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Lee YS, Im J, Yang Y, Lee HJ, Lee MR, Woo SM, Park SJ, Kong SY, Kim JY, Hwang H, Kim YH. New Function Annotation of PROSER2 in Pancreatic Ductal Adenocarcinoma. J Proteome Res 2024; 23:905-915. [PMID: 38293943 PMCID: PMC10913870 DOI: 10.1021/acs.jproteome.3c00632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/09/2024] [Accepted: 01/15/2024] [Indexed: 02/01/2024]
Abstract
Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis due to the absence of diagnostic markers and molecular targets. Here, we took an unconventional approach to identify new molecular targets for pancreatic cancer. We chose uncharacterized protein evidence level 1 without function annotation from extensive proteomic research on pancreatic cancer and focused on proline and serine-rich 2 (PROSER2), which ranked high in the cell membrane and cytoplasm. In our study using cell lines and patient-derived orthotopic xenograft cells, PROSER2 exhibited a higher expression in cells derived from primary tumors than in those from metastatic tissues. PROSER2 was localized in the cell membrane and cytosol by immunocytochemistry. PROSER2 overexpression significantly reduced the metastatic ability of cancer cells, whereas its suppression had the opposite effect. Proteomic analysis revealed that PROSER2 interacts with STK25 and PDCD10, and their binding was confirmed by immunoprecipitation and immunocytochemistry. STK25 knockdown enhanced metastasis by decreasing p-AMPK levels, whereas PROSER2-overexpressing cells increased the level of p-AMPK, indicating that PROSER2 suppresses invasion via the AMPK pathway by interacting with STK25. This is the first demonstration of the novel role of PROSER2 in antagonizing tumor progression via the STK25-AMPK pathway in PDAC. LC-MS/MS data are available at MassIVE (MSV000092953) and ProteomeXchange (PXD045646).
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Affiliation(s)
- Yu-Sun Lee
- Division
of Convergence Technology, Research Institute
of National Cancer Center, Goyang 10408, Republic
of Korea
- Department
of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic
of Korea
| | - Jieun Im
- Division
of Convergence Technology, Research Institute
of National Cancer Center, Goyang 10408, Republic
of Korea
| | - Yeji Yang
- Research
Center for Bioconvergence Analysis, Korea
Basic Science Institute, Cheongju 28119, Republic
of Korea
- Critical
Diseases Diagnostics Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Hea Ji Lee
- Research
Center for Bioconvergence Analysis, Korea
Basic Science Institute, Cheongju 28119, Republic
of Korea
| | - Mi Rim Lee
- Department
of Cancer Biomedical Science, National Cancer
Center Graduate School of Cancer Science and Policy, Goyang 10408, Republic of Korea
| | - Sang-Myung Woo
- Department
of Cancer Biomedical Science, National Cancer
Center Graduate School of Cancer Science and Policy, Goyang 10408, Republic of Korea
- Department
of Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang 10408, Republic
of Korea
| | - Sang-Jae Park
- Department
of Center for Liver and Pancreatobiliary Cancer, National Cancer Center, Goyang 10408, Republic
of Korea
- Department
of Surgical Oncology Branch, Research Institute
of National Cancer Center, Goyang 10408, Republic
of Korea
| | - Sun-Young Kong
- Department
of Cancer Biomedical Science, National Cancer
Center Graduate School of Cancer Science and Policy, Goyang 10408, Republic of Korea
- Department
of Targeted Therapy Branch, Research Institute
of National Cancer Center, Goyang 10408, Republic
of Korea
| | - Jin Young Kim
- Research
Center for Bioconvergence Analysis, Korea
Basic Science Institute, Cheongju 28119, Republic
of Korea
- Critical
Diseases Diagnostics Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Heeyoun Hwang
- Research
Center for Bioconvergence Analysis, Korea
Basic Science Institute, Cheongju 28119, Republic
of Korea
- Critical
Diseases Diagnostics Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Yun-Hee Kim
- Division
of Convergence Technology, Research Institute
of National Cancer Center, Goyang 10408, Republic
of Korea
- Department
of Cancer Biomedical Science, National Cancer
Center Graduate School of Cancer Science and Policy, Goyang 10408, Republic of Korea
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Jordaens S, Oeyen E, Willems H, Ameye F, De Wachter S, Pauwels P, Mertens I. Protein Biomarker Discovery Studies on Urinary sEV Fractions Separated with UF-SEC for the First Diagnosis and Detection of Recurrence in Bladder Cancer Patients. Biomolecules 2023; 13:932. [PMID: 37371512 DOI: 10.3390/biom13060932] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/26/2023] [Accepted: 05/30/2023] [Indexed: 06/29/2023] Open
Abstract
Urinary extracellular vesicles (EVs) are an attractive source of bladder cancer biomarkers. Here, a protein biomarker discovery study was performed on the protein content of small urinary EVs (sEVs) to identify possible biomarkers for the primary diagnosis and recurrence of non-muscle-invasive bladder cancer (NMIBC). The sEVs were isolated by ultrafiltration (UF) in combination with size-exclusion chromatography (SEC). The first part of the study compared healthy individuals with NMIBC patients with a primary diagnosis. The second part compared tumor-free patients with patients with a recurrent NMIBC diagnosis. The separated sEVs were in the size range of 40 to 200 nm. Based on manually curated high quality mass spectrometry (MS) data, the statistical analysis revealed 69 proteins that were differentially expressed in these sEV fractions of patients with a first bladder cancer tumor vs. an age- and gender-matched healthy control group. When the discriminating power between healthy individuals and first diagnosis patients is taken into account, the biomarkers with the most potential are MASP2, C3, A2M, CHMP2A and NHE-RF1. Additionally, two proteins (HBB and HBA1) were differentially expressed between bladder cancer patients with a recurrent diagnosis vs. tumor-free samples of bladder cancer patients, but their biological relevance is very limited.
