OpenLB
Open Library of Bioscience
Advanced Search
Mass spectrometry reviews
Apr 23, 2025;

Mass Spectrometry-Based Proteomics for Next-Generation Precision Oncology.

Kuen-Tyng Lin, Gul Muneer, Pei-Rong Huang, Ciao-Syuan Chen, Yu-Ju Chen
Author Information
  1. Kuen-Tyng Lin: Institute of Chemistry, Academia Sinica, Taipei, Taiwan. ORCID
  2. Gul Muneer: Institute of Chemistry, Academia Sinica, Taipei, Taiwan.
  3. Pei-Rong Huang: Institute of Chemistry, Academia Sinica, Taipei, Taiwan.
  4. Ciao-Syuan Chen: Institute of Chemistry, Academia Sinica, Taipei, Taiwan.
  5. Yu-Ju Chen: Institute of Chemistry, Academia Sinica, Taipei, Taiwan. ORCID
PMID: 40269546 DOI: 10.1002/mas.21932

Abstract

Cancer is the leading cause of death worldwide characterized by patient heterogeneity and complex tumor microenvironment. While the genomics-based testing has transformed modern medicine, the challenge of diverse clinical outcomes highlights unmet needs for precision oncology. As functional molecules regulating cellular processes, proteins hold great promise as biomarkers and drug targets. Mass spectrometry (MS)-based clinical proteomics has illuminated the molecular features of cancers and facilitated discovery of biomarkers or therapeutic targets, paving the way for innovative strategies that enhance the precision of personalized treatment. In this article, we introduced the tools and current achievements of MS-based proteomics, choice of discovery and targeted MS from discovery to validation phases, profiling sensitivity from bulk samples to single-cell level and tissue to liquid biopsy specimens, current regulatory landscape of MS-based protein laboratory-developed tests (LDTs). The challenges, success and future perspectives in translating research MS assay into clinical applications are also discussed. With well-designed validation studies to demonstrate clinical benefits and meet the regulatory requirements for both analytical and clinical performance, the future of MS-based assays is promising with numerous opportunities to improve cancer diagnosis, treatment, and monitoring.

Keywords

biomarker laboratory developed tests (LDTs) mass spectrometry precision oncology proteomics single‐cell proteomics

References

Ahn, B. C., K. H. Pyo, C. F. Xin, et al. 2019. “Comprehensive Analysis of the Characteristics and Treatment Outcomes of Patients With Non‐Small Cell Lung Cancer Treated With Anti‐PD‐1 Therapy in Real‐World Practice.” Journal of Cancer Research and Clinical Oncology 145, no. 6: 1613–1623. https://doi.org/10.1007/s00432-019-02899-y.
Ajani, J. A., T. A. D'Amico, D. J. Bentrem, et al. 2022. “Gastric Cancer, Version 2.2022, NCCN Clinical Practice Guidelines in Oncology.” Journal of the National Comprehensive Cancer Network 20, no. 2: 167–192. https://doi.org/10.6004/jnccn.2022.0008.
Allegretti, M., A. Fabi, S. Buglioni, et al. 2018. “Tearing down the Walls: FDA Approves Next Generation Sequencing (NGS) Assays for Actionable Cancer Genomic Aberrations.” Journal of Experimental & Clinical Cancer Research 37, no. 1: 47. https://doi.org/10.1186/s13046-018-0702-x.
Anderson, N. L. 2010. “The Clinical Plasma Proteome: A Survey of Clinical Assays for Proteins in Plasma and Serum.” Clinical Chemistry 56, no. 2: 177–185. https://doi.org/10.1373/clinchem.2009.126706.
Anderson, N. M., and M. C. Simon. 2020. “The Tumor Microenvironment.” Current Biology 30, no. 16: R921–R925. https://doi.org/10.1016/j.cub.2020.06.081.
