Scientists at the University of Bath have developed a diagnostic tool that can predict whether a cancer patient is likely to respond to immune checkpoint inhibitor therapy. The method uses an imaging technique, iFRET, to directly assess interaction between programmed death ligand-1 (PD-L1) ligand with its receptor programmed death receptor-1 (PD-1), in patients’ tumor samples. The team hopes that the technique will allow clinicians to tailor treatments to individual patients and avoid treatment paths that are unlikely to be successful.
“Currently, decisions on whether to proceed with checkpoint inhibitor treatment are based simply on whether PD-1 and PD-L1 are present in biopsies, rather than their functional state,” stated Banafshé Larijani, PhD, director of the Centre for Therapeutic Innovation (CTI-Bath). “However, our work has shown it is far more important to know that the two proteins are actually interacting and therefore likely to be having a functional impact on tumor survival.” Larijani and colleagues reported on the new tool in Cancer Research, in a paper titled, “High PD-1/PD-L1 Checkpoint Interaction Infers Tumor Selection and Therapeutic Sensitivity to Anti-PD-1/PD-L1 Treatment.”
Immunotherapy is a type of cancer treatment that helps a patient’s immune system fight cancer, and is having a profoundly positive impact on cancer treatment for many patients. Cancers can evade detection by the immune system, making themselves invisible to the natural anti-tumor response and actively blocking it. Antibody-based immune checkpoint inhibitor therapy effectively removes the brakes that tumors can put on the immune system, and so reactivates the patients’ natural anticancer response, which then destroys the tumor. Checkpoint inhibitors have been hugely successful for some subsets of cancer patients, but for many this type of treatment has little or no effect, and “notwithstanding some remarkable successes with immune checkpoint inhibitors, the majority of patients display primary or acquired resistance to treatment,” the authors wrote.
Co-author José I López, PhD, from the department of pathology, Cruces University Hospital, in Bilbao, noted, “Immune checkpoint blockade is becoming a therapeutic milestone in some cancers in the last years. Patients are selected for this treatment option using immunohistochemistry, however, this technique does not reliably detect all of the candidates that would potentially benefit. Actually, up to 19% of patients supposedly negative do respond to this therapy.”
So, given the inherent toxicity risks associated with immunotherapy, there is a real need to define which patients are most likely to benefit from treatment, and avoid unnecessary exposure for those patients who won’t respond. As the researchers commented, “There is, therefore, an unmet clinical need to identify biomarkers that distinguish potential responders from nonresponders to ensure that nonresponders are not exposed to the side-effects of these drug for no therapeutic benefit.”
The team in Bath led by Larijani, working with colleagues in the U.K. and Spain, including the company FASTBASE Solutions, has now developed a prognostic tool that uses an advanced microscopy platform to identify immune cell interactions with tumor cells, and also reported on the activation status of immune-checkpoints that dampen the antitumor response. The scientists used the technique to evaluate the immune checkpoint involving PD-1, which is present on immune cells called T lymphocytes, and PD-L1, which is present on other types of immune cells and on the surface of many different types of tumors. When PD-1 on the surface of T lymphocytes engages with PD-L1 on the surface of other immune cells, it effectively switches off the immune function of the T cell. In a healthy individual, these checkpoints tightly regulate the body’s immune response, acting as an off-switch to prevent autoimmune and inflammatory disease. Tumor cells essentially hijack this mechanism by expressing PD-L1 on their surface, enabling them to activate PD-1 on the T lymphocyte, thus switching off its antitumor function, allowing survival and growth of the tumor.
Immunotherapy checkpoint inhibitors work by disrupting the interaction between PD-L1 expressed on the tumor and PD-1 on the T cell, and thus re-establish the patient’s antitumor activity. “Conceptually, it is surmised that a high degree of PD-1/PD-L1 interaction infers tumor selection in patients, indicating that the patient’s tumor may be reliant on PD-1/PD-L1 interaction to facilitate immune evasion. It is precisely this group of patients that would be expected to respond to immune checkpoint inhibition,” the investigators explained.
The new iFRET imaging tool developed by the Bath researchers can quantify the extent of PD-1/PD-L1 interaction in a biopsy of the tumor, to help predict whether the checkpoint inhibitor therapy is likely to have significant clinical benefit. Results from tests with the system on tumor biopsy samples confirmed that immunotherapy-treated patients with metastatic non-small cell lung cancer (NSCLC) who displayed a low extent of PD-1/PD-L1 interaction showed significantly worse outcome than those with a high interaction.
The team hopes that the same approach could be used to monitor other immune cell interactions in cancer. “iFRET can be exploited to monitor other intercellular protein interactions and there are ongoing developments designed to capture related immune modulatory interactions pertinent to cancer and emerging cancer treatments,” the scientists noted. “This provides the potential for iFRET to become a useful predictive tool informing on the nature of the tumor immune-privileged state.’
Stephen Ward, PhD, vice-chair of CTI-Bath and a co-author of the study, said, “The tool we have developed is an important step towards personalized medicine. By using it, we can precisely select who will benefit from immunotherapy. It will also show which patients are unlikely to respond well before they start a long course of treatment, and these patients can be offered a different treatment route … “It should make treatment with these expensive biotherapeutics much more efficient for the NHS.”
Tests in additional patients are now being planned, according to Eunate Arana, PhD, scientific coordinator of BioCruces Health Research Institute. “We find this technology and its application in the field of immunotherapy truly interesting. Therefore, we are going to carry out a clinical trial in three hospitals of BioCruces and BioDonostia, the Basque Public Health network, that will allow us to evaluate the predictive capacity of this quantitative imaging platform, to improve patient stratification for lung cancer immunotherapy.”
The authors concluded, “The exemplification of iFRET in tumor settings opens up exciting and powerful new opportunities to move beyond the cataloguing of cell phenotypes in situ and add functional attributes to our patient data inventory, impacting clinical decisions … This is a routine parameter for small-molecule inhibitors targeted at driver mutations, and we suggest it should become a routine for these more complex biotherapeutic interventions.”