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24th May 2024
While methotrexate is currently the first-line drug given for juvenile idiopathic arthritis, its effectiveness and tolerability are in fact limited in some patients. With the development of stratified medicine their top priority, Dr Stephanie Shoop-Worrall PhD, Professor Lucy Wedderburn and the CLUSTER consortium set out to discover whether machine learning could transform treatment pathways for children with this debilitating condition.
Children with a diagnosis of juvenile idiopathic arthritis (JIA) often face a long journey to get the right medications, leading to unnecessary pain, uncontrolled symptoms and risking joint damage. Currently, methotrexate is the first-line drug given for JIA, but it is only effective or tolerated in just under half of the children who are treated with it.
In a complex and varied disease like JIA, what does ‘effective’ mean? With signs and symptoms ranging from swollen joints to skin rashes, debilitating pain to symptomless, sight-risking eye inflammation, what does ‘response to treatment’ look like? And how can it mean the same thing for every child?
Researchers have started to look beyond a response versus non-response paradigm and are seeking to understand whether different elements of disease change in different ways following a new treatment, and so require different approaches to disease management. These kinds of investigations are only made possible using new methods of machine learning.
By studying large data sets from thousands of children with JIA, it is hoped that machine learning can facilitate stratified treatment, ultimately reducing pain and suffering in children, aiding clinicians with treatment pathway decisions, and saving money for the NHS and other health systems around the world.
Professor Wedderburn is a professor of paediatric rheumatology based at Great Ormond Street Hospital and University College London (UCL). Mixing clinical and research work, she leads the large UK consortium CLUSTER – a multidisciplinary group of researchers working in JIA who have come together to find ways to improve treatment.
She describes the approach in paediatric rheumatology as ‘holistic’, bringing expertise from psychology, nursing, physiotherapy, occupational therapy and many more specialities.
‘Paediatric rheumatology is an incredibly collaborative field. We do a lot of work with the patients and families. We’re relatively small compared to the adult RA [rheumatoid arthritis] research community, but we’re very linked up, and I think that is a huge benefit,’ Professor Wedderburn says.
However, Professor Wedderburn remains ‘frustrated’ by drug treatments available for children with JIA. Despite the increase in the number of medications available, the drugs are licensed without guidance on when and how to use them in children. What’s more, with a rare and complex disease such as JIA, a child’s predicted response to drugs such as methotrexate varies significantly across different disease features.
As such, the researchers want to move away from a one-size-fits-all system and provide a scientific and biological basis for medication pathways based on the predicted outcomes shown in their data.
Professor Wedderburn says: ‘That’s really what CLUSTER is all about. How can we move to a point where you have true precision medicine or stratified medicine? Many of my patients are in these studies, if they’re willing, and most people want to be involved because we explain it’s the way to get real-world data. This consortium brought together childhood data from huge cohorts – absolutely fabulous for such a rare disease.’
Professor Wedderburn’s colleague and the lead author of their recent publication, Dr Stephanie Shoop-Worrall PhD, is a research fellow at the University of Manchester. She specialises in epidemiology and data science and analyses the CLUSTER data using machine learning.
CLUSTER represents about 5,000 families, which make up approximately half the number of cases of JIA in the UK. Looking at four cohorts of these children who began their treatment before January 2018, Dr Shoop-Worrall and the team were able to find patterns in treatment outcomes which determined how effective methotrexate was on different elements of JIA for groups of children.
‘We’ve got this window of opportunity; we need to treat early on to get better outcomes,’ Dr Shoop-Worrall says. ‘This trial-and-error approach [to medicines] is just wasting people’s time and could lead to much worse outcomes, prolonging chronic pain in children, the potential for disability in the longer term, and massively impacting their lives. So, we really do need to get the right drug first.’
When a child is diagnosed with JIA, they will be diagnosed with one of seven types of the disease. Some diagnoses mirror those seen in adults, while others are unique to children. Describing the current approach as ‘a bit contentious’, Dr Shoop-Worrall has shown through machine learning that the traditional diagnosis groups do not necessarily predict how effective methotrexate will be.
The research team analysed data from when the children started taking methotrexate and followed them over the next year, looking at four outcomes: active joint count, both clinician and patient progress scores, and blood biomarker data. The aim was to capture a spectrum of objective clinical and patient-reported measurements to give an overview of the disease and determine which parts of JIA might be affected by methotrexate.
Dr Shoop-Worrall identified six different groups of children, each describing a different response to methotrexate. The first group, known as the ‘fast responders’, comprised about one in 10 children, all of whose disease responded well to the medication. By six months, this group had no swollen joints, normal bloodwork, and both looked better clinically and felt completely better. The next group, termed ‘slow improvers’, was made up of children who took about a year to achieve the same outcome.
