A manganese metabolism-related gene signature stratifies prognosis and immunotherapy efficacy in kidney cancer

TL;DR

This study identifies a set of manganese metabolism genes that can predict kidney cancer prognosis and response to immunotherapy.

Contribution

A novel manganese metabolism-related gene signature is developed for stratifying kidney cancer prognosis and immunotherapy efficacy.

Findings

11 prognosis-related manganese metabolism core genes were identified in kidney cancer.

Patients were stratified into high- and low-risk groups with distinct survival outcomes based on the MMCG risk score.

The MMCG risk score is an independent prognostic biomarker and correlates with immune therapy response.

Abstract

Manganese modulates tumorigenesis and immune regulation. High levels of manganese may promote cancer progression. While manganese toxicity causes renal tubular damage and chronic impairment, its association with kidney cancer remains poorly understood.

We systematically analyzed manganese metabolism genes in KIRC using the TCGA dataset. Through integrated bioinformatics approaches, including differential expression analysis, univariate Cox regression, and three machine learning algorithms (Boruta, GBM, and RFS), we identified prognosis-related MMCG. The Ward.D2 method was used to identify MMCG subtypes, while Lasso-cox regression analysis was performed to establish the MMCG risk model. The predictive performance was validated through time-dependent ROC analysis, calibration curves, and decision curve analysis.

We identified 11 prognosis-related manganese metabolism core genes (MMCGs). KIRC patients were stratified into two clusters based on MMCG expression levels. Patients in Cluster I showed poorer outcomes, which were associated with tumour progression. The MMCG risk score was subsequently developed using LASSO-Cox regression analysis, and patients were classified into high- and low-risk groups. Survival analysis revealed that the outcomes of high-risk group patients were poorer than those of the low-risk group. Univariate and multivariate analyses confirmed the MMCG risk score as an independent prognostic biomarker. Pathway enrichment analysis showed differential enrichment of immune and metabolic pathways across subtypes and risk groups. We constructed a clinical nomogram incorporating the MMCG risk score and other clinical parameters, which demonstrated highly accurate predictive capabilities. Immune infiltration analysis and immune therapy response predictions indicated that patients in Cluster I and the high-risk group showed low responses to immune therapy.

Our findings provide a basis for clinical stratification strategies and future research on manganese-based interventions for renal cell carcinoma (RCC).

The online version contains supplementary material available at 10.1007/s12672-025-03050-9.

Figures