# A TP53-Pathway-Based Prognostic Signature for Radiotherapy and Functional Validation of TP53I3 in Non-Small-Cell Lung Cancer

**Authors:** Xiang Huang, Li Jiao, Xu Cheng, Yue Fang, Jian Qi, Zongtao Hu, Bo Hong, Jinfu Nie, Hongzhi Wang

PMC · DOI: 10.3390/cancers18030457 · Cancers · 2026-01-30

## TL;DR

This study creates a gene-based model to predict outcomes for lung cancer patients undergoing radiotherapy and validates a key gene's role in improving treatment response.

## Contribution

A novel TP53-pathway-based five-gene prognostic model and functional validation of TP53I3's role in radiosensitivity in NSCLC.

## Key findings

- A five-gene model (MDM2, THBS1, TP53I3, ATM, SESN3) effectively stratifies NSCLC patients into high- and low-risk groups for radiotherapy outcomes.
- TP53I3 knockdown increases radiosensitivity via DNA damage, cell cycle arrest, and apoptosis in NSCLC.
- The model correlates with immune cell infiltration patterns, showing lower anti-tumor and higher immunosuppressive cell infiltration in high-risk patients.

## Abstract

Radiotherapy is a common treatment for non-small cell lung cancer (NSCLC); however, the variability in therapeutic response poses a significant clinical challenge. This study develops a five-gene prognostic model (MDM2, THBS1, TP53I3, ATM, SESN3) from the TP53 signaling pathway to predict outcomes for NSCLC patients receiving radiotherapy. The model demonstrates high accuracy in stratifying patients into distinct risk groups, correlating with specific immune cell infiltration patterns. Experimental validation, both in vitro and in vivo, demonstrates that knockdown of the key gene TP53I3 significantly enhances radiosensitivity. This effect is mediated through increased DNA damage, induction of cell cycle arrest, and promotion of apoptosis. The findings position this gene signature as a promising biomarker tool for personalizing and optimizing radiotherapy regimens in NSCLC.

Background: 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. Methods: 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 selection was performed using LASSO regression, followed by the construction of a multivariate-Cox-regression-based prognostic prediction model. In vitro validation was performed using a cell viability assay, colony formation, cell cycle analysis, apoptosis detection, γH2AX immunofluorescence staining and comet electrophoresis. In vivo validation was performed utilizing a subcutaneous tumor-bearing mouse model, where radiosensitivity was assessed by monitoring tumor volume post-irradiation. Results: We constructed a robust prognostic prediction model based on five TP53-signaling-pathway-related genes (MDM2, THBS1, TP53I3, ATM, and SESN3), achieving a 5-year AUC of 0.828 in the training set and a 3-year AUC of 0.824 in the validation set. The model exhibited a significant ability to stratify patients into distinct high- and low-risk groups, demonstrating good predictive performance. The poor prognosis observed in the high-risk group was associated with lower infiltration of anti-tumor immune cells but higher infiltration of immunosuppressive cells. Both in vitro and in vivo experiments demonstrated that TP53I3 knockdown significantly enhanced the radiosensitivity of NSCLC through increased DNA damage, cell cycle arrest and apoptosis. Conclusions: In this study, a five-gene signature derived from the TP53 signaling pathway was developed, and the model was shown to effectively predict the prognoses of NSCLC patients undergoing radiotherapy. This signature has the potential to be developed into a clinically applicable tool for personalizing radiotherapy regimens for NSCLC.

## Linked entities

- **Genes:** TP53I3 (tumor protein p53 inducible protein 3) [NCBI Gene 9540], MDM2 (MDM2 proto-oncogene) [NCBI Gene 4193], THBS1 (thrombospondin 1) [NCBI Gene 7057], ATM (ATM serine/threonine kinase) [NCBI Gene 472], SESN3 (sestrin 3) [NCBI Gene 143686]
- **Diseases:** non-small-cell lung cancer (MONDO:0005233), NSCLC (MONDO:0005233)

## Full-text entities

- **Genes:** TP53 (tumor protein p53) [NCBI Gene 7157] {aka BCC7, BMFS5, LFS1, P53, TRP53}, SESN3 (sestrin 3) [NCBI Gene 143686] {aka SEST3}, TP53I3 (tumor protein p53 inducible protein 3) [NCBI Gene 9540] {aka PIG3}, ATM (ATM serine/threonine kinase) [NCBI Gene 472] {aka AT1, ATA, ATC, ATD, ATDC, ATE}, THBS1 (thrombospondin 1) [NCBI Gene 7057] {aka THBS, THBS-1, TSP, TSP-1, TSP1}, MDM2 (MDM2 proto-oncogene) [NCBI Gene 4193] {aka ACTFS, HDMX, LSKB, hdm2}
- **Diseases:** tumor (MESH:D009369), NSCLC (MESH:D002289)
- **Species:** Homo sapiens (human, species) [taxon 9606], Mus musculus (house mouse, species) [taxon 10090]

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12896867/full.md

## References

39 references — full list in the complete paper: https://tomesphere.com/paper/PMC12896867/full.md

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Source: https://tomesphere.com/paper/PMC12896867