{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T01:47:41Z","timestamp":1792460861942,"version":"4.5.0"},"reference-count":147,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T00:00:00Z","timestamp":1775520000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"crossref","award":["0200168"],"award-info":[{"award-number":["0200168"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proteomes"],"abstract":"<jats:p>Proteomics represents a fundamental layer for understanding the molecular complexity of solid tumors by quantifying protein abundance and capturing proteoforms and post-translational modifications undetected in genomics or transcriptomics analyses. As mass spectrometry-based technologies and public proteomics repositories have expanded, opportunities for large-scale data reuse have grown accordingly. Nevertheless, data availability has not been translated into straightforward reuse: differences in experimental design, acquisition strategies, quantification workflows and metadata quality still limit the reproducibility and cross-study comparability. In this review, proteomics data reuse is defined as the systematic reanalysis and integration of publicly available datasets to support precision oncology applications such as biomarker assessment and antibody\u2013drug conjugate target prioritization. We discuss reuse as an end-to-end analytical process, focusing on data analysis workflows, harmonization strategies, and the impact of heterogeneous experimental and analytical choices on interoperability. The increased application of artificial intelligence in proteomics data integration and reuse is also addressed, highlighting its analytical potential while underscoring the risks of overinterpretation when biological context and data structure are not adequately considered. Using colorectal and prostate cancer as representative examples, we illustrate how proteomics data reuse can support biological discovery and translational research, while critically examining the factors that limit robustness and clinical relevance.<\/jats:p>","DOI":"10.3390\/proteomes14020016","type":"journal-article","created":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T09:40:31Z","timestamp":1775554831000},"page":"16","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Beyond Reanalysis: Critical Issues in Data Reuse for Solid Tumor Proteomics"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-5599-6585","authenticated-orcid":false,"given":"Federica","family":"Franzetti","sequence":"first","affiliation":[{"name":"Department of Science and High Technology, University of Insubria, 21052 Busto Arsizio, Italy"},{"name":"Department of Medicine and Technological Innovation, University of Insubria, 21100 Varese, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3929-5071","authenticated-orcid":false,"given":"Nicole","family":"Giugni","sequence":"additional","affiliation":[{"name":"Department of Science and High Technology, University of Insubria, 21052 Busto Arsizio, Italy"},{"name":"Department of Medicine and Technological Innovation, University of Insubria, 21100 Varese, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0094-4576","authenticated-orcid":false,"given":"Manuel","family":"Airoldi","sequence":"additional","affiliation":[{"name":"Department of Science and High Technology, University of Insubria, 21052 Busto Arsizio, Italy"},{"name":"Department of Medicine and Technological Innovation, University of Insubria, 21100 Varese, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4845-0022","authenticated-orcid":false,"given":"Heather","family":"Bondi","sequence":"additional","affiliation":[{"name":"Department of Science and High Technology, University of Insubria, 21052 Busto Arsizio, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6065-6699","authenticated-orcid":false,"given":"Tiziana","family":"Alberio","sequence":"additional","affiliation":[{"name":"Department of Science and High Technology, University of Insubria, 21052 Busto Arsizio, Italy"},{"name":"Neuroscience Research Center, University of Insubria, 21052 Busto Arsizio, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0628-5871","authenticated-orcid":false,"given":"Mauro","family":"Fasano","sequence":"additional","affiliation":[{"name":"Department of Science and High Technology, University of Insubria, 21052 Busto Arsizio, Italy"},{"name":"Neuroscience Research Center, University of Insubria, 21052 Busto Arsizio, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Wani, S. (2023). Proteomic Profiling and Its Applications in Cancer Research. Proteomics, Academic Press.","DOI":"10.1016\/B978-0-323-95072-5.00015-8"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1900041","DOI":"10.1002\/smtd.201900041","article-title":"Advances of Proteomics in Novel PTM Discovery: Applications in Cancer Therapy","volume":"3","author":"Wang","year":"2019","journal-title":"Small Methods"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"eabm5164","DOI":"10.1126\/sciadv.abm5164","article-title":"Proteomic Profiling Platforms Head to Head: Leveraging Genetics and Clinical Traits to Compare Aptamer- and Antibody-Based Methods","volume":"8","author":"Katz","year":"2022","journal-title":"Sci. Adv."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1021\/acs.jproteome.0c00641","article-title":"Multiplatform Approach for Plasma Proteomics: Complementarity of Olink Proximity Extension Assay Technology to Mass Spectrometry-Based Protein Profiling","volume":"20","author":"Petrera","year":"2021","journal-title":"J. Proteome Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"19359","DOI":"10.1038\/s41598-024-68565-7","article-title":"Unraveling Druggable Cancer-Driving Proteins and Targeted Drugs Using Artificial Intelligence and Multi-Omics Analyses","volume":"14","author":"Elsitdie","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"nwaf278","DOI":"10.1093\/nsr\/nwaf278","article-title":"The Coming Era of Proteomics-Driven Precision Medicine","volume":"12","author":"Jiang","year":"2025","journal-title":"Natl. Sci. Rev."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Robles, J., Prakash, A., Vizca\u00edno, J.A., and Casal, J.I. (2024). Integrated Meta-Analysis of Colorectal Cancer Public Proteomic Datasets for Biomarker Discovery and Validation. PLoS Comput. Biol., 20.","DOI":"10.1371\/journal.pcbi.1011828"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2707","DOI":"10.1021\/pr501254j","article-title":"The CPTAC Data Portal: A Resource for Cancer Proteomics Research","volume":"14","author":"Edwards","year":"2015","journal-title":"J. Proteome Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"D655","DOI":"10.1093\/nar\/gkj040","article-title":"The PeptideAtlas Project","volume":"34","author":"Desiere","year":"2006","journal-title":"Nucleic Acids Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1270","DOI":"10.1002\/mas.21860","article-title":"Tissue Proteomics Repositories for Data Reanalysis","volume":"43","author":"Stroggilos","year":"2024","journal-title":"Mass Spectrom. Rev."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1038\/nbt.2839","article-title":"ProteomeXchange Provides Globally Co-Ordinated Proteomics Data Submission and Dissemination","volume":"32","author":"Deutsch","year":"2014","journal-title":"Nat. Biotechnol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1021\/acs.jproteome.2c00644","article-title":"Machine Learning on Large-Scale Proteomics Data Identifies Tissue and Cell-Type Specific Proteins","volume":"22","author":"Claeys","year":"2023","journal-title":"J. Proteome Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"101069","DOI":"10.1016\/j.xcrp.2022.101069","article-title":"Advances, Obstacles, and Opportunities for Machine Learning in Proteomics","volume":"3","author":"Desaire","year":"2022","journal-title":"Cell Rep. Phys. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1242","DOI":"10.1074\/mcp.RA118.001288","article-title":"Analysis of 1508 Plasma Samples by Capillary-Flow Data-Independent Acquisition Profiles Proteomics of Weight Loss and Maintenance","volume":"18","author":"Bruderer","year":"2019","journal-title":"Mol. Cell. Proteom."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1021\/acs.jproteome.5b00981","article-title":"Accounting for the Multiple Natures of Missing Values in Label-Free Quantitative Proteomics Data Sets to Compare Imputation Strategies","volume":"15","author":"Lazar","year":"2016","journal-title":"J. Proteome Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3777","DOI":"10.1038\/s41467-024-48177-5","article-title":"BERNN: Enhancing Classification of Liquid Chromatography Mass Spectrometry Data with Batch Effect Removal Neural Networks","volume":"15","author":"Pelletier","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1021\/acs.jproteome.2c00671","article-title":"BIRCH: An Automated Workflow for Evaluation, Correction, and Visualization of Batch Effect in Bottom-Up Mass Spectrometry-Based Proteomics Data","volume":"22","author":"Sundararaman","year":"2023","journal-title":"J. Proteome Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1951","DOI":"10.3390\/ijms13021951","article-title":"Tumor Heterogeneity: Mechanisms and Bases for a Reliable Application of Molecular Marker Design","volume":"13","year":"2012","journal-title":"Int. J. Mol. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Stanta, G., and Bonin, S. (2018). Overview on Clinical Relevance of Intra-Tumor Heterogeneity. Front. Med., 5.","DOI":"10.3389\/fmed.2018.00085"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1016\/j.ccell.2023.02.016","article-title":"The Evolving Tumor Microenvironment: From Cancer Initiation to Metastatic Outgrowth","volume":"41","author":"Joyce","year":"2023","journal-title":"Cancer Cell"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Shaw, T.I., Zhao, B., Li, Y., Wang, H., Wang, L., Manley, B., Stewart, P.A., and Karolak, A. (2022). Multi-Omics Approach to Identifying Isoform Variants as Therapeutic Targets in Cancer Patients. Front. Oncol., 12.","DOI":"10.3389\/fonc.2022.1051487"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"23","DOI":"10.3892\/ijo.2022.5471","article-title":"Role of the Tumor Microenvironment in Cancer Hallmarks and Targeted Therapy (Review)","volume":"62","author":"Naser","year":"2023","journal-title":"Int. J. Oncol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"217865","DOI":"10.1016\/j.canlet.2025.217865","article-title":"The Role of Tumor Microenvironment and Immune Cell Crosstalk in Triple-Negative Breast Cancer (TNBC): Emerging Therapeutic Opportunities","volume":"628","author":"Sabit","year":"2025","journal-title":"Cancer Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1038\/s41392-025-02280-1","article-title":"Immune Evasion in Cancer: Mechanisms and Cutting-Edge Therapeutic Approaches","volume":"10","author":"Tufail","year":"2025","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/s13045-024-01634-6","article-title":"Harnessing the Tumor Microenvironment: Targeted Cancer Therapies through Modulation of Epithelial-Mesenchymal Transition","volume":"18","author":"Glaviano","year":"2025","journal-title":"J. Hematol. Oncol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"105524","DOI":"10.1016\/j.jprot.2025.105524","article-title":"Proteoformics: Current Status and Future Perspectives","volume":"321","author":"Fang","year":"2025","journal-title":"J. Proteom."