Aoki, M., S. Iwasa, and N. Boku. 2021. “Trastuzumab Deruxtecan for the Treatment of HER2‐positive Advanced Gastric Cancer: A Clinical Perspective.” Gastric Cancer 24, no. 3: 567–576. https://doi.org/10.1007/s10120-021-01164-x.
Arun, B., F. J. Couch, J. Abraham, N. Tung, and P. A. Fasching. 2024. “BRCA‐Mutated Breast Cancer: The Unmet Need, Challenges and Therapeutic Benefits of Genetic Testing.” British Journal of Cancer 131, no. 9: 1400–1414. https://doi.org/10.1038/s41416-024-02827-z.
Avataneo, V., E. Fanelli, A. De Nicolò, et al. 2021. “A Non‐Invasive Method for Detection of Antihypertensive Drugs in Biological Fluids: The Salivary Therapeutic Drug Monitoring.” Frontiers in Pharmacology 12: 755184. https://doi.org/10.3389/fphar.2021.755184.
Baker, E., T. Liu, V. A. Petyuk, et al. 2012. “Mass Spectrometry for Translational Proteomics: Progress and Clinical Implications.” Genome Medicine 4, no. 8: 63. https://doi.org/10.1186/gm364.
Baldelli, E., E. El Gazzah, J. C. Moran, et al. 2021. “Wild‐Type KRAS Allele Effects on Druggable Targets in KRAS Mutant Lung Adenocarcinomas.” Genes 12, no. 9: 1402. https://doi.org/10.3390/genes12091402.
Banerjee, S. 2020. “Empowering Clinical Diagnostics With Mass Spectrometry.” ACS Omega 5, no. 5: 2041–2048. https://doi.org/10.1021/acsomega.9b03764.
Barros, O., V. G. D'Agostino, L. Lara Santos, R. Vitorino, and R. Ferreira. 2024. “Shaping the Future of Oral Cancer Diagnosis: Advances in Salivary Proteomics.” Expert Review of Proteomics 21, no. 4: 149–168. https://doi.org/10.1080/14789450.2024.2343585.
Beaufrère, A., S. Caruso, J. Calderaro, et al. 2022. “Gene Expression Signature as a Surrogate Marker of Microvascular Invasion on Routine Hepatocellular Carcinoma Biopsies.” Journal of Hepatology 76, no. 2: 343–352. https://doi.org/10.1016/j.jhep.2021.09.034.
Bera, K., N. Braman, A. Gupta, V. Velcheti, and A. Madabhushi. 2022. “Predicting Cancer Outcomes With Radiomics and Artificial Intelligence in Radiology.” Nature Reviews Clinical Oncology 19, no. 2: 132–146. https://doi.org/10.1038/s41571-021-00560-7.
Bhatia, H. S., A. D. Brunner, F. Öztürk, et al. 2022. “Spatial Proteomics in Three‐Dimensional Intact Specimens.” Cell 185, no. 26: 5040–5058.e19. https://doi.org/10.1016/j.cell.2022.11.021.
Binnewies, M., E. W. Roberts, K. Kersten, et al. 2018. “Understanding the Tumor Immune Microenvironment (TIME) for Effective Therapy.” Nature Medicine 24, no. 5: 541–550. https://doi.org/10.1038/s41591-018-0014-x.
Birhanu, A. G. 2023. “Mass Spectrometry‐Based Proteomics as an Emerging Tool in Clinical Laboratories.” Clinical Proteomics 20, no. 1: 32. https://doi.org/10.1186/s12014-023-09424-x.
Blume, J. E., W. C. Manning, G. Troiano, et al. 2020. “Rapid, Deep and Precise Profiling of the Plasma Proteome With Multi‐Nanoparticle Protein Corona.” Nature Communications 11, no. 1: 3662. https://doi.org/10.1038/s41467-020-17033-7.
Böttger, F., T. Radonic, I. Bahce, et al. 2024. “Identification of Protein Biomarkers for Prediction of Response to Platinum‐Based Treatment Regimens in Patients With Non‐Small Cell Lung Cancer.” Molecular Oncology 18, no. 6: 1417–1436. https://doi.org/10.1002/1878-0261.13555.
