Department of Microbiology, Biochemistry and Immunology, Morehouse School of Medicine, Atlanta, GA 30310, USA.
Department of Obstetrics & Gynecology, Morehouse School of Medicine, Atlanta, GA 30310, USA.
Int J Mol Sci. 2024 Nov 18;25(22):12356. doi: 10.3390/ijms252212356.
Endometrial cancer (EC) presents a substantial health challenge, with increasing incidence and mortality rates. Despite advances in diagnosis and treatment, understanding the molecular underpinnings of EC progression remains unknown. In this study, we conducted a comprehensive investigation utilizing The Cancer Genome Atlas (TCGA-UCEC = 588) data to analyze gene co-expression patterns, elucidate biological process pathways, and identify potential prognostic and diagnostic biomarkers for EC, using weighted gene co-expression network analysis (WGCNA), differential gene expression, survival analysis, and functional analysis, respectively. We determined that the Green module (M5) was significantly correlated with patient survival. Functional analysis of the genes in module M5 indicates involvement in cell cycle regulation, mitotic spindle assembly, and intercellular signaling. , , and were among the top differentially expressed genes in the Green module, suggesting their involvement in critical pathways that contribute to disease progression and patient survival outcomes. The biological and clinical assessments of our findings provide an understanding of the molecular landscape of EC and identified several potential prognostic markers for patient risk stratification and treatment selection.
子宫内膜癌（EC）是一个严峻的健康挑战，其发病率和死亡率呈上升趋势。尽管在诊断和治疗方面取得了进展，但对 EC 进展的分子基础仍知之甚少。在这项研究中，我们利用癌症基因组图谱（TCGA-UCEC=588）数据进行了全面的分析，分别使用加权基因共表达网络分析（WGCNA）、差异基因表达、生存分析和功能分析，以探讨基因共表达模式、阐明生物学过程途径，并确定用于 EC 的潜在预后和诊断生物标志物。我们确定 Green 模块（M5）与患者的生存显著相关。模块 M5 中基因的功能分析表明其参与细胞周期调控、有丝分裂纺锤体组装和细胞间信号传递。在 Green 模块中， 、 和 是差异表达基因中的前几位，表明它们参与了对疾病进展和患者生存结果有贡献的关键途径。我们研究结果的生物学和临床评估提供了对 EC 分子图谱的理解，并确定了几个潜在的预后标志物，用于患者风险分层和治疗选择。