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1021\/acsmeasuresciau.3c00068","article-title":"Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry","volume":"4","author":"Jiang","year":"2024","journal-title":"ACS Meas. Sci. Au"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"901","DOI":"10.1038\/s41586-025-08584-0","article-title":"Mass-Spectrometry-Based Proteomics: From Single Cells to Clinical Applications","volume":"638","author":"Guo","year":"2025","journal-title":"Nature"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Marcus, K., Eisenacher, M., and Sitek, B. (2021). Quantitative Mass Spectrometry-Based Proteomics: An Overview. Quantitative Methods in Proteomics, Springer.","DOI":"10.1007\/978-1-0716-1024-4"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Carbonara, K., Andonovski, M., and Coorssen, J.R. (2021). Proteomes Are of Proteoforms: Embracing the Complexity. Proteomes, 9.","DOI":"10.3390\/proteomes9030038"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1361","DOI":"10.1021\/jasms.0c00484","article-title":"Capillary Zone Electrophoresis-Electron-Capture Collision-Induced Dissociation on a Quadrupole Time-of-Flight Mass Spectrometer for Top-Down Characterization of Intact Proteins","volume":"32","author":"Shen","year":"2021","journal-title":"J. Am. Soc. Mass Spectrom."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2470","DOI":"10.1007\/s13361-019-02206-6","article-title":"Capillary Zone Electrophoresis-Tandem Mass Spectrometry with Activated Ion Electron Transfer Dissociation for Large-Scale Top-down Proteomics","volume":"30","author":"McCool","year":"2019","journal-title":"J. Am. Soc. Mass Spectrom."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1038\/s43586-024-00318-2","article-title":"Top-down Proteomics","volume":"4","author":"Roberts","year":"2024","journal-title":"Nat. Rev. Methods Primers"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1007\/s00216-007-1486-6","article-title":"Quantitative Mass Spectrometry in Proteomics: A Critical Review","volume":"389","author":"Bantscheff","year":"2007","journal-title":"Anal. Bioanal. Chem."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Keerthikumar, S., and Mathivanan, S. (2017). Label-Based and Label-Free Strategies for Protein Quantitation. Proteome Bioinformatics, Springer.","DOI":"10.1007\/978-1-4939-6740-7"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1002\/pmic.201000553","article-title":"Less Label, More Free: Approaches in Label-Free Quantitative Mass Spectrometry","volume":"11","author":"Neilson","year":"2011","journal-title":"Proteomics"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"180","DOI":"10.3390\/proteomes1030180","article-title":"Comparative and Quantitative Global Proteomics Approaches: An Overview","volume":"1","author":"Deracinois","year":"2013","journal-title":"Proteomes"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/s12014-018-9184-2","article-title":"Current Applications of Antibody Microarrays","volume":"15","author":"Chen","year":"2018","journal-title":"Clin. Proteom."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"100155","DOI":"10.1016\/j.mcpro.2021.100155","article-title":"Uncovering the Depths of the Human Proteome: Antibody-Based Technologies for Ultrasensitive Multiplexed Protein Detection and Quantification","volume":"20","author":"Ren","year":"2021","journal-title":"Mol. Cell. Proteom."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"15","DOI":"10.7171\/jbt.21-3202-001","article-title":"Reverse-Phase Protein Array: Technology, Application, Data Processing, and Integration","volume":"32","author":"Coarfa","year":"2021","journal-title":"J. Biomol. Tech."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Carlyle, B.C., Kitchen, R.R., Mattingly, Z., Celia, A.M., Trombetta, B.A., Das, S., Hyman, B.T., Kivis\u00e4kk, P., and Arnold, S.E. (2022). Technical Performance Evaluation of Olink Proximity Extension Assay for Blood-Based Biomarker Discovery in Longitudinal Studies of Alzheimer\u2019s Disease. Front. Neurol., 13.","DOI":"10.3389\/fneur.2022.889647"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2300233","DOI":"10.1002\/prca.202300233","article-title":"Methods and Clinical Biomarker Discovery for Targeted Proteomics Using Olink Technology","volume":"18","author":"Wang","year":"2024","journal-title":"Proteom. Clin. Appl."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"638","DOI":"10.1002\/pmic.201300187","article-title":"Beyond Antibodies: New Affinity Reagents to Unlock the Proteome","volume":"14","author":"Lollo","year":"2014","journal-title":"Proteomics"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.ymeth.2019.01.007","article-title":"The Genesis and Evolution of Bead-Based Multiplexing","volume":"158","author":"Graham","year":"2019","journal-title":"Methods"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3064643","DOI":"10.1155\/2016\/3064643","article-title":"Serum Cytokinome Profile Evaluation: A Tool to Define New Diagnostic and Prognostic Markers of Cancer Using Multiplexed Bead-Based Immunoassays","volume":"2016","author":"Capone","year":"2016","journal-title":"Mediat. Inflamm."