Nomogram Based on A-To-I RNA Editing for Predicting Overall Survival in Patients With Breast Cancer

Area of Science:

• Molecular Biology
• Genomics
• Oncology

Background:

• Adenosine-to-inosine RNA editing (ATIRE) is prevalent in eukaryotes and linked to various cancers.
• While some ATIRE sites predict cancer prognosis, their role in breast cancer (BRCA) is unclear.

Purpose of the Study:

• To investigate the diagnostic and prognostic potential of ATIRE sites in BRCA.
• To develop and validate a prognostic model for BRCA patients based on ATIRE sites.

Main Methods:

• Utilized TCGA data for BRCA patients, dividing them into training and validation cohorts.
• Employed univariate Cox, Lasso, and multivariate Cox regression to identify prognostic ATIRE sites.
• Constructed a prognostic model and risk score, validated using nomograms, calibration, and decision curves.

Main Results:

• Identified nine ATIRE sites associated with BRCA prognosis, forming a predictive model.
• High-risk scores correlated with significantly shorter median survival times.
• Five ATIRE sites showed correlation with gene expression; four were upregulated in tumor tissues.

Conclusions:

• An ATIRE-based prognostic model can accurately predict survival in BRCA patients.
• This model offers a novel tool for personalized clinical decision-making in BRCA management.