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Novel imaging device enters first round of development funding programme

Proton-beam-therapy (PBT) is becoming increasingly important for treating cancer, with projected increases of up to 50% more patients per year being treated with the technology in the UK and worldwide by 2025.

Although the precision of PBT has many advantages over traditional radiotherapy, there some uncertainty over the range of delivery the beam provides. There is risk of potential overdose to normal tissues or underdose to tumour, resulting in reduced tumour-control and long-term side-effects due to treatment of healthy tissue. This can be detrimental to patients and a burden on healthcare systems if side-effects become apparent later in a patient’s life.

Therefore, a method to verify the range of treatment beams when using PBT on patients is crucial to increase the treatment accuracy. Dr Anna Vella, Postdoctoral with the Radiation Therapy Medical Physics Group, led by Prof. Frank Van Den Heuvel, at the University of Oxford’s Department of Oncology, is investigating the efficacy of a device with this purpose.

Anna is leading CAPULET (Coded Aperture Prompt-gamma Ultra-Light imaging detector), an imaging device for quality assurance assessment of radiotherapy plan efficacy, designed for daily use in clinical practice. CAPULET could be installed onto a variety of PBT devices, and used to verify and fine-tune the dose between fractions in particle-beam radiotherapy. It does this through collecting 3D images of the particle beam penetrating soft-tissue, with the ultimate goal to fine-tune planning doses and improving the efficacy of the overall radiotherapy treatment.

This novel and unique technology is faster & more compact than current devices, increases the field-of-view, and improves the signal-to-noise ratio. The impact on patients will be to improve cancer-control, fewer complications, and improved quality-of-life following treatment.

CAPULET has recently been selected as one of 35 projects in the Pre-Development Phase of the Alderley Park Oncology Development Programme – a national programme designed to develop and progress start-up oncology projects. Funded by Innovate UK and Cancer Research UK. It will now be work-shopped, and potentially be chosen to join the full development programme with grant funding.

Proof-of-concept experiments will be performed in collaboration with the CRUK-funded ART-NET. The long-term plan of CAPULET is to develop a large-area detector to fully image the beam delivery range within lungs, liver, H&N and other large sites in the human body to overcome limited field-of-view found in other existing devices on the market.

Oxford spin out influencing patient care world wide

Optellum, a lung health company aiming to redefine early diagnosis and treatment of lung disease, today announced it received FDA clearance for its “Virtual Nodule Clinic”.

Optellum was co-founded by Oxford cancer researcher Prof. Sir Michael Brady with the mission of seeing every lung disease patient diagnosed and treated at the earliest possible stage, and cured.

Optellum’s initial product is the Virtual Nodule Clinic, the first AI-powered Clinical Decision Support software for lung cancer management. Their platform helps clinicians identify and track at-risk patients and speed up decisions for those with cancer while reducing unnecessary procedures.

Lung cancer kills more people than any other cancer. The current five-year survival rate is an abysmal 20%, primarily due to the majority of patients being diagnosed after symptoms have appeared and the disease has progressed to an advanced stage. This much-needed platform is the first such application of AI decision support for early lung cancer diagnosis cleared by the FDA.

Physician use of Virtual Nodule Clinic is shown to improve diagnostic accuracy and clinical decision-making. A clinical study, which underpinned the FDA clearance for the Virtual Nodule Clinic, engaged pulmonologists and radiologists to assess the accuracy for diagnosing lung nodules when using the Optellum software.

Dr Václav Potěšil, co-founder and CEO of Optellum says:

“This clearance will ensure clinicians have the clinical decision support they need to diagnose and treat lung cancer at the earliest possible stage, harnessing the power of physicians and AI working together – to the benefit of patients.

Our goal at Optellum is to redefine early diagnosis and treatment of lung cancer, and this FDA clearance is the first step on that journey. We look forward to empowering clinicians in every hospital, from our current customers at academic medical centers to local community hospitals, to offer patients with lung cancer and other deadly lung diseases the most optimal diagnosis and treatment.”