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1612","DOI":"10.1074\/mcp.R112.019695","article-title":"File Formats Commonly Used in Mass Spectrometry Proteomics","volume":"11","author":"Deutsch","year":"2012","journal-title":"Mol. Cell. Proteom."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1021\/acs.jproteome.0c00192","article-title":"mzMLb: A Future-Proof Raw Mass Spectrometry Data Format Based on Standards-Compliant mzML and Optimized for Speed and Storage Requirements","volume":"20","author":"Bhamber","year":"2021","journal-title":"J. Proteome Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1038\/nature19949","article-title":"Mass-Spectrometric Exploration of Proteome Structure and Function","volume":"537","author":"Aebersold","year":"2016","journal-title":"Nature"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1367","DOI":"10.1038\/nbt.1511","article-title":"MaxQuant Enables High Peptide Identification Rates, Individualized p.p.b.-Range Mass Accuracies and Proteome-Wide Protein Quantification","volume":"26","author":"Cox","year":"2008","journal-title":"Nat. Biotechnol."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1016\/j.cell.2020.01.026","article-title":"Proteogenomic Characterization of Endometrial Carcinoma","volume":"180","author":"Dou","year":"2020","journal-title":"Cell"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1255","DOI":"10.1016\/j.cell.2024.01.027","article-title":"Pan-Cancer Proteogenomics Characterization of Tumor Immunity","volume":"187","author":"Petralia","year":"2024","journal-title":"Cell"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1038\/nature18003","article-title":"Proteogenomics Connects Somatic Mutations to Signaling in Breast Cancer","volume":"534","author":"Mertins","year":"2016","journal-title":"Nature"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"eabk0734","DOI":"10.1126\/sciadv.abk0734","article-title":"The Human Proteoform Project: Defining the Human Proteome","volume":"7","author":"Smith","year":"2021","journal-title":"Sci. Adv."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"5497","DOI":"10.1109\/ACCESS.2020.3047588","article-title":"Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey","volume":"9","author":"Tariq","year":"2021","journal-title":"IEEE Access"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"8421","DOI":"10.1038\/s41467-025-64089-4","article-title":"Facilitating Analysis and Dissemination of Proteomics Data through Metadata Integration in MaxQuant","volume":"16","author":"Viegener","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1466","DOI":"10.1093\/bioinformatics\/bth092","article-title":"TANDEM: Matching Proteins with Tandem Mass Spectra","volume":"20","author":"Craig","year":"2004","journal-title":"Bioinformatics"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"4154","DOI":"10.1038\/s41467-023-39869-5","article-title":"Analysis of DIA Proteomics Data Using MSFragger-DIA and FragPipe Computational Platform","volume":"14","author":"Yu","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1038\/s41592-019-0638-x","article-title":"DIA-NN: Neural Networks and Interference Correction Enable Deep Proteome Coverage in High Throughput","volume":"17","author":"Demichev","year":"2020","journal-title":"Nat. Methods"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"M111.014381-1\u2013M111.014381-10","DOI":"10.1074\/mcp.M111.014381","article-title":"The mzIdentML Data Standard for Mass Spectrometry-Based Proteomics Results","volume":"11","author":"Jones","year":"2012","journal-title":"Mol. Cell. Proteom."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2765","DOI":"10.1074\/mcp.O113.036681","article-title":"The mzTab Data Exchange Format: Communicating Mass-Spectrometry-Based Proteomics and Metabolomics Experimental Results to a Wider Audience","volume":"13","author":"Griss","year":"2014","journal-title":"Mol. Cell. Proteom."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1074\/mcp.M117.068429","article-title":"The mzIdentML Data Standard Version 1.2, Supporting Advances in Proteome Informatics","volume":"16","author":"Mayer","year":"2017","journal-title":"Mol. Cell. Proteom."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1021\/acs.jproteome.5c00980","article-title":"Evaluating and Optimizing Mass Spectrometry Proteomics Data to Deconvolve Cell-Type-Specific Protein Expression in Tumors","volume":"25","author":"Song","year":"2026","journal-title":"J. Proteome Res."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1021\/acs.jproteome.1c00771","article-title":"Proteomics Standards Initiative\u2019s ProForma 2.0: Unifying the Encoding of Proteoforms and Peptidoforms","volume":"21","author":"LeDuc","year":"2022","journal-title":"J. Proteome Res."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"5854","DOI":"10.1038\/s41467-021-26111-3","article-title":"A Proteomics Sample Metadata Representation for Multiomics Integration and Big Data Analysis","volume":"12","author":"Dai","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"3906","DOI":"10.1021\/acs.jproteome.0c00376","article-title":"Towards a Sample Metadata Standard in Public Proteomics Repositories","volume":"19","year":"2020","journal-title":"J. Proteome Res."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"100731","DOI":"10.1016\/j.mcpro.2024.100731","article-title":"The Importance, Challenges, and Possible Solutions for Sharing Proteomics Data While Safeguarding Individuals\u2019 Privacy","volume":"23","author":"Shome","year":"2024","journal-title":"Mol. Cell. Proteom."