Asian Pacific journal of cancer prevention : APJCP · 2026
Integrated Analysis of the STING1-IRF1 Signaling Pathway and Genomic Alterations in Breast Cancer: Implications for Immune Evasion and Patient Prognosis.
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Alhamadani Isra, Alzeyadi Mohammad
Аннотация
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.