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To investigate the potential association between Anoikis-related genes, which are responsible for preventing abnormal cellular proliferation, and rheumatoid arthritis (RA). Datasets GSE89408, GSE198520, and GSE97165 were obtained from the GEO with 282 RA patients and 28 healthy controls. We performed differential analysis of all genes and genes. We performed a protein-protein interaction network analysis and identified hub genes based on and cytoscape. Consistent clustering was performed with subgrouping of the disease. SsGSEA were used to calculate immune cell infiltration. Spearman's correlation analysis was employed to identify correlations. Enrichment scores of the GO and KEGG were calculated with the ssGSEA algorithm. The WGCNA and the database were used to mine hub genes' interactions with drugs. There were 26 differentially expressed Anoikis-related genes ( = 0.05, log2FC = 1) and HLA genes exhibited differential expression ( < 0.05) between the disease and control groups. Protein-protein interaction was observed among differentially expressed genes, and the correlation between and was found to be the highest; There were significant differences in the degree of immune cell infiltration between most of the immune cell types in the disease group and normal controls ( < 0.05). Anoikis-related genes were highly correlated with HLA genes. Based on the expression of Anoikis-related genes, RA patients were divided into two disease subtypes (cluster1 and cluster2). There were 59 differentially expressed Anoikis-related genes found, which exhibited significant differences in functional enrichment, immune cell infiltration degree, and gene expression ( < 0.05). Cluster2 had significantly higher levels in all aspects than cluster1 did. The co-expression network analysis showed that cluster1 had 51 hub differentially expressed genes and cluster2 had 72 hub differentially expressed genes. Among them, three hub genes of cluster1 were interconnected with 187 drugs, and five hub genes of cluster2 were interconnected with 57 drugs. Our study identified a link between Anoikis-related genes and RA, and two distinct subtypes of RA were determined based on Anoikis-related gene expression. Notably, cluster2 may represent a more severe state of RA.
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http://dx.doi.org/10.3389/fmolb.2023.1202371 | DOI Listing |
Front Genet
August 2025
Anorectal Department, Affiliated Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Background: Rectal adenocarcinoma (READ) is a common malignant tumor. This study aims to establish a risk model based on anoikis-related genes (ARGs) to predict prognosis and the tumor microenvironment in READ.
Methods: Transcriptomic data and clinical data downloaded from the TCGA and GEO databases were used for differential analysis and Cox regression analysis.
Front Mol Biosci
August 2025
Department of Otolaryngology, Head and Neck Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Introduction: Chronic rhinosinusitis with nasal polyps (CRSwNP) is characterized by stromal edema, albumin deposition, and pseudocyst formation. Anoikis, a process in which cells detach from the correct extracellular matrix, disrupts integrin junctions, thereby inhibiting improperly proliferating cells from growing or adhering to an inappropriate matrix. Although anoikis is implicated in immune regulation and CRSwNP pathogenesis, its specific mechanistic role remains poorly defined.
View Article and Find Full Text PDFJ Cancer
July 2025
Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, P. R. China.
The acquisition of resistance to anoikis is a critical driver of metastasis in various tumor types. However, the combined role of anoikis apoptosis in the progression and prognosis of hepatocellular carcinoma (HCC) remains largely unexplored. This study integrates known anoikis genes with single-cell datasets to identify differentially expressed Anoikis (DE-Anoikis) through unsupervised clustering, enabling the classification of samples from The Cancer Genome Atlas (TCGA).
View Article and Find Full Text PDFAnn Med
December 2025
Jiangxi Provincial Key Laboratory of Urinary System Diseases, Department of Urology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, P.R. China.
Background: Metastasis represents the primary cause of cancer-related mortality, with a high incidence observed in renal cell carcinoma (RCC). Anoikis, a specialized form of apoptosis, plays a crucial role in preventing displaced cells from adhering to new extracellular matrices (ECM), thus inhibiting their aberrant growth. Notably, cancer cells, especially metastatic ones, exhibit resistance to anoikis.
View Article and Find Full Text PDFSci Rep
August 2025
Key Clinical Laboratory of Henan Province, Department of Clinical Laboratory, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, Henan, China.
Colorectal cancer (CRC) is a most deadly cancer, and effective prognostic biomarkers are urgently needed. Although anoikis has diverse regulatory roles in tumor progression, the impact of anoikis-related genes (ANRG) by single-cell and bulk transcriptome analyses on the prognostic value for CRC have not been studied. Differentially expressed genes (DEGs) associated with anoikis were obtained by performing single-cell RNA-sequencing (scRNA-seq) analysis in cells with high and low ANRG expression and weighted correlation network analysis (WGCNA) in a bulk RNA sequencing dataset.
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