ArticleOpen life sciences2025
Integrated genomic and clinical modeling for prognostic assessment of radiotherapy response in rectal neoplasms.
Article in Open life sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
The aim of this study is to develop a prognostic model for evaluating radiotherapy response in patients diagnosed with rectal neoplasms by integrating genomic and clinical data. Publicly accessible datasets from The Cancer Genome Atlas and Gene Expression Omnibus were analyzed to identify differentially expressed genes associated with drug resistance and mitophagy. Functional enrichment analyses were conducted to investigate relevant biological pathways. A prognostic risk model was constructed using least absolute shrinkage and selection operator regression and validated via receiver operating characteristic (ROC) curve analysis and Kaplan-Meier survival analysis. The final model incorporated 15 genes selected from an initial set of 121 differentially expressed genes and demonstrated moderate to high predictive accuracy for 1-, 2-, and 3-year overall survival (area under the ROC curve: 0.70-0.90). Kaplan-Meier analysis revealed statistically significant differences in survival outcomes between high-risk and low-risk patient groups. Pathway enrichment analysis indicated that the selected genes were involved in actin cytoskeleton reorganization and antiviral immune responses. Differential expression of key genes within the model was confirmed through quantitative polymerase chain reaction assays. The resulting prognostic model enhances understanding of the molecular mechanisms underlying radiotherapy response in rectal neoplasms and may support individualized therapeutic decision-making in clinical oncology.
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