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

Simple Summary

The future of cancer immunotherapy relies on a combination of individually targeted therapies. However, a lot of experiments are needed to define the most effective combinations of drugs. A computational and modelling approach could help reduce the number of experiments and suggest optimal treatments to test. This article presents a logical model of T cell activation influenced by immune checkpoints, and explores the effect of these checkpoints, suggests mechanisms that would explain why some treatments might be better suited than others. The model includes not only programmed cell death protein 1 (PD1) and cytotoxic T-lymphocyte-associated protein 4 (CTL4) downstream pathways but also those of other immune checkpoints such as T cell immunoglobulin and ITIM (immunoreceptor tyrosine-based inhibition motif) domain (TIGIT), lymphocyte activation gene 3 (LAG3), T cell immunoglobulin and mucin domain-containing protein 3 (TIM3), cluster of differentiation 226 (CD226), inducible T-cell costimulator (ICOS), and tumour necrosis factor receptors (TNFRs).

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.

An exploration of lifestyle/obesity programmes for adults with intellectual disabilities through a realist lens: Impact of a 'context, mechanism and outcome' evaluation

BACKGROUND

Obesity is higher in people with intellectual disabilities.

AIMS

There are two aims of this explorative paper. Firstly, using a realist lens, to go beyond 'what works' and examine the 'context, mechanisms and outcomes' (CMO) of lifestyle/obesity programmes for this population. Second, using a logic model framework to inform how these programmes could be implemented within practice.

METHOD

We explored six-review papers and the individual lifestyle/obesity programmes that these papers reviewed using the CMO framework.

RESULTS

There were few theoretically underpinned, multi-component programmes that were effective in the short to long-term and many failed to explore the 'context and mechanisms'. We developed a logic model and engaged in two co-production workshops to refine this model.

DISCUSSION

Using a realist approach, programmes need to be underpinned by both individual and systems change theories, be multi-component, have a closer understanding of the interplay of the 'context and mechanisms', and co-designed using a logic model framework.

Integrating Patient-Specific Information into Logic Models of Complex Diseases: Application to Acute Myeloid Leukemia

High throughput technologies such as deep sequencing and proteomics are increasingly becoming mainstream in clinical practice and support diagnosis and patient stratification. Developing computational models that recapitulate cell physiology and its perturbations in disease is a required step to help with the interpretation of results of high content experiments and to devise personalized treatments. As complete cell-models are difficult to achieve, given limited experimental information and insurmountable computational problems, approximate approaches should be considered. We present here a general approach to modeling complex diseases by embedding patient-specific genomics data into actionable logic models that take into account prior knowledge. We apply the strategy to acute myeloid leukemia (AML) and assemble a network of logical relationships linking most of the genes that are found frequently mutated in AML patients. We derive Boolean models from this network and we show that by priming the model with genomic data we can infer relevant patient-specific clinical features. Here we propose that the integration of literature-derived causal networks with patient-specific data should be explored to help bedside decisions.

Logic modelling as hermeneutic praxis: Bringing knowledge systems into view during comprehensive primary health care planning for homelessness in Australia

Logic modelling is used widely in health promotion planning for complex health and social problems. It is often undertaken collaboratively with stakeholders across sectors that hold and enact different institutional approaches. We use hermeneutic philosophy to explore how knowledge is 'lived' by - and unfolds differently for - cross-sectoral stakeholders during comprehensive primary healthcare service planning. An Organisational Action Research partnership was established with a non-government organisation designing comprehensive primary health care for individuals experiencing homelessness in Adelaide, Australia. Grey literature, stakeholder input, academic feedback, a targeted literature review and evidence synthesis were integrated in iterative cycles to inform and refine the logic model. Diverse knowledge systems are active when cross-sectoral stakeholders collaborate on logic models for comprehensive primary health care planning. Considering logic modelling as a hermeneutic praxis helps to foreground and explore these differences. In our case, divergent ideas emerged in how health/wellbeing and trust were conceptualised; language had different meanings across sectors; and the outcomes and data sought were nuanced for various collaborators. We explicate these methodological insights and also contribute our evidence-informed, collaboratively-derived model for design of a comprehensive primary health care service with populations experiencing homelessness. We outline the value of considering cross-sectoral logic modelling as hermeneutic praxis. Engaging with points of difference in cross-sectoral knowledge systems can strengthen logic modelling processes, partnerships and potential outcomes for complex and comprehensive primary health care services.