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Chen YE, Ge X, Woyshner K, McDermott M, Manousopoulou A, Ficarro SB, Marto JA, Li K, Wang LD, Li JJ. APIR: Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control. GENOMICS, PROTEOMICS & BIOINFORMATICS 2024; 22:qzae042. [PMID: 39198030 DOI: 10.1093/gpbjnl/qzae042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 02/26/2024] [Accepted: 03/11/2024] [Indexed: 09/01/2024]
Abstract
Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences. Different database search algorithms use distinct search strategies and thus may identify unique PSMs. However, no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and a control on the false discovery rate (FDR). To fill in this gap, we proposed a statistical framework, Aggregation of Peptide Identification Results (APIR), that is universally compatible with all database search algorithms. Notably, under an FDR threshold, APIR is guaranteed to identify at least as many, if not more, peptides as individual database search algorithms do. Evaluation of APIR on a complex proteomics standard dataset showed that APIR outpowers individual database search algorithms and empirically controls the FDR. Real data studies showed that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search algorithms. The APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis, e.g., differential gene expression analysis on RNA sequencing data. The APIR R package is available at https://github.com/yiling0210/APIR.
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Affiliation(s)
- Yiling Elaine Chen
- Department of Statistics and Data Science, University of California, Los Angeles, CA 90095, USA
| | - Xinzhou Ge
- Department of Statistics and Data Science, University of California, Los Angeles, CA 90095, USA
| | - Kyla Woyshner
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - MeiLu McDermott
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Antigoni Manousopoulou
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Scott B Ficarro
- Department of Cancer Biology and Blais Proteomics Center, Dana-Farber Cancer Institute, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215, USA
| | - Jarrod A Marto
- Department of Cancer Biology and Blais Proteomics Center, Dana-Farber Cancer Institute, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02215, USA
| | - Kexin Li
- Department of Statistics and Data Science, University of California, Los Angeles, CA 90095, USA
| | - Leo David Wang
- Department of Immuno-Oncology, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA
- Department of Pediatrics, City of Hope National Medical Center, Duarte, CA 91010, USA
| | - Jingyi Jessica Li
- Department of Statistics and Data Science, University of California, Los Angeles, CA 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA 90095, USA
- Department of Human Genetics, University of California, Los Angeles, CA 90095, USA
- Department of Computational Medicine, University of California, Los Angeles, CA 90095, USA
- Department of Biostatistics, University of California, Los Angeles, CA 90095, USA
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Nuclear Proteomics of Induced Leukemia Cell Differentiation. Cells 2022; 11:cells11203221. [PMID: 36291090 PMCID: PMC9600443 DOI: 10.3390/cells11203221] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 10/06/2022] [Accepted: 10/11/2022] [Indexed: 11/16/2022] Open
Abstract
Studies of induced granulocytic differentiation help to reveal molecular mechanisms of cell maturation. The nuclear proteome represents a rich source of regulatory molecules, including transcription factors (TFs). It is important to have an understanding of molecular perturbations at the early stages of the differentiation processes. By applying the proteomic quantitative profiling using isobaric labeling, we found that the contents of 214, 319, 376, 426, and 391 proteins were altered at 3, 6, 9, 12, and 72 h, respectively, compared to 0 h in the HL-60 cell nuclear fraction under all-trans-retinoid acid (ATRA) treatment. From 1860 identified nuclear proteins, 231 proteins were annotated as proteins with transcription factor (TF) activity. Six TFs (RREB1, SRCAP, CCDC124, TRIM24, BRD7, and BUD31) were downregulated and three TFs EWSR1, ENO1, and FUS were upregulated at early time points (3–12 h) after ATRA treatment. Bioinformatic annotation indicates involvement of the HL-60 nuclear proteome in DNA damage recognition in the RUNX1-triggered pathway, and in the p53-regulation pathway. By applying scheduled multiple reaction monitoring using stable isotopically labeled peptide standards (MRM/SIS), we found a persistent increase in the content of the following proteins: PRAM1, CEPBP, RBPJ, and HIC1 in the HL-60 cell nuclear fraction during ATRA-induced granulocytic differentiation. In the case of STAT1, CASP3, PARP1, and PRKDC proteins, a transient increase in their content was observed at early time points (3–12 h) after the ATRA treatment. Obtained data on nuclear proteome composition and dynamics during granulocytic differentiation could be beneficial for the development of new treatment approaches for leukemias with the mutated p53 gene.
