Predicting immunotherapy response in melanoma using a novel tumor immunological phenotype-related gene index.

ABSTRACT:

Introduction

Melanoma is a highly aggressive and recurrent form of skin cancer, posing challenges in prognosis and therapy prediction.

Methods

In this study, we developed a novel TIPRGPI consisting of 20 genes using Univariate Cox regression and the LASSO algorithm. The high and low-risk groups based on TIPRGPI exhibited distinct mutation profiles, hallmark pathways, and immune cell infiltration in the tumor microenvironment.

Results

Notably, significant differences in tumor immunogenicity and TIDE were observed between the risk groups, suggesting a better response to immune checkpoint blockade therapy in the low-TIPRGPI group. Additionally, molecular docking predicted 10 potential drugs that bind to the core target, PTPRC, of the TIPRGPI signature.

Discussion

SUBMITTER: Zheng S 

PROVIDER: S-EPMC10987686 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature