# The gene signature linked to lactate metabolism predicts the prognosis and correlates with the immune status of head and neck squamous cell carcinoma

## TL;DR

This study identifies a gene signature linked to lactate metabolism that predicts survival and immune status in head and neck cancer patients.

## Contribution

A novel prognostic model based on lactate metabolism genes is developed for head and neck squamous cell carcinoma.

## Key findings

- A five-gene model achieved AUC values over 0.8 for five-year survival prediction in HNSC patients.
- Higher risk scores correlated with a more tumor-promoting and immune-suppressive microenvironment.
- Low-risk patients showed better prognosis and enhanced immune characteristics.

## Abstract

Lactate, traditionally viewed as a byproduct of glycolysis, is increasingly recognized as a pivotal regulatory factor in cancer biology. This study addresses the limited understanding of lactate metabolism-related genes in head and neck squamous cell carcinoma (HNSC) by constructing a prognostic risk model centered on these genes to enhance prediction and treatment strategies for HNSC. Utilizing the Lactate Metabolism score (LMs) derived from The Cancer Genome Atlas (TCGA), we identified five key genes significantly associated with prognosis in HNSC patients. These genes were integrated into a prognostic risk model developed through Cox regression analysis, which demonstrated superior predictive performance, achieving area under the curve (AUC) values greater than 0.8 for five-year survival. The risk scores generated by our model were significantly correlated with critical features of the tumor microenvironment, including immune characteristics and markers of immune evasion. Higher risk scores correlated with a more tumor-promoting microenvironment and increased immune suppression, underscoring the model’s relevance in understanding HNSC progression. Additionally, eight critical hub genes were identified, revealing significant differences in gene expression between risk score groups. Functional analyses demonstrated that the low-risk group exhibited a more favorable prognosis and enhanced immune characteristics. Our findings suggest that the lactate metabolism-based prognostic model may have implications for guiding the development of personalized treatment approaches, as it highlights the potential for targeted interventions that could modulate the tumor microenvironment and immune response.