Identification of genetic and immune mechanisms linking preeclampsia and endometrial cancer: a prognostic model for survival and treatment response

Preeclampsia (PE) and endometrial cancer (EC) are two distinct conditions that share common genetic and molecular mechanisms involving immune dysregulation, endothelial dysfunction, and angiogenesis. This study aimed to investigate the potential genetic links between PE and EC, identify key prognostic genes, and develop a risk model to predict overall survival in EC patients. We conducted comprehensive genetic and molecular analyses, revealing significant overlaps in immune and angiogenic pathways between PE and EC. Through LASSO regression and multivariate Cox analysis, we identified five core prognostic genes-FSTL3, PRSS23, IGFBP4, MYDGF, and TSC22D3-that were used to construct a risk model. This model effectively stratified EC patients into high- and low-risk groups, with significant differences in overall survival. Patients in the low-risk group exhibited better 1-, 3-, and 5-year survival outcomes and had higher immune cell infiltration and expression of immune checkpoint-related genes, indicating a more favorable tumor microenvironment. Additionally, the analysis showed that these genes are also implicated in the pathogenesis of PE, highlighting potential shared molecular mechanisms. Our findings suggest that these PE-related genes may serve as valuable prognostic biomarkers for EC and could lead to improved prognostic tools and personalized treatment strategies for EC patients.

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Publication Details

Journal
Discover Oncology
Published
2024-11-29
DOI
https://doi.org/10.1007/s12672-024-01622-9
Primary Topic
Pregnancy and preeclampsia studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Identification of genetic and immune mechanisms linking preeclampsia and endometrial cancer: a prognostic model for survival and treatment response

Fei Teng, Guiqing Fang, Yongxiu Yang, Jing Wang
Discover Oncology
Pregnancy and preeclampsia studies
article

Identification of genetic and immune mechanisms linking preeclampsia and endometrial cancer: a prognostic model for survival and treatment response

Fei Teng, Guiqing Fang, Yongxiu Yang, Jing Wang
article en

Abstract

Preeclampsia (PE) and endometrial cancer (EC) are two distinct conditions that share common genetic and molecular mechanisms involving immune dysregulation, endothelial dysfunction, and angiogenesis. This study aimed to investigate the potential genetic links between PE and EC, identify key prognostic genes, and develop a risk model to predict overall survival in EC patients. We conducted comprehensive genetic and molecular analyses, revealing significant overlaps in immune and angiogenic pathways between PE and EC. Through LASSO regression and multivariate Cox analysis, we identified five core prognostic genes-FSTL3, PRSS23, IGFBP4, MYDGF, and TSC22D3-that were used to construct a risk model. This model effectively stratified EC patients into high- and low-risk groups, with significant differences in overall survival. Patients in the low-risk group exhibited better 1-, 3-, and 5-year survival outcomes and had higher immune cell infiltration and expression of immune checkpoint-related genes, indicating a more favorable tumor microenvironment. Additionally, the analysis showed that these genes are also implicated in the pathogenesis of PE, highlighting potential shared molecular mechanisms. Our findings suggest that these PE-related genes may serve as valuable prognostic biomarkers for EC and could lead to improved prognostic tools and personalized treatment strategies for EC patients.

Discover OncologyVol. 15(1)
First Hospital of Lanzhou University (CN), Lanzhou University (CN)
Natural Science Foundation of Gansu Province
Good health and well-being
Openalex Percentile: Top 66%
Pregnancy and preeclampsia studies
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Identification of genetic and immune mechanisms linking preeclampsia and endometrial cancer: a prognostic model for survival and treatment response — Fei Teng, Guiqing Fang, et al. · Discover Oncology (2024) | TGRS Research Map | TGRS