A landmark national study, led by Genomics England, NHS England, Queen Mary University of London and the University of Westminster, has demonstrated that linking both clinical and whole genome sequencing (WGS) data together can support the delivery of cancer diagnosis and treatment tailored to the individual.

The Largest Study of its Kind

The research, published in Nature Medicine here, revealed that linking WGS data to real-world clinical data can identify changes in cancer DNA that could be relevant for an individual patient’s care, helping identify what treatment might work best for them.

More than 13,000 participants with cancer were involved in the 100,000 Genomes Project, and 30 plus solid tumour types were analysed, alongside routine clinical data collected from participants over a 5-year period. This information, which included details such as hospital visits and the type of treatment received, allowed scientists to see specific genetic changes in the cancer associated with better or worse survival rates and improved patient outcomes.

For example, over 90% of brain tumours and more than 50% of colon and lung cancers showed genetic changes that could affect how patients were treated, guiding decisions about surgery or specific treatments they might need.

Precision Medicine & Tailored Treatments

Professor Alastair Greystoke, Clinical Director (Cancer) NEY GMS commented:

“This paper highlights the importance of precision medicine in treating patients with cancer, and represents a huge amount of work, implementing routine whole genome sequencing within the NHS. This is now routinely available for a number of indications, including paediatric tumours, leukaemia, sarcomas, and in patients who have run out of standard treatment options.

We continue to work within the GMS to determine how these advanced technologies can best be implemented into clinical care to help patients and clinicians get the best possible outcomes from treatment.”

Together, the findings show the value of combining genomic and clinical data at scale to help healthcare professionals make the best treatment decisions with their patients.