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Monitoring PD-1-Blocking Antibodies Bound to T Cells Derived from a Drop of Peripheral Blood
Published on: February 5, 2020
Circulating immune landscape in melanoma patients undergoing anti-PD1 therapy reveals key immune features according
Eleonora Sosa Cuevas1,2, Stéphane Mouret3, Guillaume Vayssière1,2
1Institute for Advanced Biosciences, Team: Epigenetics, Immunity, Metabolism, Cell Signaling & Cancer, Inserm U 1209, CNRS UMR, Université Grenoble Alpes, Grenoble, France.
Introduction:
Immune checkpoint blockers (ICB) bring unprecedented clinical success, yet many patients endure immune mediated adverse effects and/or fail to respond. Predictive signatures of response to ICB and mechanisms of clinical efficacy or failure remain understudied. DC subsets, in network with conventional αβ T (Tconv), NK, γδ T and iNKT cells, harbor pivotal roles in tumor control, yet their involvement in response to ICB remained underexplored.
Methods:
We performed an extensive longitudinal monitoring of circulating immune cells from melanoma patients treated with first-line anti-PD1, before (T0) and during treatment. We assessed the phenotypic and functional features of DC and effector cells' subsets by multi-parametric flow cytometry and ProcartaPlex® dosages.
Results:
We revealed differences according to response to treatment and modulations of patterns during treatment, highlighting a strong link between the immune landscape and the outcome of anti-PD1 therapy. Responders exhibited higher frequencies of circulating cDC1s, CD8+ T cells, and γδ2+ T cells in central memory (CM) stage. Notably, we observed a distinct remodeling of ICP expression profile, activation status and natural cytotoxicity receptor patterns of immune subsets during treatment. Anti-PD1 modulated DCs' functionality and triggered deep changes in the functional orientation of Tconv and γδT cells.
Discussion:
Overall, our work provides new insights into the immunological landscape sustaining favorable clinical responses or resistance to first-line anti-PD1 therapy in melanoma patients. Such exploration participates in uncovering the mechanism of action of anti-PD1, discovering innovative predictive signatures of response, and paves the way to design pertinent combination strategies to improve patient clinical benefits in the future.
Insights
This study reveals key immune cell differences in melanoma patients responding to anti-PD1 therapy. Understanding these immune signatures can improve treatment strategies for better patient outcomes.
Area of Science:
- Immunology
- Oncology
- Cancer Research
Background:
- Immune checkpoint blockers (ICB) show clinical success in cancer but patient response varies, with some experiencing adverse effects or treatment failure.
- Predictive signatures for ICB response and mechanisms of efficacy/failure are not fully understood.
- Dendritic cell (DC) subsets and their interactions with T cells are crucial for tumor control but their role in ICB response is underexplored.
Purpose of the Study:
- To longitudinally monitor circulating immune cells in melanoma patients receiving anti-PD1 therapy.
- To identify immune cell signatures associated with response or resistance to anti-PD1 therapy.
- To elucidate the impact of anti-PD1 on immune cell function and interactions.
Main Methods:
- Longitudinal monitoring of circulating immune cells before and during first-line anti-PD1 therapy in melanoma patients.
- Multi-parametric flow cytometry and ProcartaPlex® assays to assess phenotypic and functional features of DC and effector cell subsets.
- Analysis of immune cell frequencies, activation status, and cytokine profiles.
Main Results:
- Distinct immune cell profiles were observed between responders and non-responders to anti-PD1 therapy.
- Responders showed higher frequencies of circulating cDC1s, CD8+ T cells, and central memory γδ2+ T cells.
- Anti-PD1 treatment modulated DC functionality and altered the functional orientation of Tconv and γδT cells.
Conclusions:
- The study identifies immunological landscapes linked to favorable responses or resistance to anti-PD1 therapy in melanoma.
- Findings contribute to understanding anti-PD1 mechanisms of action and discovering predictive response signatures.
- This research may inform combination strategies to enhance clinical benefits for patients.
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