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

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Zhang Haichao; Qu Xin; Han Lu; Di Xu

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

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Journal: Iranian Journal of Biotechnology Year:621 | Volume: | Issue: Page(s): 26-41

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Title

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

Author(s)

Zhang Haichao | Qu Xin | Han Lu | Di Xu | Issue Writer Certificate

Keywords

DAPL1

breast cancer

Prognosis

TCGA

geo

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 aims 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 DAPL1 and poor clinical Prognosis regarding overall survival. Based on the survival data of geo, the low DAPL1 expression was associated with a poor Prognosis of distant metastasis-free and relapse-free survival. Furthermore, DAPL1 expression was linked to the mutation status or copy number variation of several genes, such as MAP3K1 (mitogen-activated protein kinase kinase kinase 1), NUP98 (nucleoporin 98), and CCDC59 (coiled-coil domain containing 59). The infiltration level of immune cells (e.g., M1 macrophage, B cells, etc.) may be involved in the etiology of breast cancer. Based on the DAPL1-correlated genes, enrichment analysis data indicated the association between DAPL1 expression and a series of biological issues, such as ubiquitin proteasome pathway. Additionally, there were several potential DAPL1-associated phosphorylation kinases, including CDC2 (cell division cycle 2), MAPK (mitogen-activated protein kinases), and PKA (protein kinase A).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.

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