How a tumour's genetics influences the cancer-immune setpoint
In the first of two posts exploring the different types of factors that can influence a person’s cancer-immune profile, we look more closely at tumour genetics.
As I explored in my previous post, depending on what step in the cancer-immunity cycle is impacted, it’s possible to group cancer-immune phenotypes into three broad categories: immune-desert tumours, immune-excluded tumours, and inflamed tumours.
Expanding on this in their seminal review, Chen & Mellman then went on to collate the factors identified so far that can influence an individual’s cancer-immune setpoint. They grouped these according to their type – tumour genetics, host genetics, the microbiome, the environment and therapeutic agents.
Delving deeper into a tumour’s genetics and epigenetics, they discussed the following themes about how these can influence the cancer-immune setpoint:
- The higher the mutational burden of a tumour increases the probability that some will be immunogenic, providing targets for T-cell attack.
- Truncal mutations, which arise early on in a tumour’s evolution, are more widely shared throughout the cancer cell population. So they may generate better T-cell responses than branch mutations that are limited to fewer cancer cells.
- Although most mutations may promote T-cell mediated immunity, some (especially cancer-associated driver mutations) may act to dampen immune responses.
- Tumours can selectively increase, through amplification or increased transcription, the expression of genes that encode proteins associated with immunosuppression.
- Epigenetic modifications and expression of microRNAs that lead to changes in gene expression probably contribute directly to the cancer-immune microenvironment and tumour immunogenicity.
- Another influence on the cancer-immune profile is the tissue where a tumour originates, as gene expression patterns of a particular cell or tissue type involves epigenetic mechanisms.
You can explore all of the factors that have been proposed so far on our interactive framework. But it needs to continually evolve as new data are published.
Chen & Mellman state in their review, “It should be noted that this representation is only a partial list and that factors will be added, removed or modified in the future.”
We want to accelerate its evolution through a crowdsourcing of ideas from the community. But this requires your help. Please go to the framework to add or comment on existing factors – or suggest new ones.
To help get you started, please follow our a simple step-by-step guide in our ‘how to’ post.