EXPLORING AGEING-RELATED BIOMARKERS IN INDIVIDUALS WITH BREAST CANCER AND WITHOUT CANCER

In recent years, it has been increasingly recognized that different persons undergo the ageing process at different rates. Although chronological age has traditionally served as a measure of ageing, it only provides a one-dimensional view. We now know that age-related diseases or conditions independently contribute to unfavorable outcomes and hasten the ageing process, resulting in a wide range of biological ageing rates. The use of biomarkers may contribute to the understanding of the multifaceted ageing process and tailoring interventions to meet the unique needs of this highly diverse population.

This heterogeneous pattern of ageing is reflected by various degrees of frailty, a clinical setting associated with adverse events like institutionalization, functional dependence and survival. In Chapter II, we aimed to identify such a biomarker, methylmalonic acid (MMA). We included a cohort of older individuals (≥70 years) with breast cancer who had undergone geriatric assessment (n=119). We measured their baseline serum MMA levels and collected classic clinical parameters such as age and renal function. Our results showed that MMA levels accurately predicted clinical frailty, and strongly correlated with mobility.

Furthermore, the relationship between ageing and cancer is intricately intertwined, as advanced age is widely recognized as a significant risk factor for various types of cancer. Nevertheless, the precise mechanisms underlying the complex interplay between ageing and cancer progression remain inadequately elucidated, warranting additional research efforts. By exploring ageing-related biomarkers such as MMA as potential indicators of metastasis, we can acquire valuable insights into the intricate connections between ageing and the advancement of cancer. To this end, we conducted a 1:1 matched case-control study that included 84 breast cancer patients who developed distant metastasis within 5 years after diagnosis, and an equal number of matched controls who were free from metastasis within 5 years. Our results showed no significant difference in MMA levels between the metastasis group and the non-metastasis group.

Given older persons with cancer are often undertreated in clinical trials due to concerns about treatment tolerability, we aimed to evaluate the impact of chemotherapy on the immune system in Chapter III. We included a cohort of older individuals (≥70 years) with breast cancer who had undergone upfront surgery and were assigned to receive either chemotherapy (n=39) or hormone therapy (n=32) based on the clinician's choice. We monitored a range of immunosenescent-related biomarkers before, during, and after chemotherapy. Our results indicate that chemotherapy only caused a transient perturbation in these biomarkers, with the potential to stimulate the immune system in the long term. Furthermore, patients with better nutritional status at baseline may experience less perturbation.

Lastly, more and more older persons become functionally dependent and highly frail, leading to the need for transfer to a nursing home. Nursing home residents are generally much frailer than the general older population living in the community, and have a poorer survival. Therefore, in Chapter IV, we evaluated the value of several ageing biomarkers for the prediction of survival for this frail population. We included 94 nursing home residents, and measured the baseline level of several miRNAs and multiple inflammatory molecules in their plasma. We found that chronological age alone failed to predict survival, but by constructing a nomogram prediction model using 6 signatures (sex, miR-122-5p, miR-27b-3p, IL-8, miR-30a-5p, and miR-885-5p), we could successfully predict 1- and 3-year mortality in both training and validating sets (all AUC>0.7). The model performed best at 3-year mortality predictions, with all AUC values > 0.82.

In summary, this PhD project provides new evidence for the potential of biomarkers to improve the care of older adults. Specifically, selected ageing biomarkers can help to identify specific areas of impairment in patients with frailty. Additionally, biomarkers can be used to evaluate the impact of chemotherapy, with the potential to customize treatments based on individual health status, such as nutritional status. Furthermore, biomarkers can predict survival in very frail older adults, a task that is difficult to achieve through chronological age alone. Overall, these findings suggest that biomarkers can uncover the heterogeneity of the ageing process and enable the development of personalized treatment approaches.