New partnership enables access to state-of-the-art radiotherapy machine

The first NHS patient has received treatment on the cutting-edge ViewRay MRIdian technology, thanks to a new partnership between the University of Oxford, Oxford University Hospitals (OUH) NHS Foundation Trust and GenesisCare.

The partners, with the support of the John Black Charitable Foundation, have collaborated to establish a ten-year programme of clinical treatment for NHS patients, with further research into improving cancer treatment using the Viewray MRIdian.

Due to the natural, unavoidable movement of soft tissue inside the body, normal tissue around the cancer can be exposed to radiotherapy treatment, particularly when targeting soft-tissue tumours deep within the body. It can be challenging to visualise these organs during radiotherapy with routine radiotherapy delivery.

The ViewRay MRIdian machine is the only one of its kind in the UK, with only 41 machines worldwide. It allows doctors to see the normal soft tissue and the tumour in real time by combining MRI scanning with targeted radiotherapy. Incorporating MRI scans will allow doctors to then tailor doses in real time to the specific internal anatomy of the patient on the day of treatment.

MRIdian technology also minimises the damage to surrounding healthy tissues by switching off when tumour tissue moves outside of the targeted beam. This could mean less side effects for patients and increased dosage of treatment delivered directly to the tumour.

GenesisCare, the University of Oxford and OUH will also partner in research collaborations to develop real-world evidence which will inform future utilisation of the MRIdian technology in hard-to-reach tumours, such as pancreatic cancers. The research partnership will assess the benefits of the MRIdian technology in terms of improved cancer outcomes and reduced toxicity.

Elizabeth Rapple, from South Oxfordshire, is the first patient to use the machine to treat her renal cancer, as part of the new partnership. She says:

“I feel very fortunate to be able to access this machine as part of a new Oxford-wide partnership. Any operation to remove my tumour would have been highly invasive, so it’s lucky that my cancer was suitable for MRIdian radiotherapy. I am so grateful that this unique machine has been made accessible through the NHS, and that I can be the first of many to benefit from this partnership going forward.”

Project leader Professor Tim Maughan, from the University of Oxford, said:

“Treating patients on the MRIdian is like a surgeon putting on their spectacles for an operation – for the first time we can see exactly what the cancer is doing during treatment and adapt to change accordingly.  This accuracy allows us to reduce side effects and we hope to improve cancer outcomes in hard-to-treat cancers.”

Dr James Good, Clinical Oncologist at GenesisCare, said:

“The MRIdian machine is at the cutting-edge of what is possible in radiotherapy technology. The ability to visualise the tumour more accurately, to follow it while it’s being treated and to adapt the plan every day means we can deliver the best possible outcomes.

“This collaboration with the University of Oxford and Oxford University Hospitals will be truly beneficial for cancer patients in the UK. Not only will it provide patients who otherwise would have limited, or sadly, no options with a really viable treatment option, but we can also help demonstrate the effectiveness of this treatment, with the ambition to make it available for all NHS patients in the future.”

Carol Scott, Lead Therapeutic Radiographer & Deputy Clinical Director at Oxford University Hospitals , said:

“OUH are excited to be part of this collaboration offering NHS patients the opportunity to take part in these clinical trials. The use of daily advanced imaging that clearly shows us the tumour and normal soft tissue around it will enable us to take the next step in making our treatments even more personalised and effective”

Developing a system to simultaneously detect genetic and epigenetic information

Many diseases are associated with changes to the DNA sequence, most notably cancer. Also altered in disease is the way that the DNA is decorated with chemical modifications such as methylation (epigenetic modifications). Being able to extract genetic and epigenetic information using DNA sequencing has revolutionised biomedical research and has led to new ways to diagnose diseases. A particular interest currently is in using genetic and epigenetic characteristics of tumour DNA circulating in the blood or other bodily fluids as a strategy for detecting cancer earlier. However, despite the potential utility of combining genetic and epigenetic information to enhance disease detection, no methods currently exist that can efficiently simultaneously extract this information from the same DNA sequencing data.

