Distinct predictive biomarker candidates for response to anti-CTLA-4 and anti-PD-1 immunotherapy in melanoma patients

Abstract

BackgroundWhile immune checkpoint blockade has greatly improved clinical outcomes in diseases such as melanoma, there remains a need for predictive biomarkers to determine who will likely benefit most from which therapy. To date, most biomarkers of response have been identified in the tumors themselves. Biomarkers that could be assessed from peripheral blood would be even more desirable, because of ease of access and reproducibility of sampling.MethodsWe used mass cytometry (CyTOF) to comprehensively profile peripheral blood of melanoma patients, in order to find predictive biomarkers of response to anti-CTLA-4 or anti-PD-1 therapy. Using a panel of ~ 40 surface and intracellular markers, we performed in-depth phenotypic and functional immune profiling to identify potential predictive biomarker candidates.ResultsImmune profiling of baseline peripheral blood samples using CyTOF revealed that anti-CTLA-4 and anti-PD-1 therapies have distinct sets of candidate biomarkers. The distribution of CD4+ and CD8+ memory/non-memory cells and other memory subsets was different between responders and non-responders to anti-CTLA-4 therapy. In anti-PD-1 (but not anti-CTLA-4) treated patients, we discovered differences in CD69 and MIP-1β expressing NK cells between responders and non-responders. Finally, multivariate analysis was used to develop a model for the prediction of response.ConclusionsOur results indicate that anti-CTLA-4 and anti-PD-1 have distinct predictive biomarker candidates. CD4+ and CD8+ memory T cell subsets play an important role in response to anti-CTLA-4, and are potential biomarker candidates. For anti-PD-1 therapy, NK cell subsets (but not memory T cell subsets) correlated with clinical response to therapy. These functionally active NK cell subsets likely play a critical role in the anti-tumor response triggered by anti-PD-1.Electronic supplementary materialThe online version of this article (10.1186/s40425-018-0328-8) contains supplementary material, which is available to authorized users.

Beyond the message: advantages of snapshot proteomics with single‐cell mass cytometry in solid tumors

“…A key finding in this study was the identification of a specific subset of an activated, effector memory CD4 + T H 1 cell that conferred immunoprotection against tumors . However, the relationship between the presence of circulating effector memory CD4 + T cells and anti‐PD1 immunotherapy response in melanoma patients is debated: one found a lower frequency of these cells with response , another found increase of these cells correlated with response , and yet another claimed no correlation with response . T cells in melanoma patients who responded to anti‐PD1 immunotherapy demonstrated an upregulation of CTLA‐4 and CD69 .…”

Immune checkpoint inhibitors: The linchpins of modern immunotherapy

“…One area that remains understudied are the identification of specific biomarkers for CTLA‐4 therapy. Immune profiling by mass cytometry of peripheral blood melanoma patients demonstrated that non‐responders to anti‐PD‐1 had lower CD69 and MIP‐1β‐expressing NK cells, whereas CTLA‐4 responders had lower frequencies of CD45RA + cells in both CD4 + and CD8 + T cells, which did not correlate with PD‐1 inhibitor responses . CTLA‐4 methylation has been shown to inversely correlated with CTLA4 mRNA, with low‐methylated CTLA‐4 correlating with response to both anti‐PD‐1 and anti‐CTLA4 .…”

“…Immune profiling by mass cytometry of peripheral blood melanoma patients demonstrated that non-responders to anti-PD-1 had lower CD69 and MIP-1β-expressing NK cells, whereas CTLA-4 responders had lower frequencies of CD45RA + cells in both CD4 + and CD8 + T cells, which did not correlate with PD-1 inhibitor responses. 127 CTLA-4 methylation has been shown to inversely correlated with CTLA4 mRNA, with lowmethylated CTLA-4 correlating with response to both anti-PD-1 and anti-CTLA4. 15 High baseline serum biomarkers of excessive extracellular matrix remodeling and collagen breakdown products correlated with worse response to anti-CTLA-4 blockade with ipilimumab and shorter OS, perhaps reflecting worsened T-cell recruitment/infiltration and association with TGF-β activity.…”

Global immune fingerprinting in glioblastoma reveals immune-suppression signatures associated with prognosis

“…While RNA-seq provides new insights into the immune landscape of GBM, these analyses have been performed on bulk tumors and are thus not an ideal way to examine multiple immune cell lineages to determine the composition of the immune microenvironment. An emerging technology with the potential to shed light on the immune microenvironment of many cancers is mass cytometry time of flight (CyTOF) [33][34][35]. CyTOF can identify immune cell response and differentiation, which can not be performed by traditional techniques [29].…”

“…CyTOF can identify immune cell response and differentiation, which can not be performed by traditional techniques [29]. This approach is currently being used in multiple cancers to examine the immune landscape of tumors in order to identify how to best enhance the anti-tumor immune response [29,33,34]. Here, we use a combination of approaches including flow cytometry, immunofluorescence, and CyTOF to identify an immunosuppressive phenotype with increased MDSCs and reduced anti-tumoral response in GBM patients with a poor prognosis compared to low-grade glioma (LGG) patients and GBM patients with a good prognosis.…”