Oestrogen Signalling Influences Breast Cancer Treatment Responses, Study Finds

New research highlights the role of oestrogen signalling in early-stage breast cancer and its potential to refine treatment strategies for patients undergoing neoadjuvant chemotherapy and immunotherapy. The study, published in Cancer Treatment Reviews, investigates how oestrogen receptor (ER) expression influences responses to treatment, offering insights that could lead to more tailored therapeutic approaches.

The research focuses on two primary groups of patients, those with triple-negative breast cancer (TNBC) and those with oestrogen receptor-positive, human epidermal growth factor receptor 2-negative (ER+HER2-) breast cancer. While immunotherapy in combination with chemotherapy has already demonstrated improved outcomes for TNBC, its efficacy in ER+HER2- breast cancer remains less clear. The study finds that oestrogen signalling plays a significant role in modulating immune responses within tumours, which in turn affects how well patients respond to neoadjuvant treatments.

One of the key findings suggests that higher ER expression correlates with reduced immune activity within the tumour microenvironment. This could mean that ER+ tumours are less likely to benefit from immunotherapy when compared to TNBC, which typically has a more active immune landscape. The study also highlights that patients with high levels of proliferating tumour cells may respond better to neoadjuvant chemotherapy, as rapidly dividing cancer cells are more susceptible to treatment.

Another significant aspect of the study explores the potential for predictive models that integrate ER expression, immune cell presence, and genetic markers to determine which patients are most likely to benefit from chemoimmunotherapy. Current treatment strategies often take a generalised approach, but personalised treatment planning could help avoid unnecessary immune-related toxicities, which can be severe and sometimes irreversible.

The study also discusses how sex hormones influence the tumour immune response, with oestrogen potentially suppressing anti-tumour immunity. This could explain why some ER+ breast cancers do not respond as effectively to immunotherapy. The authors suggest that hormonal manipulation might improve responses in certain cases, though further research is needed to confirm these findings.

Despite these advancements, the study acknowledges the limitations of existing predictive models. Many current approaches are qualitative rather than quantitative, making it difficult to integrate multiple factors into a single, reliable framework for clinical decision-making. The rapid evolution of artificial intelligence and machine learning in oncology, however, offers hope that more precise predictive tools could soon become available.

The implications of this research are significant for clinicians and patients alike. A better understanding of how oestrogen signalling affects treatment response could lead to more personalised therapies, improving outcomes while reducing unnecessary side effects. While immunotherapy remains a key area of exploration for early-stage breast cancer, it is clear that not all patients will benefit equally. The study underscores the importance of refining treatment selection based on individual tumour characteristics, rather than a one-size-fits-all approach.