Construction and validation of a nomogram model for predicting peritoneal metastasis in gastric cancer based on ferroptosis-relate genes and clinicopathological features.

ABSTRACT:

Background

Gastric cancer peritoneal metastasis (GCPM) is a lethal condition. Current diagnostic methods for GCPM, such as imaging and serum tumor markers, lack specificity and sensitivity. Research suggests that utilizing gene signatures to predict GCPM shows significant predictive ability. Nonetheless, the predictability of GCPM using ferroptosis-related genes (FRGs) remains unknown. We aim to construct a nomogram based on FRGs for early diagnosis of GCPM.

Methods

RNA sequencing and clinical data of patients with gastric cancer (GC) were downloaded from Gene Expression Omnibus (GEO) databases. GCPM was diagnosed through imaging, biopsy and cytology. A GCPM prediction model was developed based on six distinctively expressed FRGs, and the efficiency of the model was assessed

SUBMITTER: Sun X 

PROVIDER: S-EPMC11921409 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature