# Diverse Landscape of Group 1 Innate Lymphoid Cells Predicts the Prognosis in Patients with Head and Neck Squamous Cell Carcinoma

## TL;DR

This study explores the role of innate lymphoid cells in head and neck cancer, finding that specific cell types predict poor patient outcomes.

## Contribution

The study identifies distinct group 1 innate lymphoid cell clusters and their prognostic value in head and neck squamous cell carcinoma.

## Key findings

- Four group 1 ILC clusters were identified, with ieILC1-1 showing the highest immunological activity.
- ieILC1-1 was mainly found in human papillomavirus-positive samples and predicted poor prognosis.
- Risk scores based on gene expression in these clusters were strong indicators of shorter survival.

## Abstract

Innate lymphoid cells (ILCs) and natural killer (NK) cells are a heterogeneous family of innate immune cells exhibiting not only antitumoral but also protumoral activities. The objective of this study was to determine the landscape and prognostic significance of ILC/NK cells in patients with head and neck squamous cell carcinoma (HNSCC). Publicly available single-cell RNA sequencing data were analyzed, and four group 1 ILC clusters were identified: intraepithelial ILC1 (ieILC1)-1, ieILC1-2, ieILC1–NK-intermediate, and NK cells. Among the ieILC1/NK clusters, ieILC1-1 was the most immunologically active phenotype, mainly comprising human papillomavirus-positive samples. Risk scores calculated based on the differentially expressed genes of the ieILC1/NK clusters strongly predicted a poor prognosis. Our results suggest that further exploring group 1 ILCs could provide new insights into the development of cancer immunotherapy and biomarkers for patients with HNSCC.

Objectives: Innate lymphoid cells (ILCs) and natural killer (NK) cells represent a diverse group of innate immune populations that modulate immune responses and tissue equilibrium across various diseases, including cancer. In the present study, we analyzed single-cell RNA sequencing (scRNA-seq) data to explore the landscape and functional status of ILC subsets in patients with head and neck squamous cell carcinoma (HNSCC). Methods: The GSE164690 dataset, which includes preprocessed scRNA-seq and clinical data, was acquired from the Gene Expression Omnibus database. The Cancer Genome Atlas database was used to develop the survival prediction model. Results: A total of 95,809 immune cells were clustered into 16 immune cell clusters, among which 7278 NK cells were further subdivided into 11 clusters. Among the 11 clusters, eight NK cell clusters, two intraepithelial ILC1 (ieILC1) clusters, and one ieILC1–NK-intermediate (ieILC1-NK-int) cluster were identified. Among the ieILC1/NK clusters, ieILC1-1 exhibited the highest immunological activity and was mainly derived from human papillomavirus-positive samples. Further, ieILC1s showed higher enrichment of pathways related to inflammation and effector functions—such as inflammatory response, interferon-gamma response, and interferon-alpha response—compared to the other clusters. Moreover, we developed prognostic prediction models based on differentially expressed genes in the ieILC1/NK clusters. Risk scores of the ieILC1-1, ieILC1-NK-int, and NK clusters were identified as independent prognostic factors for shorter overall survival (OS) and progression-free survival (PFS). Recursive partitioning revealed that combining ieILC1-1 and the NK clusters strongly predicted shorter OS and PFS. Conclusions: Our findings highlight the diverse landscape and prognostic significance of ieILC1/NK cells in patients with HNSCC.