Protein analysis identifies predictors of effectiveness of breast cancer treatment
New insights into the multifaceted nature of drug resistance
By mapping the proteins present in breast cancer cells, researchers Donna Debets and Kelly Stecker from the AltelaarLab investigated how one can predict the effectiveness of conventional treatment for HER2 positive breast cancer. The study sheds light on the why and how behind breast cancer's diverse responses to treatment, presenting a step towards personalised oncology. The research is a joint effort of Utrecht University and the Netherlands Cancer Institute and was recently published in Cell Reports Medicine.
Breast cancer is a heterogenous disease, that evolves differently from person to person. Because of the variety in tumors, a certain type of treatment sometimes works for one person, but not for the other. This is also the case with a subtype of breast cancer, HER2 positive or HER2+ breast cancer. Even though all forms of HER2+ breast cancer are triggered by an upregulated protein (the Human Epidermal growth factor Receptor 2 or HER2), 20-40% of the patients suffering from this type of cancer do not respond to HER2-targeted treatment.
How do you know whether treatment will be effective for someone, or not? Donna Debets, Kelly Stecker and colleagues studied what role tumor proteins and their degree of activation play in a patient’s response to the regular, HER2-targeted treatment of HER2+ breast cancer. Using tumor needle biopsies provided by the Netherlands Cancer Institute, they performed a full analysis of all proteins and their expression levels and correlated this data to treatment outcome. With their study, the researchers demonstrated the multifaceted nature of treatment response.
Complex resistance mechanisms
To date, choice of treatment is based on the presence of specific biomarkers in tumor cells. In HER2+ breast cancer, this biomarker is the HER2-protein. According to Maarten Altelaar, head of the AltelaarLab, merely assessing the presence of biomarkers isn’t sufficient to provide appropriate treatment.
Altelaar explains that activation of proteins that are somehow connected to the biomarker should also be taken into account: “The heterogeneity between patients is larger than the information that is currently used in the clinic for determining treatment; the molecular variations are much more diverse.” By looking at the presence of biomarkers as well as their signatures of activation, therapy can be matched better to a patient and it can become clear which patients are prone to risk and need better monitoring.
The role of protein activity
“We looked at a more comprehensive view of protein activation in tumors, that could improve current methods of diagnosis," says Altelaar. The researchers did this by analysing the proteome and phosphoproteome of tumor biopsies: they examined all proteins, expression of proteins and protein pathways. The analysis included measurement of protein phosphorylation levels in the tumors. Phosphorylation is a chemical modification added to a protein that regulates its function and that can be an important indicator of activity.
A more comprehensive view of protein activation in tumors could improve current methods for diagnosis
The analysis of the proteome and phosphoproteome uncovered various resistance mechanisms and showed that activity levels of multiple proteins (HER2, HER4, ER, IGF1R and Kalirin) predicted treatment response in patients. The identification of these mechanisms offers an important insight into the challenges faced in breast cancer treatment and paves the way for more accurate, targeted interventions.
In the world of clinical purposes, analysis of the proteome and the phosphoproteome from small tumor biopsies is quite new. According to Kelly Stecker, it is a promising way of studying tumor biology at a molecular level. Medical technology is now at a stage that a big amount of additional information can be extracted from a very small, but clinically relevant tissue sample. Stecker: “We can analyse increasingly smaller samples, making the intervention less invasive for people and the analysis more precise.”
Debets et al., Deep (phospho)proteomics profiling of pre-treatment needle biopsies identifies signatures of treatment resistance in HER2+ breast cancer, Cell Reports Medicine (2023), https://doi.org/10.1016/j.xcrm.2023.101203