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Affiliation(s)
- Stephanie Jordaens
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, 2610 Wilrijk, Belgium
| | - Eline Oeyen
- Health Unit, Flemish Institute for Technological Research (VITO), 2400 Mol, Belgium
- Centre for Proteomics (CfP), University of Antwerp, 2020 Antwerp, Belgium
| | - Hanny Willems
- Health Unit, Flemish Institute for Technological Research (VITO), 2400 Mol, Belgium
| | - Filip Ameye
- Department of Urology, AZ Maria Middelares, 9000 Ghent, Belgium
| | - Stefan De Wachter
- Department of Urology, Antwerp University Hospital (UZA), 2650 Edegem, Belgium
| | - Patrick Pauwels
- Center for Oncological Research (CORE), Integrated Personalized & Precision Oncology Network (IPPON), University of Antwerp, 2610 Wilrijk, Belgium
- Laboratory of Pathological Anatomy, Antwerp University Hospital (UZA), 2650 Edegem, Belgium
| | - Inge Mertens
- Health Unit, Flemish Institute for Technological Research (VITO), 2400 Mol, Belgium
- Centre for Proteomics (CfP), University of Antwerp, 2020 Antwerp, Belgium
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Yang Y, Hwang H, Im JE, Lee K, Bhoo SH, Yoo JS, Kim YH, Kim JY. Flashlight into the Function of Unannotated C11orf52 using Affinity Purification Mass Spectrometry. J Proteome Res 2021; 20:5340-5346. [PMID: 34739247 DOI: 10.1021/acs.jproteome.1c00540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
For an enhanced understanding of the biological mechanisms of human disease, it is essential to investigate protein functions. In a previous study, we developed a prediction method of gene ontology (GO) terms by the I-TASSER/COFACTOR result, and we applied this to uPE1 in chromosome 11. Here, to validate the bioinformatics prediction of C11orf52, we utilized affinity purification and mass spectrometry to identify interacting partners of C11orf52. Using immunoprecipitation methods with three different peptide tags (Myc, Flag, and 2B8) in HEK 293T cell lines, we identified 79 candidate proteins that are expected to interact with C11orf52. The results of a pathway analysis of the GO and STRING database with candidate proteins showed that C11orf52 could be related to signaling receptor binding, cell-cell adhesion, and ribosome biogenesis. Then, we selected three partner candidates of DSG1, JUP, and PTPN11 for verification of the interaction with C11orf52 and confirmed them by colocalization at the cell-cell junctions by coimmunofluorescence experiments. On the basis of this study, we expect that C11orf52 is related to the Wnt signaling pathway via DSG1 from the protein-protein interactions, given the results of a comprehensive analysis of the bioinformatic predictions. The data set is available at the ProteomeXchange consortium via PRIDE repository (PXD026986).
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Affiliation(s)
- Yeji Yang
- Research Center for Bioconvergence Analysis, Korea Basic Science Institute, Cheongju 28119, Republic of Korea
| | - Heeyoun Hwang
- Research Center for Bioconvergence Analysis, Korea Basic Science Institute, Cheongju 28119, Republic of Korea
| | - Ji Eun Im
- Division of Convergence Technology, Research Institute of National Cancer Center, Goyang 10408, Republic of Korea
| | - Kyungha Lee
- Graduate School of Biotechnology, Kyung Hee University, Yongin 17104, Republic of Korea
| | - Seong Hee Bhoo
- Graduate School of Biotechnology, Kyung Hee University, Yongin 17104, Republic of Korea
| | - Jong Shin Yoo
- Research Center for Bioconvergence Analysis, Korea Basic Science Institute, Cheongju 28119, Republic of Korea.,Graduate School of Analytical Science and Technology, Chungnam National University, Daejeon 34134, Republic of Korea
| | - Yun-Hee Kim
- Division of Convergence Technology, Research Institute of National Cancer Center, Goyang 10408, Republic of Korea.,Department of Cancer Biomedical Science, The National Cancer Center Graduate School of Cancer Science and Policy, Goyang 10408, Republic of Korea
| | - Jin Young Kim
- Research Center for Bioconvergence Analysis, Korea Basic Science Institute, Cheongju 28119, Republic of Korea
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