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Li C, Wang M, Shi Y, Xin H. SOSTDC1 acts as a tumor inhibitor in acute myeloid leukemia by downregulating the Wnt/β-catenin pathway. ENVIRONMENTAL TOXICOLOGY 2022; 37:1934-1943. [PMID: 35442555 DOI: 10.1002/tox.23540] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 03/31/2022] [Accepted: 04/10/2022] [Indexed: 06/14/2023]
Abstract
Sclerostin domain-containing 1 (SOSTDC1) has been documented as a key tumor-associated protein that is differentially expressed in multiple malignancies. However, the function of SOSTDC1 in acute myeloid leukemia (AML) is unexplored. The goal of this work was to assess the possible role of SOSTDC1 in AML. Our data showed decreased SOSTDC1 level in bone marrow from AML patients, and patients with low levels of SOSTDC1 had a reduced survival rate. SOSTC1 upregulation restrained the proliferative ability and promoted the apoptotic rate of AML cells. SOSTDC1 suppressed the activation of the Wnt/β-catenin pathway in AML cells. Reactivation of the Wnt/β-catenin pathway reversed SOSTDC1-mediated antitumor effects. SOSTDC1 upregulation weakened the tumorigenicity of AML cells in vivo. Collectively, our work demonstrates that SOSTDC1 has a tumor-inhibiting role in AML via downregulation of the Wnt/β-catenin pathway. This work underscores a key function for the SOSTDC1/Wnt/β-catenin pathway in AML.
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Affiliation(s)
- Chengliang Li
- Department of Hematology, The First Affiliated Hospital of Xi'an Medical University, Xi'an, China
| | - Minjuan Wang
- Department of General Practice, The First Affiliated Hospital of Xi'an Medical University, Xi'an, China
| | - Yingpeng Shi
- Department of General Practice, The First Affiliated Hospital of Xi'an Medical University, Xi'an, China
| | - Hong Xin
- Department of Cardiovasology, The First Affiliated Hospital of Xi'an Medical University, Xi'an, China
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Barroso-Gomila O, Trulsson F, Muratore V, Canosa I, Merino-Cacho L, Cortazar AR, Pérez C, Azkargorta M, Iloro I, Carracedo A, Aransay AM, Elortza F, Mayor U, Vertegaal ACO, Barrio R, Sutherland JD. Identification of proximal SUMO-dependent interactors using SUMO-ID. Nat Commun 2021; 12:6671. [PMID: 34795231 PMCID: PMC8602451 DOI: 10.1038/s41467-021-26807-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 10/19/2021] [Indexed: 12/13/2022] Open
Abstract
The fast dynamics and reversibility of posttranslational modifications by the ubiquitin family pose significant challenges for research. Here we present SUMO-ID, a technology that merges proximity biotinylation by TurboID and protein-fragment complementation to find SUMO-dependent interactors of proteins of interest. We develop an optimized split-TurboID version and show SUMO interaction-dependent labelling of proteins proximal to PML and RANGAP1. SUMO-dependent interactors of PML are involved in transcription, DNA damage, stress response and SUMO modification and are highly enriched in SUMO Interacting Motifs, but may only represent a subset of the total PML proximal proteome. Likewise, SUMO-ID also allow us to identify interactors of SUMOylated SALL1, a less characterized SUMO substrate. Furthermore, using TP53 as a substrate, we identify SUMO1, SUMO2 and Ubiquitin preferential interactors. Thus, SUMO-ID is a powerful tool that allows to study the consequences of SUMO-dependent interactions, and may further unravel the complexity of the ubiquitin code.
