Completed Infection & Immunity Cancer

Human Natural Killer cell-related receptors: diversity, ligands and disease susceptibility.

In plain English

AI plain-English summary

Natural killer cells patrol the body like security guards, using surface proteins to spot cells that have been hijacked by viruses or turned cancerous. This research programme will map the genetic variations in those proteins across different people, and identify the specific molecules on infected or cancerous cells that the proteins latch onto. The problem is that not everyone responds to infections or tumours in the same way. Some people are more susceptible to certain diseases, and the immune system’s first line of defence—natural killer cells—may hold the key to why. Currently, scientists do not fully understand how variations in these surface proteins affect a person’s ability to recognise threats. If this research succeeds, it could explain why some individuals are prone to particular viral infections or cancers. That knowledge might eventually help doctors predict disease risk or design therapies that boost natural killer cell activity. For now, the work is fundamental science: it aims to answer a basic question about how the immune system distinguishes friend from foe. Past discoveries about immune receptors have led to breakthroughs in immunotherapy, so a deeper understanding of these proteins could open unexpected doors.

View original technical description
Natural killer cells provide defence for your body against viruses and tumours. These cells have proteins on their surfaces, which allow them to detect cells that are infected or cancerous. This programme of research will examine these proteins in detail. We will find out how they differ between different people as this may help to understand why some people are susceptible to certain diseases. We also determine what the proteins are interacting with, in other words, their target molecules. This will help to understand how an infected or cancerous cell is recognised by the immune system.

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Researchers

John Trowsdale (Principal Investigator)

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Original classification

Research Grant

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