SOX9, GATA3, and GATA4 Overexpression in Liposarcomas: Insights into the Molecular Biology of Adipocytic Sarcomas

脂肪肉瘤中SOX9、GATA3和GATA4的过表达:脂肪细胞肉瘤分子生物学的启示

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Abstract

Liposarcomas represent a heterogeneous group of malignant mesenchymal neoplasms, with diverse histological subtypes and molecular alterations. This study aimed to investigate the gene expression profiles of SOX9, GATA3, and GATA4 in liposarcoma subtypes and to assess their associations with clinicopathological parameters. Forty-two formalin-fixed, paraffin-embedded liposarcoma samples were analyzed. Total RNA was extracted, reverse-transcribed, and quantified by qRT-PCR using GAPDH as an endogenous control. Relative quantification (RQ) values were categorized, and statistical analyses included Fisher's exact test, Kaplan-Meier survival analysis, and Cox proportional hazards modeling. SOX9 expression significantly varied among histological subtypes (p = 0.017), with ALT/WDLS cases showing a predominance of high-level expression (RQ > 50 in 12/15 cases), in contrast to myxoid subtypes clustering mainly in the 10-50 RQ range. GATA4 overexpression correlated with smaller tumor size (<100 mm) (p = 0.049), being more frequent in 15/20 small tumors compared to 10/22 larger ones. GATA3 and GATA4 demonstrated the strongest inter-gene correlation (r = 0.68, p < 0.05), suggesting possible functional interplay. Kaplan-Meier analysis revealed no statistically significant survival differences for individual gene expression, but a high combined GATA3-GATA4 signature was associated with a favorable trend. These findings indicate that SOX9, GATA3, and GATA4 are broadly upregulated in liposarcomas, with subtype- and size-dependent expression patterns. The strong association between GATA3 and GATA4 expression supports their potential synergistic role in tumor biology. Integration of these molecular markers into diagnostic and prognostic workflows may enhance subtype characterization and inform targeted therapeutic strategies. Further studies in larger cohorts are warranted to validate these biomarkers and explore their mechanistic interplay in liposarcoma pathogenesis.

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