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Affiliation(s)
- Orhi Barroso-Gomila
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain
| | - Fredrik Trulsson
- grid.10419.3d0000000089452978Cell and Chemical Biology, Leiden University Medical Center (LUMC), 2333 ZA Leiden, The Netherlands
| | - Veronica Muratore
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain
| | - Iñigo Canosa
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain
| | - Laura Merino-Cacho
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain
| | - Ana Rosa Cortazar
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain ,grid.413448.e0000 0000 9314 1427CIBERONC, Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
| | - Coralia Pérez
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain
| | - Mikel Azkargorta
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain ,grid.413448.e0000 0000 9314 1427CIBERehd, Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain ,grid.413448.e0000 0000 9314 1427ProteoRed-ISCIII, Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
| | - Ibon Iloro
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain ,grid.413448.e0000 0000 9314 1427CIBERehd, Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain ,grid.413448.e0000 0000 9314 1427ProteoRed-ISCIII, Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
| | - Arkaitz Carracedo
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain ,grid.413448.e0000 0000 9314 1427CIBERONC, Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain ,grid.424810.b0000 0004 0467 2314Ikerbasque, Basque Foundation for Science, 48011 Bilbao, Spain ,grid.11480.3c0000000121671098Biochemistry and Molecular Biology Department, University of the Basque Country (UPV/EHU), E-48940 Leioa, Spain
| | - Ana M. Aransay
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain ,grid.413448.e0000 0000 9314 1427CIBERehd, Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
| | - Felix Elortza
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain ,grid.413448.e0000 0000 9314 1427CIBERehd, Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain ,grid.413448.e0000 0000 9314 1427ProteoRed-ISCIII, Instituto de Salud Carlos III, C/ Monforte de Lemos 3-5, Pabellón 11, Planta 0, 28029 Madrid, Spain
| | - Ugo Mayor
- grid.424810.b0000 0004 0467 2314Ikerbasque, Basque Foundation for Science, 48011 Bilbao, Spain ,grid.11480.3c0000000121671098Biochemistry and Molecular Biology Department, University of the Basque Country (UPV/EHU), E-48940 Leioa, Spain
| | - Alfred C. O. Vertegaal
- grid.10419.3d0000000089452978Cell and Chemical Biology, Leiden University Medical Center (LUMC), 2333 ZA Leiden, The Netherlands
| | - Rosa Barrio
- Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160, Derio, Spain.
| | - James D. Sutherland
- grid.420175.50000 0004 0639 2420Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance (BRTA), Bizkaia Technology Park, Building 801 A, 48160 Derio, Spain
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Zhou H, Jia X, Yang F, Shi P. Long noncoding RNA SATB1-AS1 contributes to the chemotherapy resistance through the microRNA-580/ 2'-5'-oligoadenylate synthetase 2 axis in acute myeloid leukemia. Bioengineered 2021; 12:6403-6417. [PMID: 34516354 PMCID: PMC8806783 DOI: 10.1080/21655979.2021.1971508] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Acute myeloid leukemia (AML) represents a hematopoietic cancer with an invasive property. Chemoresistance blunts the therapeutic effect of chemotherapeutics in AML. Long noncoding RNAs (lncRNAs) have been implicated in chemotherapy resistance in AML. Transcriptome sequencing in the current study was applied to clarify the differentially expressed lncRNAs between peripheral blood mononuclear cells of AML and normal samples. The expression of special AT-rich sequence binding protein 1 antisense RNA 1 (SATB1-AS1) and 2ʹ-5ʹ-oligoadenylate synthetase 2 (OAS2) in AML patients was evaluated by qRT-PCR. The relationships among SATB1-AS1, microRNA-580 (miR-580) and OAS2 were investigated by dual-luciferase reporter assay. We observed that SATB1-AS1 and OAS2 were upregulated, while miR-580 was downregulated in AML patients. SATB1-AS1 depletion suppressed proliferation, and enhanced apoptosis and sensitivity of AML cells. Additionally, SATB1-AS1 promoted the expression of OAS2 by acting as a molecular sponge of miR-580 in AML. miR-580 downregulation, OAS2 overexpression and a selective glycogen synthase kinase (GSK)-3β inhibitor AR-A014418 abolished the effects of SATB1-AS1 deletion on the chemosensitivity of AML cells. In conclusion, SATB1-AS1 knockdown promotes the sensitivity of AML cells by upregulating miR-580 and downregulating OAS2 through the GSK3β/β-catenin pathway, providing new insights into the function of SATB1-AS1 as a miRNA sponge in AML.
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Affiliation(s)
- Hong Zhou
- Department of Hematology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P.R. China
| | - Xiaofeng Jia
- College of Life Sciences, China Jiliang University, Hangzhou, Zhejiang, P.R. China
| | - Fan Yang
- Department of Hematology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P.R. China
| | - Pengfei Shi
- Department of Hematology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, P.R. China
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