Detecting myeloma earlier

Several research projects are underway in Oxford focusing on different points in the clinical care pathway to improve myeloma early detection.

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.

Investigating the effects of co-morbidities on liver cancer risk

Hepatitis B virus (HBV) infection is one of the world’s leading causes of infection-related death and levels are increasing. A large proportion viral of hepatitis-associated deaths are due to liver cancer and cirrhosis. However, because not everyone with chronic HBV will develop liver cancer, more needs to be understood about the additional risk factors for liver cancer in people with chronic HBV infection. This will allow improved risk prediction for liver cancer, which, in addition to more sensitive diagnostic technologies, is an important part of the strategy for monitoring, to support earlier liver cancer detection and improved survival.

In this review published in the Journal of Viral Hepatitis, Cori Campbell and colleagues from Dr Philippa Matthews’ and Professor Ellie Barnes’ groups (Nuffield Department of Medicine) performed a literature review and meta-analysis to look for evidence of risk factors linked to HBV-associated liver cancer. Given the increasing prevalence of co-morbidities such as diabetes, high blood pressure and kidney disease, and metabolic risk factors such as obesity and dyslipidaemia (abnormal lipid blood profiles), the focus of this review was placed on these risk factors.

The researchers identified 40 studies that showed an association between liver cancer risk in the presence of chronic HBV infection and diabetes, high blood pressure, dyslipidaemia and obesity. Out of all these associated co-morbidities, only diabetes had enough published studies on it to be able to perform further analysis.

The risk of liver cancer was over 25% higher in individuals with chronic HBV infection and diabetes compared to those without diabetes, although there was some variation between the effect of diabetes seen in different studies. This suggests that it may be worth increasing liver cancer screening in individuals with both chronic HBV infection and diabetes. Interestingly, in studies where metformin was given as a treatment for diabetes, the association of diabetes with risk of liver cancer was weakened, warranting further investigation.

The full review article can be accessed on the Journal of Viral Hepatitis website.

For more information about liver cancer early detection research in Oxford, see the liver cancer research showcase.

Potential of DNA-based blood tests for detecting pancreatic cancer earlier

Pancreatic cancer is sadly a disease with very poor outcomes and only 7.3% of people survive this cancer for 5 years or longer in England (Cancer Research UK). The majority of patients with pancreatic cancer are diagnosed too late for potentially curable treatment to be applied and so there is an urgent need to detect pancreatic cancers earlier with the aim of improving outcomes from this disease.

One strategy for earlier detection is to screen people before they experience any symptoms using a minimally invasive test such as a blood test to look for indicators of pancreatic cancer. Published in the journal Cancers, Dr Shivan Sivakumar (Department of Oncology and Oxford University Hospitals NHS Trust) and colleagues Dr Jedrzej Jaworski (University of Oxford) and Dr Robert Morgan (University of Manchester and Christie NHS Foundation Trust) review the potential of cancer DNA in the blood as an effective and reliable indicator of pancreatic cancer.

DNA from cancer cells can be distinguished from DNA from healthy tissue using either genetic or epigenetic methods (or a combination of both). In the genetic method, cancer can be detected by looking at the DNA sequence, with the presence of cancer-associated DNA sequence changes called mutations or altered fragmentation patterns indicating cancer. In the epigenetic method, chemical modifications to the DNA called methylation are measured that have been shown to change in cancer.

In this review, the authors discuss the potential for DNA-based blood tests for pancreatic cancer earlier detection, the challenges that still need to be overcome and the future perspectives.

Read the full review article on the Cancers journal website.

Pancreatic cancer blood test research in Oxford

In Oxford, we have a couple of research projects underway to study both the genetic and epigenetic methods for detecting pancreatic cancer-derived DNA in the blood.

Dr Siim Pauklin (Botnar Research Centre, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences) is working to identify a pancreatic cancer-specific DNA signature. In the long-term, it is hoped that this can be used as the basis of a simple blood test to detect the presence of pancreatic cancer earlier. This project is funded by the Pancreatic Cancer UK Research Innovation Fund. Read more about Siim’s project here.

Dr Chunxiao Song (Ludwig Institute for Cancer Research) is collaborating with Dr Shivan Sivakumar to apply his TAPS technology to pancreatic cancer. TAPS is a new, more sensitive method for detecting methylation on DNA, which gives it an advantage over other detection methods for measuring the very small levels of circulating tumour DNA in the blood. The team are working to identify patterns of DNA methylation that are specific for pancreatic cancer with the aim of developing this into a diagnostic test. Read more about Chunxiao’s and Shivan’s project on the CRUK Oxford Centre website.

