FERROPTOSIS GENE SIGNATURES REVEAL DISTINCT REGULATORY LANDSCAPES IN GASTRIC ADENOCARCINOMA AND OTHER TISSUES

preprint OA: closed
📄 Open PDF Full text JSON View at publisher
Full text 1,830 characters · extracted from oa-doi-fallback · 4 sections · click to expand

Abstract

Background Gastric adenocarcinoma (GAC) remains one of the most lethal malignancies worldwide, with late-stage diagnosis and limited therapeutic options. Ferroptosis, a regulated form of cell death driven by iron-dependent lipid peroxidation, has emerged as a promising target for overcoming tumor resistance mechanisms. This study aimed to characterize the transcriptional landscape of ferroptosis-related genes in GAC, comparing tumor, peritumoral, metaplastic, and normal gastric tissues.

Methods

RNA-Seq was performed on 385 biopsied samples from patients treated at the João de Barros Barreto University Hospital. Differential expression analysis was conducted using DESeq2, and genes related to ferroptosis were identified based on FerrDb V2 annotations. Visualization included volcano plots, DAPC clustering, heatmaps, and gene dominance scoring.

Results

GAC samples showed a distinct ferroptotic expression signature, with simultaneous upregulation of key promoters (e.g., CDKN2A, NOX4, EGFR, IL6) and suppressors (e.g., HSPB1, SCD, NUPR1, GDF15). Notably, the tumor tissue exhibited a net dominance of ferroptosis-inhibitory genes, suggesting an adaptive response to oxidative stress. Adjacent tissues showed partial overlap with tumor profiles, while metaplastic tissue displayed a hybrid signature with selective suppression of ferroptosis. Normal mucosa exhibited dominant expression of promoters, contrasting with the tumor’s anti-ferroptotic phenotype.

Conclusion

The transcriptional heterogeneity and regulatory imbalance of ferroptosis-related genes in GAC support its role as a potential therapeutic axis. These findings provide molecular insights for biomarker discovery and ferroptosis-targeted strategies in gastric cancer. Competing Interest Statement The authors have declared no competing interest.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00