Journal
JOURNAL FOR IMMUNOTHERAPY OF CANCER
Volume 11, Issue 8, Pages -Publisher
BMJ PUBLISHING GROUP
DOI: 10.1136/jitc-2023-007023
Keywords
Immune Checkpoint Inhibitors; Non-Small Cell Lung Cancer; Blood Cell Count; Biomarkers; Tumor; Review
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The use of immune checkpoint inhibitors (ICIs) has significantly impacted the treatment of non-small cell lung cancer (NSCLC), but reliable predictive biomarkers are still lacking. Comprehensive analysis of peripheral blood immune cell subsets can provide important information for guiding immunotherapy decision-making.
The use of immune checkpoint inhibitors (ICIs) continues to transform the therapeutic landscape of non-small cell lung cancer (NSCLC), with these drugs now being evaluated at every stage of the disease. In contrast to these advances, little progress has been made with respect to reliable predictive biomarkers that can inform clinicians on therapeutic efficacy. All current biomarkers for outcome prediction, including PD-L1, tumor mutational burden or complex immune gene expression signatures, require access to tumor tissue. Besides the invasive nature of the sampling procedure, other disadvantages of tumor tissue biopsies are the inability to capture the complete spatial heterogeneity of the tumor and the difficulty to perform longitudinal follow-up on treatment. A concept emerges in which systemic immune events developing at a distance from the tumor reflect local response or resistance to immunotherapy. The importance of this cancer 'macroenvironment', which can be deciphered by comprehensive analysis of peripheral blood immune cell subsets, has been demonstrated in several cutting-edge preclinical reports, and is corroborated by intriguing data emerging from ICI-treated patients. In this review, we will provide the biological rationale underlying the potential of blood immune cell-based biomarkers in guiding treatment decision in immunotherapy-eligible NSCLC patients. Finally, we will describe new techniques that will facilitate the discovery of more immune cell subpopulations with potential to become predictive biomarkers, and reflect on ways and the remaining challenges to bring this type of analysis to the routine clinical care in the near future.
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