# Development and validation of a prognostic model for predicting survival and immunotherapy benefits in melanoma based on metabolism-relevant genes

## TL;DR

This study develops a model to predict survival and immunotherapy response in melanoma patients using metabolism-related genes and validates it with experiments and computational methods.

## Contribution

A novel prognostic model for melanoma using metabolism-relevant genes and their association with immunotherapy response is developed and validated.

## Key findings

- Three molecular subtypes of SKCM were identified based on metabolism-related gene expression.
- A prognostic model using five signature genes was developed to predict survival and immunotherapy response.
- SLC5A3 suppression reduced cell proliferation and migration in melanoma cell lines.

## Abstract

Skin cutaneous melanoma (SKCM) is a fatal form of skin cancer. Metabolism-related genes (MRGs) comprise a group of genes that possess the ability to modulate and regulate metabolic pathways. In this study, the expression levels of MRGs were used to classify SKCM patients into three molecular subtypes. Then the differentially expressed genes (DEGs) among the three MRGs molecular clusters were applied into the LASSO and COX regression analysis to identify five signature genes. Furthermore, we developed a prognostic model to predict the prognosis of SKCM patients and evaluate the response of SKCM patients to immunotherapy based on the expression of signature genes. Pathological features were extracted using the ResNet50 deep learning framework and Cellprofiler software, and feature selection was performed using elastic regression and univariate Cox analysis to obtain 13 pathological features related to the MRGs prognostic model. Single-cell RNA sequencing (scRNA-seq) analysis identified the expression of MRGs in multiple cell types and found that SLC5A3 + malignant cells may mediate potential communication with tumor-associated fibroblasts through the PI3K-AKT pathway and cholesterol metabolism pathway. It is worth noting that, through in vitro experiments, including western blot (WB), quantitative PCR (qPCR), and immunohistochemistry (IHC) techniques, we found differences in the expression levels of signature genes between normal melanocytes and SKCM cells. In addition, suppressing the expression of the signature gene, SLC5A3, in a SKCM cell line through the utilization of small interfering RNAs (siRNAs) could inhibit the proliferation and migration of cells, as evidenced by the implementation of colony formation assay, CCK8, and cell transfection techniques.

The online version contains supplementary material available at 10.1007/s12672-025-03186-8.