Up until now, DNA methylation has predominantly been detected using methods that rely on a process called bisulphite conversion. Bisulphite is a harsh chemical that damages DNA, resulting in decreased sensitivity and a high error rate in the sequencing data. Because it is not known whether any changes in the DNA compared to a reference genome are introduced by bisulphite or real mutations, it is very challenging to simultaneously detect methylation and mutation data using these methods.

Recently, a new bisulphite-free method for detecting DNA methylation called TET-assisted pyridine borane sequencing (TAPS) has been developed by Ludwig Oxford’s Dr Chunxiao Song and Dr Benjamin Schuster-Böckler. This method is both cheaper than bisulphite sequencing and importantly produces data of higher quality, similar to that of standard DNA sequencing.

In this project, funded by an MRC Methodology Research Grant, Dr Benjamin Schuster-Böckler will collaborate with Professor Gerton Lunter (Visiting Professor, Radcliffe Department of Medicine) to develop algorithms that simultaneously detect mutations and DNA methylation from TAPS data.  Experimental data will be provided in collaboration with Ludwig Oxford’s Dr Chunxiao Song and Professor Xin Lu, and Professor Ellie Barnes (Nuffield Department of Medicine). Test data will be used to train machine-learning algorithms to optimise the accuracy of the sequencing method and to establish the best possible experimental parameters for this technique.

The resulting method will greatly increase the utility of the TAPS technique and will make it possible to routinely query a patient’s genetic background, while simultaneously measuring their epigenetic state. This will lead to a much broader understanding of the role of epigenetics in disease and would raise the possibility of using combined genetic and epigenetic information from sequencing data to aid earlier detection of cancer.

Image attribution: Darryl Leja, National Human Genome Research Institute (NHGRI) from Bethesda, MD, USA, CC BY 2.0 https://creativecommons.org/licenses/by/2.0, via Wikimedia Commons

New Oxford spin-out Singula Bio launches

Singula Bio is a bold new seed-stage biotechnology company spun out of Oxford University. It aims to become a world leader in developing neoantigen-based individualised cell therapies to use against difficult-to-treat solid malignancies such as ovarian cancer.

This patient-centred approach will pioneer immunological, medical, surgical and computational technologies to generate selective therapies that eliminate cancer, and the ultimate hope is to achieve long-term, high-quality disease-free survival for cancer patients.

Singula Bio was co-founded by Professors Ahmed Ahmed, Enzo Cerundolo and Enda McVeigh from the Nuffield Department of Women’s & Reproductive Health at Oxford University. It is supported by Oxford University Innovation (OUI), the University’s research commercialisation company, and it has secured generous seed-stage investment from IIU Nominees Limited to pursue its goals. Singula Bio is a landmark for OUI as it is the 250th OUI-supported venture to have passed through the office since it opened its doors in 1987.

Motivated by their many patients (and laboratory funding from charities Ovarian Cancer Action and Cancer Research UK) Profs Ahmed and Cerundolo were inspired to improve an individual’s gruelling experience of cancer and to lessen their suffering of other treatments. Together, they have an enormous knowledge in cancer medicine, cancer immunology, cell and molecular biology, and computational biology which has enabled them to design patient-specific cancer cell therapies that harness the power of the patient’s own immune system to fight cancer.

In a tumour, cancer cells carry mutations that appear foreign to a patient’s body and, therefore, their immune system reacts to these mutations. One strong form of an immune reaction is through generating mutation-specific cells called “T cells”.

Prof Ahmed, Professor of Gynaecological Oncology at the Nuffield Department of Women’s & Reproductive Health, Oxford University, said:

“A key feature of cancer cells is the preponderance of genetic aberrations in their DNA. These aberrations can make proteins appear foreign to our body’s immune system which then develops immune cells (T cells) to fight cancer cells. Thanks to years of research and technology development we now know how to identify relevant tumour-specific T cells to grow them outside the body and deliver them back to patients to fight cancer cells.”

