PD-1 checkpoint blockade in advanced melanoma patients: NK cells, monocytic subsets and host PD-L1 expression as predictive biomarker candidates.
Blockade of the PD-1 receptor has revolutionized the treatment of metastatic melanoma, with significant increases in overall survival (OS) and a dramatic improvement in patient quality of life. Despite the success of this approach, the number of benefitting patients is limited and there is a need for predictive biomarkers as well as a deeper mechanistic analysis of the cellular populations involved in clinical responses. With the aim to find predictive biomarkers for PD-1 checkpoint blockade, an in-depth immune monitoring study was conducted in 36 advanced melanoma patients receiving pembrolizumab or nivolumab treatment at Karolinska University Hospital. Blood samples were collected before treatment and before administration of the second and fourth doses. Peripheral blood mononuclear cells were isolated and stained for flow cytometric analysis within 2 h of sample collection. Overall survival and progression-free survival (PFS) were inversely correlated with CD69 expression NK cells. In the myeloid compartment, high frequencies of non-classical monocytes and low frequencies of monocytic myeloid derived suppressor cells (MoMDSCs) correlated with response rates and OS. A deeper characterization of monocytic subsets showed that PD-L1 expression in MDSCs, non-classical and intermediate monocytes was significantly increased in patients with shorter PFS in addition to correlating inversely with OS. Our results suggest that cellular populations other than T cells can be critical in the outcome of PD-1 blockade treatment. Specifically, the frequencies of activated NK cells and monocytic subsets are inversely correlated with survival and clinical benefit, suggesting that their role as predictive biomarkers should be further evaluated.
|Authors:||Pico de Coaña Y, Wolodarski M, van der Haar Àvila I, Nakajima T, Rentouli S, Lundqvist A, Masucci G, Hansson J, Kiessling R,|
|Journal:||Oncoimmunology; 2020 Aug 28 ; 9 (1) 1786888. doi:10.1080/2162402X.2020.1786888|
|PubMed:||PMID: 32939320 (Go to PubMed)|