Research projects to detect pancreatic cancer in the blood through non-DNA markers are also in progress in Oxford.

Bioengineering the human gut

The ability to grow human tissue in the lab has progressed rapidly over recent years, promising a new frontier for regenerative medicine and experimental modelling of human diseases, including for early detection research. The in vitro culture of the gastrointestinal (GI) tract is particularly attractive due to the prevalence of disorders of this tissue, including irritable bowel disease and cancer, and the need for replacement tissue for transplantation. However, the number of different cell types and the precise arrangement required to form a functional tubular GI tract makes this tissue challenging to grow in the lab.

A common strategy for constructing GI tracts is to use a scaffold material to establish the tissue structure, which is then seeded with human cells that stick to the structure and grow. Various different scaffold materials have been tested but there is still room for improvement.

To generate GI tracts that are representative of those in the body, Dr Linna Zhou and Dr Carlos Ruiz Puig from Professor Xin Lu’s (Ludwig Institute for Cancer Research) and Professor Hagan Bayley’s (Department of Chemistry) labs have researched the use of collagen protein as a scaffold. In their paper published in the journal Advanced Functional Materials, the researchers developed a new and simple method to construct tubular GI tracts from collagen without some of the additional steps that have been used by others previously.

Their method uses precise 3D printing of droplets containing cells and collagen, which then form into continuous tubes. Importantly, the complex tubular shape was produced by controlling the density of the fibroblasts – cells that produce the structural framework for animal tissues – seeded at different sections of the GI tracts.

They generated different types of GI tract (intestine and stomach) by seeding the collagen structures with human cells from different tissues and were able to demonstrate the important layered structural features found in the natural GI tract. The engineered stomach tissues were susceptible to infection with the cancer-associated bacteria Helicobacter pylori, providing a valuable early disease model.

These advanced bioengineered GI tracts therefore show great potential both for use as a disease model in biological research and for regenerative medicine. Future plans include using these engineered GI tracts to study GI cancer development and progression. Understanding more about the biology of early cancer will assist with strategies for early detection. This model will also be used to test therapeutic agents.

Full article on the OxCODE website.

Using AI to improve the quality of endoscopy videos

Cancers detected at an earlier stage have a much higher chance of being treated successfully. The main method for diagnosing cancers of the gastrointestinal tract is endoscopy, when a long flexible tube with a camera at the end is inserted into the body, such as the oesophagus, stomach or colon, to observe any changes in the organ lining. Endoscopic methods such as radiofrequency ablation can also be used to prevent pre-cancerous regions from progressing to cancer if they are detected in time.

Unfortunately, during conventional endoscopy, the more easily treated pre-cancerous conditions and early stage cancers are harder to spot and often missed, especially by less experienced endoscopists. Cancer detection is made even more challenging by artefacts in the endoscopy video such as bubbles, debris, overexposure, light reflection and blurring, which can obscure key features and hinder efforts to automatically analyse endoscopy videos.

In an effort to improve the quality of video endoscopy, a team of researchers from the Institute for Biomedical Engineering (Sharib Ali and Jens Rittscher), the Translational Gastroenterology Unit (Barbara Braden, Adam Bailey and James East) and the Ludwig Institute for Cancer Research (Felix Zhou and Xin Lu) have developed a deep-learning framework for quality assessment of endoscopy videos in near real-time. This framework, published in the journal Medical Image Analysis, is able to reliably identify six different types of artefacts in the video, generate a quality score for each frame and restore mildly corrupted frames. Frame restoration can help in building visually coherent 2D or 3D maps for further analysis. In addition, providing quality scores can help trainees to assess and improve their endoscopy screening performance.

Future work aims to employ real-time computer algorithm-aided analysis of endoscopic images and videos, which will enable earlier identification of potentially cancerous changes automatically during endoscopy.

This work was supported by the NIHR Oxford Biomedical Research Centre, the EPSRC, the Ludwig Institute for Cancer Research and Health Data Research UK.

(1)Real-time detection of artefacts of different types including specularity, saturation, artefact, blur, contrast, bubbles, each indicated with different coloured boxes on the image. Artefact statistics and quality score are generated. Frames suitable for restoration of blur, artefact and saturation are identified. (2) Fast and realistic frames restoration. Discriminator-generator networks are used. (3) Restoration of the entire video. Before restoration, many more frames were corrupted and fewer frames were of good quality compared to after restoration when over 50% of frames had been restored.

