The dynamic role of immune checkpoint molecules in diagnosis, prognosis, and treatment of head and neck cancers

Head and neck cancer (HNC) is the sixth most common cancer type, accounting for approximately 277,597 deaths worldwide. Recently, the Food and Drug Administration (FDA) has approved immune checkpoint blockade (ICB) agents targeting programmed death-1 (PD-1) and programmed death-ligand 1 (PD-L1) as a treatment regimen for head and neck squamous cell carcinomas (HNSCC). Studies have reported the role of immune checkpoint inhibitors as targeted therapeutic regimens that unleash the immune response against HNSCC tumors. However, the overall response rates to immunotherapy vary between 14–32% in recurrent or metastatic HNSCC, with clinical response and treatment success being unpredictable. Keeping this perspective in mind, it is imperative to understand the role of T cells, natural killer cells, and antigen-presenting cells in modulating the immune response to immunotherapy. In lieu of this, these immune molecules could serve as prognostic and predictive biomarkers to facilitate longitudinal monitoring and understanding of treatment dynamics. These immune biomarkers could pave the path for personalized monitoring and management of HNSCC. In this review, we aim to provide updated immunological insight on the mechanism of action, expression, and the clinical application of immune cells' stimulatory and inhibitory molecules as prognostic and predictive biomarkers in HNC. The review is focused mainly on CD27 and CD137 (members of the TNF-receptor superfamily), natural killer group 2 member D (NKG2D), tumor necrosis factor receptor superfamily member 4 (TNFRSF4 or OX40), S100 proteins, PD-1, PD-L1, PD-L2, T cell immunoglobulin and mucin domain 3 (TIM-3), cytotoxic T lymphocyte–associated antigen 4 (CTLA-4), lymphocyte-activation gene 3 (LAG-3), indoleamine-pyrrole 2,3-dioxygenase (IDO), B and T lymphocyte attenuator (BTLA). It also highlights the importance of T, natural killer, and antigen-presenting cells as robust biomarker tools for understanding immune checkpoint inhibitor-based treatment dynamics. Though a comprehensive review, all aspects of the immune molecules could not be covered as they were beyond the scope of the review; Further review articles can cover other aspects to bridge the knowledge gap.