# Identification of Natural Killer Cell‐Associated Clusters in Skin Melanoma and the Impact on Prognosis and Drug Sensitivity

## TL;DR

This study identifies two distinct natural killer cell-related clusters in skin melanoma patients, which differ in survival rates and drug responses, suggesting personalized treatment strategies based on immune profiles.

## Contribution

The study introduces a gene classifier to identify NK cell-associated clusters in melanoma, revealing distinct prognostic and therapeutic implications.

## Key findings

- Cluster 1 has higher NK cell activity and better survival, while Cluster 2 shows lower NK activity and worse outcomes.
- Cluster 1 is more responsive to most melanoma treatments, except trametinib, which is more effective in Cluster 2.
- The gene classifier achieved an AUC of 0.913 and was validated across external databases.

## Abstract

Skin melanoma exhibits significant heterogeneity in clinical outcomes and treatment responses among patients. This study aimed to investigate natural killer (NK) cell clusters in skin melanoma, their impact on patient prognosis, and their value as biomarkers for tailoring treatment.

We used data from TCGA, GSE19234, GSE65904, GSE244982, and GSE78220. A gene classifier was developed to identify two distinct clusters of melanoma patients. Survival analysis, NK cell infiltration levels, and responses to immune and targeted therapies were evaluated.

Unsupervised clustering revealed two distinct melanoma patient clusters with significant differences in NK cell activity and clinical outcomes. Cluster 1 showed higher NK cell infiltration, better overall survival (OS) (p < 0.0001), and greater activity in NK‐cell‐related pathways. In contrast, Cluster 2, characterized by lower NK cell activity and higher exhaustion markers, had poorer OS. Drug sensitivity analysis indicated that Cluster 1 was more responsive to most melanoma treatments, whereas Cluster 2 had higher sensitivity to trametinib (p < 0.001). The developed gene classifier had an AUC of 0.913 and effectively differentiated between clusters. Additionally, Cluster 1 showed better responses to immunotherapy with a higher rate of complete and partial responses (p < 0.001). These findings were validated in external databases.

This study identifies two distinct NK‐cell‐related clusters in melanoma with differential prognoses and treatment responses. These findings underscore the importance of integrating NK‐cell‐related profiles into personalized treatment strategies, offering a pathway to optimize therapeutic outcomes based on specific immune profiles.

Unsupervised clustering of NK cell‐related gene expression revealed two distinct patient clusters within TCGA‐SKCM data, each with significantly different clinical outcomes. Cluster 1 showed higher NK cell activity and better overall survival (OS), while Cluster 2 had lower NK cell levels and higher NK cell exhaustion, resulting in a poorer prognosis. Cluster 1 was more sensitive to most melanoma treatments, except trametinib, which showed better sensitivity in Cluster 2.