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T-cell activation

Immune checkpoints

Summary: 

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.

Curation
Submitter: 
Aurelien Naldi

T cells response to CTLA4 and PD-1 checkpoint inhibitors

Summary: 

This comprehensive model integrates the available data on T cell activation, taking into account CTLA4 and PD-1 checkpoint inhibitory pathways. It encompasses 216 components and 451 regulatory arcs.

To ease the verification of the behaviour of this large logical model, we have designed a modular approach based on a unit testing framework used in software development. Furthermore, to compare the respective impact of the activation of the two checkpoints, we have designed a value propagation technique enabling the analytical computation of all the nodes frozen following the persisting activation or inhibition of any model component. The model verification approach greatly eased the delineation of logical rules complying with predefined dynamical specifications, while the use of the value propagation technique provided interesting insights into the differential potential of CTLA4 and PD-1 immunotherapies.

All our analyses have been implemented into two python notebooks, enabling their reproduction or extension with the most recent version of the CoLoMoTo Docker image (http://www.colomoto.org/notebook).

Preview the unit testing notebook

Preview the value propagation analysis notebook

Curation
Submitter: 
Aurelien Naldi

Contribution of ROS and metabolic status to neonatal and adult CD8+ T cell activation

Summary: 

The low response to infection in neonatal T cells contributes to a high incidence of morbidity and mortality. Here we evaluated the effect of the cytoplasmic and mitochondrial levels of Reactive Oxygen Species (ROS) of neonatal CD8+T cells on their low activation. This model captures the interplay between antigen recognition with ROS and metabolic status in T cell responses. This model displays alternative stable states, which corresponds to different cell fates, i.e. quiescent, activated and anergic, depending on ROS status.

The associated notebook can be loaded using the CoLoMoTo notebook docker image (see http://www.colomoto.org/notebook).

Curation
Submitter: 
Aurelien Naldi

TCR and TLR5 merged Boolean model

Summary: 

CD4+ T cells recognize antigens through their T cell receptors TCR). However, additional signals involving co-stimulatory receptors, for example CD28, are required for proper T cell activation. Alternative co-stimulatory receptors have been proposed, including members of the Toll-like receptor family, such as TLR5 and TLR2.

We report here three Boolean models for:
- the T cell receptor (TCR) signalling pathway;
- the Toll-like receptor (TLR5) signalling pathway;
- the combination of TCR and TLR5 pathway, taking into accounting cross-interactions.

These models were validated by analysing the responses of T cells to the activation of these pathways alone or in combination, in terms of CREB, c-Jun and p65 activation.
The resulting merged model accurately reproduces the experimental results, showing that the activation of TLR5 can play a similar role to that of CD28, regarding AP-1, CREB and NF-кB activation, thereby, providing insights regarding the cross-regulation of these pathways in CD4+ T cells.

Curation
Submitter: 
Pedro Monteiro
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