From Lab bench
to Bed

Worldwide, 25% of female cancer patients are diagnosed with breast cancer. The majority of those women are positive for the expression of the estrogen receptor. This means that their cancer cells grow in the presence of the hormone estrogen. Generally, this is a “good” prognosis, since there are treatment options available, such as endocrine treatment with drugs as tamoxifen and fulvestrant for premenopausal women or aromatase inhibitors for postmenopausal women. These drugs block or inhibit the action of the estrogen receptor or lower estrogen levels and thereby prevent the tumour from growing further. However, over 20% of the patients expressing hormone receptors show treatment relapse within 10 years to endocrine therapies. To improve and personalize the treatment for breast cancer patients, it is important to understand why some patients become resistant where others do not. Why do cancer cells initially expressing hormone receptors, become resistant to hormone therapy?

This challenge, of how therapy resistance develops in estrogen receptor positive breast cancer is the key motivation for our scientific research consortium EpiPredict. A team of 12 PhD students from several European institutes and companies combine the latest technologies and insights to find out why these resistant tumours have a different behaviour.

The answer may be found in the epigenetics of the cell. Epigenetics is the study of changes to the DNA structure that activates or inactivates genes. Interestingly, those modifications do not change the DNA code and can therefore be reversed. So far, most scientists have focussed only on the DNA code of the tumour, to look for mutations in genes that may explain the resistance. But with only genetics the appearance of resistance cannot fully be explained and therefore it is necessary to go beyond the genetic code.

To study epigenetics in these resistant tumours, we bring together a broad variety of disciplines like bioinformatics, modelling as well as laboratory research. We will determine the status of several epigenetic markers in different cancer cell lines and in patient tissue. Markers are like flags that are placed at particular places in the genome. The patterns of flags will be sometimes similar and sometimes different among the different samples. Based on these (“flag”) profiles we will test models to see if we can find a correlation of certain marked places in the genome between samples that do respond or do not respond to therapy.

The interplay between different research fields offers the advantage of having many researchers working synergistically towards a common goal, each bringing its own specific knowledge into the group of a field or technique. This also stresses the importance of good communication between EpiPredict consortium members to ensure that results from separate institutions are comparable.

However, scientific collaborations are not enough to make our research successful. We are also dependent on the available tissue from patient cohorts that we can use in our research.

Beyond the need for materials, we aim to let future patients benefit from any of our findings. Our results should be translated from the laboratory into the clinic to be able to improve patients’ treatment plans. Note that — like any scientific research — this is a leap in the dark and it will take many years of thoroughly testing before patients may benefit from it. This doesn’t take away that communication between lab and clinic should be constant to keep the researchers informed what the actual need in the clinic is. Thus, good collaboration between the lab and the clinic is equally important.

To review these challenges, we will present the first Science café at the German cancer research center (DKFZ) in Heidelberg, Germany, on January 26th 2017. A panel discussion between EpiPredict members and experts in molecular biology and health research will address key questions and challenges regarding epigenetic research, the impact of personalised medicine on patients and communication in science, particularly within our consortium and between researchers and clinicians. EpiPredict would like to invite all who are interested to attend.

Reference:
http://www.wcrf.org/int/cancer-facts-figures/data-specific-cancers/breast-cancer-statistics'