Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach
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 sev...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/11/7/1204 |
| _version_ | 1797527300928962560 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Tak-Kee Choy |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T09:41:59Z |
| format | Article |
| id | doaj.art-452a2186c703486eb2c8fc000925b762 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T09:41:59Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-452a2186c703486eb2c8fc000925b7622023-11-22T03:34:14ZengMDPI AGDiagnostics2075-44182021-07-01117120410.3390/diagnostics11071204Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics ApproachTak-Kee Choy0Chih-Yang Wang1Nam Nhut Phan2Hoang Dang Khoa Ta3Gangga Anuraga4Yen-Hsi Liu5Yung-Fu Wu6Kuen-Haur Lee7Jian-Ying Chuang8Tzu-Jen Kao9Department of Surgery, Division of Gastroenterologic Surgery, Yuan’s General Hospital, Kaohsiung 80249, TaiwanPhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanNTT Institute of Hi-Technology, Nguyen Tat Thanh University, Ho Chi Minh City 700000, VietnamPhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanPhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanSchool of Chinese Medicine for Post-Baccalaureate, I-Shou University, Kaohsiung 82445, TaiwanNational Defense Medical Center, Department of Medical Research, School of Medicine, Tri-Service General Hospital, Taipei 11490, TaiwanPhD Program for Cancer Molecular Biology and Drug Discovery, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanGraduate Institute of Neural Regenerative Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanGraduate Institute of Neural Regenerative Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, TaiwanBreast 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.https://www.mdpi.com/2075-4418/11/7/1204DPP family genesbreast cancerbioinformatics |
| spellingShingle | 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 Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach Diagnostics DPP family genes breast cancer bioinformatics |
| title | Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach |
| title_full | Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach |
| title_fullStr | Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach |
| title_full_unstemmed | Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach |
| title_short | Identification of Dipeptidyl Peptidase (DPP) Family Genes in Clinical Breast Cancer Patients via an Integrated Bioinformatics Approach |
| title_sort | identification of dipeptidyl peptidase dpp family genes in clinical breast cancer patients via an integrated bioinformatics approach |
| topic | DPP family genes breast cancer bioinformatics |
| url | https://www.mdpi.com/2075-4418/11/7/1204 |
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