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Comparative transcriptome analysis between patient and endometrial cancer cell lines to determine common signaling pathways and markers linked to cancer progression.
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.
Afiliação
  • Cho-Clark MJ; Department of Gynecologic Surgery & Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
  • Sukumar G; Collaborative Health Initiative Research Program, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
  • Vidal NM; National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.
  • Raiciulescu S; Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
  • Oyola MG; Department of Gynecologic Surgery & Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
  • Olsen C; Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
  • Mariño-Ramírez L; National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD 20814, USA.
  • Dalgard CL; Collaborative Health Initiative Research Program, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
  • Wu TJ; Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
Oncotarget ; 12(26): 2500-2513, 2021 Dec 21.
Article em En | MEDLINE | ID: mdl-34966482
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Oncotarget Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Oncotarget Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos