ACTIVATED CD4 T LYMPHOCYTES AND NON-CLASSICAL MONOCYTES IN PERIPHERAL BLOOD AT BASELINE PREDICT RESPONSE TO IMMUNOTHERAPY IN NSCLC PATIENTS

Background: The discovery of immune checkpoint inhibitors initiated new therapies aimed at activating a previously inhibited anti-tumor T cell response, presenting very promising results. Although effective for some patients, others are primarily refractory to this treatment. The identification of predictive biomarkers for response to therapy is essential for targeting immune checkpoint inhibitors to those that will benefit most. Methods: Here, we performed a prospective non-interventional study and evaluated the immunological status of 26 patients with stage IV NSCLC treated with anti-PD-1 (pembrolizumab) combined with chemotherapy. The cellular immune profile was evaluated in peripheral blood by multiparametric flow cytometry before starting the treatment. Results: We found an objective response rate of 42.3% in our group of patients. Responder patients presented a higher frequency of activated CD4 T lymphocytes (CD69+ cells) and non-classical monocytes. Both activated CD4 T lymphocytes and non-classical monocytes were able to predict patients  response to immunotherapy, with high specificity and sensitivity, as shown by the ROC curves. The combination of total CD4 T lymphocytes and CD4+CD69+ T lymphocytes increased the power of the test. Confirming the data obtained with response assessment at 9 weeks, patients with durable responses (at 6 months) had a higher frequency of activated CD4 T lymphocytes, despite lower frequency of total CD4 T lymphocytes, when compared with non-responders patients. On the other hand, non-classical monocytes did not predict a durable response. The median PFS was longer for patients with high frequencies of both immune cell populations. Conclusion: Together, our results are quite promising, proposing predictive biomarkers of response to immunotherapy for patients with NSCLC. These biomarkers can be detected early, and they would eventually allow for therapy customization, increasing response rates, in addition to avoiding the use of expensive and potentially toxic treatments for patients who would not derive clinical benefit.