Author Identifier

James Freeman Orcid: https://orcid.org/0000-0001-8065-8416 Ashleigh McEvoy Orcid: https://orcid.org/0000-0001-5692-1317 Johnny Lo Orcid: https://orcid.org/0000-0003-1913-5354 Mel Ziman Orcid: https://orcid.org/0000-0001-7527-3538 Elin Gray Orcid: https://orcid.org/0000-0002-8613-3570

Document Type

Journal Article

Publication Title

The oncologist

ISSN

1549-490X

PubMed ID

31806779

Publisher

Wiley

School

School of Medical and Health Sciences / School of Engineering

RAS ID

30276

Grant Number

NHMRC : 1013349

Comments

Khattak, M. A., Reid, A., Freeman, J., Pereira, M., McEvoy, A., Lo, J., ... & Amanuel, B. (2019). PD-L1 Expression on Circulating Tumor Cells May Be Predictive of Response to Pembrolizumab in Advanced Melanoma: Results from a Pilot Study. The oncologist. Advance online publication.

https://doi.org/10.1634/theoncologist.2019-0557

Abstract

BACKGROUND: PD-1 inhibitors are routinely used for the treatment of advanced melanoma. This study sought to determine whether PD-L1 expression on circulating tumor cells (CTCs) can serve as a predictive biomarker of clinical benefit and response to treatment with the PD-1 inhibitor pembrolizumab.

METHODS: Blood samples were collected from patients with metastatic melanoma receiving pembrolizumab, prior to treatment and 6-12 weeks after initiation of therapy. Multiparametric flow cytometry was used to identify CTCs and evaluate the expression of PD-L1.

RESULTS: CTCs were detected in 25 of 40 patients (63%). Patients with detectable PD-L1

CONCLUSION: Our results reveal the potential of CTCs as a noninvasive real-time biopsy to evaluate PD-L1 expression in patients with melanoma. PD-L1 expression on CTCs may be predictive of response to pembrolizumab and longer PFS.

IMPLICATIONS FOR PRACTICE: The present data suggest that PD-L1 expression on circulating tumor cells may predict response to pembrolizumab in advanced melanoma. This needs further validation in a larger trial and, if proven, might be a useful liquid biopsy tool that could be used to stratify patients into groups more likely to respond to immunotherapy, hence leading to health cost savings.

DOI

10.1634/theoncologist.2019-0557

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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