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"930","DOI":"10.1002\/pmic.201400302","article-title":"Making Proteomics Data Accessible and Reusable: Current State of Proteomics Databases and Repositories","volume":"15","author":"Alpi","year":"2015","journal-title":"Proteomics"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"D459","DOI":"10.1093\/nar\/gkaf1146","article-title":"The ProteomeXchange Consortium in 2026: Making Proteomics Data FAIR","volume":"54","author":"Deutsch","year":"2026","journal-title":"Nucleic Acids Res."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"R110.000133","DOI":"10.1074\/mcp.R110.000133","article-title":"mzML\u2014A Community Standard for Mass Spectrometry Data","volume":"10","author":"Martens","year":"2011","journal-title":"Mol. Cell. Proteom."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"160018","DOI":"10.1038\/sdata.2016.18","article-title":"The FAIR Guiding Principles for Scientific Data Management and Stewardship","volume":"3","author":"Wilkinson","year":"2016","journal-title":"Sci. Data"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1038\/s41592-021-01184-6","article-title":"Universal Spectrum Identifier for Mass Spectra","volume":"18","author":"Deutsch","year":"2021","journal-title":"Nat. Methods"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"D1211","DOI":"10.1093\/nar\/gky869","article-title":"iProX: An Integrated Proteome Resource","volume":"47","author":"Ma","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1038\/nbt.3790","article-title":"Discovering and Linking Public \u2018Omics\u2019 Datasets Using the Omics Discovery Index","volume":"35","author":"Bai","year":"2017","journal-title":"Nat. Biotechnol."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"D1539","DOI":"10.1093\/nar\/gkac1040","article-title":"The ProteomeXchange Consortium at 10 Years: 2023 Update","volume":"51","author":"Deutsch","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"ref_75","first-page":"D543","article-title":"The PRIDE Database Resources in 2022: A Hub for Mass Spectrometry-Based Proteomics Evidences","volume":"50","author":"Bai","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"D543","DOI":"10.1093\/nar\/gkae1011","article-title":"The PRIDE Database at 20 Years: 2025 Update","volume":"53","author":"Bandla","year":"2025","journal-title":"Nucleic Acids Res."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1080\/14789450.2022.2160324","article-title":"Proteomic Repository Data Submission, Dissemination, and Reuse: Key Messages","volume":"19","year":"2022","journal-title":"Expert Rev. Proteom."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.cels.2018.08.004","article-title":"Assembling the Community-Scale Discoverable Human Proteome","volume":"7","author":"Wang","year":"2018","journal-title":"Cell Syst."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"D462","DOI":"10.1093\/nar\/gkae1032","article-title":"jPOST Environment Accelerates the Reuse and Reanalysis of Public Proteome Mass Spectrometry Data","volume":"53","author":"Okuda","year":"2025","journal-title":"Nucleic Acids Res."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"D1107","DOI":"10.1093\/nar\/gkw1080","article-title":"jPOSTrepo: An International Standard Data Repository for Proteomes","volume":"45","author":"Okuda","year":"2017","journal-title":"Nucleic Acids Res."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"4205","DOI":"10.1021\/pr5006636","article-title":"Panorama: A Targeted Proteomics Knowledge Base","volume":"13","author":"Sharma","year":"2014","journal-title":"J. Proteome Res."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"D1522","DOI":"10.1093\/nar\/gkab1081","article-title":"iProX in 2021: Connecting Proteomics Data Sharing with Big Data","volume":"50","author":"Chen","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1002\/pro.3307","article-title":"The Human Protein Atlas: A Spatial Map of the Human Proteome","volume":"27","author":"Thul","year":"2018","journal-title":"Protein Sci."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"1328","DOI":"10.1016\/j.ccell.2025.05.003","article-title":"The Pan-Cancer Proteome Atlas, a Mass Spectrometry-Based Landscape for Discovering Tumor Biology, Biomarkers, and Therapeutic Targets","volume":"43","author":"Knol","year":"2025","journal-title":"Cancer Cell"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1016\/j.ccell.2025.05.012","article-title":"A Unified Pan-Cancer Proteome Atlas","volume":"43","author":"Du","year":"2025","journal-title":"Cancer Cell"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"100919","DOI":"10.1016\/j.mcpro.2025.100919","article-title":"Integrated Analysis of Proteome and Transcriptome Profiling Reveals Pan-Cancer-Associated Pathways and Molecular Biomarkers","volume":"24","author":"Hu","year":"2025","journal-title":"Mol. Cell. Proteom."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"114500","DOI":"10.1016\/j.isci.2025.114500","article-title":"A Data-Driven Pan-Cancer Proteogenomic Analysis Reveals the Characteristics of Human Cancer Protein Expression","volume":"29","author":"Li","year":"2025","journal-title":"iScience"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.1016\/j.ccell.2023.06.009","article-title":"Proteogenomic Data and Resources for Pan-Cancer Analysis","volume":"41","author":"Li","year":"2023","journal-title":"Cancer Cell"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"D526","DOI":"10.1093\/nar\/gkab1086","article-title":"The Human Proteoform Atlas: A FAIR Community Resource for Experimentally Derived Proteoforms","volume":"50","author":"Hollas","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"100071","DOI":"10.1016\/j.mcpro.2021.100071","article-title":"Data Management of Sensitive Human Proteomics Data: Current Practices, Recommendations, and Perspectives for the Future","volume":"20","author":"Bandeira","year":"2021","journal-title":"Mol. Cell. Proteom."