Revealing the key modules and potential prognostic markers of gastric cancer transformation based on weighted gene co-expression networks

WGCNA reveals modules associated with gastric precancerous lesions and cancer progression. <i>FCRL3</i>, <i>EFEMP1</i>, <i>ANKRD29</i>, and <i>STOX2</i> may serve as potential biomarkers for monitoring the transition from precancerous lesions to gastric cancer, offering insights into the mechanisms of gastric carcinogenesis and supporting early diagnosis and intervention strategies.

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Publication Details

Journal
Frontiers in Genetics
Published
2025-11-25
DOI
https://doi.org/10.3389/fgene.2025.1613682
Primary Topic
Ferroptosis and cancer prognosis
Type
article
Field-Weighted Citation Impact
0.00

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article

Revealing the key modules and potential prognostic markers of gastric cancer transformation based on weighted gene co-expression networks

Hao Gu, Zhen Yang, Heng Li, Xiao–Ping Zhang et al.
Frontiers in Genetics
Ferroptosis and cancer prognosis
article

Revealing the key modules and potential prognostic markers of gastric cancer transformation based on weighted gene co-expression networks

Hao Gu, Zhen Yang, Heng Li, Xiao–Ping Zhang, Yufeng Zhao, Haiyu Liu, Wen Li
article en

Abstract

WGCNA reveals modules associated with gastric precancerous lesions and cancer progression. <i>FCRL3</i>, <i>EFEMP1</i>, <i>ANKRD29</i>, and <i>STOX2</i> may serve as potential biomarkers for monitoring the transition from precancerous lesions to gastric cancer, offering insights into the mechanisms of gastric carcinogenesis and supporting early diagnosis and intervention strategies.

Frontiers in GeneticsVol. 16
Tianjin University of Traditional Chinese Medicine (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Lanzhou University (CN)
National Natural Science Foundation of China, China Academy of Chinese Medical Sciences
Openalex Percentile: Top 46%
Ferroptosis and cancer prognosis
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Revealing the key modules and potential prognostic markers of gastric cancer transformation based on weighted gene co-expression networks — Hao Gu, Zhen Yang, et al. · Frontiers in Genetics (2025) | TGRS Research Map | TGRS