Boulanger, M., C. Mitchell, J. Zhong, and M. Hsu. 2022. “Financial Toxicity in Lung Cancer.” Frontiers in Oncology 12: 1004102. https://doi.org/10.3389/fonc.2022.1004102.
Boys, E. L., J. Liu, P. J. Robinson, and R. R. Reddel. 2023. “Clinical Applications of Mass Spectrometry‐Based Proteomics in Cancer: Where Are We?.” Proteomics 23, no. 7–8: e2200238. https://doi.org/10.1002/pmic.202200238.
Bray, F., M. Laversanne, H. Sung, et al. 2024. “Global Cancer Statistics 2022: Globocan Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries.” CA: A Cancer Journal for Clinicians 74, no. 3: 229–263. https://doi.org/10.3322/caac.21834.
Brunner, A. D., M. Thielert, C. Vasilopoulou, et al. 2022. “Ultra‐High Sensitivity Mass Spectrometry Quantifies Single‐Cell Proteome Changes Upon Perturbation.” Molecular Systems Biology 18, no. 3: e10798. https://doi.org/10.15252/msb.202110798.
Budnik, B., E. Levy, G. Harmange, and N. Slavov. 2018. “Scope‐Ms: Mass Spectrometry of Single Mammalian Cells Quantifies Proteome Heterogeneity During Cell Differentiation.” Genome Biology 19, no. 1: 161. https://doi.org/10.1186/s13059-018-1547-5.
Cai, R., Z. I. Kolabas, C. Pan, et al. 2023. “Whole‐Mouse Clearing and Imaging at the Cellular Level With vDISCO.” Nature Protocols 18, no. 4: 1197–1242. https://doi.org/10.1038/s41596-022-00788-2.
Calderaro, J., N. Ghaffari Laleh, Q. Zeng, et al. 2023. “Deep Learning‐Based Phenotyping Reclassifies Combined Hepatocellular‐Cholangiocarcinoma.” Nature Communications 14, no. 1: 8290. https://doi.org/10.1038/s41467-023-43749-3.
Chan, A., I. Prassas, A. Dimitromanolakis, et al. 2014. “Validation of Biomarkers That Complement CA19.9 in Detecting Early Pancreatic Cancer.” Clinical Cancer Research 20, no. 22: 5787–5795. https://doi.org/10.1158/1078-0432.CCR-14-0289.
Chao, Y., W. Jiang, X. Wang, et al. 2022. “Discovery of Efficacy Biomarkers for Non‐Small Cell Lung Cancer With First‐Line Anti‐PD‐1 Immunotherapy by Data‐Independent Acquisition Mass Spectrometry.” Clinical and Experimental Immunology 208, no. 1: 60–71. https://doi.org/10.1093/cei/uxac021.
Chau, T. H., A. Chernykh, R. Kawahara, and M. Thaysen‐Andersen. 2023. “Critical Considerations in N‐Glycoproteomics.” Current Opinion in Chemical Biology 73: 102272. https://doi.org/10.1016/j.cbpa.2023.102272.
Chen, Q., G. Yan, M. Gao, and X. Zhang. 2015. “Ultrasensitive Proteome Profiling for 100 Living Cells by Direct Cell Injection, Online Digestion and Nano‐LC‐MS/MS Analysis.” Analytical Chemistry 87, no. 13: 6674–6680. https://doi.org/10.1021/acs.analchem.5b00808.
Chen, X., J. Zheng, M. l. Zhuo, A. Zhang, and Z. You. 2020. “A Six‐Gene‐Based Signature for Breast Cancer Radiotherapy Sensitivity Estimation.” Bioscience Reports 40, no. 12: BSR20202376. https://doi.org/10.1042/BSR20202376.
