From bench to bedside – Innovating blood cancer clinical practice

Innovation takes many forms – from a tweak that improves technology, all the way to the development of new medicines. Translating science is about adapting research, moving our science beyond the lab, or closing gaps in technologies so that they can be used to improve our lives. Jyoti spoke to us about spotting those opportunities, and the challenges of her work.

The first one is called Predict Blood - we have just launched the new website, hosted by the NHS, which is registered with the Medicines & Healthcare Products Regulatory Agency as a Class 1 medical device. This means that it’s now an official tool for clinicians and patients to use. In short, it’s an online tool to support health professionals in assessing how a person's blood cancer (specifically those known as myeloproliferative neoplasm, or MPNs) might develop given a set of variables - age, gender, health and any other information about the genetic variations the patient may carry that could affect the outcome from their cancer.

Myeloproliferative neoplasms, or MPNs as we normally call them, are a group of rare disorders in which the bone marrow overproduces blood cells in an uncontrolled way. This can eventually lead to blood clots and bleeding as well as making patients feel ill.  In our field, we are now using our knowledge of the mutations present in cancer cells to try and personalise the expected behaviour of this disease in patients. We know that patients are very heterogeneous - people with the same cancer can demonstrate quite a lot of differences in terms of their patterns of progression or remission of the disease and the symptoms that they suffer.

I’m particularly passionate about these types of blood cancers - myeloproliferative neoplasms - because it's the condition that I have treated for a long time at Addenbrooke's Hospital, Cambridge University's NHS Trust. Seeing the patients every week provides direct motivation for studying the conditions further within the research group to address unanswered questions. When the first predictive algorithm was published in 2018, the associated website got a lot of attention.

“I’m particularly passionate about Myeloproliferative Neoplasms because it's the condition that I treat ... That’s what motivated me and my team to build the algorithm behind the tool in the first place.”

Dr Jyoti Nangalia,
Group Leader, Wellcome Sanger Institute

Over the years, we realised that clinicians and patients were both accessing the website and that the site could be improved further. Our tool is now a medical device in the UK  and comes with the assurance of detailed governance and procedures to carry out risk assessments, which will be constantly under review for its ongoing relevance to patient management moving forward. We were fortunate to be able to develop this new tool with the support of the Genomics Innovation office and colleagues at the Winton Institute who have previously looked into the psychology behind communicating risk to patients and clinicians in many of their projects to identify effective ways of displaying the results.

The predictive tool hosted at Predict Blood is particularly useful for healthcare professionals who are treating patients with this condition. The tool gives clinicians information on the patient's likely prognosis - how the condition is most likely going to progress. The tool uses information from the behaviour of past patients to predict what is the most likely outcome for an individual patient. 

With this information, clinicians can then counsel patients and better guide their monitoring strategy. In the future, we anticipate that this work can be used to identify patients at high risk of poor outcomes. For me, this is key - to identify patients at high risk at an earlier stage so that we can try novel strategies to divert the expected outcome of their disease. Our ultimate aim is to be able to target the best therapies to those patients most likely to benefit. There’s still more work to do, but this is a step in the right direction.

The second tool, called TiNCan is software for the identification of mutations in blood cancers. Let me give you some context - there has been a pain point in blood cancer mutation detection for some years. To identify DNA mutations that drive cancers or diseases, we have to differentiate those mutations from the natural variations in DNA that people are born with, ie we need to separate the mutations in DNA that occur during our lifetime from the DNA variants that make us different to the next person, those that are present with us from birth. Separating these out in blood samples can be very tricky. 

This algorithm can give a prediction on which mutations are the ones causing the specific blood cancer by only sequencing one sample. It seems to work quite well and we have patented this technology. We believe that it would be of value in the clinic where we are increasingly undertaking genomic sequencing in patients as standard. With the Genomics Innovation office at Sanger, we are looking forward to exploring its clinical utility with different external partners.

“TiNCan  can give a prediction on which mutations are the ones causing the specific blood cancer by sequencing only one sample.”

Dr Jyoti Nangalia,
Group Leader, Wellcome Sanger Institute

I've always wanted to be involved in research, right from when I was a medical student. During medical school, I spent a year doing research and very much enjoyed asking new questions from which you can learn something about human biology, and then seeing how the findings can lead to changes in what we do in the clinic.

The turning point for me was when I undertook a PhD at the University of Cambridge and the Sanger Institute. During my research, and analysing vast datasets of patient data with MPNs, I realised that the majority of patients with a certain variety of the disease had a specific mutation in a gene called CALR. It was a game changer for clinical practice and testing for CALR mutations is now a routine diagnostic test in the clinic. 

“The turning point for me was when I undertook a PhD at the University of Cambridge and the Sanger Institute. During my research, and analysing vast datasets of patient data with MPNs, I realised that the majority of patients with a certain variety of the disease had a specific mutation in a gene called CALR. It was a game changer for clinical practice and testing for CALR mutations is now a routine diagnostic test in the clinic.”

Dr Jyoti Nangalia,
Group Leader, Wellcome Sanger Institute

Of course, that gave me the bug for research which is what I spend the majority of my time doing at the Sanger Institute. At the same time, I was passionate about remaining active in clinical care for patients. What I particularly like about haematology is how involved we are as haematologists, in the whole process: you can go and see a patient suffering from a problem related to the blood. After assessing the patient, you take their blood sample, and then it's you again who's going to the lab and looking down the microscope and diagnosing the condition. Then you go back to the patient and the family to tell them the news and to start the first line of therapy. It’s a privilege to be part of the whole process with the patient and the family and to work with the large haematology hospital team helping make each step of the journey work smoothly. It is very much the lab and bench side in one job.

Yes! I've always enjoyed that aspect of my work. Haematology, both clinically and in our research in particular. The focus has been shifting to the research side now, the interests are much broader, particularly since joining the Sanger Institute. But MPNs is where it all started. 

Looking into the future, I see the Predict Blood project expanding to other types of blood cancers and also other types of cancers in general. We don't always need to develop those tools, we can also take existing tools, put them in this medical device governance framework we have developed to help host them on our platform. 

To date, all the work on this project has been supported by various research grants. Long term, though, the tool requires maintenance and ongoing resources, especially now that it’s regulated. This is not our expertise at Sanger, so we’re exploring commercialisation as a route to provide a long-term sustainable future for the project.

It’s been a great learning journey. It’s given me insight as to how to do it better the next time. We now have improved tools for healthcare professionals to diagnose MNPs. When thinking of Predict Blood, it also means that we have a framework with which we can extend this to other tools, widening the scope of our work and giving it a commercial structure that can help expand it further.