Jun 2026· Naunyn-Schmiedeberg's Archives of Pharmacology· 0 citations· 68 references
Medicine
TL;DR
Prognostic features associated with uric acid metabolism in gastric cancer are identified and suggest that ABCG4, SERPINE1, and GPX3 may be involved in metabolic dysregulation, matrix remodeling, and predicted pharmacogenomics response patterns.
The proposed glutathione metabolism-related signature demonstrated prognostic value in both training and validation cohorts and was associated with immune characteristics, pathway enrichment patterns, genomic alterations, and tumor mutation burden in LUAD.
Z. Sheng, Si-Yu Chen, Su Chen· Cancer Informatics· 0 citations
The seven-gene risk model provides a reliable tool for survival prediction and may guide personalized therapeutic strategies in gastric cancer as well as predict therapeutic response in gastric cancer.
Li-Nen Li, Hui-Ling Zhu, Guangjun Gao et al.· Cancer Informatics· 0 citations
The risk model and nomogram aided prognosis prediction, providing new insights for CESC treatment and VAC14 and INPP5K were PPM-related prognostic genes for CESC.
H. Meng, Li Tan, Ying Chen et al.· BMC Cancer· 0 citations
A five-gene prognostic model established from 220 FMRGs demonstrated moderate prognostic performance in identifying high-risk stomach adenocarcinoma patients with poorer survival and served as a robust independent prognostic indicator in STAD.
Liu He, Lilei Zhuang, Shenbao Wu· Discover Oncology· 0 citations
An ARG-based prognostic model for HCC was established and preliminarily suggested that PGF may be involved in regulating the sensitivity of HCC cells toimatinib, and a preliminary basis for further investigation of ARG-relaterognostic assessment and PGF-mediated drug sensitivity.
Jian-Wen Duan, Ren-Ya Jiang, Lei Yuan et al.· Digestive Diseases and Scien...· 0 citations
It is suggested that glycolytic activity is closely associated with both drug resistance and clinical prognosis in LUAD, and the proposed integrative model holds promise for enhancing precision treatment decision-making through optimized risk assessment and rational selection of chemotherapeutic regimens.
Qian Zheng, Yunxiao Liu, Tianli Li et al.· Frontiers in Oncology· 0 citations
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