Immunotherapies, cancer treatments that target the immune system, have drastically improved patient care over the past decade. Biomarkers, signs that help inform doctors about a disease or condition, can help determine which patients will best respond to a certain immunotherapy.
Our immune systems, under normal conditions, operate in the background, searching for potential threats and only activating when encountering a foreign invader. Unnecessary stimulation of the immune response can damage or kill the body's healthy cells, and this phenomenon forms the basis of many autoimmune disorders. Our cells contain proteins called immune checkpoints. which regulate immunity. When an immune checkpoint on an immune cell engages with a matching ligand on another cell, the immune response turns itself down or even off.
As a survival mechanism, some tumors, particularly many solid tumors, have evolved to express the ligands capable of turning off the immune response. While immune regulation benefits us under normal conditions, any hindrance of the immune response in the presence of cancer can become detrimental. Understanding these biological processes has led to the development of a promising immunotherapeutic modality: the immune checkpoint inhibitor (ICI). ICIs work by blocking the signals that dampen the immune response.
One prominent checkpoint pathway consists of programmed death 1 (PD1), located on immune cells, and programmed death ligand 1 (PD-L1), expressed on tumor cells. The FDA has approved numerous ICIs to block the interaction of PD-1 and PD-L1 for patients with various solid tumors, including skin, lung, and liver cancers.
Predicting the patients most likely to benefit from PD-1/PD-L1 interventions remains a high priority. Depending on the type of cancer, different tests can predict a patient’s likelihood of responding to ICIs. In some cancers, a readout used to access ICI responsiveness is a patient’s tumor mutational burden (TMB), an estimate of how many mutations appear in the cancer genome. However, better predictive models could help identify more patients who could benefit from these therapies.
A paper recently published in Communications Medicine describes a new method to predict ICI responsiveness which the authors call the Immunotherapy Response Score (IRS). The researchers developed IRS using clinical trial (NCT03061305) data from over 600 patients with 24 different types of cancer. The study calculated IRS using TMB and expression of four genetic markers (CD274, PDCD1, ADAM12, TOP2A) and assigned patients as IRS-low or IRS-high. After developing the scoring system, the researchers validated it in a cohort of 248 patients representing 24 tumor types, demonstrating significantly longer survival in IRS-high compared to IRS-low patients.
Further, the researchers evaluated samples from nearly 25,000 patients using the IRS system. Based on IRS, almost 8% of these patients may benefit from ICI treatment but would not receive treatment based on TMB-driven standards. In addition to presenting a promising new way to identify patients who will most likely benefit from ICIs, this model applies to many different cancers and could significantly streamline treatment planning procedures.
Sources: Oncologist, Commun Med