New Oxford technology assesses cancer patient vulnerability to COVID-19

The web-based COVID risk prediction tool, QCovid, is the product of the latest research to emerge from the QResearch database co-founded by Prof Julia Hippisley-Cox based at the University of Oxford. The analysis of anonymised UK health records of more than 8 million adults using GP records, hospital records including intensive care data, mortality data, Cancer Registry data and COVID-19 testing data from late January 2020 to April 2020 allows clinicians to estimate someone’s  risk of COVID-19 infection as well as the risk of being admitted to hospital with serious illness due to the virus and the potential risk of COVID-19-related death. QCovid takes into account a range of risk factors such as age, gender ethnicity and medical conditions and enables the NHS to make evidenced based decisions when prioritising different patient groups for shielding and COVID-19 vaccination.

The work was commission by England’s Chief Medical Officer Chris Whitty, who involved the team led by clinical epidemiologist, Prof Julia Hippisley-Cox, at the University of Oxford as the group has acquired extensive experience in developing risk prediction tools for a range of diseases, including QCancer for the prediction of having  undiagnosed cancer, which are widely used in the NHS. QCovid has now been validated and published in the British Medical Journal, is accessible to the public at www.qcovid.org and has been adopted by NHS Digital as a way to assess the relative risk of COVID-19 for all members of the population, based on their medical history and other risk factors.

Based on the prediction tool, 1.7 million patients have been added to the shielding list, including many cancer patients. Those within the most ‘vulnerable’ group who are over 70 will have already been invited for vaccination and 820,000 adults between 19 and 69 years will now be prioritised for a vaccination.

CANCER & VULNERABILITY

Although previous studies from the University of Oxford have shown that blood cancer patients are at higher risk of COVID-19, until now no research or model had been published that assessed patients with different types of cancer, including their treatment history and backgrounds. The QCovid algorithm feeding into the prediction tool takes cancer factors such as diagnosis of blood, lung, oral or bone cancers and different cancer therapies into account.

Thus using the QCovid prediction tool, it has a been highlighted that those with blood (acute myeloid leukaemia, chronic myeloid leukaemia, acute lymphoblastic leukaemia, chronic lymphocytic leukaemia, Hodgkin lymphoma, non-Hodgkin lymphoma, multiple myeloma) and respiratory (lung, laryngeal, nasopharyngeal and mouth) cancers are at increased COVID-19 risk.

In addition, those undergoing therapy (including recent bone marrow or stem cell transplant, chemotherapy, radiotherapy, immunotherapy or other antibody treatments for cancer and treatments that affect the immune system such as protein kinase inhibitors or PARP inhibitors), have also been identified at higher risk.

Thanks to the QCovid algorithm cancer patients now can be appropriately categorised and prioritised based on their type of cancer, current or previous cancer treatment and other factors such as corresponding health conditions that could make them more vulnerable to COVID-19.

The development of the QCovid model was led by the University of Oxford and involved researchers from Cambridge, Edinburgh, Swansea, Leicester, Nottingham, Liverpool, the London School of Hygiene & Tropical Medicine, Queen’s University Belfast, Queen Mary University of London and University College London. It was funded by the NIHR, NIHR Oxford Biomedical Research Centre, Wellcome Trust (ISSF) and John Fell Fund and supported by EMIS GP practices and the University of Nottingham.

Detecting for multiple cancers in one simple test

Biomarkers – or biological markers – are used in many areas of health and disease as measures of a biological or clinical state. In the context of cancer, identifying biomarkers of early stage cancer is crucial for being able to detect disease earlier and improving the outcomes of patients with cancer. However, biomarkers alone are not sufficient for earlier detection. We also need to develop cost-effective, non-invasive, simple-to-use technologies that can be used in the clinic to detect these biomarkers with high sensitivity, specificity and accuracy.

Professor Jason Davis in the Department of Chemistry at the University of Oxford is working on just that. Professor Davis’ research has focused on developing portable, handheld diagnostic tests that use a range of electroanalytical methods for biomarker detection. This includes recent work on using novel electrochemical impedance-based sensing technology to detect C-reactive protein, a marker of inflammation in the body.

