Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach.

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

doi:10.3390/diagnostics11071204

Abstract

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.

Highlights

30% of all cancers that occurred in women in the United States in 2020 were breast cancer [1]
Results from an Oncomine analysis showed that mRNA expression levels of dipeptidyl peptidase 3 (DPP3) and dipeptidyl peptidase 9 (DPP9) were highly upregulated in breast cancer tissues, whereas dipeptidyl peptidase 4 (DPP4), dipeptidyl peptidase 6 (DPP6), and dipeptidyl peptidase 8 (DPP8) exhibited downregulated levels in breast cancer tissues relative to normal breast tissues (Figure 1)
We found that dipeptidyl peptidase 10 (DPP10) expression was positively correlated with MAMLD1, RGS20, correlated with MAMLD1, RGS20, ASNS, E2F3, C9orf140, DTNA, PRKCA, LRP8, KCNN2, ASNS, E2F3, C9orf140, DTNA, PRKCA, LRP8, KCNN2, TMSB15A, LOC286052, TMEM65, TMSB15A, LOC286052, TMEM65, CHD7, GGH, C2lorf30, ANKS6, CLTCL1, EIF5A2, and

Summary

Introduction

30% of all cancers that occurred in women in the United States in 2020 were breast cancer [1]. Breast cancer is subtyped by the expression levels of the estrogen receptor (ER, the gene of which is named ESR1), progesterone receptor (PR), and human epidermal growth factor receptor (HER)-2. Many genetic therapies are applied to breast cancer patients, such as fulvestrant [2,3], cyclin-dependent kinase inhibitors [4], aromatase-related inhibitors [5], and histone deacetylase (HDAC) inhibitors [6]. It has been reported that 70% of metastatic breast cancer cases have high expression of B-cell lymphoma 2 (BCL2). Using BCL2 inhibitors for these metastatic cases improved cancer cell apoptosis in a preclinical model of breast cancer [7,8]. Genes that are involved in this biological process are dipeptidyl peptidase (DPP) family genes, extracellular-signalregulated kinase (ERK), GATA-binding protein 3 (GATA3), signal transducer and activator of transcription 3 (STAT3), phosphatidylinositol 3-kinase (PI3K), and NOTCH [9,10,11,12]

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Conclusion