Choosing the most effective treatment for people with triple-negative breast cancer (TNBC) is often challenging because the tumours can behave very differently at the molecular level. Now, researchers have developed an artificial-intelligence-based 'virtual cell model' that can help in choosing the best treatment for this aggressive form of breast cancer ' by predicting how an individual's tumour cells respond to various drugs. TNBC cells lack receptors to hormones oestrogen and progesterone, as well as to a protein that controls cell growth. This makes the condition harder to treat because hormone and targeted therapies cannot target the tumour cells. In experiments using biopsies taken from individuals with TNBC, the new model showed promising results in identifying the same drugs that would prove to be effective when given to people. The authors say this raises the possibility of more personalized care for TNBC, which accounts for 15'20% of breast cancer cases. 'This is the first...
learn more