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1038\/s41467-022-28524-0","article-title":"Proteomic Analysis of Archival Breast Cancer Clinical Specimens Identifies Biological Subtypes with Distinct Survival Outcomes","volume":"13","author":"Asleh","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_92","doi-asserted-by":"crossref","unstructured":"Boonen, K., Hens, K., Menschaert, G., Baggerman, G., Valkenborg, D., and Ertaylan, G. (2019). Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine. Genes, 10.","DOI":"10.3390\/genes10090682"},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/j.tig.2024.03.004","article-title":"Patient Privacy in AI-Driven Omics Methods","volume":"40","author":"Zhou","year":"2024","journal-title":"Trends Genet."},{"key":"ref_94","first-page":"122","article-title":"On the Privacy Risks of Sharing Clinical Proteomics Data","volume":"2016","author":"Li","year":"2016","journal-title":"AMIA Jt. Summits Transl. Sci. Proc."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"9254","DOI":"10.1038\/s41598-023-34866-6","article-title":"Large Scale Proteomic Studies Create Novel Privacy Considerations","volume":"13","author":"Hill","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"100035","DOI":"10.1074\/mcp.RA120.002359","article-title":"Plasma Proteomes Can Be Reidentifiable and Potentially Contain Personally Sensitive and Incidental Findings","volume":"20","author":"Geyer","year":"2021","journal-title":"Mol. Cell. Proteom."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"59","DOI":"10.12688\/openreseurope.15810.1","article-title":"Foresight in Clinical Proteomics: Current Status, Ethical Considerations, and Future Perspectives","volume":"3","author":"Mundt","year":"2023","journal-title":"Open Res. Eur."},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1038\/s43588-025-00832-7","article-title":"Privacy-Preserving Multicenter Differential Protein Abundance Analysis with FedProt","volume":"5","author":"Burankova","year":"2025","journal-title":"Nat. Comput. Sci."},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1021\/acs.jproteome.2c00629","article-title":"ProteomicsML: An Online Platform for Community-Curated Data Sets and Tutorials for Machine Learning in Proteomics","volume":"22","author":"Rehfeldt","year":"2023","journal-title":"J. Proteome Res."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"100003","DOI":"10.1016\/j.crmeth.2021.100003","article-title":"Deep Learning Neural Network Tools for Proteomics","volume":"1","author":"Meyer","year":"2021","journal-title":"Cell Rep. Methods"},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.jprot.2018.12.004","article-title":"Statistical Analysis of Proteomics Data: A Review on Feature Selection","volume":"198","author":"Lualdi","year":"2019","journal-title":"J. Proteom."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"100083","DOI":"10.1016\/j.mcpro.2021.100083","article-title":"Feature Selection Methods for Protein Biomarker Discovery from Proteomics or Multiomics Data","volume":"20","author":"Shi","year":"2021","journal-title":"Mol. Cell. Proteom."},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1038\/s41416-024-02706-7","article-title":"Graph Machine Learning for Integrated Multi-Omics Analysis","volume":"131","author":"Valous","year":"2024","journal-title":"Br. J. Cancer"},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"2143","DOI":"10.1021\/jasms.4c00180","article-title":"Machine Learning Strategies to Tackle Data Challenges in Mass Spectrometry-Based Proteomics","volume":"35","author":"Dens","year":"2024","journal-title":"J. Am. Soc. Mass Spectrom."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1016\/j.tibtech.2017.02.012","article-title":"Why Batch Effects Matter in Omics Data, and How to Avoid Them","volume":"35","author":"Goh","year":"2017","journal-title":"Trends Biotechnol."},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"7877","DOI":"10.1038\/s41467-022-35564-z","article-title":"Benchmarking Tools for Detecting Longitudinal Differential Expression in Proteomics Data Allows Establishing a Robust Reproducibility Optimization Regression Approach","volume":"13","author":"Suomi","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"e10240","DOI":"10.15252\/msb.202110240","article-title":"Diagnostics and Correction of Batch Effects in Large-scale Proteomic Studies: A Tutorial","volume":"17","author":"Lee","year":"2021","journal-title":"Mol. Syst. Biol."},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Airoldi, M., Remori, V., and Fasano, M. (2025). Statistical Methods for Multi-Omics Analysis in Neurodevelopmental Disorders: From High Dimensionality to Mechanistic Insight. Biomolecules, 15.","DOI":"10.3390\/biom15101401"},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"2200092","DOI":"10.1002\/pmic.202200092","article-title":"Dealing with Missing Values in Proteomics Data","volume":"22","author":"Kong","year":"2022","journal-title":"Proteomics"},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"3523","DOI":"10.1038\/s41467-022-31007-x","article-title":"HarmonizR Enables Data Harmonization across Independent Proteomic Datasets with Appropriate Handling of Missing Values","volume":"13","author":"Schlumbohm","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_111","doi-asserted-by":"crossref","first-page":"6743","DOI":"10.1038\/s41467-023-42543-5","article-title":"lesSDRF Is More: Maximizing the Value of Proteomics Data through Streamlined Metadata Annotation","volume":"14","author":"Claeys","year":"2023","journal-title":"Nat. Commun."