These methods are advantageous for use in diagnostics since they generate results in a few minutes and are more sensitive than other commonly used techniques such as ELISA (enzyme-linked immunosorbent assay). They also do not require the sample to be processed before testing, meaning that a single drop of blood can be analysed directly, without needing further reagents or equipment. Multiple different biomarkers can be analysed simultaneously, potentially allowing multi-cancer blood tests in the future.

To further develop this technology into a clinically implementable assay, five years ago, Osler Diagnostics was spun out of Professor Davis’ lab. The ultimate aim is that this assay could be applied in GP surgeries to test for disease in asymptomatic individuals.

Professor Davis is currently looking at clinical applications within cardiac, cancer and neurological diseases and welcomes interest from researchers who would like to contribute their biomarker ideas and clinical problems.

About the researchers

The Davis Group runs an interdisciplinary research programme within the Department of Chemistry that develops and applies methods for the fabrication of advanced functional interfaces, and are actively engaged in the development of molecular detection, diagnostic, theranostic, and imaging methodologies.

Following the cancer metabolomic breadcrumb trail

By analysing the metabolic molecules that tumour cells leave behind, Dr James Larkin is investigating the applications of metabolomics in the early detection of many cancers.

New sequencing methods for distinguishing DNA modifications

Chemical modifications made to the DNA base cytosine play an important role in the regulation of gene expression across the genome. Cytosine can be chemically modified in four ways, with 5-methylcytosine (5mC) being the most common. Demethylation of 5mC by the TET family of enzymes results in the stable intermediates 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC) and 5-carboxycytosine (5caC). From what has been discovered so far, these modifications appear to have distinct functions. For example, 5mC is associated with repressed regions of the genome whereas 5hmC is present in active ones. However, to study these modifications further, robust sequencing methods are needed that can detect each of these four modifications specifically.

The traditional gold standard method for detecting DNA methylation is bisulphite sequencing. However, this relies on a harsh chemical treatment that degrades most of the DNA sample and is an indirect detection method, which decreases sequencing quality. Recently, a bisulphite-free method called TAPS has been developed by Ludwig Oxford’s Song lab, which has the advantage of preserving more of the DNA, increasing sensitivity, and directly detecting modified cytosines for improved DNA sequencing quality.

Despite its advantages, TAPS cannot distinguish between the different types of cytosine modifications. Other methods already exist that can do so but these use subtraction, for example, measuring 5mC and subtracting this signal from a combined measure of 5mC and 5hmC to obtain 5hmC levels. In addition to the disadvantages of using bisulphite and/or indirect detection strategies, these subtraction methods also need higher sequencing depths and generate very noisy data that can be difficult to interpret. New subtraction-free methods are therefore needed to specifically, directly and sensitively detect these four cytosine modifications in the genome.

In this paper published in Nature Communications, Dr Yibin Liu from Dr Chunxiao Song’s lab (Ludwig Oxford) and Dr Zhiyuan Hu from Professor Ahmed Ahmed’s lab (Weatherall Institute of Molecular Medicine and Nuffield Department of Women’s and Reproductive Health, University of Oxford) have developed a suite of TAPS-related whole genome sequencing methods for specifically detecting 5mC, 5hmC, 5fC and 5caC. They have named these TAPSβ (for 5mC), chemical-assisted pyridine borane sequencing (CAPS; for 5hmC), pyridine borane sequencing (PS; for 5caC and 5fC) and pyridine borane sequencing for 5caC (PS-c; for 5caC).

With these new methods, the research community is now armed to tackle more of the questions about the distinct and important functions of cytosine modifications in the genome and how their distribution is altered in diseases such as in cancer.

“The Oxford Classic” classification system uncovers new information about ovarian cancers

In 2020, using single cell RNA sequencing, Oxford cancer researchers made a breakthrough by identifying  new types of Fallopian tube cells that are the cells of origin for the majority of ovarian cancers. They showed that that the types of these newly-discovered non-cancer cells are “mirrored” into different ovarian cancer subtypes. These subtypes correlated well with survival.

