Translational Insights into NK Immunophenotyping: Comparative Surface Marker Analysis and Circulating Immune Cell Profiling in Cancer Immunotherapy

TL;DR

This paper explores NK cell markers in humans and mice to improve cancer immunotherapy by enabling better immune profiling and predicting treatment outcomes.

Contribution

The study proposes a standardized immunoprofiling strategy using surface markers compatible with flow cytometry for translational cancer immunotherapy.

Findings

Surface markers of NK and immune cells in humans and mice are associated with specific functional profiles.

Bioinformatic visualization enables rapid immunoprofiling and highlights interspecies variations.

Prioritized markers support streamlined workflows for monitoring immune status and immunotherapy efficacy.

Abstract

Cells of the innate immune system, particularly natural killer (NK) cells, serve as the first line of defense against tumor development and play a critical role in antitumor immunity. Characterizing the immune cell pool and its functional state is essential for understanding immunotherapy mechanisms and identifying key cellular players. However, defining NK cell populations in mice, the primary model for cancer immunotherapy, is challenging due to strain-specific marker variability and the absence of a universal NK cell marker, such as human CD56. This study evaluates surface markers of NK and other peripheral blood immune cells in both humans and mice, associating these markers with specific functional profiles. Bioinformatic approaches are employed to visualize these markers, enabling rapid immunoprofiling. We explore the translational relevance of these markers in assessing immunotherapy efficacy, including their gene associations, ligand interactions, and interspecies variations. Markers compatible with rapid flow-cytometry-based detection are prioritized to streamline experimental workflows. We propose a standardized immunoprofiling strategy for monitoring systemic immune status and evaluating the effectiveness of immunotherapy in preclinical and clinical settings. This approach facilitates the design of preclinical studies that aim to identify predictive biomarkers for immunotherapy outcomes by monitoring immune status.

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