Aging of an individual entails a progressive decline of functional reserves and loss of homeostasis that eventually lead to mortality. This process is highly individualized and is influenced by multiple genetic, epigenetic and environmental factors. This individualization and the diversity of factors influencing aging result in a significant heterogeneity among people with the same chronological age, representing a major challenge in daily oncology practice. Thus, many factors other than mere chronological age will contribute to treatment tolerance and outcome in the older patients with cancer. Clinical/comprehensive geriatric assessment can provide information on the general health status of individuals, but is far from perfect as a prognostic/predictive tool for individual patients. On the other hand, aging can also be assessed in terms of biological changes in certain tissues like the blood compartment which result from adaptive alterations due to past history of exposures, as well as intrinsic aging processes. There are major signs of 'aging' in lymphocytes (e.g. lymphocyte subset distribution, telomere length, p16INK4A expression), and also in (inflammatory) cytokine expression and gene expression patterns. These result from a combination of the above two processes, overlaying genetic predispositions which contribute significantly to the aging phenotype. These potential "aging biomarkers" might provide additional prognostic/predictive information supplementing clinical evaluation. The purpose of the current paper is to describe the most relevant potential "aging biomarkers" (markers that indicate the biological functional age of patients) which focus on the biological background, the (limited) available clinical data, and technical challenges. Despite their great potential interest, there is a need for much more (validated) clinical data before these biomarkers could be used in a routine clinical setting. This manuscript tries to provide a guideline on how these markers can be integrated in future research aimed at providing such data.
Keywords: Aging; Aging genes; CRAMP; Cancer; Chitinase; Elderly; IGF-1; IL-6; Immunosenescence; Inflammaging; MCP-1; RANTES; SASP; Telomeres.
© 2013.