A Four-Gene Autophagy-Related Prognostic Model Signature and Its Association With Immune Phenotype in Lung Squamous Cell Carcinoma

Abstract

Background

In the era of immunotherapy, there is a critical need for effective biomarkers to improve outcome prediction and guide treatment decisions for patients with lung squamous cell carcinoma (LUSC). We hypothesized that the immune contexture of LUSC may be influenced by tumor intrinsic events, such as autophagy.

Aims

We aimed to develop an autophagy-related risk signature and assess its predictive value for immune phenotype.

Methods and Results

Expression profiles of autophagy-related genes (ARGs) in LUSC samples were obtained from the TCGA and GEO databases. Survival analyses were conducted to identify survival-related ARGs and construct a risk signature using the Random Forest algorithm. Four ARGs (CFLAR, RGS19, PINK1, and CTSD) with the most significant prognostic value were selected to construct the risk signature. Patients in the high-risk group exhibited worse prognosis than those in the low-risk group (p < 0.0001 in TCGA; p < 0.01 in GEO) and the risk score was identified as an independent prognostic factor. We observed that the high-risk group displayed an immune-suppressive status and showed higher levels of infiltrating regulatory T cells and macrophages, which are associated with poorer outcomes. Additionally, the risk score exhibited a significantly positive correlation with the expression of PD-1 and CTLA4, as well as the estimate score and immune score.

Conclusion

This study provided an effective autophagy-related prognostic signature, which could also predict the immune phenotype.