Over recent months we’ve written about exciting new research looking at how the genetic makeup of an individual patient’s cancer shifts and evolves as the disease develops and spreads.
At the moment the only way to monitor this is to take a sample of a tumour (called a biopsy) and test it in the lab. But this approach isn’t perfect – for a start, a doctor needs to be able to reach a tumour in order to take a biopsy, which often has to be done surgically. And monitoring the disease over time means repeated biopsies, which may need to be taken from multiple places if the cancer has spread.
Wouldn’t it be fantastic if there was a simple blood test that could reveal the genetic fingerprints of a tumour, no matter where it’s located in the body?
This solution may be closer than you think. Although it’s still at an early stage and needs more work, scientists at our Cambridge Research Institute have developed a blood test that can detect genetic mutations in tiny fragments of DNA shed into the bloodstream by dying cancer cells. And it has the potential to be a game-changer for the way the disease is monitored and treated – and maybe even diagnosed – in the future.
The Cambridge team has just published their results in the journal Science Translational Medicine, so let’s look in a bit more detail about how the test works and where this research might take us in the future.
What did they do?
When cancer cells die – either as a result of chemotherapy or radiotherapy, or due to ‘natural causes’ – they shed tiny fragments of their DNA into the bloodstream known as circulating tumour DNA (ctDNA). But because cancer cells usually have many genetic changes compared to healthy cells, some of these ctDNA fragments will be very different from the corresponding DNA sequence in healthy cells.
Although scientists have been aware of the existence of ctDNA for several years, it’s not been easy to analyse in great detail. The tumour DNA fragments are very small – only around 150 ‘letters’ (basepairs) long – and levels in the bloodstream are relatively low. But by combining some of the latest technology, the researchers developed a way of analysing ctDNA from just a couple of millilitres of blood.
To look at gene faults in ctDNA, the researchers first made multiple copies of all the DNA fragments present using a technique called PCR – a bit like taking multiple photocopies of all the pages in a recipe book. Next, they made copies of these copies, but focusing on specific genes known to be involved in cancer and tagging each of them with a clever molecular ‘barcode’ – to use our book analogy, it’s like making further copies of specific recipes while ignoring the rest.
Finally, the researchers read (sequenced) the DNA letters in each of these copied genes, looking for critical faults – analogous to reading through each individual photocopied recipe and searching for typos.
What did they find?
Before they looked at ctDNA, the researchers tested their new technique, called TAm-Seq, to look at six genes implicated in cancer in stored samples of ovarian tumours. Samples like this are normally quite degraded, and the DNA is broken into small fragments similar to those found in ctDNA. The researchers found that they could consistently get good quality data with very few mistakes.
Next, they went on to test whether the technique worked on ctDNA using a ‘mock’ sample created by mixing plasma from healthy volunteers (plasma is the fluid left over from blood when red and white blood cells are removed, and contains the ctDNA). When that worked, the team went on to look at more than 60 plasma samples from nearly 40 women with an aggressive form of ovarian cancer, and could pick up key gene faults in ctDNA with a high degree of accuracy.
Importantly, the team detected a fault in the EGFR gene in a sample from a woman whose cancer had come back after treatment but that wasn’t present in her original tumour biopsy. This shows that the technique might be useful for monitoring how tumours evolve over time, picking up new gene faults as they become resistant to drugs or radiotherapy.
Next, the researchers also measured how the levels of certain faulty genes present in ctDNA fluctuated over time in two women who were being treated for advanced ovarian cancer and one breast cancer patient.
Impressively, their technique could detect a drop in the relative proportions of faulty DNA following chemotherapy, showing that the number of cancer cells in the body had dropped. But the proportion of faulty ctDNA began to rise again once they stopped treatment, revealing that the cancer was growing again.
Finally, the team used TAm-Seq to look at samples from a woman who’d developed both ovarian and bowel cancer. She had surgery to remove both tumours at the same time, but five years later found a lump in her tummy. For various reasons, it wasn’t possible to do a surgical biopsy to find out whether this was the return of the ovarian or the bowel cancer.
The researchers tested her ctDNA, and discovered that it bore the same gene faults as her original ovarian cancer, but not the original bowel tumour. Fortunately for the woman, her doctors had already started her on a course of ovarian cancer chemotherapy, based on other factors, but had this test been available at the time it would have clearly helped their decision.
How could this be useful?
One of the biggest challenges we face in treating cancer effectively is the fact that tumours evolve and change over time, picking up new faults in their genes as they spread through the body and become resistant to treatment.
And as we discussed in our posts about recent research from Professors Charles Swanton and Mike Stratton, the discovery that the genetic fingerprint of tumours change over time within an individual patient raises big questions about how to pick the most appropriate drugs from the growing arsenal of targeted treatments.
At the moment, there isn’t a good way to monitor these genetic changes, except through repeated, invasive biopsies. So if this blood test lives up to its initial promise, then it could provide a simple way to help doctors analyse what’s actually going on within a patient’s body.
Not only would that help doctors pick the most appropriate treatment, based on the genetic signatures they find, but it could also be a quick way to see whether that therapy is working. And it could also be a useful tool to help researchers select patients for clinical trials of brand new agents that target specific gene faults in cancer cells.
At the moment this test just looks at a relatively small panel of specific genes known to be involved in different types of cancer. But advances in technology – along with the heaps of data being generated by large-scale cancer sequencing projects such as ICGC – mean that maybe one day it’ll be possible for doctors to sequence all the cancer genes in a patient’s ctDNA on a regular basis and use this as the basis for ‘real time’ decisions on treatment.
That’s a truly mind-blowing prospect.
There’s also the possibility that the test could be used as a screening tool, picking up genetic changes at the very earliest stages of disease when the chances of survival are much greater. But this would need to go hand-in-hand with imaging technology to ensure that a tumour can be found wherever it is lurking in the body, so the most appropriate treatment can be given.
Before we get too excited, there are some important limitations to be aware of. Firstly, the test isn’t perfect. Although it’s good at picking up DNA typos analogous to spelling mistakes or missing words and paragraphs, it’s bad at detecting particular gene faults known as amplifications. These happen when a gene is duplicated many times, often in ‘driver’ genes that fuel the growth of cancer.
Of course, the technique now needs to be tested in much larger numbers of patients to make sure it can accurately detect changes in their disease. And if it gets that far, there will doubtless be cost implications for rolling it out on a grand scale to cancer patients across the UK.
Although these are big questions, we still welcome this important and exciting step, and we look forward to seeing the results of further research in the not-too-distant future.
Forshew, T. et al (2012). Noninvasive Identification and Monitoring of Cancer Mutations by Targeted Deep Sequencing of Plasma DNA Science Translational Medicine, 4 (136), 136-136 DOI: 10.1126/scitranslmed.3003726