A stemness-based signature with inspiring indications in discriminating the prognosis, immune response, and somatic mutation of endometrial cancer patients revealed by machine learning.

Endometrial cancer (EC) is a fatal gynecologic tumor. Bioinformatic tools are increasingly developed to screen out molecular targets related to EC. Our study aimed to identify stemness-related prognostic biomarkers for new therapeutic strategies in EC.

Value of serum p53, PKD1, and MAP2K4 in evaluating the condition and prognosis of endometrial carcinoma.

Objective: To analyze the p53, PKD1, and MAP2K4 expressions in serum of patients with endometrial carcinoma (EC) and their prognostic value.

Methods: A total of 84 patients with EC who were treated in our hospital between January 2018 and January 2020 were enrolled into a research group. There were 50 healthy individuals over the same time who were included in a control group for a retrospective analysis.

[WITHDRAWN] miR-144-3p Functions as a Tumor Suppressor in Endometrial Cancer by Targeting PRR11.

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A seven-m6A regulator-related CpG site-based prognostic signature for endometrial carcinoma.

Background: Endometrial carcinoma (EC) has become a common gynecologic malignancy with a high mortality. The m6A regulators have been identified to be closely associated with multiple human cancers including EC. However, the CpG methylation signature related to m6A regulators in EC remains unclear.

Development and validation of m6A regulators' prognostic significance for endometrial cancer.

Background: Endometrial cancer (EC) is the sixth most common cancer in women globally. It has been found that the expression levels of m6A regulators can be potentially used for prognostic stratification in some cancers, but the role of m6A regulators in EC prognosis remains unclear.

Methods: The data of 584 EC samples were downloaded from The Cancer Genome Atlas and the mRNA expression profiles of 20 m6A regulators were analyzed, followed by functional enrichment analysis, immune infiltration analysis, and least absolute shrinkage and selection operator method-COX regression analysis.