Mining in Endometrial Cancer Based on the TCGA Database and Constructing Prognostic Models

Summary

This protocol outlines a computational approach for identifying genes associated with nicotinamide metabolism in endometrial cancer, utilizing TCGA and GEO datasets. To facilitate the discovery of biomarkers and enhance risk estimation in uterine corpus endometrial carcinoma, this research describes the analysis of distinct expression, route enhancement, prognostic model design, and evaluation procedures.

Abstract

Endometrial cancer (EC) ranks among the least prevalent gynecological tumors worldwide, with rising incidence due to aging and obesity. Lymph node metastasis remains common in Uterine Corpus Endometrial Carcinoma (UCEC), necessitating new prognostic biomarkers to guide treatment. In this research, UCEC information from the Cancer Genome Atlas (TCGA) was analyzed, and the results were validated using the Gene Expression Omnibus (GEO). Eighteen differentially expressed genetic factors associated with nicotinamide metabolism (NMRDEGs) were identified. Gene Set Enrichment Analysis (GSEA) indicated their role in oxidative stress, hypoxia, glycolysis, and apoptosis processes. Univariate Cox regression identified six key genes (AURKA, CDKN3, FOXM1, CDKN2A, TK1, and CDK1), utilized to progress a hazard prediction framework. Protein-protein interaction (PPI) analysis uncovered additional hub genes such as CDK2, CCNA2, TP53, and FOXM1. The six key genes showed strong prognostic value, and the study's risk model could guide clinical decisions. Nicotinamide metabolism was found to be significantly linked with EC progression. This study offers new perceptions into the role of nicotinamide metabolism in EC and suggests possible avenues for treatment advancements.

Introduction

Endometrial cancer (EC) is common in female patients¹. EC can be classified into the hormone-dependent type and the hormone-independent type². In 2020, the updates of guidelines for managing EC patients included molecular marker detection and molecular typing, significantly influencing postoperative adjuvant treatment and clinical prognosis for EC³. The pathogenesis of EC is multifaceted, involving mutations or loss of several oncogenes and/or tumor suppressor genes, along with abnormalities in multiple signaling pathways that can influence disease progression and outcome. Searching for new biomar....

Protocol

This study used publicly available, de-identified clinical and transcriptomic data from The Cancer Genome Atlas and the Gene Expression Omnibus. All contributing studies had prior institutional review board approval and informed consent. As only secondary analysis of anonymized data was performed, no additional ethical approval was required. The databases and software used are listed in the Table of Materials.

1. Data download

Research utilized the EC (TCGA-Uterine Corpus Endometrial Carcinoma (TCGA-UCEC)) dataset¹⁰, which consists of 589 samples, including ....

Results

Merging the correction of the GEO dataset

Research used the SVA R set to precise for batch possessions in the combined GSE115810 and GSE63678 datasets, producing a unified dataset termed Combined-Datasets. The results of group result elimination were verified using circulation boxplots (Figure 2A,B) and PCA plots (Figure 2C,D), which demonstrated that the batch effects were largely el.......

Discussion

The role of energy metabolism in the microenvironment of cancer cells has garnered considerable attention recently. Research has shown that genes involved in nicotinamide metabolism are closely linked to the progression of various malignancies. Once absorbed by the body, Nicotinamide is converted into NAD and NADP, both of which are pivotal in numerous cancer-related processes. Consequently, NAD metabolism is emerging as a promising therapeutic goal for tumor action. It is critical in various cellular activities, includi.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
clusterProfiler package	Bioconductor	v4.8.0	GO and KEGG enrichment analysis
Cytoscape	Cytoscape Consortium	v3.9.1	PPI network visualization
DESeq2 package	Bioconductor	v1.40.0	Normalization and expression analysis
GeneCards database	GeneCards Suite	N/A	Source of nicotinamide metabolism-related genes
GeneMANIA platform	genemania.org	N/A	Gene function and interaction prediction
GEO datasets (GSE115810, GSE63678)	Gene Expression Omnibus (GEO)	N/A	Public gene expression datasets for EC
ggplot2 package	CRAN	v3.4.2	Data visualization
limma package	Bioconductor	v3.54.0 (example)	Differential expression analysis
pheatmap package	CRAN	v1.0.12	Heatmap plotting
R software (v4.3.0)	R Foundation for Statistical Computing	Version 4.3.0	Data analysis platform
STRING database	STRING (string-db.org)	v11.5	Protein-protein interaction analysis
survminer package	CRAN	v0.4.9	Survival analysis
sva package	Bioconductor	v3.46.0	Batch effect removal
TCGA-UCEC dataset	The Cancer Genome Atlas (TCGA)	N/A	Transcriptome and clinical data of UCEC patients
UCSC Xena	University of California, Santa Cruz	N/A	Platform for clinical/genomic data download