Cho-Clark Madelaine J, Sukumar Gauthaman, Vidal Newton Medeiros, Raiciulescu Sorana, Oyola Mario G, Olsen Cara, Mariño-Ramírez Leonardo, Dalgard Clifton L, Wu T John
Department of Gynecologic Surgery & Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
Collaborative Health Initiative Research Program, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
Oncotarget. 2021 Dec 21;12(26):2500-2513. doi: 10.18632/oncotarget.28161.
The rising incidence and mortality of endometrial cancer (EC) in the United States calls for an improved understanding of the disease's progression. Current methodologies for diagnosis and treatment rely on the use of cell lines as models for tumor biology. However, due to inherent heterogeneity and differential growing environments between cell lines and tumors, these comparative studies have found little parallels in molecular signatures. As a consequence, the development and discovery of preclinical models and reliable drug targets are delayed. In this study, we established transcriptome parallels between cell lines and tumors from The Cancer Genome Atlas (TCGA) with the use of optimized normalization methods. We identified genes and signaling pathways associated with regulating the transformation and progression of EC. Specifically, the LXR/RXR activation, neuroprotective role for THOP1 in Alzheimer's disease, and glutamate receptor signaling pathways were observed to be mostly downregulated in advanced cancer stage. While some of these highlighted markers and signaling pathways are commonly found in the central nervous system (CNS), our results suggest a novel function of these genes in the periphery. Finally, our study underscores the value of implementing appropriate normalization methods in comparative studies to improve the identification of accurate and reliable markers.
美国子宫内膜癌（EC）发病率和死亡率的上升，要求我们更好地了解该疾病的进展。目前的诊断和治疗方法依赖于使用细胞系作为肿瘤生物学模型。然而，由于细胞系与肿瘤之间存在固有的异质性和不同的生长环境，这些比较研究在分子特征方面几乎没有发现相似之处。因此，临床前模型和可靠药物靶点的开发与发现被延迟。在本研究中，我们使用优化的标准化方法，建立了来自癌症基因组图谱（TCGA）的细胞系与肿瘤之间的转录组相似性。我们确定了与调节EC转化和进展相关的基因和信号通路。具体而言，在癌症晚期，LXR/RXR激活、THOP1在阿尔茨海默病中的神经保护作用以及谷氨酸受体信号通路大多被下调。虽然这些突出的标志物和信号通路中的一些常见于中枢神经系统（CNS），但我们的结果表明这些基因在外周具有新功能。最后，我们的研究强调了在比较研究中采用适当标准化方法以改善准确可靠标志物识别的价值。
