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Modelling of Immune Checkpoint Network Explains Synergistic Effects of Combined Immune Checkpoint Inhibitor Therapy and the Impact of Cytokines in Patient Response.

ABSTRACT: After the success of the new generation of immune therapies, immune checkpoint receptors have become one important center of attention of molecular oncologists. The initial success and hopes of anti-programmed cell death protein 1 (anti-PD1) and anti-cytotoxic T-lymphocyte-associated protein 4 (anti-CTLA4) therapies have shown some limitations since a majority of patients have continued to show resistance. Other immune checkpoints have raised some interest and are under investigation, such as T cell immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibition motif) domain (TIGIT), inducible T-cell costimulator (ICOS), and T cell immunoglobulin and mucin domain-containing protein 3 (TIM3), which appear as promising targets for immunotherapy. To explore their role and study possible synergetic effects of these different checkpoints, we have built a model of T cell receptor (TCR) regulation including not only PD1 and CTLA4, but also other well studied checkpoints (TIGIT, TIM3, lymphocyte activation gene 3 (LAG3), cluster of differentiation 226 (CD226), ICOS, and tumour necrosis factor receptors (TNFRs)) and simulated different aspects of T cell biology. Our model shows good correspondence with observations from available experimental studies of anti-PD1 and anti-CTLA4 therapies and suggest efficient combinations of immune checkpoint inhibitors (ICI). Among the possible candidates, TIGIT appears to be the most promising drug target in our model. The model predicts that signal transducer and activator of transcription 1 (STAT1)/STAT4-dependent pathways, activated by cytokines such as interleukin 12 (IL12) and interferon gamma (IFNG), could improve the effect of ICI therapy via upregulation of Tbet, suggesting that the effect of the cytokines related to STAT3/STAT1 activity is dependent on the balance between STAT1 and STAT3 downstream signalling.

SUBMITTER: Kondratova M

PROVIDER: S-EPMC7761568 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Modelling of Immune Checkpoint Network Explains Synergistic Effects of Combined Immune Checkpoint Inhibitor Therapy and the Impact of Cytokines in Patient Response.

Kondratova Maria M Barillot Emmanuel E Zinovyev Andrei A Calzone Laurence L

Cancers 20201202 12

After the success of the new generation of immune therapies, immune checkpoint receptors have become one important center of attention of molecular oncologists. The initial success and hopes of anti-programmed cell death protein 1 (anti-PD1) and anti-cytotoxic T-lymphocyte-associated protein 4 (anti-CTLA4) therapies have shown some limitations since a majority of patients have continued to show resistance. Other immune checkpoints have raised some interest and are under investigation, such as T ...[more]

PMID: 33276543

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Project description:BACKGROUND:Pneumonitis from immune checkpoint inhibitors (ICI) is a potentially fatal immune-related adverse event (irAE) from antiprogrammed death 1/programmed death ligand 1 immunotherapy. Most cases of ICI pneumonitis improve or resolve with 4-6 weeks of corticosteroid therapy. Herein, we report the incidence, clinicopathological features and management of patients with non-small cell lung cancer (NSCLC) and melanoma who developed chronic ICI pneumonitis that warrants ?12 weeks of immunosuppression. METHODS:Patients with ICI pneumonitis were identified from institutional databases of ICI-treated patients with advanced melanoma and NSCLC between January 2011 and July 2018. ICI pneumonitis was defined as clinical/radiographic evidence of lung inflammation without alternative diagnoses, adjudicated by a multidisciplinary team. Chronic ICI pneumonitis was defined as pneumonitis that persists or worsens with steroid tapering, and necessitates ?12 weeks of immunosuppression, after ICI discontinuation. Serial chest CT was used to assess radiological features, and tumor response by Response EvaluationCriteria for Solid Tumors V.1.1. Bronchoalveolar lavage fluid (BALF) samples were assessed by cell differential. Lung biopsy samples were evaluated by H&E staining and multiplex immunofluorescence (mIF), where available. RESULTS:Among 299 patients, 44 developed ICI pneumonitis (NSCLC: 5/205; melanoma: 1/94), and of these, 6 experienced chronic ICI pneumonitis. The overall incidence of chronic ICI pneumonitis was thus 2%. Of those who developed chronic ICI pneumonitis: the majority had NSCLC (5/6), all sustained disease control from ICIs, and none had other concurrent irAEs. Timing of chronic ICI pneumonitis development was variable (range: 0-50 months), and occurred at a median of 12 months post ICI start. Recrudescence of ICI pneumonitis occurred at a median of 6 weeks after initial steroid start (range: 3-12 weeks), with all patients requiring steroid reintroduction when tapered to ?10 mg prednisone/equivalent. The median total duration of steroids was 37 weeks (range: 16-43+weeks). Re-emergence of radiographic ICI pneumonitis occurred in the same locations on chest CT, in most cases (5/6). All patients who developed chronic ICI pneumonitis had BALF lymphocytosis on cell differential and organising pneumonia on lung biopsy at initial ICI pneumonitis presentation, with persistent BALF lymphocytosis and brisk CD8+ infiltration on mIF at pneumonitis re-emergence during steroid taper. CONCLUSIONS:A subset of patients who develop pneumonitis from ICIs will develop chronic ICI pneumonitis, that warrants long-term immunosuppression of ?12 weeks, and has distinct clinicopathological features.

Project description:Immune checkpoint inhibitors (ICIs) have shown clinical benefit in solid tumors, with modest rates of clinical response. Hence, improved therapeutic approaches need to be investigated. Herein, we assessed a combination of chidamide plus celecoxib (called CC-01) combined with programmed cell death protein 1 (PD-1) blockade in a CT26 model as potent tumor microenvironment (TME) regulator. The antitumor activity was assessed by measuring tumor size, overall response rate, and survival rate. Immune profiling of tumor-infiltrating lymphocytes was performed by flow cytometry. Tumor tissues were assessed by chip assay to predict the possible pathway. Tumor size was significantly reduced in mice treated with CC-01 combined with or without anti-PD-1 antibody, however the triple combination therapy consistently demonstrated that it significantly increased both the ORR and survival rate in term of clinical applications. In the combination group, immune landscape profiling revealed decreased populations of immunosuppressive regulatory T cells, myeloid-derived suppressor cells, and tumor-associated macrophages. Analysis of the mouse tumor chip data using Gene Ontology enrichment analysis of biological processes revealed that the triple combination upregulated genes associated with responses to interferon-gamma. Our results demonstrated that CC-01 possessed potent TME regulatory properties, augmenting the antitumor effect when combined with ICIs. This antitumor effect was achieved by altering the immune landscape in TILs (tumor-infiltrating lymphocytes) and was associated with immune cell activation in the TME. Furthermore, CC-01 demonstrated potent anticancer immune response activity, mainly reducing the number and function of several immunosuppressive cells. The combination of CC-01 with an ICI will further enhance the anticancer effect and boost the immune response rate. Collectively, our results support the clinical evaluation of CC-01 in combination with ICIs in several advanced cancers.

Dataset Information

Modelling of Immune Checkpoint Network Explains Synergistic Effects of Combined Immune Checkpoint Inhibitor Therapy and the Impact of Cytokines in Patient Response.

Publications

Modelling of Immune Checkpoint Network Explains Synergistic Effects of Combined Immune Checkpoint Inhibitor Therapy and the Impact of Cytokines in Patient Response.

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