New model could improve vaccine, immunotherapy design

By Samantha Black, PhD, The Science Advisory Board editor in chief

October 28, 2020 -- A new model used to predict the outcomes of pathogen detection systems as a function of innate immunity may lead to more effective cancer immunotherapies and vaccines against existing and novel pathogens, according to results published in Cell Systems on October 27.

The human body responds to combinations of multiple signals to counteract pathogens such as bacteria or viruses. Molecular signals derived from pathogens are largely processed by pattern recognition receptors (PRRs) of the innate immune system.

Most of these pathways are studied one at a time, even though there are many examples of synergy, independence, and antagonism between various pathogen-sensing pathways. The higher-order effects of microbial inputs on pathogen sensing pathways and the downstream immune responses have not been systematically analyzed.

Researchers from the Pritzker School of Molecular Engineering (PME) at the University of Chicago sought to study combinations of microbial signals underlying innate immune sensing. They examined the effects of singles, pairs, and triplets of input signals to determine the combinatorial logic governing microbial sensing by the immune system.

Understanding signal combinations of microbial sensing

First, researchers measured the effects of a representative set of seven microbial stimuli and all corresponding pairwise (21) and triplet (35) combinations on T-cell responses using dendritic cell (DC)-T-cell cocultures in vitro. Importantly, DCs act as messengers between the innate and adaptive immune systems, which present antigens to naïve T cells to initiate adaptive immune responses.

The data revealed that the effects of triplet combinations of microbial signals can be accurately predicted with data from the effects of singles and pairs of stimuli. The innate immune system permits pairwise interactions between pathways, but all but eliminates higher-order interactions. By removing higher-order interactions, the pathogen-sensing system may increase its ability to reliably perform its function, according to the authors.

Moreover, the researchers found that the behavior of activated T cells, which came into contact with DCs processing combinatorial stimuli, are useful to predict higher-order triplet effects from singles and pairs. This indicates that singles and pairs of signals dictate the information signaled by triplets in mouse and human DCs at the transcriptional, chromatin, and protein secretion levels.

"It could have been infinitely complex, but it's not," said author Nicolas Chevrier, PhD, assistant professor at the University of Chicago, in a statement. "We are the first to show you can predict higher-order effects across immune pathways with very simple models."

Using the simplified model of microbial sensing to improve therapies and vaccines

The simplified analysis of pathogen sensing pathways was applied to cell cocultures in vitro and cell-based immunotherapies in mouse models of cancer. The researchers demonstrated with an in vivo mouse model that DC-based vaccines prepared with triplet combinations of adjuvants (substances that improve immune responses to antigens) can induce potent anti-tumor responses. The triplet adjuvant responses can be largely explained by pairwise and single adjuvant effects.

While DC-based vaccines have shown only limited efficacy in the past, the team suggested that improved formulations that consider combinations of adjuvants could improve the use of the cell-based immunotherapies in the future.

Overall, the findings add to the fundamental understanding of how the innate immune system processes complex information which can go on to inform rational drug design.

"Now that we can predict the effects of multiple adjuvants with little data and a simple model, we need to extend this knowledge to the design of vaccines against both new and old threats," Chevrier said.

Do you have a unique perspective on your research related to immunology or molecular biology? Contact the editor today to learn more.

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