Prognostic and Genomic Analysis of Proteasome 20S Subunit Alpha (PSMA) Family Members in Breast Cancer

被引:30
|
作者
Chiao, Chung-Chieh [1 ,2 ]
Liu, Yen-Hsi [2 ]
Phan, Nam Nhut [3 ]
Ton, Nu Thuy An [3 ]
Ta, Hoang Dang Khoa [1 ,2 ]
Anuraga, Gangga [1 ,2 ,4 ]
Xuan, Do Thi Minh [2 ]
Fitriani, Fenny [4 ]
Hermanto, Elvira Mustikawati Putri [4 ]
Athoillah, Muhammad [4 ]
Andriani, Vivin [5 ]
Ajiningrum, Purity Sabila [5 ]
Wu, Yung-Fu [6 ]
Lee, Kuen-Haur [1 ,2 ,7 ,8 ]
Chuang, Jian-Ying [8 ,9 ,10 ]
Wang, Chih-Yang [1 ,2 ]
Kao, Tzu-Jen [8 ,9 ,10 ]
机构
[1] Taipei Med Univ, Coll Med Sci, PhD Program Canc Mol Biol & Drug Discovery, Taipei 11031, Taiwan
[2] Taipei Med Univ, Coll Med Sci & Technol, Grad Inst Canc Biol & Drug Discovery, Taipei 11031, Taiwan
[3] Nguyen Tat Thanh Univ, NTT Inst Hitechnol, Ho Chi Minh City 700000, Vietnam
[4] Univ PGRI Adi Buana, Fac Sci & Technol, Dept Stat, Surabaya 60234, Indonesia
[5] Univ PGRI Adi Buana, Fac Sci & Technol, Dept Biol Sci, Surabaya 60234, Indonesia
[6] Natl Def Med Ctr, Sch Med, Tri Serv Gen Hosp, Dept Med Res, Taipei 11490, Taiwan
[7] Taipei Med Univ, Wan Fang Hosp, Canc Ctr, Taipei 11031, Taiwan
[8] Taipei Med Univ, TMU Res Ctr Canc Translat Med, Taipei 11031, Taiwan
[9] Taipei Med Univ, PhD Program Neural Regenerat Med, Taipei 11031, Taiwan
[10] Taipei Med Univ, Res Ctr Neurosci, Taipei 11031, Taiwan
关键词
PSMA family genes; bioinformatics; breast cancer; GENE-EXPRESSION; PPAR-GAMMA; UP-REGULATION; PROLIFERATION; BIOMARKERS; POLYMORPHISMS; ASSOCIATION; DEGRADATION; RESISTANCE; SIGNATURES;
D O I
10.3390/diagnostics11122220
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The complexity of breast cancer includes many interacting biological processes, and proteasome alpha (PSMA) subunits are reported to be involved in many cancerous diseases, although the transcriptomic expression of this gene family in breast cancer still needs to be more thoroughly investigated. Consequently, we used a holistic bioinformatics approach to study the PSMA genes involved in breast cancer by integrating several well-established high-throughput databases and tools, such as cBioPortal, Oncomine, and the Kaplan-Meier plotter. Additionally, correlations of breast cancer patient survival and PSMA messenger RNA expressions were also studied. The results demonstrated that breast cancer tissues had higher expression levels of PSMA genes compared to normal breast tissues. Furthermore, PSMA2, PSMA3, PSMA4, PSMA6, and PSMA7 showed high expression levels, which were correlated with poor survival of breast cancer patients. In contrast, PSMA5 and PSMA8 had high expression levels, which were associated with good prognoses. We also found that PSMA family genes were positively correlated with the cell cycle, ubiquinone metabolism, oxidative stress, and immune response signaling, including antigen presentation by major histocompatibility class, interferon-gamma, and the cluster of differentiation signaling. Collectively, these findings suggest that PSMA genes have the potential to serve as novel biomarkers and therapeutic targets for breast cancer. Nevertheless, the bioinformatic results from the present study would be strengthened with experimental validation in the future by prospective studies on the underlying biological mechanisms of PSMA genes and breast cancer.
引用
收藏
页数:19
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