AccScience Publishing / GPD / Volume 3 / Issue 1 / DOI: 10.36922/gpd.2607
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ORIGINAL RESEARCH ARTICLE

High expression of apoptosis-related LMNB2 predicts an unfavorable outcome: A potential prognostic biomarker for liposarcoma

Xinyu Li1,2† ,  Jialin Wu1,2† ,  Man Yue1,2 ,  Mengwen Hou1,2 ,  Jiayang Han1,2 ,  Binbin Zhao1,2 ,  Tiantian Sun1,2 ,  Xu Han1,2 ,  Guangchao Liu1,2 ,  Kaifeng Zhang1,2 ,  Tinggai Wu1,2 ,  Ting Ye1,2 ,  Mengjie Tu1,2 ,  Yang An1,2*
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1 Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Henan University, Kaifeng, China
2 Henan Provincial Engineering Center for Tumor Molecular Medicine, Kaifeng Key Laboratory of Cell Signal Transduction, Henan University, Kaifeng, China
GPD 2024, 3(1), 2607 https://doi.org/10.36922/gpd.2607
Submitted: 1 January 2024 | Accepted: 27 February 2024 | Published: 26 March 2024
© 2024 by the Author (s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Liposarcoma (LPS) is the most prevalent soft-tissue sarcoma and the second most common malignant mesenchymal sarcoma. Molecular markers have proven instrumental in guiding the diagnosis, prognosis, and treatment strategies for LPS patients. Identifying potential therapeutic targets is essential for developing effective intervention strategies for LPS. LMNB2, an apoptosis-related gene, exhibits associations with various tumors. Therefore, exploring the feasibility of LMNB2 as a prognostic biomarker for LPS is crucial. After screening for differentially expressed genes (DEGs), which were analyzed by GEO2R, 14 apoptosis-related genes were obtained by overlapping DEGs from the GSE21122 and GSE159659 datasets. SPSS software was used for univariate analysis. Receiver operating characteristic curves were constructed by GraphPad software to compare the expression of LMNB2 between LPS and normal tissues. Kaplan–Meier curves were generated to verify the correlation between LMNB2 expression and survival time. GeneMANIA and STRING were used to construct LMNB2-related gene-gene and protein–protein interaction networks. Hiplot software facilitated function and pathway enrichment analysis to determine the potential mechanism of LMNB2-mediated LPS progression. CIBERSORT was used to evaluate the correlation between LMNB2 expression and immune cell infiltration. The expression level of LMNB2 was significantly higher in LPS, and the high expression of LMNB2 was significantly related to poor prognosis in LPS patients. Further analysis indicated that LMNB2 was mainly involved in “senescence” and “apoptosis,” further confirming its role in regulating the occurrence and development of LPS by modulating the cell cycle progression and apoptosis. This study demonstrates that the elevated expression of LMNB2 is significantly associated with poor prognostic outcomes in LPS, suggesting that LMNB2 holds high potential as a new biomarker for LPS. This study is designed to elucidate the potential mechanism of LMNB2-mediated LPS progression, with the prospect of improving therapeutic development by identifying LMNB2 as a promising prognostic biomarker for LPS.

Keywords
LMNB2
Liposarcoma
Prognostic biomarker
Apoptosis
Funding
This work was supported by the Program for Science and Technology Development in Henan Province (No.212102310616) and the Innovation Project for College Students of Henan University (Nos. 20237003002; 20237003003; 202310475091).
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Conflict of interest
The authors declare no conflicts of interest.
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