Chen, Y. J., T. I. Roumeliotis, Y. H. Chang, et al. 2020. “Proteogenomics of Non‐Smoking Lung Cancer in East Asia Delineates Molecular Signatures of Pathogenesis and Progression.” Cell 182, no. 1: 226–244.e17. https://doi.org/10.1016/j.cell.2020.06.012.
Chu, H. W., K. P. Chang, C. W. Hsu, et al. 2019. “Identification of Salivary Biomarkers for Oral Cancer Detection With Untargeted and Targeted Quantitative Proteomics Approaches.” Molecular & Cellular Proteomics 18, no. 9: 1796–1806. https://doi.org/10.1074/mcp.RA119.001530.
Clair, G., P. D. Piehowski, T. Nicola, et al. 2016. “Spatially‐Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples.” Scientific Reports 6: 39223. https://doi.org/10.1038/srep39223.
Clark, D. J., S. M. Dhanasekaran, F. Petralia, et al. 2019. “Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.” Cell 179, no. 4: 964–983.e31. https://doi.org/10.1016/j.cell.2019.10.007.
Cominetti, O., A. Núñez Galindo, J. Corthésy, et al. 2016. “Proteomic Biomarker Discovery in 1000 Human Plasma Samples With Mass Spectrometry.” Journal of Proteome Research 15, no. 2: 389–399. https://doi.org/10.1021/acs.jproteome.5b00901.
Cong, Y., Y. Liang, K. Motamedchaboki, et al. 2020. “Improved Single‐Cell Proteome Coverage Using Narrow‐Bore Packed NanoLC Columns and Ultrasensitive Mass Spectrometry.” Analytical Chemistry 92, no. 3: 2665–2671. https://doi.org/10.1021/acs.analchem.9b04631.
Cong, Y., K. Motamedchaboki, S. A. Misal, et al. 2021. “Ultrasensitive Single‐Cell Proteomics Workflow Identifies > 1000 Protein Groups Per Mammalian Cell.” Chemical Science 12, no. 3: 1001–1006. https://doi.org/10.1039/d0sc03636f.
Conroy, T., P. Pfeiffer, V. Vilgrain, et al. 2023. “Pancreatic Cancer: Esmo Clinical Practice Guideline for Diagnosis, Treatment and Follow‐Up.” Annals of Oncology 34, no. 11: 987–1002. https://doi.org/10.1016/j.annonc.2023.08.009.
Correia, L., R. Magno, J. M. Xavier, et al. 2022. “Allelic Expression Imbalance of PIK3CA Mutations is Frequent in Breast Cancer and Prognostically Significant.” NPJ Breast Cancer 8, no. 1: 71. https://doi.org/10.1038/s41523-022-00435-9.
Coscia, F., S. Doll, J. M. Bech, et al. 2020. “A Streamlined Mass Spectrometry‐Based Proteomics Workflow for Large‐Scale FFPE Tissue Analysis.” Journal of Pathology 251, no. 1: 100–112. https://doi.org/10.1002/path.5420.
Cox, J. 2023. “Prediction of Peptide Mass Spectral Libraries With Machine Learning.” Nature Biotechnology 41, no. 1: 33–43. https://doi.org/10.1038/s41587-022-01424-w.
Croner, R. S., C. I. Geppert, F. G. Bader, et al. 2014. “Molecular Staging of Lymph Node‐Negative Colon Carcinomas by One‐Step Nucleic Acid Amplification (OSNA) Results in Upstaging of a Quarter of Patients in a Prospective, European, Multicentre Study.” British Journal of Cancer 110, no. 10: 2544–2550. https://doi.org/10.1038/bjc.2014.170.
Ctortecka, C., N. M. Clark, B. W. Boyle, et al. 2024. “Automated Single‐Cell Proteomics Providing Sufficient Proteome Depth to Study Complex Biology Beyond Cell Type Classifications.” Nature Communications 15, no. 1: 5707. https://doi.org/10.1038/s41467-024-49651-w.
