Integrating single-cell and bulk RNA sequencing data to construct a pyroptosis-related prognostic signature and analyze the tumor microenvironment in gastric cancer.

BACKGROUND

Gastric cancer (GC) is a prevalent malignancy with high morbidity and mortality. Pyroptosis, a form of programmed cell death, plays a significant role in cancer progression and immune regulation. This study aimed to construct a pyroptosis-related prognostic signature (PRPS) and analyze its association with the tumor microenvironment in GC by integrating single-cell and bulk RNA sequencing data.

METHODS

Pyroptosis-related differentially expressed genes in GC were identified by integrating single-cell and bulk RNA sequencing data. The PRPS was constructed using univariate and multivariate Cox regression analyses, and evaluated by Kaplan-Meier curves, receiver operating characteristic curves, and nomogram analysis. Subsequently, genomic variations, immune landscapes, immune checkpoint inhibitors (ICIs) responses, and drug sensitivity were evaluated in different risk subgroups.

RESULTS

We constructed a PRPS in GC by integrating single-cell and bulk RNA sequencing data. The PRPS exhibited strong predictive efficiency, with the high-risk group showing significantly lower overall survival, progression-free survival, and disease-specific survival. Multivariate Cox regression validated the PRPS as an independent prognostic factor, while the PRPS-based nomogram showed high predictive accuracy. Functional enrichment and immune landscape analysis revealed the differences between the risk subgroups in immune pathways, gene mutations, immune cell infiltration, and tumor mutational burden. Analysis of ICIs responses and drug sensitivity showed the differences in treatment among different risk subgroups, providing a basis for personalized treatment.

CONCLUSIONS

The PRPS provides a promising tool for the prognostic prediction, targeted prevention, and personalized treatment for GC, and may promote the precision medicine for GC patients.