Identification of dipeptidyl peptidase (Dpp) family genes in clinical breast cancer patients via an integrated bioinformatics approach

Tak Kee Choy, Chih Yang Wang, Nam Nhut Phan, Hoang Dang Khoa Ta, Gangga Anuraga, Yen Hsi Liu, Yung Fu Wu, Kuen Haur Lee, Jian Ying Chuang, Tzu Jen Kao

研究成果: 雜誌貢獻文章同行評審

23 引文 斯高帕斯(Scopus)


Breast cancer is a heterogeneous disease involving complex interactions of biological processes; thus, it is important to develop therapeutic biomarkers for treatment. Members of the dipeptidyl peptidase (DPP) family are metalloproteases that specifically cleave dipeptides. This family comprises seven members, including DPP3, DPP4, DPP6, DPP7, DPP8, DPP9, and DPP10; however, information on the involvement of DPPs in breast cancer is lacking in the literature. As such, we aimed to study their roles in this cancerous disease using publicly available databases such as cBioportal, Oncomine, and Kaplan–Meier Plotter. These databases comprise comprehensive high-throughput transcriptomic profiles of breast cancer across multiple datasets. Furthermore, together with investigating the messenger RNA expression levels of these genes, we also aimed to correlate these expression levels with breast cancer patient survival. The results showed that DPP3 and DPP9 had significantly high expression profiles in breast cancer tissues relative to normal breast tissues. High expression levels of DPP3 and DPP4 were associated with poor survival of breast cancer patients, whereas high expression levels of DPP6, DPP7, DPP8, and DPP9 were associated with good prognoses. Additionally, positive correlations were also revealed of DPP family genes with the cell cycle, transforming growth factor (TGF)-beta, kappa-type opioid receptor, and immune response signaling, such as interleukin (IL)-4, IL6, IL-17, tumor necrosis factor (TNF), and interferon (IFN)alpha/beta. Collectively, DPP family members, especially DPP3, may serve as essential prognostic biomarkers in breast cancer.

出版狀態已發佈 - 7月 2021

ASJC Scopus subject areas

  • 臨床生物化學


深入研究「Identification of dipeptidyl peptidase (Dpp) family genes in clinical breast cancer patients via an integrated bioinformatics approach」主題。共同形成了獨特的指紋。