DAPL1 Identified as a Novel Prognostic Biomarker in Breast Cancer: Insights from Comprehensive in Silico Analysis.

Haichao Zhang, Xin Qu, Lu Han, Xu Di

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Article in Iranian journal of biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 authors.

Haichao ZhangDepartment of Thyroid and Breast Surgery, Tianjin Fourth Central Hospital; The Fourth Center Clinical College of Tianjin Medical University, Tianjin, 300140, China.

Xin QuDepartment of Thyroid and Breast Surgery, Tianjin Fourth Central Hospital; The Fourth Center Clinical College of Tianjin Medical University, Tianjin, 300140, China.

Lu HanDepartment of Thyroid and Breast Surgery, Tianjin Fourth Central Hospital; The Fourth Center Clinical College of Tianjin Medical University, Tianjin, 300140, China.

Xu DiDepartment of Thyroid and Breast Surgery, Tianjin Fourth Central Hospital; The Fourth Center Clinical College of Tianjin Medical University, Tianjin, 300140, China.

Funding

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6 · The paper itself

Abstract

Background: Characterizing tumor-associated gene expression variations in breast cancer is crucial for identifying molecular drivers and therapeutic targets, thereby advancing precision strategies for early detection, prognosis, and treatment optimization. Objectives: This study aimed to investigate the oncogenic role of death-associated protein-like 1 (DAPL1) in breast cancer. Materials and Methods: We employed a bioinformatics approach to conduct a comprehensive analysis of DAPL1, including DNA methylation, genetic alterations, kinase analysis, immune cell infiltration, and signaling pathways. The breast cancer datasets from TCGA (the cancer genome atlas) and GEO (gene expression omnibus) were utilized. Results: DAPL1 is lowly expressed in breast cancer tissues compared to normal tissues. In the TCGA-BRCA (breast invasive carcinoma) cohort, we observed a correlation between low expression of Conclusion: DAPL1 has been recognized as a prognostic biomarker in breast cancer. The molecular mechanisms may involve protein phosphorylation, immune cell infiltration, and several biological issues, especially protein ubiquitination.

Indexed as

Breast cancerDAPL1GEOPrognosisTCGA

Identifiers

PMID41111983

DOI10.30498/ijb.2025.492536.4037

PMCPMC12535287

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