A four-gene signature identified by integrated transcriptomic analysis for differential diagnosis and prognosis of uterine smooth muscle tumors

Introduction Uterine leiomyomas (ULM) and uterine leiomyosarcomas (ULMS) are smooth muscle tumors of the uterus that share overlapping histopathological features but exhibit markedly different biological behaviors and clinical outcomes. Whereas ULMs are benign, ULMS are rare yet highly aggressive. Clinically, accurately distinguishing tumor tissue from normal myometrial tissue remains challenging, particularly due to substantial uncertainty in preoperative diagnosis. In this study, we aim to identify molecular biomarkers capable of distinguishing uterine smooth muscle tumors (including ULM and ULMS) from normal myometrium in order to uncover driver genes involved in tumorigenesis. Methods We analyzed RNA-seq datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) using GEO2R, Limma, and Weighted Gene Co-expression Network Analysis (WGCNA) to identify differentially expressed genes (DEGs) in ULMS and ULM. Results Four hub genes—ABLIM1, FHL5, MAP3K8, and TOP2A—were consistently dysregulated in both tumor types relative to normal tissue, suggesting their common role in tumor development. Specifically, ABLIM1, FHL5, and MAP3K8 were downregulated, whereas TOP2A was upregulated, with further differential expression noted between ULMS and ULM. These findings were validated across independent cohorts and confirmed at the protein level via immunohistochemistry. Moreover, survival analysis revealed the prognostic significance of this four-gene signature: high TOP2A with low ABLIM1, FHL5, and MAP3K8 expression correlated with decreased overall survival in ULMS, implicating their potential role as diagnostic and prognostic markers. Discussion Our study identifies ABLIM1, FHL5, MAP3K8, and TOP2A as key molecular drivers of uterine smooth muscle tumorigenesis. The four-gene signature shows promise as a biomarker panel for early diagnosis and differentiation between tumor and normal tissues, providing a potential molecular foundation for targeted therapeutic strategies.