Graphical abstract summarising the main messages of the publication. © The Authors CC-BY-NC-ND 4.0

The search for pancreatic cancer biomarkers

Pancreatic cancer has the lowest survival rate of any cancer in the UK, due in part to the limited ability to diagnose it at an early stage. Earlier detection of pancreatic cancer is a major priority of cancer researchers, in order to identify tumours at an earlier stage when they are more easily treatable.

Identifiable biomarkers (naturally occurring molecules which can be related to the presence of a cancer) is one method that can be used to predict or diagnose pancreatic cancer. Currently, the previously-identified biomarkers available have a limited ability to accurately diagnose pancreatic cancer. There is a need to identify new biomarkers that more accurately predict the presence of pancreatic cancer for improved earlier diagnosis.

Dr Christiana Kartsonaki, a senior scientist at the MRC Population Health Research Unit in the Nuffield Department of Population Health, is leading investigations on the potential of protein biomarkers in blood, using data from the China Kadoorie Biobank. Blood samples from over 500,000 Chinese adults have been collected as part of this data set, allowing researchers to identify circulating proteins in the blood and see which individuals went on to develop pancreatic cancer.

During 9 years of follow-up, 700 individuals from the ~500,000 went on to develop pancreatic cancer. From their blood samples, Dr Christiana Kartsonaki and her colleagues will be able to identify a number of protein biomarkers that are associated with a future risk of pancreatic cancer. This study builds on their previous work on the associations of metabolic and lifestyle factors with risk of pancreatic cancer.

Identification of biomarkers may prove very useful in the establishment of strategies to utilise these proteins in predicting the development of pancreatic cancer and help with its diagnosis.

Results from this research will likely be published next year. Once biomarkers are identified, this work may help researchers understand the role that individual proteins play in the development and progression of pancreatic cancer, and whether they may have therapeutic potential as drug targets in its treatment.

About the study

This study is funded by the Nuffield Department of Population Health, Pancreatic Cancer UK and the CRUK Oxford Centre. It was co-led by Associate Professor Michael Holmes, Professor Zhengming Chen, Dr Yuanjie Pang and Dr Christiana Kartsonaki.

Early stage ‘red flag’ symptoms for pancreatic cancer

Pancreatic cancer is the 11th most common cancer in the UK. However, the mortality rate remains the highest among all cancers, due to diagnosis at late stages. As a result, less than 20% of patients diagnosed with pancreatic cancer are suitable for surgery with curable intent, and only 16% of patients are likely to live longer than a year after diagnosis.

The survival rate is much higher when the cancer is found at an earlier stage. However, there is no national screening programme or reliable tests for pancreatic cancer. Most symptoms reported to be associated with pancreatic cancer are vague and non-specific, which increases the difficulty of general practitioners (GPs) recognising early signs of pancreatic cancer in the community.

Identifying red flag symptoms

To address this research gap, the ADEPTS study was set up, using linked data from GP records, hospital records, ONS mortality data, and cancer registry data from the QResearch database, with the aim to better understand the symptom profile of pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine neoplasms (PNEN, a rarer type of pancreatic cancer). The ADEPTS study is run by researchers from the Nuffield Department of Primary Care Health Sciences.

This is a case-control study. The team identified about 23600 patients diagnosed with PDAC and 600 patients with PNEN from the QResearch database in the last 20 years.

Up to 10 patients without cancer (controls) with the same age, sex, calendar year registered in the same general practice were identified and matched with each case (patient diagnosed with PDAC/PNEN). The team also identified a list of potential symptoms that may be associated with PDAC and/or PNEN through literature review, leading research charities like Cancer Research UK and Pancreatic Cancer UK, NICE guidelines, and patient representatives. The team explored the presentation of symptoms in different time windows (e.g. within 3 months, 6 months, 1 year, and 2 years before diagnosis) and the association with the diagnosis of PDAC and PNEN.

Through this analysis, a profile of symptoms that are associated with PNEN and PDAC can be determined, which can be used to update the QCancer (Pancreas) prediction model. The model can be used in primary care settings to help GP identify patients who are at high risk and investigate these patients in a timely manner.

So far, the team have already identified a number of red flag symptoms. The results will be published next year. They have also identified certain ethnic groups that are less likely to develop PDAC, along with certain co-morbidities (other health conditions beside pancreatic cancer) that could also be used to predict cancer risk.

Increasing public awareness and GP pathways

After publishing their study findings, the research team hope to engage with relevant stakeholders, to increase public awareness of symptoms that are associated with pancreatic cancer, such as weight loss, abdominal pain, jaundice, etc.

In conjunction with this, the ADEPTS study is working with GPs to improve better direct access to diagnostic investigation resources, such as ultrasound, CT scans and MRIs. This way, when a patient presents to their GP with symptoms, they can be quickly and accurately diagnosed in the hopes of identifying PDAC earlier.