},{"key":"ref_112","doi-asserted-by":"crossref","first-page":"1700","DOI":"10.1074\/mcp.TIR119.001505","article-title":"MARMoSET\u2014Extracting Publication-Ready Mass Spectrometry Metadata from RAW Files","volume":"18","author":"Kiweler","year":"2019","journal-title":"Mol. Cell. Proteom."},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"eadp6040","DOI":"10.1126\/sciadv.adp6040","article-title":"Domain Adaptation in Small-Scale and Heterogeneous Biological Datasets","volume":"10","author":"Orouji","year":"2024","journal-title":"Sci. Adv."},{"key":"ref_114","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1038\/s42004-025-01540-z","article-title":"Leveraging Pretrained Deep Protein Language Model to Predict Peptide Collision Cross Section","volume":"8","author":"Ogata","year":"2025","journal-title":"Commun. Chem."},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1016\/j.cell.2019.08.052","article-title":"Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma","volume":"179","author":"Gao","year":"2019","journal-title":"Cell"},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"2669","DOI":"10.1038\/s41467-022-30342-3","article-title":"Proteogenomic Characterization of 2002 Human Cancers Reveals Pan-Cancer Molecular Subtypes and Associated Pathways","volume":"13","author":"Zhang","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"755","DOI":"10.1016\/j.cell.2016.05.069","article-title":"Integrated Proteogenomic Characterization of Human High Grade Serous Ovarian Cancer","volume":"166","author":"Zhang","year":"2016","journal-title":"Cell"},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1038\/s41576-025-00915-1","article-title":"Proteoform Medicine: Characterizing and Targeting Protein Forms in Human Disease","volume":"27","author":"Korchak","year":"2026","journal-title":"Nat. Rev. Genet."},{"key":"ref_119","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.breast.2022.10.016","article-title":"Antibody Drug Conjugates Targeting HER2: Clinical Development in Metastatic Breast Cancer","volume":"66","author":"Rassy","year":"2022","journal-title":"Breast"},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"1948","DOI":"10.1038\/s41467-024-54654-8","article-title":"Functional Proteoform Group Deconvolution Reveals a Broader Spectrum of Ibrutinib Off-Targets","volume":"16","author":"Leo","year":"2025","journal-title":"Nat. Commun."},{"key":"ref_121","doi-asserted-by":"crossref","unstructured":"Su, M., Zhang, Z., Zhou, L., Han, C., Huang, C., and Nice, E.C. (2021). Proteomics, Personalized Medicine and Cancer. Cancers, 13.","DOI":"10.3390\/cancers13112512"},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"2300088","DOI":"10.1002\/pmic.202300088","article-title":"Computational Approaches to Identify Sites of Phosphorylation","volume":"24","author":"Joyce","year":"2024","journal-title":"Proteomics"},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"6725","DOI":"10.1038\/s41467-022-34407-1","article-title":"Connecting Multiple Microenvironment Proteomes Uncovers the Biology in Head and Neck Cancer","volume":"13","author":"Neves","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"D447","DOI":"10.1093\/nar\/gkv1145","article-title":"2016 Update of the PRIDE Database and Its Related Tools","volume":"44","author":"Csordas","year":"2016","journal-title":"Nucleic Acids Res."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1001\/jama.2025.0228","article-title":"Prostate Cancer: A Review","volume":"333","author":"Raychaudhuri","year":"2025","journal-title":"J. Am. Med. Assoc."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1186\/s13059-020-02188-9","article-title":"Convergent Network Effects along the Axis of Gene Expression during Prostate Cancer Progression","volume":"21","author":"Charmpi","year":"2020","journal-title":"Genome Biol."},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1038\/s41597-021-00890-2","article-title":"An Integrated Landscape of Protein Expression in Human Cancer","volume":"8","author":"Jarnuczak","year":"2021","journal-title":"Sci. Data"},{"key":"ref_128","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1038\/s41597-022-01380-9","article-title":"Implementing the Reuse of Public DIA Proteomics Datasets: From the PRIDE Database to Expression Atlas","volume":"9","author":"Walzer","year":"2022","journal-title":"Sci. Data"},{"key":"ref_129","doi-asserted-by":"crossref","first-page":"100305","DOI":"10.1016\/j.jlb.2025.100305","article-title":"Blood and Urine-Based Biomarkers in Prostate Cancer: Current Advances, Clinical Applications, and Future Directions","volume":"9","author":"Crocetto","year":"2025","journal-title":"J. Liq. Biopsy"},{"key":"ref_130","doi-asserted-by":"crossref","unstructured":"Majewska, Z., Zajkowska, M., P\u0105czek, S., Nowi\u0144ski, A.R., Sok\u00f3lska, W., Gryko, M., and Orywal, K. (2025). The Clinical Relevance of Tumor Biomarkers in Prostate Cancer\u2014A Review. Cancers, 17.","DOI":"10.3390\/cancers17233742"},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1016\/j.eururo.2015.06.046","article-title":"A Contemporary Prostate Cancer Grading System: A Validated Alternative to the Gleason Score","volume":"69","author":"Epstein","year":"2016","journal-title":"Eur. Urol."