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Real-Time Monitoring of Aurora kinase A Activation using Conformational FRET Biosensors in Live Cells
Published on: July 30, 2020
Bioinformatics analysis identifies AURKB as a prognostic biomarker across multiple human cancers
Haomin Xie1, Aibing Wu2, Meiqiang Xie2
1The First Clinical Medical School of Guangdong Pharmaceutical University, Guangzhou, 510080, China.
Background:
Cancer is a major global health issue. Aurora kinase B (AURKB) is known to regulate cell division and linked to poor prognosis in some cancers, but its role across all cancer types is unclear.
Objective:
The goal of this study is to examine how AURKB expression, epigenetic regulation, and immune cell infiltration relate to its potential as a prognostic biomarker.
Methods:
We conducted a comprehensive analysis of transcriptomic and clinical data from TCGA, HPA, and CCLE to assess AURKB expression in various cancers. RNA-seq data processing involved TCGAbiolinks, normalization to TPM, and filtering based on the completeness of survival data and sequencing quality. The maxstat method was used to categorize groups into high and low expression. The prognostic significance was evaluated using Cox regression and Kaplan-Meier analysis for OS, DFS, PFI, and DSS. UALCAN was used to analyze promoter methylation, and immune infiltration was assessed with TIMER2 and CIBERSORT. Using the GDSC and CTRP datasets, researchers carried out functional enrichment (KEGG, GO) and examined drug sensitivity correlations. With more than 11,000 cases, the sample size provided enough statistical power.
Results:
AURKB was found to be significantly overexpressed in multiple malignancies, including breast (BRCA), liver (LIHC), kidney (KIRP), and lung (LUAD) cancers, with high expression linked to advanced clinical stages and poorer prognosis. Elevated AURKB levels were associated with significantly reduced OS, DFS, PFI and DSS, particularly in cancers like KIRP (HR = 2.04 for OS, p < 4.2e-10). ROC analysis demonstrated the high diagnostic potential of AURKB, with Area Under the Curve (AUC) values of 1.000 for CHOL and GBM, indicating strong sensitivity and specificity. Additionally, AURKB overexpression was often accompanied by promoter hypomethylation, suggesting an epigenetic mechanism underlying its dysregulation. Immune infiltration analysis revealed that increased AURKB expression correlated with reduced CD8 + T cell infiltration and enhanced immune suppression, particularly in aggressive subtypes. Drug sensitivity analysis showed a negative correlation between AURKB expression and chemotherapy response, suggesting that AURKB overexpression contributes to drug resistance.
Conclusion:
AURKB is a significant prognostic biomarker and potential therapeutic target, with overexpression linked to poor outcomes and chemotherapy resistance. The association with hypomethylation suggests an epigenetic role, supporting targeted therapies. AURKB's influence on immune suppression highlights its role in the tumor microenvironment. Clinical integration of AURKB analysis could enhance personalized treatment, and future research should explore combination therapies with AURKB inhibitors.
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