Cancer is a disease where genetic mutation has resulted in changes in normal regulatory processes, causing cells to grow out of control and become invasive (1). T cells can recognize antigens that are over-expressed in tumor cells. Tumors can also express neoantigens: newly formed antigens that have not been previously recognized by the immune system, further distinguishing the tumor cells from normal cells. While T cells can respond to tumors, we know that this rarely provides protective immunity. Cancer continues to obtain genetic alterations as it grows, making the tumor microenvironment dynamic over time.

Clearly, it is a challenge for the immune system to fight the genetic complexities of cancer. Immuno-oncology is the study and development of treatments to help the immune system in this fight. It is fundamental for researchers in this area to understand the cancer-immunity cycle and learn how the immune system recognizes cancer. Tools such as next-generation sequencing (NGS) can help with biomarker discovery and to improve predictive outcomes for future therapy.

What is the cancer-immunity cycle?

The cancer-immunity cycle is a 7-step framework used to describe how the immune system recognizes and kills cancer cells (2) (Figure 1). In the first step, the transformation of normal cells to cancer cells (oncogenesis) causes the release of neoantigens. The neoantigens are then captured by dendritic cells, which process the neoantigens and present the captured materials to T cells (Step 2). This prepares and activates effector T cell response against cancer-specific antigens (Step 3), which are now recognized as foreign. The activated effector T cells migrate to (Step 4) and infiltrate (Step 5) the tumor. Within the tumor, the T cells recognize and bind to cancer cells (Step 6) and subsequently kill the target cancer cells (Step 7). Killing the cancer cells releases additional antigens and begins the cycle again. Since additional antigens are released with each subsequent cycle, the immune response can increase in scope over time.

In cancer patients, the cycle is not operating properly. For example, tumor antigens may not be detected correctly by dendritic cells, or the tumor microenvironment might suppress the effector cells that are produced. With cancer immunotherapy, the goal is to help ensure the cancer-immunity cycle is self-sustaining while simultaneously ensuring the immune system is not amplified to cause an adverse autoimmune response. Thus, cancer immunotherapies must be carefully considered to address a particular step in the cancer-immunity cycle and tailored to a given patient. For example, tumor-infiltration lymphocytes (TILs) can be taken from tumor tissue, modified in vitro, and infused back into the patient’s body in activated form to re-infiltrate the tumor (step 5 of the cycle) and attack tumor cells. T-cell regulation can be modified using antibodies that target the PD-1/PD-L1 pathway, allowing T cells to recognize cancer cells.

To better understand the complex immune-tumor interactions that occur within the cancer-immunity cycle, researchers turn to the accuracy, sensitivity, and throughput of NGS to find the genetic variants that drive oncogenesis and help determine appropriate treatment options. NGS assays can be designed to focus on a specific step within the cycle to study each component accurately. For example, tumor mutation load assays can help us better understand what neoantigens are released within a patient (Step 1). We can now sequence the TCR repertoire to better understand which T cells are recognizing and attacking cancer cells (Step 6).  A multi-dimensional approach is possible, enabling an understanding of the cancer-immunity cycle and the tumor microenvironment at an unprecedented level.