The Tumor Microenvironment in the Response to Immune Checkpoint Blockade Therapies

Petitprez, Florent; Meylan, Maxime; Reyniès, Aurélien de; Sautès-Fridman, Catheriné; Fridman, Wolf Herman

doi:10.3389/fimmu.2020.00784

Cited by 432 publications

(363 citation statements)

References 143 publications

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“…It is becoming more and more evident that multiple immune cell subsets in a concerted action may help for selecting patients that are likely to respond to ICI. 38 We identified that increasing amounts of neutrophils in the peripheral blood of patients with cancer were associated Open access with less benefit from ICI treatment. Neutrophils have been reported to support for example the development of metastasis through multiple mechanisms, such as the release of proteases that degrade antitumor factors, and leukotrienes that propagate metastasis-initiating cells.…”

Section: Discussionmentioning

confidence: 98%

Prospective development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with recurrent/metastatic cancer to immune checkpoint inhibitors

Zhou

Donaubauer²,

Frey³

et al. 2021

J Immunother Cancer

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BackgroundThe predictive power of novel biological markers for treatment response to immune checkpoint inhibitors (ICI) is still not satisfactory for the majority of patients with cancer. One should identify valid predictive markers in the peripheral blood, as this is easily available before and during treatment. The current interim analysis of patients of the ST-ICI cohort therefore focuses on the development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with metastatic cancer to ICI targeting the programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) axis.MethodsA total of 104 patients were prospectively enrolled. 54 immune cell subsets were prospectively analyzed in patients’ peripheral blood by multicolor flow cytometry before treatment with ICI (pre-ICI; n=89), and after the first application of ICI (n=65). Pre-ICI, patients were randomly allocated to a training (n=56) and a validation cohort (n=33). Univariate Cox proportional hazards regression analysis and least absolute shrinkage and selection operator Cox model were used to create a predictive immune signature, which was also checked after the first ICI, to consider the dynamics of changes in the immune status.ResultsWhole blood samples were provided by 89 patients pre-ICI and by 65 patients after the first ICI. We identified a LIPS which is based on five immune cell subtypes: CD14high monocytes, CD8+/PD-1+ T cells, plasmacytoid dendritic cells, neutrophils, and CD3+/CD56+/CD16+ natural killer (NK)T cells. The signature achieved a high accuracy (C-index 0.74 vs 0.71) for predicting overall survival (OS) benefit in both the training and the validation cohort. In both cohorts, the low-risk group had significantly longer OS than the high-risk group (HR 0.26, 95% CI 0.12 to 0.56, p=0.00025; HR 0.30, 95% CI 0.10 to 0.91, p=0.024, respectively). Regarding the whole cohort, LIPS also predicted progression-free survival (PFS). The identified LIPS was not affected by clinicopathological features with the exception of brain metastases. NKT cells and neutrophils of the LIPS can be used as dynamic predictive biomarkers for OS and PFS after first administration of the ICI.ConclusionOur study identified a predictive LIPS for survival of patients with cancer treated with PD-1/PD-L1 ICI, which is based on immune cell subsets in the peripheral whole blood.Trial registration numberNCT03453892.

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Section: Discussionmentioning

confidence: 98%

Prospective development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with recurrent/metastatic cancer to immune checkpoint inhibitors

Zhou

Donaubauer²,

Frey³

et al. 2021

J Immunother Cancer

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“…The distinction between hot, altered (excluded and immunosuppressed) and cold tumors, based on the cytotoxic T cell landscape within a tumor, establishes the important role of the TME but only a thorough profiling of the TME can analyze the complexity of the tumors and provide dynamic information about the complex networks operating in the TME to guide clinical decisions (7,8). Combining immune and genomic data has revealed six immune subtypes across 33 different cancer types including immune (macrophage or lymphocyte signatures, Th1:Th2 cell ratio, expression of immunomodulatory genes) and non-immune parameters (intratumoral heterogeneity, aneuploidy, neoantigen load, overall cell proliferation, and patients' prognosis) (9).…”

Section: Characterizing the Immune Function In The Response To Checkpmentioning

confidence: 99%

Therapy-Induced Modulation of the Tumor Microenvironment: New Opportunities for Cancer Therapies

et al. 2020

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Advances in immunotherapy have achieved remarkable clinical outcomes in tumors with low curability, but their effects are limited, and increasing evidence has implicated tumoral and non-tumoral components of the tumor microenvironment as critical mediators of cancer progression. At the same time, the clinical successes achieved with minimally invasive and optically-guided surgery and image-guided and ablative radiation strategies have been successfully implemented in clinical care. More effective, localized and safer treatments have fueled strong research interest in radioimmunotherapy, which has shown the potential immunomodulatory effects of ionizing radiation. However, increasingly more observations suggest that immunosuppressive changes, metabolic remodeling, and angiogenic responses in the local tumor microenvironment play a central role in tumor recurrence. In this review, we address challenges to identify responders vs. non-responders to the immune checkpoint blockade, discuss recent developments in combinations of immunotherapy and radiotherapy for clinical evaluation, and consider the clinical impact of immunosuppressive changes in the tumor microenvironment in the context of surgery and radiation. Since the therapy-induced modulation of the tumor microenvironment presents a multiplicity of forms, we propose that overcoming microenvironment related resistance can become clinically relevant and represents a novel strategy to optimize treatment immunogenicity and improve patient outcome.

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“…Anti-tumoral, innate immune cells, such as dendritic cells, link the innate and adaptive immune response through antigen presentation, priming of T cells, and cytokine secretion. Furthermore, an effective adaptive immune response to immunotherapy treatments such as immune checkpoint blockade is often dictated by how tumor innate immunity shapes the immune microenvironment ( Petitprez et al., 2020 ). Macrophages are particularly relevant due to their plasticity that results in polarization into phenotypes that tend to be pro-tumoral (M2) or anti-tumoral (M1), as well as their ability to guide other processes pertinent to the TME, such as angiogenesis, fibrosis, and inflammation ( Long and Beatty, 2013 ).…”

Section: Introduction: the Intersection Of Immune Cells Cancer Andmentioning

confidence: 99%

Engineering approaches for studying immune-tumor cell interactions and immunotherapy

et al. 2021

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The Tumor Microenvironment in the Response to Immune Checkpoint Blockade Therapies

Cited by 432 publications

References 143 publications

Prospective development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with recurrent/metastatic cancer to immune checkpoint inhibitors

Prospective development and validation of a liquid immune profile-based signature (LIPS) to predict response of patients with recurrent/metastatic cancer to immune checkpoint inhibitors

Therapy-Induced Modulation of the Tumor Microenvironment: New Opportunities for Cancer Therapies

Engineering approaches for studying immune-tumor cell interactions and immunotherapy

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