Hui Liu, Yongming Huang, Guanghua Fu, Bo Lei, Ke Liu
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引用次数: 0
Abstract
Introduction: Metabolism-related genes (MRGs) critically influence cancer prognosis, yet their role in gastric carcinoma (GC) remains poorly understood.
Methods: We analyzed 24,991 genes from 407 GC patients in TCGA to identify a metabolic gene-based prognostic signature. In vitro and in vivo functional experiments validated key findings, while transcriptional regulation mechanisms were explored through promoter interaction assays.
Results: A robust 10-metabolic gene signature was identified as strongly predictive of recurrence-free survival (RFS) in GC. Elevated insulin-like growth factor binding protein 1 (IGFBP1) expression correlated with reduced overall survival and disease-free survival. Functional studies demonstrated IGFBP1's oncogenic role in promoting GC proliferation and metastasis. Mechanistically, zinc finger protein X-linked (ZFX) activated IGFBP1 transcription by directly binding to its promoter.
Discussion: We established a prognostic nomogram integrating the 10-metabolic gene signature for GC RFS prediction. IGFBP1 emerges as a potential therapeutic target and biomarker, with ZFX-driven transcriptional activation as a novel regulatory axis in GC progression.
期刊介绍:
OncoTargets and Therapy is an international, peer-reviewed journal focusing on molecular aspects of cancer research, that is, the molecular diagnosis of and targeted molecular or precision therapy for all types of cancer.
The journal is characterized by the rapid reporting of high-quality original research, basic science, reviews and evaluations, expert opinion and commentary that shed novel insight on a cancer or cancer subtype.
Specific topics covered by the journal include:
-Novel therapeutic targets and innovative agents
-Novel therapeutic regimens for improved benefit and/or decreased side effects
-Early stage clinical trials
Further considerations when submitting to OncoTargets and Therapy:
-Studies containing in vivo animal model data will be considered favorably.
-Tissue microarray analyses will not be considered except in cases where they are supported by comprehensive biological studies involving multiple cell lines.
-Biomarker association studies will be considered only when validated by comprehensive in vitro data and analysis of human tissue samples.
-Studies utilizing publicly available data (e.g. GWAS/TCGA/GEO etc.) should add to the body of knowledge about a specific disease or relevant phenotype and must be validated using the authors’ own data through replication in an independent sample set and functional follow-up.
-Bioinformatics studies must be validated using the authors’ own data through replication in an independent sample set and functional follow-up.
-Single nucleotide polymorphism (SNP) studies will not be considered.