This Cambridge Life

This Cambridge Life

The doctor turned detective investigating the imprints of cancer

Serena Nik-Zainal outside the Addenbrooke’s Treatment Centre

Self-confessed ‘nerd’ Serena Nik-Zainal went from hospital wards to the laboratory on a mission to provide patients with the best possible treatment for their illnesses. Ten years later she is at the forefront of genomic research, creating tools for clinicians which are transforming patient care.

I’m a doctor by training; I’d always wanted to be one. I specialised in genetics and dealt with kids with inherited rare disorders. To make a diagnosis I’d often be trying to identify the genetic mutation that caused the presenting symptoms.

‘Reading’ DNA by genomic sequencing was possible but the limitation, at the time, was how expensive it was to do this. It cost thousands of pounds to sequence one little piece of the genome.

As a public sector service there was not enough money to sequence every patient. I found myself in meetings deciding who would be allowed the procedure and who wouldn’t. I found it so hard to be part of this gatekeeping exercise.

Later a technology called Next Generation Sequencing (NGS), pioneered in Cambridge, came along that allowed the whole genome to be sequenced faster than ever before. I knew this would have an impact on my work; I decided to do a PhD so I could understand how to use NGS and was offered a place at the Sanger Institute.

For my research I sequenced the whole genome of 21 breast cancers. At the time it took three months to sequence each one (now it can be done in a day which is fabulous!).

It was astonishing that sequencing as few as 21 cancers resulted in the identification of hundreds and thousands of mutations. Most of these mutations are known as passenger mutations (as opposed to driver mutations that cause cancer).

For decades research had focused on driver mutations rather than passenger mutations which I’d once heard described as “just noise”. I remember thinking: all these mutations can’t just be random. Of course, there is randomness in life, but different factors help mould you in one way or another.

This instinct proved to be correct. I found that the patterns of passenger mutations – called signatures – showed imprints of the damage and repair processes that had occurred in the DNA as the tumour developed. Some of these signatures may be seen across different tumours, whereas others are rare.

Imprints offer clues as to how the cancer arose, what specific type it is and how best to treat it. I often describe the imprints like fingerprints left at a crime scene or footprints in the sand.

 Serena Nik-Zainal using pipette in laboratory
Serena Nik-Zainal talking to colleague in laboratory
 Serena Nik-Zainal running experiments in laboratory
Serena Nik-Zainal using microscope in laboratory
Serena Nik-Zainal talking to colleague in laboratory

 

What struck me from day one was the realisation that each tumour was so different, and yet was being treated in the same way. I wanted the insights from genome sequencing to reach patients as fast as possible so that they could receive personalised treatment, giving them the best chance of surviving their cancer.

For me, it’s always been about the clinical applications. My team and I are involved in developing tools using machine learning that can interpret the results of genome sequencing quickly and efficiently so that clinicians can use them in their diagnosis and treatment of patients.

An important part of the cancer genomics journey is global collaboration. Over the past decade whole-genome sequencing has been conducted all over the world. This anonymised data has been deposited in the public domain and made available for scientists to analyse.

There is so much data; we are like kids in a candy shop! We hope the results will lead to better cancer treatment. That’s what’s keeping us going, the feeling that we’re contributing back to society.

Serena Nik-Zainal outside the Addenbrooke’s Treatment Centre

The UK is in an unprecedented position. Genomics England has led world-leading initiatives like the 100,000 Genome Project that involved sequencing the genome of 85,000 NHS patients affected by rare disease or cancer. There’s also nowhere else in the world that patients can freely access genomics services at the scale as people in England and Wales can.

However, the time taken from genomic discovery to clinical application in cancer care is 10-15 years − it’s just too long. Of course, we need to do clinical trials to prove that genomic information has an impact on cancer patient care, but perhaps how we do those trials could be modernised. We could evolve how we think about genomic data and use all the data available as effectively as possible, to truly personalise treatment plans. We need to consider what could be done to speed up this process.

I recently attended a World Health Organisation (WHO) expert panel discussion about genomics going global. I feel strongly that genomics should be democratised and accessible to people in low-and-middle income countries (LMIC) like Malaysia, where I’m from. Although I’m aware that adaptions would need to be made to meet each countries’ unique requirements.

I started off as a ‘nerd’ looking at genomes and then bioinformatics, and now I’m discussing transformations in the way we diagnose and treat patients. I’d like to reach the stage where cancer patients, not just in the UK, are offered whole or partial genomic sequencing just like they might have a routine blood testImagine the progress! We’ll be able to offer people the best possible care right from the outset.

Serena is Professor of Genomic Medicine and Bioinformatics in the Department of Medical Genetics, University of Cambridge and Honorary Consultant in Clinical Genetics at the Cambridge University Hospitals NHS Trust. Serena Nik-Zainal is an alumna and Honorary Fellow of Murray Edwards. In 2019, she was awarded the Dr Josef Steiner Cancer Research Prize.

Published 15 August 2022
With thanks to:

Serena Nik-Zainal

Words:
Charis Goodyear

Photography:
Lloyd Mann

The text in this work is licensed under a Creative Commons Attribution 4.0 International License

source: ww.cam.ac.uk