Integrated Multi-Level Investigation of Friend Leukemia Integration 1 Transcription Factor as a Novel Immune-Inflammatory Biomarker in Rheumatoid Arthritis: Bridging Bioinformatics, Clinical Cohorts, and Mechanistic Validation DOI Creative Commons
Mengyu Zhang, Lei Wan, Hui Fang

и другие.

Journal of Inflammation Research, Год журнала: 2025, Номер Volume 18, С. 3105 - 3123

Опубликована: Март 1, 2025

Friend Leukemia Integration 1 Transcription Factor (FLI1) has attracted attention due to its involvement in rheumatoid arthritis (RA). Nevertheless, the precise mechanism through which FLI1 contributes RA remains elusive. We investigated potential role of integrated bioinformatics, clinical experiments, and cellular experiments. Based on GSE1919 GSE12021 datasets, Kyoto Encyclopedia Genes Genomes (KEGG) Gene Ontology (GO) analyses identified as a differential gene RA. Clinical validation was performed by measuring expression serum collected from patients. Correlational analysis between immune-inflammatory markers confirmed association with inflammation. WGCNA analysis, along KnockTF, JASPAR, ENCODE databases, employed predict target genes FLI1. Receiver operating characteristic gene-set enrichment analysis-KEGG were conducted elucidate biological functions these genes. Finally, experiments validate FLI1's regulatory effects impact synovial cell viability apoptosis upregulated exhibited positive correlations CRP, ESR, CCP, RF, IL-6, IL-10, IL-8, TNF-α. The combined detection RF demonstrated highest efficacy evaluating disease activity. most strongly associated AGA, DCK, LRRC15, MAN2A1, TES, all suppression led decreased TES. Furthermore, inhibition reduced cells promoted their apoptosis. FLI is can promote inflammation, increase viability, or inhibit This finding suggests that may serve novel therapeutic targets present findings integrate bioinformatics experimental approaches advance our current understanding open new avenues for targeted therapies.

Язык: Английский

Promise of rheumatoid arthritis therapy: From clinical deep remission to drug-free DOI

Yuke Hou,

Yuanhong Peng,

Jiayang Jin

и другие.

Best Practice & Research Clinical Rheumatology, Год журнала: 2025, Номер unknown, С. 102031 - 102031

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
Integrated Multi-Level Investigation of Friend Leukemia Integration 1 Transcription Factor as a Novel Immune-Inflammatory Biomarker in Rheumatoid Arthritis: Bridging Bioinformatics, Clinical Cohorts, and Mechanistic Validation DOI Creative Commons
Mengyu Zhang, Lei Wan, Hui Fang

и другие.

Journal of Inflammation Research, Год журнала: 2025, Номер Volume 18, С. 3105 - 3123

Опубликована: Март 1, 2025

Friend Leukemia Integration 1 Transcription Factor (FLI1) has attracted attention due to its involvement in rheumatoid arthritis (RA). Nevertheless, the precise mechanism through which FLI1 contributes RA remains elusive. We investigated potential role of integrated bioinformatics, clinical experiments, and cellular experiments. Based on GSE1919 GSE12021 datasets, Kyoto Encyclopedia Genes Genomes (KEGG) Gene Ontology (GO) analyses identified as a differential gene RA. Clinical validation was performed by measuring expression serum collected from patients. Correlational analysis between immune-inflammatory markers confirmed association with inflammation. WGCNA analysis, along KnockTF, JASPAR, ENCODE databases, employed predict target genes FLI1. Receiver operating characteristic gene-set enrichment analysis-KEGG were conducted elucidate biological functions these genes. Finally, experiments validate FLI1's regulatory effects impact synovial cell viability apoptosis upregulated exhibited positive correlations CRP, ESR, CCP, RF, IL-6, IL-10, IL-8, TNF-α. The combined detection RF demonstrated highest efficacy evaluating disease activity. most strongly associated AGA, DCK, LRRC15, MAN2A1, TES, all suppression led decreased TES. Furthermore, inhibition reduced cells promoted their apoptosis. FLI is can promote inflammation, increase viability, or inhibit This finding suggests that may serve novel therapeutic targets present findings integrate bioinformatics experimental approaches advance our current understanding open new avenues for targeted therapies.

Язык: Английский

Процитировано

0