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How a genomics approach to radiotherapy could improve outcomes for prostate cancer patients

Institute of Cancer Research News Feb 07, 2018

Last week saw The Festival of Genomics conference, organized by Front Line Genomics, return to London for 2 days of fascinating talks and discussions about this fast-moving field of science.

As with last year’s conference, cancer was a topic that received a lot of attention. This is because a great deal of cancer research is underpinned by genomics and this is especially true for research undertaken at The Institute of Cancer Research, London.

For example, we regularly use the latest DNA sequencing technologies to let our scientists compare the genetic blueprints of healthy and tumor tissue. Identifying the specific genetic changes that have occurred in different cancers can be a vital step in being able to develop personalized treatments.

The ‘Big RT’ project

At this year’s Festival, the ICR was provided a special opportunity to host a dedicated session about some of the ways that our researchers use genome data to impact on cancer therapies. In this session, four of our early-career scientists spoke about their research projects that use genomics approaches that will hopefully lead to improved cancer treatments.

One of those talks was given by Dr. James Campbell, a Lead Bioinformatician in the Bioinformatics Facility of the ICR’s Cancer Research UK Centre.

James talked about his work on the ‘BigRT project’ that is using genomics data to predict adverse outcomes for prostate cancer patients who are undergoing radiotherapy.

Currently, about a third of prostate cancer patients undergo radiotherapy as part of their treatment and about 20% of those patients will experience toxicity side effects due to the radiotherapy. Because it is impossible to only target the prostate gland, radiation ends up affecting tissues and organs surrounding the prostate.

A path to personalized treatment

Not everyone responds to radiotherapy treatment in the same way, even when given the same amount of radiation. The variation in responses is likely to be due to a large number of small differences in people’s genetic make-up.

James’ research involves looking at datasets from previous radiotherapy treatments for prostate cancer. The key to this approach is to first combine information about individual genetic variations—derived from genome sequence data—with details of radiation doses that were given and the final outcomes of radiotherapy.

By accessing this data for over 1,900 patients, James has helped build a model that can then predict the likely extent of radiation side effects, given an individual’s own set of genetic variants (as well as factoring in details of other clinical factors such as age).

The ultimate goal of this project is to stratify patients into high- or low-risk groups to ensure that they get the radiotherapy treatment that is most suitable for them.

Dr. Bissan Al-Lazikani’s Computational Biology and Chemogenomics Team develops software tools to help cancer drug discovery efforts process the large amounts of data obtained through biomedical research.

‘Radiotherapy is here to stay’

I was impressed by the complexity of approaches that is involved in trying to build this model. James uses many state-of-the-art computational approaches, including several different ‘machine learning’ techniques as well as ‘artificial neural networks’.

This work has resulted in the identification of many specific genetic variants that are associated with the outcomes of radiotherapy in prostate cancer patients. One group of variants (known as single nucleotide polymorphism or SNPs) has been located on chromosome 8. Having a particular DNA variant at these locations can have a ‘protective’ effect, and those patients are less likely to suffer side effects such as rectal bleeding.

Although radiotherapy was first used to treat cancer over 120 years ago, it has advanced dramatically since then leading James to conclude his talk by accepting that “radiotherapy is here to stay” while acknowledging that we can continue to improve the ways in which it is used to treat cancer.

Revolutionary MR-Linac

James cited the example of the revolutionary MR-Linac machine that exists at the Sutton site of the ICR and The Royal Marsden NHS Foundation Trust. It combines two technologies—an MRI scanner and a linear accelerator—to precisely locate tumors, tailor the shape of x-ray beams in real time, and accurately deliver doses of radiation even to moving tumors.

The MR-Linac Unit in Sutton is the first of its kind in the UK and only the fourth in the world and should begin delivering life-changing radiotherapy treatments later this year.

By adopting pioneering technology and utilizing state-of-the-art approaches in computational biology, it seems likely that researchers, such as James, will be helping the ICR deliver smarter and kinder radiotherapy treatments for many more decades to come.

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