ArticleFrontiers in immunology2024
Development of an anoikis-related gene signature and prognostic model for predicting the tumor microenvironment and response to immunotherapy in colorectal cancer.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Decoding anoikis-related genes in lung adenocarcinoma brainmetastasis via single-cell RNA sequencing: CD44-mediated functions.BMC cancer · 2025Article
- Intervention of machine learning in bladder cancer research using multi-omics datasets: systematic review on biomarker identification.Discover oncology · 2025Review
- Integrating bulk, single-cell, and spatial transcriptomics to identify and functionally validate novel targets to enhance immunotherapy in NSCLC.NPJ precision oncology · 2025Article
- Identification of hub genes in myocardial infarction by bioinformatics and machine learning: insights into inflammation and immune regulation.Frontiers in molecular biosciences · 2025Article
- CD82-associated exhausted CD8Frontiers in immunology · 2025Article
- Multi-cohort validation based on a novel prognostic signature of anoikis for predicting prognosis and immunotherapy response of esophageal squamous cell carcinoma.Frontiers in oncology · 2025Article
- Effect of colorectal cancer stem cells on the development and metastasis of colorectal cancer.World journal of gastrointestinal oncology · 2024Review
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Authors and funding
5 authors.
Funding
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Abstract
The effect of anoikis-related genes (ARGs) on clinicopathological characteristics and tumor microenvironment remains unclear. We comprehensively analyzed anoikis-associated gene signatures of 1057 colorectal cancer (CRC) samples based on 18 ARGs. Anoikis-related molecular subtypes and gene features were identified through consensus clustering analysis. The biological functions and immune cell infiltration were assessed using the GSVA and ssGSEA algorithms. Prognostic risk score was constructed using multivariate Cox regression analysis. The immunological features of high-risk and low-risk groups were compared. Finally, DAPK2-overexpressing plasmid was transfected to measure its effect on tumor proliferation and metastasis
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