Researchers from the Institute of Cancer Research (ICR) and University College London have developed a new and improved technique for reading genetic material in relation to the body’s immune response in cancer to study tissue samples that have been archived for decades.
The study could lead to a further understanding of how the immune system responds during the development, progression and treatment of cancer and could open up new approaches to detecting cancer progression and developing more effective treatments.
Published in the journal Cancer Research, with funding from the ICR and Cancer Research UK, researchers developed the FFPE-suitable Unique Molecular Identifier-based TCRseq (FUME-TCRseq) technique to produce huge numbers of copies of a small section of the T-cell receptor (TCR).
TCR is a protein present on the surface of white blood cells that can recognise foreign cells and cause the immune system to attack them, playing a key role in the immune system’s fight against the disease.
Currently, genetic sequencing is used to read TCRs in the immune system. However, current TCR sequencing methods have a low success rate using hospital tissue samples that have been preserved in formalin-fixed paraffin-embedded (FFPE), which degrades the genetic material, making it harder to read.
Using a sensitive lab technique known as polymerase chain reaction (PCR), researchers found that FUME-TCRseq outperformed the currently existing commercial methods for TCR sequencing.
Researchers are now seeking a collaborative partner to help develop the technique into a widely used tool for lab research working in immunology to benefit cancer research and people with cancer.
“We believe these often-disregarded archive samples in hospitals around the world could contain a treasure trove of knowledge that will help us in our mission to defeat cancer,” said professor Trevor Graham, director, Centre for Evolution and Cancer, ICR.
Dr Ann-Marie Baker, senior staff scientist, genomics and evolutionary dynamics group, ICR, said: “Using this technique, we can quantify and track specific T-cell populations through both time and space, seeing how they respond to treatment.
“What is most exciting is that it works really well on archival FFPE material, which a lot of existing methodologies do not.”