Two more groups showed only partial improvement of JIA with methotrexate. In approximately 8% of children, their joints got better, and the children felt better, but the clinicians reported evidence of JIA, and the children remained on methotrexate. Another 13% of children showed partial improvement and looked better clinically in terms of having no swollen joints and normal blood work, but their symptoms, including pain, persisted.
A small group of about 7% of children, known as the ‘improve-relapse’ group, showed improved symptoms after six months, followed by a relapse. And in the final group of about 44% of children, methotrexate did not impact most of their disease. Small improvements in swollen joints were observed in some cases as the drug is designed to tackle inflammation, but the overall clinical picture did not improve.
Dr Shoop-Worrall says: ‘Once we’d found the clusters, we looked to see if existing subtypes of JIA match up with the patterns. And the answer is no.’
Professor Wedderburn adds: ‘It’s a rather depressing message for families to discover that the name of the condition doesn’t help us know whether they’re going to get better on methotrexate or what the next drug should be. It really isn’t a stratifier. It’s just a label based on what we see in the first few months in the clinic – a nice descriptor.’
Their findings also challenge the traditional binary classification of patients into ‘responders’ and ‘non-responders’ seen in standard clinical trials. For Professor Wedderburn, the groups described by machine learning resonate strongly with what she sees in clinic. She adds: ‘[It’s] really important to get that message across to our community that just dichotomising response doesn’t bring the real lived experience out the way this dissecting of the response can start to do.’
Machine learning has opened the door to the possibility of predicting which aspects of a child’s disease would be helped by methotrexate and which children should start other therapies either alongside, or instead of, methotrexate as first line.
‘We want to get kids into remission quickly; that’s the overall aim of stratified medicine in this disease,’ Dr Shoop-Worrall says. ‘This paper is the first step towards that. If we can figure out who should be on this drug and what kind of response they’ll get, that really pushes forward the aim of stratified treatment.’
The next steps will see the researchers bringing more biological data, such as gene expression and protein data, into their analyses and integrating their findings across different disciplines. They will also investigate the impact of the sociological and psychological elements of the illness, in both cases, working with global cohorts of JIA patients.
Dr Shoop-Worrall concludes: ‘Being able to get a panel of biomarkers or a prediction model that we can integrate into practice to say, right, okay, now we know the different types of response, and this is exactly the group you fit into. That would be a huge step forward for drug selection right from diagnosis.’
The researchers believe machine learning will play an essential role in improving understanding of treatment outcomes, minimising children’s exposure to unnecessary treatments, optimising treatment selection and ultimately improving the quality of care for children with JIA.
20th May 2024
With the potential of personalised medicine becoming ever clearer, clinicians are increasingly turning their attention to the various ways in which this can be realised, and genomics is a prime example of where huge progress can be made. Consultant in medical oncology Dr Nirupa Murugaesu discusses how the 100,000 Genomes Project has supported both research and service delivery in the UK and how whole genome sequencing can be harnessed to transform cancer care.
In October 1990, some of the best scientific brains in the world began working on an international programme to sequence an entire human genome. It took 10 years to complete an initial sequence and cost billions of US dollars.
Fast forward to today, and the picture is vastly different. ‘Because of next-generation sequencing and advances in technology we are now able to sequence a genome comprising around 20,000 genes in less than a week, at a fraction of the cost,’ says Dr Nirupa Murugaesu, consultant in medical oncology and cancer genomics lead at London’s Guy’s and St Thomas’ NHS Foundation Trust.
‘We can now see how routine sequencing to understand the mutational landscape of cancers has helped in terms of understanding more how the cancer is likely to behave, and also determining the best treatment approaches for patients.’
Dr Murugaesu is also principal clinician in cancer genomics and clinical studies at Genomics England. The organisation has been collaborating with NHS England, Queen Mary University of London and the University of Westminster on research into how whole genome sequencing can be combined with clinical data from patients to identify changes in in their cancer’s DNA.
The study, published earlier this year in the journal Nature Medicine, involved more than 13,000 participants with solid mass tumours, and examined clinicopathological data – their type of cancer, histological subtype, the behaviour of their tumour, the types of treatment and survival – over a five-year period.
By combining that information with genomic data, the researchers could pinpoint the cancer’s genetic changes and mutations that resulted in different outcomes. Crucially, this can improve precision cancer care, meaning therapies can be better targeted and individualised to each patient.
Participants were recruited as part of the UK’s 100,000 Genomes Project, which has also collected and analysed data on a number of rare diseases. The solid cancer study found that, through whole genome sequencing, clinicians can use a single test to uncover genetic changes in a tumour.
