Single-cell RNA-seq combined with bulk RNA-seq analysis identifies necroptosis-related genes as therapeutic targets for periodontitis DOI
Feixiang Zhu, Mingyan Xu,

Yixin Xiao

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: May 15, 2025

Abstract Background Necroptosis, a regulated form of cell self-destruction, exacerbates inflammatory responses by releasing damage-associated molecular patterns and factors. However, the specific mechanisms underlying necroptosis in periodontitis remain poorly explored. This study integrated single-cell RNA sequencing (scRNA-seq) transcriptome (RNA-seq) data to identify core necroptosis-related genes (NRGs) validated these findings using external datasets samples collected during our research.Methods Overlapping were identified comparing 114 NRGs from GeneCards with marker various types GSE171213 dataset. Based on genes, cells categorized into high- low-necroptosis score groups. Key via intersection analysis differentially expressed high group GSE10334 bulk RNA-seq dataset, followed Kyoto Encyclopedia Genes Genomes (KEGG)/ Gene Ontology (GO) enrichment analysis. Machine learning further hub associated response periodontitis. Consensus clustering analysis, clinical diagnostic model construction, gene set variation performed based genes. The was independent tissue samples.Results We 10 tissues observed changes abundance populations affected samples. Furthermore, we selected 35 populations, neutrophils macrophages showing higher scores. By integrating data, 29 key NRGs. KEGG/GO indicated their signaling pathways. highlighted six (CSF3R, CSF2RB, BTG2, CXCR4, GPSM3, SSR4), all which highly tissues. divided patients two subgroups distinct expression profiles. constructed exhibited excellent performance. Both validation sets sample tests confirmed tissues.Conclusion Our SSR4) positively correlated necroptosis. These may serve as therapeutic targets for diseases like

Language: Английский

Single-cell RNA-seq combined with bulk RNA-seq analysis identifies necroptosis-related genes as therapeutic targets for periodontitis DOI
Feixiang Zhu, Mingyan Xu,

Yixin Xiao

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: May 15, 2025

Abstract Background Necroptosis, a regulated form of cell self-destruction, exacerbates inflammatory responses by releasing damage-associated molecular patterns and factors. However, the specific mechanisms underlying necroptosis in periodontitis remain poorly explored. This study integrated single-cell RNA sequencing (scRNA-seq) transcriptome (RNA-seq) data to identify core necroptosis-related genes (NRGs) validated these findings using external datasets samples collected during our research.Methods Overlapping were identified comparing 114 NRGs from GeneCards with marker various types GSE171213 dataset. Based on genes, cells categorized into high- low-necroptosis score groups. Key via intersection analysis differentially expressed high group GSE10334 bulk RNA-seq dataset, followed Kyoto Encyclopedia Genes Genomes (KEGG)/ Gene Ontology (GO) enrichment analysis. Machine learning further hub associated response periodontitis. Consensus clustering analysis, clinical diagnostic model construction, gene set variation performed based genes. The was independent tissue samples.Results We 10 tissues observed changes abundance populations affected samples. Furthermore, we selected 35 populations, neutrophils macrophages showing higher scores. By integrating data, 29 key NRGs. KEGG/GO indicated their signaling pathways. highlighted six (CSF3R, CSF2RB, BTG2, CXCR4, GPSM3, SSR4), all which highly tissues. divided patients two subgroups distinct expression profiles. constructed exhibited excellent performance. Both validation sets sample tests confirmed tissues.Conclusion Our SSR4) positively correlated necroptosis. These may serve as therapeutic targets for diseases like

Language: Английский

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