},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1111\/apm.12533","article-title":"International Society of Urological Pathology (ISUP) Grading of Prostate Cancer\u2014An ISUP Consensus on Contemporary Grading","volume":"124","author":"Egevad","year":"2016","journal-title":"Acta Pathol. Microbiol. Immunol. Scand."},{"key":"ref_133","doi-asserted-by":"crossref","first-page":"e87","DOI":"10.1097\/PAS.0000000000001497","article-title":"The 2019 International Society of Urological Pathology (ISUP) Consensus Conference on Grading of Prostatic Carcinoma","volume":"44","author":"Grignon","year":"2020","journal-title":"Am. J. Surg. Pathol."},{"key":"ref_134","doi-asserted-by":"crossref","first-page":"195","DOI":"10.21873\/cgp.20180","article-title":"Identification of Novel Prognosis and Prediction Markers in Advanced Prostate Cancer Tissues Based on Quantitative Proteomics","volume":"17","author":"Kwon","year":"2020","journal-title":"Cancer Genom. Proteom."},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"942","DOI":"10.1016\/j.eururo.2015.10.053","article-title":"The Proteome of Primary Prostate Cancer","volume":"69","author":"Tyanova","year":"2016","journal-title":"Eur. Urol."},{"key":"ref_136","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1186\/s12014-019-9236-2","article-title":"Quantitative Proteomic Analysis of Prostate Tissue Specimens Identifies Deregulated Protein Complexes in Primary Prostate Cancer","volume":"16","author":"Zhou","year":"2019","journal-title":"Clin. Proteom."},{"key":"ref_137","doi-asserted-by":"crossref","first-page":"101679","DOI":"10.1016\/j.xcrm.2024.101679","article-title":"Proteomic Landscape Profiling of Primary Prostate Cancer Reveals a 16-Protein Panel for Prognosis Prediction","volume":"5","author":"Sun","year":"2024","journal-title":"Cell Rep. Med."},{"key":"ref_138","doi-asserted-by":"crossref","unstructured":"Mart\u00edn-Garc\u00eda, D., Garc\u00eda-Aranda, M., and Redondo, M. (2024). Biomarker Identification through Proteomics in Colorectal Cancer. Int. J. Mol. Sci., 25.","DOI":"10.3390\/ijms25042283"},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1186\/s12935-025-04039-8","article-title":"Recent Clinical Advances in Nonconjugated Antibodies and Antibody-Drug Conjugates for Colorectal Cancer Treatment","volume":"25","author":"Noorkhajavi","year":"2025","journal-title":"Cancer Cell Int."},{"key":"ref_140","doi-asserted-by":"crossref","first-page":"1670","DOI":"10.1038\/s41416-024-02650-6","article-title":"Functional Proteomics of Colon Cancer Consensus Molecular Subtypes","volume":"130","author":"Feliu","year":"2024","journal-title":"Br. J. Cancer"},{"key":"ref_141","doi-asserted-by":"crossref","first-page":"107897","DOI":"10.1016\/j.compbiolchem.2023.107897","article-title":"Integrated Transcriptomics and Proteomics Data Analysis Identifies CDH17 as a Key Cell Surface Target in Colorectal Cancer","volume":"105","author":"Wong","year":"2023","journal-title":"Comput. Biol. Chem."},{"key":"ref_142","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1200\/GO.2023.9.Supplement_1.25","article-title":"Phase 1A, First-in-Human Study of ARB202, Bispecific Antibody to CDH17 and CD3, in Advanced Gastrointestinal Malignancies Expressing CDH17","volume":"9","author":"Leung","year":"2023","journal-title":"JCO Glob. Oncol."},{"key":"ref_143","doi-asserted-by":"crossref","first-page":"4018","DOI":"10.1038\/s41598-025-34043-x","article-title":"Biological and Prognostic Relevance of A-to-I RNA Editing across Consensus Molecular Subtypes of Colon Cancer","volume":"16","author":"Monaco","year":"2026","journal-title":"Sci. Rep."},{"key":"ref_144","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1016\/j.tibs.2017.01.001","article-title":"A Golden Age for Working with Public Proteomics Data","volume":"42","author":"Martens","year":"2017","journal-title":"Trends Biochem. Sci."},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"2307271","DOI":"10.1002\/advs.202307271","article-title":"Glucagon Enhances Chemotherapy Efficacy By Inhibition of Tumor Vessels in Colorectal Cancer","volume":"11","author":"Xu","year":"2024","journal-title":"Adv. Sci."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.jprot.2015.05.037","article-title":"Quantitative Proteomic Analysis of Paired Colorectal Cancer and Non-Tumorigenic Tissues Reveals Signature Proteins and Perturbed Pathways Involved in CRC Progression and Metastasis","volume":"126","author":"Sethi","year":"2015","journal-title":"J. Proteom."},{"key":"ref_147","doi-asserted-by":"crossref","first-page":"813","DOI":"10.18632\/oncotarget.27491","article-title":"Prolyl 4-Hydroxylase Alpha 1 Protein Expression Risk-Stratifies Early Stage Colorectal Cancer","volume":"11","author":"Tanaka","year":"2020","journal-title":"Oncotarget"}],"container-title":["Proteomes"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2227-7382\/14\/2\/16\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T04:24:42Z","timestamp":1775708682000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2227-7382\/14\/2\/16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,7]]},"references-count":147,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,6]]}},"alternative-id":["proteomes14020016"],"URL":"https:\/\/doi.org\/10.3390\/proteomes14020016","relation":{},"ISSN":["2227-7382"],"issn-type":[{"value":"2227-7382","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,7]]}}}