Comparative transcriptome analysis between patient and endometrial cancer cell lines to determine common signaling pathways and markers linked to cancer progression

Madelaine J. Cho-Clark, Gauthaman Sukumar, Newton Medeiros Vidal, Sorana Raiciulescu, Mario G. Oyola, Cara Olsen, Leonardo Marino-Ramírez, Clifton L. Dalgard, T. John Wu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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.

Original languageEnglish
Pages (from-to)2500-2513
Number of pages14
JournalOncotarget
Volume12
Issue number26
DOIs
StatePublished - 2021
Externally publishedYes

Keywords

  • cancer stage
  • comparative transcriptome analysis
  • endometrial cancer
  • normalization
  • signaling pathways

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