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Transcriptomic analysis of stage I endometrioid endometrial carcinoma (EEC)

ABSTRACT: Transcriptome analysis aiming to identify differentially expressed genes from stage I EEC, comparing relapsed with non-relapsed tumors

ORGANISM(S): Homo sapiens

PROVIDER: GSE225956 | GEO | 2025/05/28

REPOSITORIES: GEO

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microRNA expression profile in endometrioid endometrial carcinoma (EEC)

Project description:The aim of the presented study was to define tissue and plasma miRNA signatures, which could potentially serve as diagnostic and prognostic markers in endometrioid endometrial cancer (EEC), and to investigate miRNA profiles in regard to clinicopathological characteristics of the tumors. Results: qPCR validation revealed regulation of 14 miRNAs in EEC tissues (miR-9, miR-141,miR-205,miR-203,miR-183,miR-200a*,miR-200b*,miR-200a,miR-200c,miR-429,miR-200b,miR-410,miR-92a,miR-1305) and 9 in plasma samples (miR-449a,miR-1290,miR-1228,miR-203,miR-200a,miR-141,miR-92a, miR-9, miR-301b). Expression of certain miRNAs showed association with FIGO stage, grade and relapse. Two miRNA signatures, miR-205/miR-410 and miR-410/miR-429/miR-92a, classified tumor tissues with higher accuracy in comparison to single miRNAs (AUC 0.972, 95% CI 0.919-0.995 and 0.991, 95% CI 0.948-1.000, resepctively). miRNA signature composed of miR-205 and miR-200a predicted relapse with AUC of 0.854 (95% CI 0.691-0.951). Tissue miRNA signatures were independent prognostic markers of overall (miR-1228/miR-200c/miR-429, HR 2.98) and progression-free survival (miR-1228/miR-429, HR 4.149). Plasma miRNA signatures classified EEC plasma samples with high accuracy. Conclusions: We conclude that miRNA signatures hold great promise for becoming non-invasive biomarkers for early EEC detection and prognosis. Tissue samples were collected from 122 women (77 EEC and 45 controls). Expression profiling of 866 human miRNAs and 89 human viral miRNAs was performed in 24 samples and was followed by qPCR validation in 104 patients. Of 24 samples analyzed by microarrays, 22 (18 EEC, 4 normal controls) were available for final analysis. Expression of 14 miRNAs was analysed in 48 plasma samples by qPCR.

2012-05-31 | E-GEOD-35794 | biostudies-arrayexpress

Transcriptomic analysis of stage I endometrioid endometrial carcinoma (EEC)

Project description:Transcriptomic analysis of stage I endometrioid endometrial carcinoma (EEC)

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microRNA expression profile in endometrioid endometrial carcinoma (EEC)

2012-06-01 | GSE35794 | GEO

Overexpression of HMGA1 Figures as a Potential Prognostic Factor in Endometrioid Endometrial Carcinoma (EEC).

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Inhibition of LIFR blocks adiposity driven endometrioid endometrial cancer growth

Project description:We examined the mechanisms by which adiposity regulates EEC progression. EEC cells were incubated with or without adipocyte conditioned medium (ADP-CM), and total RNA was isolated for RNA-seq analysis. Our results demonstrated that ADP-CM stimulated EEC cells showed upregulation of several LIF/LIFR modulated pathways including Jak/STAT and cytokine pathways.

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Identification of prognostic biomarkers for endometrioid endometrial carcinoma based on the miRNA and mRNA co‐expression network regulated by estradiol [miRNA]

Project description:Endometrioid endometrial carcinoma (EEC), an estradiol-related disease, remains a serious health threat to women because of its high incidence and trend of rejuvenation. Accumulating evidence has highlighted that microRNAs (miRNAs) and messenger RNAs (mRNAs) play important roles in various biological processes involved in the pathogenesis of EEC. This study aimed to identify the potential prognostic biomarkers associated with EEC regulated by estradiol.

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Single nucleus RNA sequencing analysis reveals transcriptional heterogeneity of endometrioid endometrial cancer

Project description:Endometrial cancer (EC) is the sixth most prevalent malignancy affecting women worldwide, with an increasing incidence that poses a substantial public health challenge. This study investigates the tumor microenvironment (TME) of EC, particularly high grade endometrioid endometrial cancer (HEEC), utilizing single nucleus RNA sequencing (snRNA-seq). The analysis encompassed normal endometrium (NE), HEEC, middle grade endometrioid endometrial cancer (MEEC), and low grade endometrioid endometrial cancer (LEEC). Significant cellular heterogeneity was identified within the TME, including immune cells, fibroblasts, and epithelial cells. Notably, SULF1+ NREP+ fibroblasts were significantly enriched in HEEC and associated with aggressive tumor behavior. Additionally, the study highlighted the overexpression of metabolic pathways and immune checkpoint molecules in HEEC epithelial cells, including Human Leukocyte Antigen E (HLA-E) and Killer Cell Lectin Like Receptor C1 (KLRC1), which may contribute to immune evasion and enhanced tumor aggressiveness. Identifying the EYA transcriptional coactivator and phosphatase 1 (EYA1) gene as a prospective biomarker in HEEC due to its association with poor prognosis and the enhanced proliferative and migratory capabilities of EC cells. Furthermore, analyses of cell-cell interactions revealed critical signaling pathways, such as the Leucocyte Associated Immunoglobulin Like Receptor-1 (LAIR1)- Leukocyte Immunoglobulin-like Receptor B4 (LILRB4) axis in macrophages, which may play a role in immune suppression and EEC progression. A comprehensive single-cell level characterization of the TME in EEC offers critical insights into the molecular mechanisms driving EEC progression, while identifying potential therapeutic targets. These discoveries advance our understanding of EEC pathophysiology and hold promise for the development of targeted therapies, particularly in HEEC

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