biostudies-literatureHuang XProgram of Clinical Medical Translational Research in Anhui ProvinceProgram of Research and Development of Key Common Technologies and Engineering of Major Scientific and Technological Achievements in HefeiNational Natural Science Foundation of ChinaCollaborative Innovation Program of Hefei Science Center, CAS457https://www.ebi.ac.uk/biostudies/studies/S-EPMC12896867biostudies-literatureUnknown18(3)<b>Background</b>: Radiation therapy is an important treatment method for non-small-cell lung cancer (NSCLC). However, predicting patient prognosis remains challenging due to considerable interpatient heterogeneity. The TP53 signaling pathway, implicated in tumor radiosensitivity and treatment outcomes, represents a promising predictive biomarker. Accordingly, in this study, we aimed to identify TP53-signaling pathway-related genes and develop a novel prognostic model for risk stratification for NSCLC patients undergoing radiation therapy. <b>Methods</b>: Publicly available NSCLC transcriptomic datasets were obtained from the GEO and TCGA databases. Utilizing bioinformatics approaches, we identified differentially expressed genes (DEGs) associated with the TP53 signaling pathway. Feature sCancersA TP53-Pathway-Based Prognostic Signature for Radiotherapy and Functional Validation of TP53I3 in Non-Small-Cell Lung Cancer.PMC128968672022HSC-CIP0152023042951070200922021YL00781872438Fang YJiao LQi JHu ZHuang XNie JWang HCheng XHong BfalseA TP53-Pathway-Based Prognostic Signature for Radiotherapy and Functional Validation of TP53I3 in Non-Small-Cell Lung Cancer.<b>Background</b>: Radiation therapy is an important treatment method for non-small-cell lung cancer (NSCLC). However, predicting patient prognosis remains challenging due to considerable interpatient heterogeneity. The TP53 signaling pathway, implicated in tumor radiosensitivity and treatment outcomes, represents a promising predictive biomarker. Accordingly, in this study, we aimed to identify TP53-signaling pathway-related genes and develop a novel prognostic model for risk stratification for NSCLC patients undergoing radiation therapy. <b>Methods</b>: Publicly available NSCLC transcriptomic datasets were obtained from the GEO and TCGA databases. Utilizing bioinformatics approaches, we identified differentially expressed genes (DEGs) associated with the TP53 signaling pathway. Feature s2026-01-01T00:00:00Z2026 Jan2026-07-09T13:10:35.223Z2026-07-09T13:09:01.009ZS-EPMC128968674168193210.3390/cancers18030457