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Updated: Jun 12, 2025
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Bioinformatics Analysis of Peroxisomal Biogenesis Factor Proteins in Breast Malignancy for Introducing Potential
Nima Mahdei Nasirmahalleh1, Mina Hemmati2, Negin Parsamanesh3,4
1Student Research Committee, Department of Medical Biochemistry, School of Medicine, Zanjan, Iran.
Background & Objective:
Breast cancer (BC) is the most common type of malignant neoplasm and is the primary cause of mortality among women aged 45 to 55 years. Studies indicate that cancer displays irregular metabolic patterns in contrast to normal tissue. Furthermore, there is compelling evidence supporting the significant role of peroxisomes in the intricate metabolic processes of cancer. Peroxisomal biogenesis factors (PEXs), which are peroxisomal proteins, control activities such as the degradation and biogenesis of peroxisomes. Hence, the correlation between peroxisomal biogenesis factor expression and BC was explored, to introduce key proteins and potential biomarkers by analyzing.
Methods:
This study utilized UALCAN, GenExMiner v4.8, Metascape, STRING, TIMER, the Kaplan-Meier plotter, The Human Protein Atlas, MirTarBase, and cBioportal.
Results:
The transcriptional levels of PEX6/7/10/11B/13/16 in BC tissues were significantly elevated, whereas the transcriptional levels of PEX2/3/5/11A/12/19 were significantly reduced. High expression levels of PEX 2/3/10/12/11G /26/13/16/14 were significantly related to shorter relapse-free survival, and higher mRNA expression of PEX 11B/11G/11A/12/19 was significantly associated with longer overall survival of BC patients. We identified has-miR-4318 and has-7106-3p as more correlated miRNAs with the PEX family.
Conclusion:
Our results may provide novel insights for the selection of therapeutic targets and prognostic biomarkers for BC.
