ArticleAging2022
MAGE-A3 regulates tumor stemness in gastric cancer through the PI3K/AKT pathway.
Article in Aging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Therapeutic implications of targeting cancer testis antigen MAGEA1 in cervical cancer.International journal of oncology · 2026Article
- Integration of machine learning-based screening approaches and single-cell sequencing technique to identify cancer stemness genes associated with radiotherapy resistance in lung adenocarcinoma.Discover oncology · 2026Article
- Article
- Apigenin promotes apoptosis of 4T1 cells through PI3K/AKT/Nrf2 pathway and improves tumor immune microenvironment in vivo.Toxicology research · 2024Article
- NRP1 regulates autophagy and proliferation of gastric cancer through Wnt/β-catenin signaling pathway.Aging · 2023Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastric cancer remains a malignant disease of the digestive tract with high mortality and morbidity worldwide. However, due to its complex pathological mechanisms and lack of effective clinical therapies, the survival rate of patients after receiving treatment is not satisfactory. A increasing number of studies have focused on cancer stem cells and their regulatory properties. In this study, we first constructed a co-expression network based on the WGCNA algorithm to identify modules with different degrees of association with tumor stemness indices. After selecting the most positively correlated modules of the stemness index, we performed a consensus clustering analysis on gastric cancer samples and constructed the co-expression network again. We then selected the modules of interest and applied univariate COX regression analysis to the genes in this module for preliminary screening. The results of the screening were then used in LASSO regression analysis to construct a risk prognostic model and subsequently a sixteen-gene model was obtained. Finally, after verifying the accuracy of the module and screening for risk genes, we identified MAGE-A3 as the final study subject. We then performed
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