# A novel adenosine-to-inosine RNA editing-based nomogram for predicting prognosis of hepatocellular carcinoma

**Authors:** Shiqiong Huang, Ji Sun

PMC · DOI: 10.3389/fphar.2025.1547320 · Frontiers in Pharmacology · 2025-05-14

## TL;DR

This study develops a new tool based on RNA editing to predict the survival outcomes of hepatocellular carcinoma patients.

## Contribution

A novel ATIRE-based nomogram is proposed for predicting hepatocellular carcinoma prognosis.

## Key findings

- Higher ATIRE-based risk scores correlate with worse overall survival in HCC patients.
- The nomogram shows good predictive efficiency for 1-, 2-, and 3-year survival rates.
- ATIRE sites are linked to host gene expression and cancer-related pathways.

## Abstract

Although the role of adenosine-to-inosine RNA editing (ATIRE) has gained widespread attention in multiple cancers, its predictive role in hepatocellular carcinoma (HCC) remains little known. We aimed to establish a predicting signature based on ATIRE for the prognosis of HCC.

A total of 200 HCC patients with survival data and ATIRE profiles from The Cancer Genome Atlas (TCGA) database were divided into training (n = 140) and validation (n = 60) cohorts. Survival-related ATIRE sites were identified by the least absolute shrinkage and selection operator algorithm. ATIRE-based risk score was then generated with these ATIRE sites. Cox proportional hazards regression was employed to construct the ATIRE-based nomogram signature. The receiver operating characteristic (ROC) curve was used to evaluate the predictive efficacy of the signature. Harrell’s C-index and calibration plot was utilized to evaluate the significant prognostic factors.

Nine ATIRE sites were screened to establish the ATIRE risk score, and it was found to be associated with prognosis of HCC. Survival analysis revealed that higher ATIRE-based risk scores were significantly associated with worse overall survival (OS) in both the training dataset (p < 0.001) and the validation dataset (p = 0.011), as well as in the combined dataset (p < 0.001). The ROC curve displayed a good predictive efficiency of the risk score regarding 1-year, 2-year, and 3-year OS. Furthermore, ATIRE sites were significantly correlated with the expression of host genes and were likely to be involved in certain cancer-related pathways.

Our findings provided a novel ATIRE-based nomogram, which could serve as a potential tool for predicting HCC prognosis.

## Linked entities

- **Diseases:** hepatocellular carcinoma (MONDO:0007256)

## Full-text entities

- **Diseases:** HCC (MESH:D006528), Cancer (MESH:D009369)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC12116476/full.md

## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12116476/full.md

## References

42 references — full list in the complete paper: https://tomesphere.com/paper/PMC12116476/full.md

---
Source: https://tomesphere.com/paper/PMC12116476