# Integrated genomic and clinical modeling for prognostic assessment of radiotherapy response in rectal neoplasms

## TL;DR

This study creates a model to predict how well rectal cancer patients respond to radiotherapy by combining genomic and clinical data.

## Contribution

The novel contribution is a validated prognostic model integrating 15 genes linked to radiotherapy response in rectal neoplasms.

## Key findings

- The model showed moderate to high accuracy for 1-, 2-, and 3-year overall survival (AUC: 0.70–0.90).
- High-risk and low-risk patient groups had statistically significant differences in survival outcomes.
- Selected genes were involved in actin cytoskeleton reorganization and antiviral immune responses.

## 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.