What sets this study apart from other research in genomics is that, for the first time, the information collected could be applied in real-world settings and in real time, Dr Murugaesu explains.
‘The unique selling point was to have a research study that is embedded within a healthcare system. After the genomes were sequenced, the results were in fact returned to the respective hospital trusts and treating clinicians,’ she says.
‘Normally when research is carried out, the results are not necessarily fed back. We have clinical trials and outcomes that do not always reflect what we end up seeing in practice. But here, we have that real-world clinical information linked with patients’ genomic data, so if there were relevant findings that could be acted upon, this could be undertaken by the treating clinical team.’
Currently, this can be applied in healthcare settings and influence how cancer patients are treated. In particular, it may be helpful in knowing which treatments are less likely to work, or which may not be necessary. ‘If we know from the data that a person’s tumour is likely to be less aggressive, we can decide to not overtreat them, and we can give less-toxic therapies,’ Dr Murugaesu says.
In addition, clinicians can provide patients with more information about how their cancer is likely to behave and what their prognosis may be. In the future, as more data are accumulated and genomics research progresses further, they may be used to develop new and improved therapies as well.
Having laid the groundwork for genomic testing in England, the 100,000 Genomes Project has led to a Genomic Medicine Service being developed and rolled out nationwide.
As a result, Dr Murugaesu says there are criteria for ensuring that minimum standards are met for testing different cancer types, and, importantly, that testing is provided equitably across the country, rather than only at larger cancer centres.
Enormous progress has been made from the early shoots of genomics, when sequencing took years and had a hefty price tag, to becoming embedded into routine care. Now, however, training and education must keep pace with the science, Dr Murugaesu explains.
‘It is now about upskilling the workforce – not just oncologists, but the whole multidisciplinary team – so they understand the role of genomics, and that there is a Genomic Medicine Service available to their patients,’ she says.
In addition, infrastructure and pathways must be set up efficiently to ensure that when a patient undergoes genomic sequencing, their results are returned to their treating team in a timely manner. If genomic testing is performed alongside a biopsy to confirm a cancer diagnosis, and taking that as Day 1, the goal is to have the results back by Day 14, Dr Murugaesu says.
‘That is a challenge that’s not consistently being met, but work is ongoing and one of the main focuses over the next year will be to try and understand the bottlenecks so we can streamline these pathways,’ she adds.
Other technology will have a role in supporting enhanced learning about the genomics of cancer, too. A case in point is liquid biopsies, whereby a blood sample can enable the extraction of circulating tumour DNA – which is shed by tumours, especially those that are more advanced – and sequencing of that DNA can then be undertaken, just as you would for a genomic panel. ‘The repertoire is expanding for what is available and possible to fully molecularly profile tumours,’ Dr Murugaesu says.
Again, performed as soon as there is radiological suspicion of cancer, a simple blood sample can enable genomic sequencing of the tumour’s circulating DNA. If successful, this testing can potentially circumvent problems associated with tissue biopsies, such as not getting enough tissue to yield meaningful results. This has implications for patients – needing to go through the upheaval of a repeat biopsy, for example – and places resource and time pressures on healthcare systems.
A pilot exploring this technology in non-small cell lung cancer is currently under way and has demonstrated promising results in the initial phase.
‘The next phase has now launched and there will be 10,000 tests made available across England for patients with suspected lung cancer, which is exciting because there’s a real opportunity to expand our circulating tumour DNA testing,’ Dr Murugaesu says. ‘There is more and more emerging data about what the role of circulating DNA may be, including screening and earlier detection of cancers.’
There is interesting work in genomic testing across Europe, too. For example, scientists at The Hartwig Medical Foundation in Amsterdam found clinically relevant data from almost 5,000 metastatic solid tumour samples, and supported recruitment to a large-scale trial in the Netherlands – the Drug Rediscovery Protocol (DRUP) trial.
The study is collecting information on the off-label use of registered targeted therapies for patients with incurable cancer who have exhausted standard treatment options, based on their tumour’s molecular profile.
This is one way of embedding genomic testing into cancer care. Dr Murugaesu hopes this becomes routine in the future so that not only will whole genome and genomic panel sequencing help predict the best therapies, but also it could identify whether patients are at increased risk of their cancer reoccurring.
There is enormous potential for genomic medicine to take much of the guesswork out of how tumours are treated, and to be truly transformative in cancer care globally.
18th January 2024
Combining routine clinical data with whole genome sequence (WGS) data at scale supports clinicians in the delivery of precision cancer care, according to new landmark research.
