Identification of Prognostic Markers for Endometrial Cancer Based on AT-Rich Interactive Domain-Containing Protein 1A Mutation and Exploration of Its Analytical Mechanism

Utilizing the cancer genome atlas （TCGA） to obtain RNA sequencing， gene mutation， and clinical prognosis data of endometrial cancer， this study aims to identify gene expression pairs that undergo significant reversal due to ARID1A mutations within the chromatin remodeling gene family， and to screen out those pairs that have a significant impact on patient prognosis as novel prognostic markers. Based on the identified markers， a random forest classifier is developed to predict the ARID1A mutation status of patients based on transcriptome data， thereby achieving high and low-risk classification. Furthermore， through differential expression analysis and functional enrichment， the process by which ARID1A mutations affect prognosis through molecular mechanisms such as regulating chemical reactions related to cellular energy metabolism， the coordination mechanism of platinum-based chemotherapeutic drugs， and enzyme-catalyzed reaction pathways associated with drug resistance is chemically analyzed.