RESUMO
Introduction: The discovery of immune checkpoints and the development of their specific inhibitors was acclaimed as a major breakthrough in cancer therapy. However, only a limited patient cohort shows sufficient response to therapy. Hence, there is a need for identifying new checkpoints and predictive biomarkers with the objective of overcoming immune escape and resistance to treatment. Having been associated with both, treatment response and failure, LDL seems to be a double-edged sword in anti-PD1 immunotherapy. Being embedded into complex metabolic conditions, the impact of LDL on distinct immune cells has not been sufficiently addressed. Revealing the effects of LDL on T cell performance in tumor immunity may enable individual treatment adjustments in order to enhance the response to routinely administered immunotherapies in different patient populations. The object of this work was to investigate the effect of LDL on T cell activation and tumor immunity in-vitro. Methods: Experiments were performed with different LDL dosages (LDLlow = 50 µg/ml and LDLhigh = 200 µg/ml) referring to medium control. T cell phenotype, cytokines and metabolism were analyzed. The functional relevance of our findings was studied in a HCT116 spheroid model in the context of anti-PD-1 blockade. Results: The key points of our findings showed that LDLhigh skewed the CD4+ T cell subset into a central memory-like phenotype, enhanced the expression of the co-stimulatory marker CD154 (CD40L) and significantly reduced secretion of IL-10. The exhaustion markers PD-1 and LAG-3 were downregulated on both T cell subsets and phenotypical changes were associated with a balanced T cell metabolism, in particular with a significant decrease of reactive oxygen species (ROS). T cell transfer into a HCT116 spheroid model resulted in a significant reduction of the spheroid viability in presence of an anti-PD-1 antibody combined with LDLhigh. Discussion: Further research needs to be conducted to fully understand the impact of LDL on T cells in tumor immunity and moreover, to also unravel LDL effects on other lymphocytes and myeloid cells for improving anti-PD-1 immunotherapy. The reason for improved response might be a resilient, less exhausted phenotype with balanced ROS levels.
RESUMO
Although the discovery of immune checkpoints was hailed as a major breakthrough in cancer therapy, generating a sufficient response to immunotherapy is still limited. Thus, the objective of this exploratory, hypothesis-generating study was to identify potentially novel peripheral biomarkers and discuss the possible predictive relevance of combining scarcely investigated metabolic and hormonal markers with immune subsets. Sixteen markers that differed significantly between responders and non-responders were identified. In a further step, the correlation with progression-free survival (PFS) and false discovery correction (Benjamini and Hochberg) revealed potential predictive roles for the immune subset absolute lymphocyte count (rs = 0.51; p = 0.0224 *), absolute basophil count (rs = 0.43; p = 0.04 *), PD-1+ monocytes (rs = -0.49; p = 0.04 *), hemoglobin (rs = 0.44; p = 0.04 *), metabolic markers LDL (rs = 0.53; p = 0.0224 *), free androgen index (rs = 0.57; p = 0.0224 *) and CRP (rs = -0.46; p = 0.0352 *). The absolute lymphocyte count, LDL and free androgen index were the most significant individual markers, and combining the immune subsets with the metabolic markers into a biomarker ratio enhanced correlation with PFS (rs = -0.74; p ≤ 0.0001 ****). In summary, in addition to well-established markers, we identified PD-1+ monocytes and the free androgen index as potentially novel peripheral markers in the context of immunotherapy. Furthermore, the combination of immune subsets with metabolic and hormonal markers may have the potential to enhance the power of future predictive scores and should, therefore, be investigated further in larger trials.