Genetic changes may predict relapse of breast cancer, study finds



[ad_1]

bad cancer

Mammograms showing a normal bad (left) and a bad with cancer (right). Credit: public domain

Scientists have identified genetic modifications that can predict the risk of relapse of bad cancer in women taking a common type of hormone treatment.

The results could in the future help identify women at risk so that they can benefit from alternative treatments to reduce their risk of developing secondary bad cancer, which is incurable.

Hormone therapy has improved the survival rates of patients with bad cancer. In some cases, however, tumors can come back even decades later. Little is known about the resistance of tumors to treatment.

Researchers at the University of Edinburgh have studied tumor samples of bad cancer patients who were following a type of hormone therapy called aromatase inhibitor for two years. None of the women had undergone surgery to remove their tumors.

The team examined which genes were turned on and off in the tumors during treatment.

Tumor samples were taken before the start of hormone therapy, in the first weeks and after four months of treatment. This allowed scientists to see how treatment affected tumors over time.

They discovered that hormone therapy almost immediately induced changes in the genes that were activated in the tumors. These differences have become more pronounced over time.

Crucially, they found subtle differences in changes in tumors of women whose cancer had become resistant to treatment.

The team discovered chemical signatures, called epigenetic modifications, absent from tumors developing resistance to hormone therapy, but present in tumors that had begun to grow again after an initial contraction.

These differences were present in the first weeks of hormonal treatment, suggesting that it would be possible to predict which women would risk a relapse.

The study was conducted at the Institute of Genetics and Molecular Medicine at the Center for Medical Research and at the Cancer Research Center in Edinburgh, at the University of Edinburgh. It is published in Breast cancer research and was funded by Breast Cancer Now.

Dr. Andy Sims, of the Institute of Genetics and Molecular Medicine at the MRC, said: "Resistance to treatment is difficult to study and laboratory experiments often do not look like the situation of patients. is the first time we are able to study the genetic changes in tumors of individual patients over time.

"We hope that the results will help develop new tests to predict which hormone-treated women are at risk of relapse, so that they can be offered alternative treatments."

Dr. Simon Vincent, Research Director at Breast Cancer Now, which helped fund the study, said, "This is a promising discovery that could help us better understand how certain bad cancers become resistant to treatment and what we can do about it Resistance to drugs is a major barrier to overcome if we want to finally stop women from dying from bad cancer.

"It is really encouraging to see that this study has identified epigenetic changes that could help predict which patients are most likely to return to cancer." We hope that further research will now help to accurately identify the onset of these cancers. changes and find ways to target them, allowing us to intervene at the right time.

"Through such research, we hope to be able to one day determine when treatments become less effective and when a change in treatment might be appropriate."


Potential Therapy Identified for Aggressive Breast Cancer


More information:
Cigdem Selli et al, Molecular changes in bad cancer treatment with prolonged neoadjuvant letrozole: distinction of acquired resistance of dormant tumors, Breast cancer research (2019). DOI: 10.1186 / s13058-018-1089-5

Provided by
University of Edinburgh

Quote:
Genetic changes could predict relapse of bad cancer, study finds (January 22, 2019)
recovered on January 22, 2019
from https://medicalxpress.com/news/2019-01-gene-bad-cancer-relapse.html

This document is subject to copyright. Apart from any fair use for the purposes of studies or private research, no
part may be reproduced without written permission. Content is provided for information only.

[ad_2]
Source link