Identification of ADIPOQ as a favorable prognostic biomarker for liposarcoma based on GEO database

Published on May. 29, 2024Total Views: 1364 times Total Downloads: 445 times Download Mobile

Author: ZHAO Huanhuan ^1, ²  ZHANG Guochuan ¹

Affiliation: 1. Department of Orthopedic Oncology, Hebei Medical University Third Hospital, Shijiazhuang 050051, China 2. Fourth Department of Orthopedics, Baoding NO.1 Central Hospital, Baoding 071000, Hebei Province, China

Keywords: Liposarcoma ADIPOQ GEO database Prognosis Biomarker

DOI: 10.12173/j.issn.1004-4337.202403095

Reference: Zhao HH, Zhang GC. Identification of ADIPOQ as a favorable prognostic biomarker for liposarcoma based on GEO database[J]. Journal of Mathematical Medicine, 2024, 37(5): 341-348. DOI: 10.12173/j.issn.1004-4337.202403095[Article in Chinese]  Copied

Abstract
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Abstract

Objective To explore the prognostic biomarkers for liposarcoma as potential therapeutic targets.

Methods GSE21122, GSE159659, and GSE30929 datasets were downloaded from Gene Expression Omnibus (GEO) database. The significantly differentially expressed genes between liposarcoma and normal adipose tissues were identified using the limma package of R language. The common differentially expressed genes were obtained using the ggvenn package. The survival and survminer packages were performed for Cox regression analysis and Kaplan-Meier survival analysis. The correlation between ADIPOQ and multiple immune checkpoint molecules was analyzed using the corr. text function. Functional enrichment analysis of differentially expressed genes between liposarcomas with high and low ADIPOQ was performed by clusterProfiler package.

Results In GSE21122 and GSE159659 datasets, 155 and 39 significantly differentially expressed genes were identified, respectively. The Venn plot displayed the 25 common differentially expressed genes. Multivariate Cox regression analysis showed that ADIPOQ could serve as an independent factor for the favorable prognosis of liposarcoma [HR=0.68, 95%CI (0.49, 0.94), P=0.022]. Compared with normal adipose tissues, ADIPOQ was significantly downregulated in liposarcoma tissues (P<0.001). Kaplan-Meier survival analysis showed that liposarcoma patients with high level of ADIPOQ had significantly longer distant recurrence free survival (DRFS) than those with low ADIPOQ (P<0.001). Spearman correlation analysis showed that ADIPOQ was negatively correlated with immune checkpoint molecules such as ICOS, TNFSF9, LAG3, CTLA4, CD47, CD200, CD86, and PDCD1LG2 (P<0.05). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the upregulated genes between liposarcomas with high and low ADIPOQ were abundant in nutrient metabolism and metabolism-related pathways, while downregulated genes were involved in biological function of cell division and cell cycle.

Conclusion ADIPOQ could serve as a favorable prognostic biomarker for liposarcoma, and it may have the effect of inhibiting the expression of multiple immune checkpoints, thereby improving the prognosis of liposarcoma patients.

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