Are most cancer cases a consequence of an immune deficiency caused by thymic involution?

Thymic Function and T-Cell Receptor Repertoire Diversity: Implications for Patient Response to Checkpoint Blockade Immunotherapy

The capacity of T cells to recognize and mount an immune response against tumor antigens depends on the large diversity of the T-cell receptor (TCR) repertoire generated in the thymus during the process of T-cell development. However, this process is dramatically impaired by immunological insults, such as that caused by cytoreductive cancer therapies and infections, and by the physiological decline of thymic function with age. Defective thymic function and a skewed TCR repertoire can have significant clinical consequences. The presence of an adequate pool of T cells capable of recognizing specific tumor antigens is a prerequisite for the success of cancer immunotherapy using checkpoint blockade therapy. However, while this approach has improved the chances of survival of patients with different types of cancer, a large proportion of them do not respond. The limited response rate to checkpoint blockade therapy may be linked to a suboptimal TCR repertoire in cancer patients prior to therapy. Here, we focus on the role of the thymus in shaping the T-cell pool in health and disease, discuss how the TCR repertoire influences patients’ response to checkpoint blockade therapy and highlight approaches able to manipulate thymic function to enhance anti-tumor immunity.

Implications of Tumor-Immune Coevolution on Cancer Evasion and Optimized Immunotherapy

Cancer represents a diverse collection of diseases characterized by heterogeneous cell populations that dynamically evolve in their environment. As painfully evident in cases of treatment failure and recurrence, this general feature makes identifying long-term successful therapies difficult. It is now well-established that the adaptive immune system recognizes and eliminates cancer cells, and various immunotherapeutic strategies have emerged to augment this effect. These therapies, while promising, often fail as a result of immune-specific cancer evasion. Increasingly available empirical evidence details both cancer and immune system populations pre- and post-treatment, providing rich opportunity for mathematical models of the tumor-immune interaction and subsequent co-evolution. Integrated mathematical and experimental efforts bear immediate relevance for optimized therapies and will undoubtedly accelerate our understanding of this emergent field.