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Research Domains Biomedical and Clinical Sciences Oncology and Carcinogenesis Predictive and prognostic markers
Identification of NINJ1 as a novel prognostic predictor for retroperitoneal liposarcoma

Identification of NINJ1 as a novel prognostic predictor for retroperitoneal liposarcoma

Yu Zhao ¹, Da Qin ¹, Xiangji Li ², Tiange Wang ¹, Tong Zhang ³, Xiaosong Rao ³, Li Min ¹, Zhiyi Wan ⁴, Chenghua Luo ⁵, Mengmeng Xiao ⁶

Yu Zhao ¹, Da Qin ¹, Xiangji Li ²

¹Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing, China.
²Department of Retroperitoneal Tumor Surgery, International Hospital, Peking University, Beijing, China.
³Department of Pathology, International Hospital, Peking University, Beijing, China.
⁴College of Biological Sciences, China Agricultural University, Beijing, China.
⁵Department of Retroperitoneal Tumor Surgery, Peking University People's Hospital, Beijing, China. pkuihlch@163.com.
⁶Department of Retroperitoneal Tumor Surgery, International Hospital, Peking University, Beijing, China. xiaomengmeng@pku.edu.cn.

⁰Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, National Clinical Research Center for Digestive Disease, Beijing Digestive Disease Center, Beijing Key Laboratory for Precancerous Lesion of Digestive Disease, Beijing, China.

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May 11, 2024

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View abstract on PubMed

Summary

This summary is machine-generated.

NINJ1 is a novel prognostic biomarker for retroperitoneal liposarcoma (RPLS). Higher NINJ1 expression correlates with improved overall survival (OS) and disease-free survival (DFS) in RPLS patients, aiding treatment and drug development.

Area Of Science

Oncology
Genomics
Biomarker Discovery

Background

Retroperitoneal liposarcoma (RPLS) is characterized by frequent local recurrence and poor survival.
Identifying reliable prognostic biomarkers is crucial for improving patient outcomes.

Purpose Of The Study

To identify a specific and credible prognostic biomarker for RPLS.
To validate the prognostic significance of potential biomarkers in independent cohorts.

Main Methods

Weighted gene co-expression network analysis (WGCNA) was used to construct co-expression modules from TCGA sarcoma dataset.
Hub genes within significant modules were analyzed for survival association using Kaplan-Meier and Cox regression.
External validation was performed on a Chinese RPLS cohort from the RESAR study.

Main Results

The green co-expression module positively correlated with overall survival (OS) and disease-free survival (DFS).
NINJ1, a hub gene in the green module, showed a positive association with OS in the TCGA cohort.
Elevated NINJ1 expression was linked to higher OS and DFS in both training and validation cohorts, confirmed by multivariable analysis.

Conclusions

NINJ1 emerges as a significant independent prognostic biomarker for RPLS.
This finding supports NINJ1's potential role in clinical treatment decisions and targeted therapy development for RPLS.

Keywords:

Gene expression NINJ1 Overall survival Prognosis Retroperitoneal liposarcoma

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