335This is an open access article under the terms of the Creative Commons A ttribution L icense, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2 0 2 6 The A uthor(s). A nticancer R esearch is published b y the I nternational I nstitute of A nticancer R esearch. Immune Network Construction and Prognostic Evaluation of Checkpoint Genes in Endometrial Cancer Using STRING, MCODE, and GEPIA2

Background/Aim: Endometrial cancer (EC) is an important health issue among women, with immunotherapy emerging as a promising option for advanced cases. Tumor-infiltrating lymphocytes (TILs) and immune checkpoints, including PDCD1, CD274, and PDCD1LG2, are increasingly recognized as prognostic markers. This study aimed to construct an in silico immune network and assess the prognostic impact of checkpoint genes in EC using STRING, MCODE, and GEPIA2. Materials and Methods: Retrospective analysis used TCGA-UCEC (The Cancer Genome Atlas – Uterine Corpus Endometrial Carcinoma) and GTEx datasets and reported immune-related genes. Genes were analyzed in STRING v12.0 (confidence ≥0.7; up to 10 neighbors per node) to generate a protein–protein interaction (PPI) network, exported to Cytoscape v3.10.2, and processed with MCODE to identify functional clusters. Hub genes were evaluated for expression and overall survival (OS) in GEPIA2 using median-based stratification and log-rank tests (p