ArticleThe Libyan journal of medicine2023
Construction of stomach adenocarcinoma prognostic signature based on anoikis-related lncRNAs and clinical significance.
Article in The Libyan journal of medicine, 2023. 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.
- Comprehensive Analysis of Glycosyltransferase-Related Genes Reveals their Prognostic and Therapeutic Implications in Stomach Adenocarcinoma.Current protein & peptide science · 2026Article
- Anoikis classification of lung squamous cell carcinoma reveals correlation with clinical prognosis and immune characteristics.Annals of medicine · 2025Article
- Anoikis resistance in gastric cancer: a comprehensive review.Cell death & disease · 2025Review
- Predictive Factors of Immunotherapy in Gastric Cancer: A 2024 Update.Diagnostics (Basel, Switzerland) · 2024Review
- Prognostic Implication of Plasma Metabolites in Gastric Cancer.International journal of molecular sciences · 2023Article
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Authors and funding
6 authors.
Funding
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Abstract
As a dominant type of gastric cancer, stomach adenocarcinoma (STAD) is characterized by high morbidity and mortality rates. Anoikis factors participate in tumor metastasis and invasion. This study was designed to identify prognostic risk factors in anoikis-related long non-coding RNAs (lncRNAs) for STAD. First, with STAD expression datasets and anoikis-related gene sets downloaded from public databases, anoikis-related prognostic lncRNA signatures (AC091057.1, ADAMTS9.AS1, AC090825.1, AC084880.3, EMX2OS, HHIP.AS1, AC016583.2, EDIL3.DT, DIRC1, LINC01614, and AC103702.2) were screened by Cox regression to establish a prognostic risk model. Kaplan-Meier and receiver operating characteristic curves were used to evaluate the survival status of patients and verify predictive accuracy of the model. Besides, risk score could be an independent prognostic factor to assess the prognosis of STAD patients. Nomograms of the prognostic model that combined clinical information and risk score could effectively predict survival of STAD patients, as validated by calibration curve. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were performed for differentially expressed genes (DEGs) in high- and low-risk groups. These DEGs were related to neurotransmitter transmission, signal transmission, and endocytosis. Moreover, we analyzed immune status of different risk groups and found that STAD patients in low-risk group were more sensitive to immunotherapy. A prognostic risk assessment model for STAD using anoikis-related lncRNA genes was constructed here, which was proven to have high predictive accuracy and thus could offer a reference for prognostic evaluation and clinical treatment of STAD patients.
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