Integrated Analysis of the STING1-IRF1 Signaling Pathway and Genomic Alterations in Breast Cancer: Implications for Immune Evasion and Patient Prognosis.

Authors

Isra Alhamadani, Mohammad Alzeyadi

Published in

Asian Pacific journal of cancer prevention : APJCP. Volume 27. Issue 8. Pages 3063-3071. Aug 01, 2026. Epub Aug 01, 2026.

Abstract

The STING1-IRF1 axis plays a crucial role in sensing innate immunity within the tumor microenvironment. However, the genomic landscape of this axis and its clinical implications in breast cancer still require a deeper understanding, more comprehensive explanation, and greater detail.
This study adopted a multi-cohort integrated analytical approach. Gene expression and clinical survival data were retrieved from the GEO database under the serial number GSE42568, while somatic mutation data were obtained from the TCGA-BRCA database. A comprehensive bioinformatics analysis was performed, including survival analysis (Kaplan-Meier), differential gene expression analysis (volcano plots), and genomic mutation characterization (Oncoprint), using the R programming language and suitable packages.
The results in cohort GSE42568 showed high expression of the STING1-IRF1 axis it is associated with a positive trend towards improved survival rates. Transcriptional analysis also revealed a decrease in the expression of HLA-B and HLA-C genes, immunotropic chemokines (CXCL9, CXCL 10) in tumors with low STING1 expression this suggests a "cold" immune pattern. Conversely parallel genomic analysis of the TCGA cohort has identified high frequency of mutations in the MAP3K1 (56%) and PIK3CA (53%), TP53 (46%) genes in addition to mutations in STING1which was directly linked to a disruption in tumor signaling pathways particularly in cell cycle pathways and TP53 and PIK3CA this contributes to strengthening immune escape mechanisms.
Our results indicate that the STING1-IRF1 axis is a prognostic biomarker for predicting the course of the disease, targeting this pathway may help overcome immune evasion resulting from specific genomic changes in breast cancer patients.

PMID:
42663228
Bibliographic data and abstract were imported from PubMed on 28 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.