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Overexpression of HMGA1 Figures as a Potential Prognostic Factor in Endometrioid Endometrial Carcinoma (EEC).
- Source :
-
Genes [Genes (Basel)] 2019 May 15; Vol. 10 (5). Date of Electronic Publication: 2019 May 15. - Publication Year :
- 2019
-
Abstract
- Endometrioid endometrial carcinomas (EEC) are the most common malignant gynecologic tumors. Despite the increase in EEC molecular knowledge, the identification of new biomarkers involved in disease's development and/or progression would represent an improvement in its course. High-mobility group A protein (HMGA) family members are frequently overexpressed in a wide range of malignancies, correlating with a poor prognosis. Thus, the aim of this study was to analyze HMGA1 and HMGA2 expression pattern and their potential role as EEC biomarkers. HMGA1 and HMGA2 expression was initially evaluated in a series of 46 EEC tumors (stages IA to IV), and the findings were then validated in The Cancer Genome Atlas (TCGA) EEC cohort, comprising 381 EEC tumors (stages IA to IV). Our results reveal that HMGA1 and HMGA2 mRNA and protein are overexpressed in ECC, but only HMGA1 expression is associated with increased histological grade and tumor size. Moreover, HMGA1 but not HMGA2 overexpression was identified as a negative prognostic factor to EEC patients. Finally, a positive correlation between expression of HMGA1 pseudogenes- HMGA1-P6 and HMGA1-P7 -and HMGA1 itself was detected, suggesting HMGA1 pseudogenes may play a role in HMGA1 expression regulation in EEC. Thus, these results indicate that HMGA1 overexpression possesses a potential role as a prognostic biomarker for EEC.
- Subjects :
- Adult
Biomarkers, Tumor biosynthesis
Biomarkers, Tumor genetics
Carcinoma, Endometrioid metabolism
Endometrial Neoplasms metabolism
Female
HMGA1a Protein biosynthesis
HMGA2 Protein biosynthesis
Humans
Middle Aged
Prognosis
Transcriptome
Carcinoma, Endometrioid genetics
Endometrial Neoplasms genetics
HMGA1a Protein genetics
HMGA2 Protein genetics
Subjects
Details
- Language :
- English
- ISSN :
- 2073-4425
- Volume :
- 10
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Genes
- Publication Type :
- Academic Journal
- Accession number :
- 31096664
- Full Text :
- https://doi.org/10.3390/genes10050372