Effective prognostic risk model with cuproptosis-related genes in laryngeal cancer

Abstract

Objective

Laryngeal cancer, characterized by high recurrence rates and a lack of effective biomarkers, has been associated with cuproptosis, a regulated cell death process linked to cancer progression. In this study, we aimed to explore the roles of cuproptosis-related genes in laryngeal cancer and their potential as prognostic markers and therapeutic targets.

Methods

We collected comprehensive data from The Cancer Genome Atlas and Gene Expression Omnibus databases, including gene expression profiles and clinical data of laryngeal cancer patients. Using clustering and gene analysis, we identified cuproptosis-related genes with prognostic significance. A risk model was constructed based on these genes, categorizing patients into high- and low-risk groups for outcome comparison. Univariate and multivariate analyses were conducted to identify independent prognostic factors, which were then incorporated into a nomogram. Gene Set Enrichment Analysis was employed to explore pathways distinguishing high- and low-risk groups.

Results

Our risk model, based on four genes, including transmembrane 2, dishevelled binding antagonist of β-catenin 1, stathmin 2, and G protein-coupled receptor 173, revealed significant differences in patient outcomes between high- and low-risk groups. Independent prognostic factors were identified and integrated into a nomogram, providing a valuable tool for prognostic prediction. Gene Set Enrichment Analysis uncovered up-regulated pathways specifically associated with high-risk patient samples.

Conclusion

This study highlights the potential of cuproptosis-related genes as valuable prognostic markers and promising therapeutic targets in the context of laryngeal cancer. This research sheds light on new avenues for understanding and managing this challenging disease.

Level of evidence: Level 4.

Keywords
Cuproptosis; Risk model; Prognosis; Laryngeal cancer; Immune

Highlights

Cuproptosis genes stratified laryngeal cancer into diverse prognostic subtypes.

TMEM2, DACT1, STMN2, and GPR173 form our prognostic model.

TMEM2, DACT1, STMN2, GPR173 shape the risk model.

High-risk samples upregulated angiogenesis, EMT, and KRAS pathways.

Clinical_M, Clinical_cN, risk groups predict laryngeal cancer prognosis.