respond to the ICIs therapy, and methods to identify those responsive patients are currently a hot research topic. PD-L1 expression measured on tumor tissues using immunohistochemistry (IHC) was approved as one of the companion diagnostic methods, but it is invasive and cannot be used to monitor dynamic changes in PD-L1 expression during treatments.
METHODS METHODS
In this study, we developed an Epcam-PD-L1 extracellular vesicle (EV) detection prototype using the Simoa platform. This assay detected PD-L1 expression levels on tumor-derived exosomes from the lung cancer cell lines A549 and SK-MES1. In addition, 35 plasma samples from patients with lung cancer were tested with this assay and the results were compared to the tissue PD-L1 expression levels represented by the tumor proportion score (TPS).
RESULTS RESULTS
PD-L1 TPS-positive patients (≥1% IHC TPS) had significantly higher Simoa Epcam-PD-L1 signals than TPS-negative patients (<1% IHC TPS, P=0.026). The Simoa Epcam-PD-L1 area under curve (AUC) reached 0.776, with a sensitivity of 92.86% and a specificity of 71.43%. When PD-L1 TPS-positive patients were defined as having an IHC TPS ≥10%, the greatest difference in Epcam-PD-L1 signals was observed between IHC TPS-positive and IHC TPS-negative groups (P=0.0024) and the Simoa Epcam-PD-L1 AUC reached 0.832. Finally, the Spearman's correlation coefficient showed a significant correlation between the TPS and Simoa Epcam-PD-L1 signals (0.428, P=0.0104).
CONCLUSIONS CONCLUSIONS
Based on our results, our Simoa Epcam-PD-L1 EV detection assay is a potential liquid biopsy method to predict the PD-L1 expression level in patients with lung cancer.

Identifiants

pubmed: 34295653
doi: 10.21037/tlcr-20-1277
pii: tlcr-10-06-2441
pmc: PMC8264343
doi:

Types de publication

Journal Article

Langues

eng

Pagination

2441-2451

Informations de copyright

2021 Translational Lung Cancer Research. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tlcr-20-1277). PW reports that she has received research grants from National Science Foundation of China, Shanghai Natural Science Foundation of China, and Rising-Star Program of China. The other authors have no conflicts of interest to declare.

Références

Cancer Biol Ther. 2016 Apr 2;17(4):430-8
pubmed: 26828696
J Immunol Methods. 2015 Sep;424:20-7
pubmed: 25960176
J Immunol Methods. 2012 Apr 30;378(1-2):102-15
pubmed: 22370429
N Engl J Med. 2018 Nov 22;379(21):2040-2051
pubmed: 30280635
J Clin Oncol. 2018 Jun 10;36(17):1714-1768
pubmed: 29442540
Clin Cancer Res. 2018 Feb 15;24(4):896-905
pubmed: 29233903
N Engl J Med. 2018 Mar 01;378(9):868
pubmed: 29504720
Proc Natl Acad Sci U S A. 2016 Feb 23;113(8):E968-77
pubmed: 26858453
N Engl J Med. 2018 May 31;378(22):2078-2092
pubmed: 29658856
Lancet Oncol. 2019 Jul;20(7):924-937
pubmed: 31122901
Oncologist. 2016 May;21(5):643-50
pubmed: 27026676
Ann Oncol. 2017 Jul 1;28(suppl_4):iv119-iv142
pubmed: 28881921
J Thorac Oncol. 2017 Feb;12(2):208-222
pubmed: 27913228
J Immunol. 2005 Sep 1;175(5):2900-12
pubmed: 16116176
Lancet. 2016 Apr 9;387(10027):1540-1550
pubmed: 26712084
Br J Cancer. 2007 Feb 12;96(3):417-23
pubmed: 17211480
ACS Nano. 2014 Oct 28;8(10):10998-1006
pubmed: 25300001
Curr Opin Oncol. 2016 Mar;28(2):122-9
pubmed: 26756384
J Immunother Cancer. 2016 Oct 18;4:65
pubmed: 27777774
Commun Integr Biol. 2014 Jan 1;7(1):e28231
pubmed: 24778765
Anal Chem. 2011 Mar 15;83(6):2279-85
pubmed: 21344864
Nature. 2018 Aug;560(7718):382-386
pubmed: 30089911
Ann Oncol. 2018 Oct 1;29(Suppl 4):iv264-iv266
pubmed: 29917046
Genes Cancer. 2013 Jul;4(7-8):261-72
pubmed: 24167654
Nature. 2014 Nov 27;515(7528):563-7
pubmed: 25428504
BioDrugs. 2019 Apr;33(2):137-158
pubmed: 30810948
J Clin Oncol. 2019 Mar 1;37(7):537-546
pubmed: 30620668
JAMA Oncol. 2018 Apr 1;4(4):537-544
pubmed: 29423515
Mol Cancer Ther. 2015 Apr;14(4):847-56
pubmed: 25695955
N Engl J Med. 2015 Oct 22;373(17):1627-39
pubmed: 26412456
J Extracell Vesicles. 2020 Aug 26;9(1):1809765
pubmed: 32944195
Lancet. 2016 Apr 30;387(10030):1837-46
pubmed: 26970723
Clin Cancer Res. 2017 Aug 15;23(16):4843-4854
pubmed: 28400428
Sci Adv. 2018 Mar 07;4(3):eaar2766
pubmed: 29532035
J Lab Autom. 2016 Aug;21(4):533-47
pubmed: 26077162
Cytometry A. 2021 Apr;99(4):372-381
pubmed: 33448645
Semin Oncol. 2015 Jun;42(3):474-83
pubmed: 25965366
Lancet. 2019 May 4;393(10183):1819-1830
pubmed: 30955977
Lancet Oncol. 2015 Mar;16(3):257-65
pubmed: 25704439
Cell. 2019 Apr 4;177(2):414-427.e13
pubmed: 30951669

Auteurs

Fei Wu (F)

Fudan University Shanghai Cancer Center-Institut Mérieux Laboratory, Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China.
bioMérieux (Shanghai) Company Limited, Shanghai, China.

Yanzi Gu (Y)

Biobank, Fudan University Shanghai Cancer Center, Shanghai, China.

Bin Kang (B)

Fudan University Shanghai Cancer Center-Institut Mérieux Laboratory, Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China.
bioMérieux (Shanghai) Company Limited, Shanghai, China.

Fabienne Heskia (F)

Global Medical Affairs, bioMérieux SA, Marcy l'Etoile, France.

Alexandre Pachot (A)

Open Innovation & Partnerships Department, bioMérieux SA, Marcy l'Etoile, France.

Marc Bonneville (M)

Institut Mérieux, Lyon, France.

Ping Wei (P)

Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China.

Ji Liang (J)

Fudan University Shanghai Cancer Center-Institut Mérieux Laboratory, Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China.
bioMérieux (Shanghai) Company Limited, Shanghai, China.

Classifications MeSH