Researchers have developed a promising new way to predict how patients with one of the most aggressive forms of breast cancer will respond to chemotherapy.
The discovery could help doctors choose treatments more effectively and avoid unnecessary side effects for patients unlikely to benefit.
The study, led by scientists at The University of Texas MD Anderson Cancer Center and published in the journal Cell Reports Medicine, focuses on triple-negative breast cancer (TNBC).
This type of cancer does not respond to hormone therapy or drugs that target common breast cancer markers, making chemotherapy one of the main treatment options.
However, not all patients respond equally well, and until now it has been difficult to predict who will benefit.
The new approach uses advanced computer analysis to study gene activity within tumors while also considering the tumor’s surrounding environment, known as the microenvironment. Tumors are not made up of cancer cells alone.
They also contain immune cells, connective tissue, and other normal cells that influence how the cancer behaves and how it responds to treatment. Earlier prediction methods mostly looked at the types of cells present but did not fully account for how gene activity changes within that complex environment.
To address this gap, the researchers created a new biomarker called TmS, which measures the total activity of messenger RNA in tumor cells compared with nearby non-tumor cells. Messenger RNA carries instructions from DNA that tell cells how to function.
Cancer cells often have abnormal numbers of chromosomes, which affects gene activity. The TmS marker takes this into account, offering a more accurate picture of how aggressive a tumor is and how it might respond to chemotherapy.
The team tested the new method using data from 575 patients with triple-negative breast cancer from different ethnic backgrounds. The TmS biomarker successfully grouped patients into two categories. Those with high TmS levels tended to have a better outlook and were more likely to respond well to chemotherapy. Patients with low TmS levels had a poorer prognosis and were less likely to benefit from standard treatment.
The results also showed that the biomarker worked across diverse populations, although there were differences in tumor environments between Western and Asian patients. This suggests that doctors may eventually be able to tailor treatments even more precisely based on both biological and population factors.
Although the test still needs further validation before it can be widely used in hospitals, researchers say it represents an important step toward personalized cancer care. By identifying which patients are most likely to respond to chemotherapy, doctors could choose more effective treatments from the start and spare others from treatments that may not help.
Experts hope that advances like this will move cancer treatment away from a one-size-fits-all approach and toward precision medicine, where therapy is customized for each patient’s unique tumor.