Published in the journal Nature Medicine, the study showed that WGS could provide a more comprehensive view of a tumour’s genetic landscape by detecting various genetic changes using a single test.
Led by Genomics England, NHS England, Queen Mary University of London, and the University of Westminster, researchers analysed data covering 33 types of solid tumours collected from 13,880 participants with cancer in the 100,000 Genomes Project.
By looking at the genomic data alongside real-world treatment and outcome data collected from participants over a five-year period, such as hospital visits and the type of treatment they received, they were able to find 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 over 50% of colon and lung cancers showed genetic changes that could affect how patients are treated, guiding decisions about surgery or specific treatments they might need.
In more than 10% of sarcomas, larger structural variants were identified that have the potential to impact clinical care and treatment.
And in over 10% of ovarian cancers, the study pinpointed inherited risks offering crucial insights for clinical care.
The study also found patterns across several cancers and uncovered genetic changes that might explain treatment response or predict possible patient outcomes.
‘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,’ the researchers concluded.
Dr Nirupa Murugaesu, principal clinician – cancer genomics and clinical studies at Genomics England, and oncology consultant and cancer genomics lead at Guy’s and St Thomas’ NHS Foundation Trust said: ‘This study is an important milestone in genomic medicine. We are starting to realise the promise of precision oncology that was envisioned 10 years ago when the 100,000 Genomes Project was launched.
‘We are showing how cancer genomics can be incorporated into mainstream cancer care across a national health system and the benefits that can bring patients.
‘By collecting long-term clinical data alongside genomic data, the study has created a first-of-its-kind resource for clinicians to better predict outcomes and tailor treatments, which will allow them to inform, prepare and manage the expectations of patients more effectively.’
Professor Dame Sue Hill, chief scientific officer for NHS England and senior responsible officer for genomics, added: ‘The insights gained in this study, in which genomic patterns or profiles have been mapped out in thousands of patients with different types of cancer, support and inform the NHS Genomic Medicine Service in providing a comprehensive genomic testing service for patients with cancer and signals a promising future for healthcare as we continue to hone and enhance the NHS use of genomics and tailor interventions for improved outcomes.’
8th August 2022
The NHS should offer all cancer patients genetic profiling of their cancers at diagnosis and during treatment to shape care and track how the disease evolves, a consensus group of leading experts has concluded.
Group members said action was needed to ensure use of cancer treatments was routinely guided by information about a patient’s individual cancer.
They called for barriers preventing patients from gaining access to ‘biomarker’ tests to be removed – so genetic information and other tests could routinely be used to select the most suitable precision medicine for each patient.
The consensus group was convened by The Institute of Cancer Research, London, and included nine leading institutions, charities, stakeholder groups and life-science companies, including Cancer Research UK, AbbVie, the Association of British HealthTech Industries, AstraZeneca, Bioclavis, Bristol Myers Squibb, Leukaemia UK and Precision Life and the Association of the British Pharmaceutical Industry.
Biomarker tests look for genetic, protein or imaging ‘markers’ to identify which patients are most likely to respond to treatment.
It is crucial for clinicians to be able to assess biomarkers so they can select patients with particular weaknesses in their cancers and match treatment accordingly. But the consensus group warned that testing is not always done because regulatory processes and resources have not kept pace with the science.
The statements are calling for a series of changes in the way biomarker tests are developed, made available and routinely used in the UK:
Regulatory barriers to biomarker testing and development have a direct impact on patients – potentially denying them more personalised treatment.
Biomarker testing and development is expensive – currently, the costs of developing biomarker tests often outweigh the financial benefits of doing so, discouraging industry and academia from investing in biomarker research.
But targeting therapies to those who are most likely to respond would be more cost-effective for the NHS. And clinical trials that use biomarkers to select patients are much more likely to succeed and result in marketing approval.
The ICR and the rest of the consensus group members hope that the calls to action in the new 13-point set of consensus statements will help speed up development of biomarker tests and widen access to them – so that the best treatments can reach the right patients as quickly as possible.
Professor Kristian Helin, Chief Executive of The Institute of Cancer Research, London, said: “We believe every cancer patient should have the opportunity for their cancer to be molecularly profiled to assess biomarkers that can give vital clues about how their disease should best be treated. Biomarker tests can direct treatment precisely to the patients who will most benefit, which can both improve the lives of patients and increase the cost-effectiveness of treatment for the NHS.
“It’s essential that the regulations that govern clinical trials and the approval of new tests and treatments keep pace with the rapidly moving science. At the moment, it can be hard to get new biomarker tests developed, approved and made available for patients. That can in turn act as a disincentive for companies and academics to develop new biomarkers to guide treatment in the future.”
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