ArticleMolecular diagnosis & therapy2021
Prognostic Biomarker-Based Identification of Drugs for Managing the Treatment of Endometrial Cancer.
Article in Molecular diagnosis & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- Analysis of ferritinophagy-related genes associated with the prognosis and regulatory mechanisms in non-small cell lung cancer.Frontiers in medicine · 2025Article
- CLEC3A Promotes Immune Evasion and Tumor Progression by Enhancing PD-L1 Stability to Weaken T Cell Cytotoxicity in Luminal Breast Cancer.Breast cancer (Dove Medical Press) · 2025Article
- Multi-omics evaluation of the prognostic value and immune signature of FCN1 in pan-cancer and its relationship with proliferation and apoptosis in acute myeloid leukemia.Frontiers in genetics · 2024Article
- Identification of CAPG as a potential prognostic biomarker associated with immune cell infiltration and ferroptosis in uterine corpus endometrial carcinoma.Frontiers in endocrinology · 2024Article
- Review
- Pyroptosis-related lncRNAs are potential biomarkers for predicting prognoses and immune responses in patients with UCEC.Molecular therapy. Nucleic acids · 2022Article
- Prognostic biomarkers for predicting papillary thyroid carcinoma patients at high risk using nine genes of apoptotic pathway.PloS one · 2021Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionUterine corpus endometrial carcinoma (UCEC) causes thousands of deaths per year. To improve the overall survival of patients with UCEC, there is a need to identify prognostic biomarkers and potential drugs.
objectivesThe aim of this study was twofold: the identification of prognostic gene signatures from expression profiles of pattern recognition receptor (PRR) genes and identification of the most effective existing drugs using the prognostic gene signature.
methodsThis study was based on the expression profile of PRR genes of 541 patients with UCEC obtained from The Cancer Genome Atlas. Key prognostic signatures were identified using various approaches, including survival analysis, network, and clustering. Hub genes were identified by constructing a co-expression network. Representative genes were identified using k-means and k-medoids-based clustering. Univariate Cox proportional hazard (PH) analysis was used to identify survival-associated genes. 'cmap2' was used to identify potential drugs that can suppress/enhance the expression of prognostic genes.
resultsModels were developed using hub genes and achieved a maximum hazard ratio (HR) of 1.37 (p = 0.294). Then, a clustering-based model was developed using seven genes (HR 9.14; p = 1.49 × 10
conclusionWe identified potential immunotherapeutic agents based on prognostic gene signature: hexamethonium bromide and isoflupredone. Several novel candidate drugs were suggested, including human interferon-α-2b, paclitaxel, imiquimod, MESO-DAP1, and mifamurtide. These biomolecules and repurposed drugs may be utilised for prognosis and treatment for better survival.
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