Discovering the new subtypes of cells have allowed Oxford researchers to classify and categorise tumours based on their origin in the body, and determine which ones can lead to more severe cancer outcomes – an approach which has been dubbed the ‘Oxford Classification of Carcinoma of the Ovary’ or ‘Oxford Classic’ for short. The Oxford Classic will provide much more accurate predictions for disease outcome in patients, as well as helping researchers to develop targeted therapies for each type of cancer

Professor Ahmed Ahmed, Nuffield Department of Women’s and Reproductive Health and originator of the Oxford Classic, has how published a paper in collaboration with Imperial College, demonstrating the applications of the Oxford Classic approach. As well as shedding light on some previously unknown information about ovarian cancers.

Professor Ahmed says:

“Our group is very excited that we were able to confirm the predictive role of the Oxford Classic. This work highlights that it is now important to identify new personalised therapies for the Oxford Classic-defined EMT-high ovarian cancer subtype. The finding that there is a strong connection with abundant M2 Macrophages already offers a good hint as to where we could find good treatment options for patients with this type”.

Serous ovarian cancer (SOC) is the most common cancer subtype, but is challenging to classify and predict its prognosis. Using the Oxford Classic, researchers found that specific SOC subtypes, known as EMT-high types, were associated with a lower survival rate in serous ovarian cancer patients.

Professor Christina Fotopoulou of Imperial College London says:

“This has been a very fruitful collaboration between two major UK gynaecological cancer centres; Oxford and Imperial College. We have generated very promising results towards an individualisation of care of our ovarian cancer patients. Our data will help clinicians to stratify patients to the right treatment pathway based on features of tumour biology of their disease. I hope we can continue to work together on that basis and expand and validate our data further also on a larger scale.”

EMT stands for epithelial-mesenchymal transition, it is the process by which epithelial cells change and become more mobile. This mobility provides the cells with the opportunity to spread leading to cancer progression. EMT-high subtypes are tumours that have a high number of cancer cells with greater mobility.

Researchers also found that EMT-high subtypes were associated with abundance of a type of immune cells called M2 macrophage. M2 macrophages possess immunosuppressive properties, and can lead to poorer treatment responses if they are found in high quantities within a tumour. It has previously been observed that patients with high-EMT tumours had a poor immune response. This study confirms that the EMT-high subtypes are associated with an immunosuppressive environment (and so poor patient responses to treatment) due to their association with more M2 macrophages – a link that has not previously been identified.

Whether M2 macrophages induce the EMT level or the EMT level results in higher levels of M2 macrophages will be an important question to be addressed by Prof Ahmed’s future work. However, this study has demonstrated the Oxford Classic’s strong ability to predict a patient’s prognosis.

Classifying the EMT status of a tumour, using the Oxford Classic, could potentially become a valuable part of future cancer stratification methods. This will ensure that appropriate treatment methods and attention are given to patients with a poorer overall prognosis.

Ovarian Cancer Action’s CEO, Cary Wakefield, says

“While other cancers have achieved major improvements in treatment outcomes, ovarian cancer continues to go unrecognised, underfunded, and misdiagnosed. The Oxford classic is an exciting breakthrough that will help to identify new treatment options for ovarian cancers that have a lower chance of survival. Funding important research like this will bring us closer towards a shared goal of more women surviving ovarian cancer”.

About the study

This study was co-led by Prof Ahmed Ahmed of the University of Oxford and Prof Christina Fotopoulou of Imperial College. It was funded by Ovarian Cancer Action, CRUK Oxford Centre and the National Institute for Health Research (NIHR) Biomedical Research Centre.

This study has demonstrated the potential of the Oxford Classic to:

  1. Accurately classify types of serous ovarian cancers
  2. Identify populations of cancer cells that have poorer prognoses (such as EMT high cancers)

Ahmed Ahmed is a Professor of Gynaecological Oncology at the Nuffield Department of Women’s & Reproductive Health at the University of Oxford and a Consultant Gynaecological Oncology Surgeon at the Oxford Cancer and Haematology Centre. His work focuses on surgical, medical and fundamental research into ovarian cancer, its early detection, treatment and screening.

Read the fully study here: http://clincancerres.aacrjournals.org/content/early/2021/01/12/1078-0432.CCR-20-2782