NCITA: a new consortium on cancer imaging

Cancer imaging is an umbrella term that defines diagnostic procedures to identify cancer through imaging – such as scans via x-rays, CT scans and ultrasounds. There is no single imaging test that can accurately diagnose cancer, but a variety of imaging tests can be used in the monitoring of cancer and planning of its treatments.

What is NCITA?

NCITA – the UK National Cancer Imaging Translational Accelerator – is a new consortium that brings together world leading medical imaging experts to create an infrastructure for standardising the cancer imaging process, in order to improve its application in clinical cancer treatment.

Research and medical experts from the University of Oxford have come together with UCL, University of Manchester, the Institute of Cancer Research, Imperial, Cambridge University and many more to create this open access platform.

How will NCITA help cancer research?

On top of bringing together leading experts in cancer imaging to share their knowledge, the NCITA consortium will create a variety of systems, software and facilities to help localise and distribute new research and create a centralised location for cancer-image data to be analysed.

NCITA will in include a data repository for imaging, artificial intelligence (AI) tools and training opportunities – all of which will contributing to a revolution in the speed and accuracy of cancer diagnosis, tumour classification and patient response to treatment.

The NCITA network is led by Prof Shonit Punwani, Prof James O’Connor, Prof Eric Aboagye, Prof Geoff Higgins, Prof Evis Sala, Prof Dow Mu Koh, Prof Tony Ng, Prof Hing Leung and Prof Ruth Plummer with up to 49 co-investigators supporting the NCITA initiative.  NCITA is keen to expand and bring in new academic and industrial partnerships as it develops.

Go to the NCITA website to stay up to date of news about cancer imaging research.

For more information on this exciting new initiative, see the media release about the NCITA launch here.

What is a clinical trial? – new video series

Discover what it means to take part in a cancer treatment clinical trial with this new video series

The Early Phase Clinical Trials Unit (EPCTU) is a specialist unit that supports the transition of cancer research findings into clinical applications for helping treat cancer.

The unit integrates oncology and haematology findings and applies them through clinical trials, with around 150 patients per year recruited into novel cancer therapies. By taking part in the clinical trials, the patients help to contribute to discovering new, more efficient or patient-focused treatments for their type of cancer in the future.

What should I expect?

When a patient is referred to EPCTU, they are often given a lot of information about what it means to be involved in the clinical trial process. This information can often be over-whelming, and in response to a patient satisfaction survey, the EPCTU created the following video series so that patients can better understand the process and how clinical trials effect their daily lives.

Video 1 – before the trial

The first video below touches on the aspects that influence a patient’s consideration in taking part in a clinical trial. Clinical trials deal with new, innovative treatments, and as such, are part of a clinical learning curve.

The video below touches on topics such as time frames and how you can expect to receive information. It’s important to give clinical trials proper consideration and understand what will happen at every stage, before reaching the later screening and eligibility process.

 

 

Video 2 – taking part

The second video is about what to expect after the screening process, once a patient has been recruited onto the trial.

Clinical trials can take a long time, both in the treatment process and the requirements later down the line after treatment. The second video in the series, seen below, outlines what to expect once you are on a trial and the benefits of seeing the trial to the very end.

 

Video 3 – trials at the EPCTU

The final video of the series, coming soon, will explain further about the EPCTU and the facilities in the centre.

It is designed for new patients to find the unit’s location and know where to find everything that they will need during the trial process.

Be sure to check back to our website homepage or this news article to see the final video in the series.

AI research discovers link between smell genes and colon cancer

Research from Dr Heba Sailem, recently published in Molecular Systems Biology, showed that patients with specific smell-sensing genes ‘turned on’ are more likely to have worse colon cancer outcomes.

Through the development of a machine-learning approach to analyse the perturbation of over 18,000 genes, Dr Sailem and her team found that olfactory receptor gene expression may have some effect on the way that colon cancer cells are structured.

Dr Sailem used layers of Artificial Intelligence (AI), including computer algorithms, to detect the changes of cancer cell appearance and organisation when the genes are turned down using siRNA technology. AI played a crucial part of this research, as it allowed for speed and efficient analysis and mapping of cell image data to various gene functions that were studied, which greatly increase the amount of information that can be extracted and reduced human error.

Dr Sailem surveyed over 18,000 genes and found that specific smell-sensing genes called olfactory receptor genes are strongly associated with how colon cancer cells spread and align with each other akin to the changes induced by turning down key colon cancer genes.

The practical patient implications of this research include how we might approach patients with colon cancer, depending on their genetic makeup. In the long run, Dr Sailem hopes that these findings will allow clinicians to survey patient genes, create specific predictions based on their genetics and create tailored treatments to best treat their cancer.

There is already a large body of research into the genes that influence the structure of cancer tissues, but studies such as this might help to find new target genes. For example, by reducing the expression of olfactory genes, we could potentially inhibit cancer cells from spreading and eventually invading other tissues which is the major cause of cancer death

About the Author

Dr Heba Sailem is a Sir Henry Wellcome Research Fellow at the Big Data Institute and Institute of Biomedical Engineering at the University of Oxford. Her research is focused on developing intelligent systems that help further biological discoveries in the field of cancer.

This paper is a result of three years of work, focusing on identifying the role of genetic expression on the spread and management of colon cancer.

Future research

Following this research Dr Sailem hopes to apply this AI approach to a wider range of cancer, to see what genes are associated with and influence cancer tissue structure, proliferation and motility.

For more information about this research, see Dr Heba Sailem’s paper here.