Breast cancer cells. Credit: Jason Caroll, CRI
More than 53,600 women are diagnosed with breast cancer ever year in the UK. And around 1 in 5 of these women have tumours that are classified as ‘HER2 positive’.
That’s because the surface of each breast cancer cell is littered with extra copies of a molecule called the human epidermal growth factor receptor 2 (HER2). And this leaves the cells extremely sensitive to signals that cause them to grow and divide.
The majority of women diagnosed with this type of breast cancer have treatment aimed at interfering with these signals, the most common of which is trastuzumab (Herceptin).
Doctors can tell whether a patient’s breast cancer is ‘HER2 positive’ – and whether they should be given HER2 targeting drugs – by analysing a sample from their tumour and counting the number of HER copies present using a molecular labelling technique called immunohistochemistry.
At the moment, this is the main way doctors classify breast cancers as ‘HER2 positive’, ‘HER2 negative’ or otherwise.
But in a study published today, Cancer Research UK scientists at King’s College London, in collaboration with scientists at the CRUK/MRC Oxford Institute for Radiation Oncology, have shown how a new imaging technique could spot cancers that might respond to HER2 targeted treatments with greater accuracy.
The HER family of proteins
HER2 is one of four similar molecules, all of which are involved in helping cells grow when the conditions are right.
But if things go wrong, cells can start to misbehave. For example, if cells don’t make enough of these molecules, it can lead to neurodegenerative disorders like Alzheimer’s disease. Conversely, if they make too much, it can cause cancers to develop.
When they receive an external signal, HER molecules stick together in pairs, called dimers, causing their shape to change. And this shape-shift activates a range of different cellular processes, causing the cell to divide.
But the different HER proteins can pair up with each other, to have different effects on a cell. So studying how and whether these molecules stick together is important for understanding how cancer cells might be growing.
Studying HER proteins
To study how HER proteins stick together, scientists use a range of different techniques – the gold standard of which is a combination of two techniques called fluorescence lifetime imaging microscopy (FLIM) and Förster Resonance Energy Transfer (FRET) – collectively called FLIM/FRET.
Using FLIM/FRET, scientists can tell whether two proteins are really, really close together (in technical terms, it tells whether they’re within less than 10 nanometres of each other – around the width of a DNA helix).
In this study the researchers – led by Professor Tony Ng, at King’s College London and University College London – examined the way HER molecules paired up on the cells’ surface. In particular, they were looking at interactions between HER2 and its molecular cousin – HER3.
They also wanted to find out if the number of dimers present in a breast tumour could tell them anything about how well a patient’s tumour might respond to treatment.
HER2/HER3 – a prognostic dimer?
Based on an analysis of 131 breast cancer samples, Ng’s team found they could relatively easily – and very accurately – identify the number of HER2/HER3 dimers present in these samples.
They also found that patients with high numbers of HER2/HER3 dimers didn’t necessarily have high levels of the HER2 or HER3 proteins.
They also showed for the first time that neither HER2 nor HER3 protein levels are an accurate indication for the amount of HER2/HER3 dimers present in a breast cancer tissue sample.
This is important because until now, it was presumed that to have high numbers of dimers, there had to be high levels of both molecules.
It also showed that women who have low levels of HER2 (‘HER2 negative’) can still form cancer-boosting HER2/HER3 dimers, which could be important when it comes to making decisions around treatment.
But could the number of dimers present in a patient’s breast cancer sample help predict how well a patient was likely to do?
When Ng’s team looked at the outcomes of each of the patients whose tumour samples had been included in the study, they found that the disease was more likely to spread – and come back – in patients with a high number of HER2/HER3 dimers.
This meant that, overall, these patients had a worse outlook.
A potential new treatment marker
Armed with these findings, the researchers turned their attention to what this could mean for breast cancer treatment.
Ng and his team believe that in the future, as well as using FLIM/FRET to determine whether a breast cancer patient’s tumour has HER2/HER3 dimers or not, it could also be used to guide treatment of these patients.
At the moment, HER2 targeted treatments are only given to women whose cancers are classified as ‘HER2 positive’.
But these new findings indicate that patients with high numbers of HER2/HER3 dimers might also benefit from HER2 targeted treatment, regardless of whether or not they have high levels of HER2.
“This could help us pick up patients who might benefit from HER2 targeted treatments, but have in the past been overlooked,” says Ng.
“As well as identifying more patients who could benefit from these targeted treatments, we may also be able to predict which patients won’t respond to these drugs, and so avoid prescribing them unnecessary treatment.”
They hope that in the future, this imaging technique could be used alongside other tests to determine the most appropriate treatment for women with breast cancer.
It’s early days
Finding a new way of grouping patients so they get the most accurate and appropriate treatment for them is always exciting and promising.
But, equally, it requires a lot of testing to make sure it works.
The next step is to run clinical trials to see whether this combination of imaging techniques can be used in the clinical setting and to help patients
– Professor Tony Ng, Cancer Research UK
And the researchers will now be testing this approach in a larger group of patients to confirm their findings.
Clinical trials will now have to be carried out to test whether grouping patients and treating them based on the number of HER2/HER3 dimers their tumour has truly offers a new treatment option in ‘HER2 negative’ patients.
“The next step is to run clinical trials to see whether this combination of imaging techniques can be used in the clinical setting and to help patients,” says Ng.
And he believes the approach could also be adapted for other cancers that may be fuelled by the same molecules.
“We hope that one day it could not only improve treatment for breast cancer patients but also for other cancers – including bowel and lung cancer,” he adds.
So it’s early days for this research, but nonetheless it holds promise and could help improve treatment for breast cancer patients in the future.
Weitsman, G., et al. (2014). HER2-HER3 dimer quantification by FLIM-FRET predicts breast cancer metastatic relapse independently of HER2 IHC status. Oncotarget. DOI: 10.18632/oncotarget.9963