Document Type : Original Article(s)

Authors

• Amin Ramezani ¹
• Zohreh Koohini ²
• Mohammad Reza Haghshenas ³
• Ahmad Tahmasebi ⁴
• Zahra Shiravani ⁵
• Fatemeh Sadat Najib ⁵
• Maryam Aghdaki ⁵
• Mahntaj Dara ⁶
• Nafiseh Maghsoodi ⁷
• Abbas Ghaderi ³

¹ Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical

² Department of Immunology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

³ Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

⁴ Institute of Biotechnology, Shiraz University, Shiraz, Iran

⁵ Department of Obstetrics and Gynecology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran

⁶ Stem Cells Technology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

⁷ Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran

Abstract

Background: The mortality rate from endometrial cancer remains high despite advances in treatment. The five-year relative survival rate of advanced and metastatic patients is less than 10%. The present study aimed to evaluate selected molecular markers and their possible associations with disease characteristics and clinical outcomes in endometrial cancer.
 Methods: In this study, gene expression datasets of endometrial cancer and non-tumoral samples were obtained from The Cancer Genome Atlas (TCGA). To find effector genes associated with endometrial cancer, we used a feature selection technique based on the Random Forest–Recursive Feature Elimination algorithm. The reliability of the selected featured genes was determined using quantitative reverse transcription polymerase chain reaction (qRT-PCR). The data were analyzed using GraphPad Prism version 8.0. A P-value less than 0.05 was considered statistically significant, and a P-value of less than 0.05 was considered statistically significant.
 Results: Analytical focus on the TCGA dataset led to the identification of nine genes, SMIM22, RHEX, UHRF1, IKBKE, H3C10, FXYD1, MYZAP, GPIHBP1, and MMP28, of significance in endometrial cancer. These genes were overexpressed in the endometrial tissue of endometrial cancer compared with non-tumoral tissue. Two genes, RHEX and IKBKE, from the list of feature genes were prioritized for further analysis and qRT-PCR based on our criteria. Results from patient samples showed that both genes were upregulated compared with the non-tumoral group and exhibited increased expression with disease progression.
Conclusion: Our findings suggest that altered expression of RHEX and IKBKE may be linked to clinical features of endometrial cancer.

Highlights

Zohreh Koohini (google scholar)

Amin Ramezani (google scholar)

Keywords

• Endometrial Neoplasms
• Gene Expression Profiling
• RHEX
• NF-kappa B Kinase subunit Epsilon

Main Subjects

• Cancer Rehabilitation

Please cite this article as: Koohini Z, Haghshenas MR, Tahmasebi A, Shiravani Z, Najib FS, Aghdaki M, Dara M, Maghsoodi N, Ramezani A, Ghaderi A. Bioinformatics Analysis and Experimental Assessment of RHEX and IKBKE in Endometrial Cancer. Middle East J Cancer. 2027; 18(1): p-p. doi: 10.30476/mejc.2025.109375.2367.