Improved GP assessment tools are being developed as part of the study. By improving the identification and quantification of red flag symptoms associated with pancreatic cancer, the ADEPTS study will help GPs ensure that right patients are sent for the right investigatory methods, making efficient use of scarce or expensive resources such as MRI scans. By communicating its findings with GPs and patients, the ADEPTS study will increase public awareness of symptoms and prompt earlier diagnosis through investigation. Look out for the published findings next year.

About this study

 The ADEPTS study is funded by Pancreatic Cancer UK, and conducted by Weiqi Liao, Ashley Clift, Martina Patone, and Julia Hippisley-Cox from the Nuffield Department of Primary Care Health Sciences.

The QResearch database is founded and directed by Prof Julia Hippisley-Cox, who is the Principal Investigator of the ADEPTS project. External collaborators include Prof Carol Coupland (Medical Statistics) from the University of Nottingham, and Prof Stephen Pereira (Hepatology & Gastroenterology) from University College London.

Oxford Cancer alumni’s biotech success

Scenic Biotech was founded in March 2017 as a spin-out of the University of Oxford and the Netherlands Cancer Institute. The company is based on the Cell-seq technology developed by co-founders Sebastian Nijman and Thijn Brummelkamp in their academic labs.

Cell-seq is a large-scale genetic screening platform that allows the identification of genetic modifiers – or disease suppressors – that act to decrease the severity of a disease. These disease-specific genetic modifiers are difficult to identify by more traditional population genetics approaches, especially in the case of rare genetic diseases. By mapping all the genetic modifiers that can influence the severity of a particular disease, Cell-seq unveils a new class of potential drug targets that can be taken forward for drug development.

In a deal worth $375m, Scenic Biotech has recently entered into a strategic collaboration with Genentech, a member of the Roche Group. This will enable discovery, development and commercialisation of novel therapeutics that target genetic modifiers.

Detecting pancreatic cancer through blood tests

Pancreatic ductal adenocarcinoma (PDAC) makes up 95% of all pancreatic cancer cases and has the lowest survival rate, and early diagnostic methods have yet to be developed. As a result, diagnosis often comes at a later stage when treatment options are limited and prognosis is poor.

Diagnosis at this stage often comes from imaging techniques followed by tissue biopsies, which are not appropriate options to use as standardised, early screening methods. New ways to diagnose PDAC at an earlier stage are needed, without the use of invasive procedures.

Liquid biopsies are becoming a more popular option to fill this demand. Taking a blood sample is minimally invasive, quick, and can tell us a lot of information about a person from their cfDNA (cell free DNA). cfDNA is released from cells and circulates in the blood, containing information about the cell they come from.

Methylation on cfDNA often appears in cancer patients, making it an effective biomarker that can be used to diagnose the presence of cancer with high accuracy and specificity about the cancer (such as location). The concept has many applications, including in the earlier diagnosis of PDAC.

The identification of these biomarkers in blood is often limited to the technology used, with DNA being damaged by the harsh chemicals that are used in the processing. The recent development of TAPS technology at the University of Oxford has helped to overcome this, using a bisulphate-free method, and making it a perfect method for PDAC biomarker identification.

DPhil students Paulina Siejka-Zielinska and Felix Jackson and Postdoctoral Researcher Jingfei Chang from Dr Chunxiao Song’s lab in collaboration with Dr Shivan Sivakumar (consultant medical oncologist) have been investigating TAPS as a method to identify PDAC biomarkers. Using blood samples from PDAC patients and healthy individuals, they are applying TAPS technology to prove that it can be used to accurately detect pancreatic cancer biomarkers in cfDNA.

Preliminary results from this study suggest that cfDNA methylation can be used for the identification of PDAC, as well as being able to accurately distinguish between pancreatic cancer and other pancreatic disorders that effect the DNA, such as pancreatitis.

If this is the case, then the results from this study will make for solid grounds for the application of TAPS in the earlier screening for pancreatic cancer.

About the Song Lab

The Song Lab combine various chemical biology and genome technologies to develop novel tools to analyse the epigenome. The lab apply these tools to two main research areas: the use of epigenetic modifications in circulating cell-free DNA from the blood for non-invasive disease diagnostics including early detection of cancer, and understanding the contribution of epigenetic heterogeneity in cancer development.

Most recently, the TAPS technology developed at the Song Lab has led to the creation of the start up Base Genomics, which has been launched to set a new gold standard in DNA methylation detection using this TAPS technology. Base Genomics will initially focus on developing a blood test for early-stage cancer and minimal residual disease. You can read more about it here.