Identifying PSIP1 as a critical R-loop regulator in osteosarcoma via machine-learning and multi-omics analysis DOI Creative Commons
Jiangbo Nie, Shijiang Wang,

Yanxin Zhong

et al.

Cancer Cell International, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 22, 2025

Dysregulation of R-loops has been implicated in tumor development, progression, and the regulation immune microenvironment (TME). However, their roles osteosarcoma (OS) remain underexplored. In this study, we firstly constructed a novel R-loop Gene Prognostic Score Model (RGPSM) based on RNA-sequencing (RNA-seq) datasets evaluated relationships between RGPSM scores TME. Additionally, identified key R-loop-related genes involved OS progression using single-cell RNA sequencing (scRNA-seq) dataset, validated these findings through experiments. We found that patients with high-RGPSM exhibited poorer prognosis, lower Huvos grades more suppressive Moreover, proportion malignant cells was significantly higher group. And integrated analysis RNA-seq scRNA-seq revealed PC4 SRSF1 Interacting Protein 1 (PSIP1) highly expressed osteoblastic proliferative cells. Notably, high expression PSIP1 associated poor prognosis patients. Subsequent experiments demonstrated knockdown inhibited both vivo vitro, leading increased accumulation DNA damage. Conversely, overexpression facilitated resolution reduced damage induced by cisplatin. conclusion, developed effectively predicted outcomes across diverse cohorts as critical modulator regulating

Language: Английский

Identifying PSIP1 as a critical R-loop regulator in osteosarcoma via machine-learning and multi-omics analysis DOI Creative Commons
Jiangbo Nie, Shijiang Wang,

Yanxin Zhong

et al.

Cancer Cell International, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 22, 2025

Dysregulation of R-loops has been implicated in tumor development, progression, and the regulation immune microenvironment (TME). However, their roles osteosarcoma (OS) remain underexplored. In this study, we firstly constructed a novel R-loop Gene Prognostic Score Model (RGPSM) based on RNA-sequencing (RNA-seq) datasets evaluated relationships between RGPSM scores TME. Additionally, identified key R-loop-related genes involved OS progression using single-cell RNA sequencing (scRNA-seq) dataset, validated these findings through experiments. We found that patients with high-RGPSM exhibited poorer prognosis, lower Huvos grades more suppressive Moreover, proportion malignant cells was significantly higher group. And integrated analysis RNA-seq scRNA-seq revealed PC4 SRSF1 Interacting Protein 1 (PSIP1) highly expressed osteoblastic proliferative cells. Notably, high expression PSIP1 associated poor prognosis patients. Subsequent experiments demonstrated knockdown inhibited both vivo vitro, leading increased accumulation DNA damage. Conversely, overexpression facilitated resolution reduced damage induced by cisplatin. conclusion, developed effectively predicted outcomes across diverse cohorts as critical modulator regulating

Language: Английский

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