Comprehensive Single‐Cell RNA Sequencing Analysis of Cervical Cancer: Insights Into Tumor Microenvironment and Gene Expression Dynamics DOI Creative Commons

Xin Shen,

Huier Sun,

Shanshan Zhang

и другие.

International Journal of Genomics, Год журнала: 2025, Номер 2025(1)

Опубликована: Янв. 1, 2025

Background: Cervical cancer is a complex disease with considerable cellular heterogeneity, which hampers our understanding of its progression and the development effective treatments. Single-cell RNA sequencing (scRNA-seq)-a technology that enables gene expression analysis at level-has emerged as an important tool to explore this heterogeneity on cell-to-cell basis. We perform data quality differential in cervical via scRNA-seq, giving insights into tumor microenvironment likely therapeutic targets. Methods: scRNA-seq for sample advanced bioinformatics were utilized. Scatter plots generated assess control metrics based mitochondrial total count. Cell clustering identified significant genes each cell cluster. Gene coexpression networks modules performed network analysis. utilized pseudotime model experience state transitions infer trajectory functional enrichment understand biological processes involved. Results: revealed distinct cluster pattern high profile. Ultimately, suggested genes: TP53, GNG4, CCL5 had degrees potential roles progression. Some these have unique functions by analysis, while dynamic changes across reveal differences during transition. next immune response metabolic play pivotal role cancer. Conclusion: Our large scale provide dynamics within microenvironment.

Язык: Английский

Comprehensive Single‐Cell RNA Sequencing Analysis of Cervical Cancer: Insights Into Tumor Microenvironment and Gene Expression Dynamics DOI Creative Commons

Xin Shen,

Huier Sun,

Shanshan Zhang

и другие.

International Journal of Genomics, Год журнала: 2025, Номер 2025(1)

Опубликована: Янв. 1, 2025

Background: Cervical cancer is a complex disease with considerable cellular heterogeneity, which hampers our understanding of its progression and the development effective treatments. Single-cell RNA sequencing (scRNA-seq)-a technology that enables gene expression analysis at level-has emerged as an important tool to explore this heterogeneity on cell-to-cell basis. We perform data quality differential in cervical via scRNA-seq, giving insights into tumor microenvironment likely therapeutic targets. Methods: scRNA-seq for sample advanced bioinformatics were utilized. Scatter plots generated assess control metrics based mitochondrial total count. Cell clustering identified significant genes each cell cluster. Gene coexpression networks modules performed network analysis. utilized pseudotime model experience state transitions infer trajectory functional enrichment understand biological processes involved. Results: revealed distinct cluster pattern high profile. Ultimately, suggested genes: TP53, GNG4, CCL5 had degrees potential roles progression. Some these have unique functions by analysis, while dynamic changes across reveal differences during transition. next immune response metabolic play pivotal role cancer. Conclusion: Our large scale provide dynamics within microenvironment.

Язык: Английский

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