ArticleAging2023
Development and validation of a novel anoikis-related gene signature for predicting prognosis in ovarian cancer.
Article in Aging, 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Discovery of Anoikis-correlated Biomarkers for Ovarian Cancer Through Integrated Transcriptome and Single-cell RNA Sequencing Analyses.Current topics in medicinal chemistry · 2026Article
- Integration of Multi-omics Data Based on Deep Learning for Subtyping of Low-Grade Glioma.Journal of molecular neuroscience : MN · 2025Article
- Identification of anoikis-related genes to develop a risk model and predict the prognosis and tumor microenvironment in rectal adenocarcinoma.Frontiers in genetics · 2025Article
- Anoikis-related signature predicts prognosis and characterizes immune landscape of ovarian cancer.Cancer cell international · 2024Article
- Identification of Novel Anoikis-Related Gene Signatures to Predict the Prognosis, Immune Microenvironment, and Drug Sensitivity of Breast Cancer Patients.Cancer control : journal of the Moffitt Cancer CenterArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Anoikis plays a critical role in variable cancer types. However, studies that focus on the prognostic values of anoikis-related genes (ANRGs) in OV are scarce. Cohorts with transcriptome data and corresponding clinicopathologic data of OV patients were collected and consolidated from public databases. Multiple bioinformatics approaches were used to screen key genes from 446 anoikis-related genes, including Cox regression analysis, random survival forest analysis, and Kaplan-Meier analysis of best combinations. A five-gene signature was constructed in the discovery cohort (TCGA) and validated in four validation cohorts (GEO). Risk score of the signature stratified patients into high-risk (HRisk) and low-risk (LRisk) subgroups. Patients in the HRisk group were associated with worse OS than those in the LRisk group in both the TCGA cohort (p<0.0001, HR=2.718, 95%CI:1.872-3.947) and the four GEO cohorts (p<0.05). Multivariate Cox regression analyses confirmed that the risk score served as an independent prognostic factor in both cohorts. The signature's predictive capacity was further demonstrated by the nomogram analysis. Pathway enrichment analysis revealed that immunosuppressive and malignant progression-related pathways were enriched in the HRisk group, including TGF-β, WNT and ECM pathways. The LRisk group was characterized by immune-active signaling pathways (interferon-gamma, T cell activation, etc.) and higher proportions of anti-tumor immune cells (NK, M1, etc.) while HRisk patients were associated with higher stromal scores and less TCR richness. In conclusion, the signature reveals a close relationship between the anoikis and prognosis and may provide a potential therapeutic target for OV patients.
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