Comparative transcriptome analysis between patient and endometrial cancer cell lines to determine common signaling pathways and markers linked to cancer progression
Metrics: PDF 259 views | Full Text 1432 views | ?
Madelaine J. Cho-Clark1, Gauthaman Sukumar2, Newton Medeiros Vidal3, Sorana Raiciulescu4, Mario G. Oyola1, Cara Olsen4, Leonardo Mariño-Ramírez5, Clifton L. Dalgard2,6 and T. John Wu1
1 Department of Gynecologic Surgery & Obstetrics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
2 Collaborative Health Initiative Research Program, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
3 National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
4 Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
5 National Institute on Minority Health and Health Disparities, National Institutes of Health, Bethesda, MD 20814, USA
6 Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
|T. John Wu,||email:||email@example.com|
Keywords: endometrial cancer; cancer stage; comparative transcriptome analysis; signaling pathways; normalization
Received: November 08, 2021 Accepted: December 10, 2021 Published: December 21, 2021
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.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.