Ctortecka, C., D. Hartlmayr, A. Seth, et al. 2023. “An Automated Nanowell‐Array Workflow for Quantitative Multiplexed Single‐Cell Proteomics Sample Preparation at High Sensitivity.” Molecular & Cellular Proteomics 22, no. 12: 100665. https://doi.org/10.1016/j.mcpro.2023.100665.
Dapic, I., N. Uwugiaren, P. J. Jansen, and G. L. Corthals. 2017. “Fast and Simple Protocols for Mass Spectrometry‐Based Proteomics of Small Fresh Frozen Uterine Tissue Sections.” Analytical Chemistry 89, no. 20: 10769–10775. https://doi.org/10.1021/acs.analchem.7b01937.
Davis, S., C. Scott, O. Ansorge, and R. Fischer. 2019. “Development of a Sensitive, Scalable Method for Spatial, Cell‐Type‐Resolved Proteomics of the Human Brain.” Journal of Proteome Research 18, no. 4: 1787–1795. https://doi.org/10.1021/acs.jproteome.8b00981.
Davis‐Marcisak, E. F., A. Deshpande, G. L. Stein‐O'Brien, et al. 2021. “From Bench to Bedside: Single‐Cell Analysis for Cancer Immunotherapy.” Cancer Cell 39, no. 8: 1062–1080. https://doi.org/10.1016/j.ccell.2021.07.004.
DeMarco, M. L., Q. Nguyen, A. Fok, G. R. Hsiung, and J. G. van der Gugten. 2020. “An Automated Clinical Mass Spectrometric Method for Identification and Quantification of Variant and Wild‐Type amyloid‐β 1‐40 and 1‐42 Peptides in CSF.” Alzheimer's & Dementia (Amsterdam, Netherlands) 12, no. 1: 12036. https://doi.org/10.1002/dad2.12036.
Doerr, A. 2013. “Mass Spectrometry‐Based Targeted Proteomics.” Nature Methods 10, no. 1: 23. https://doi.org/10.1038/nmeth.2286.
Doll, S., F. Gnad, and M. Mann. 2019. “The Case for Proteomics and Phospho‐Proteomics in Personalized Cancer Medicine.” PROTEOMICS – Clinical Applications 13, no. 2: e1800113. https://doi.org/10.1002/prca.201800113.
Dou, Y., E. A. Kawaler, D. Cui Zhou, et al. 2020. “Proteogenomic Characterization of Endometrial Carcinoma.” Cell 180, no. 4: 729–748.e26. https://doi.org/10.1016/j.cell.2020.01.026.
Dunn, B., P. Stein, and P. Cavazzoni. 2021. “Approval of Aducanumab for Alzheimer Disease‐The FDA's Perspective.” JAMA Internal Medicine 181, no. 10: 1276–1278. https://doi.org/10.1001/jamainternmed.2021.4607.
Eberhard, C. D., and B. C. Orsburn. 2024. “A Multiplexed Single‐Cell Proteomic Workflow Applicable to Drug Treatment Studies.” Methods in Molecular Biology 2823: 1–10. https://doi.org/10.1007/978-1-0716-3922-1_1.
Edsjö, A., D. Gisselsson, J. Staaf, et al. 2024. “Current and Emerging Sequencing‐Based Tools for Precision Cancer Medicine.” Molecular Aspects of Medicine 96: 101250. https://doi.org/10.1016/j.mam.2024.101250.
Erstad, D. J., and K. K. Tanabe. 2019. “Prognostic and Therapeutic Implications of Microvascular Invasion in Hepatocellular Carcinoma.” Annals of Surgical Oncology 26, no. 5: 1474–1493. https://doi.org/10.1245/s10434-019-07227-9.
Ettinger, D. S., D. E. Wood, D. L. Aisner, et al. 2022. “Non‐Small Cell Lung Cancer, Version 3.2022, NCCN Clinical Practice Guidelines in Oncology.” Journal of the National Comprehensive Cancer Network 20, no. 5: 497–530. https://doi.org/10.6004/jnccn.2022.0025.
Food & Drug Administration, H. H. S. 2004. “Medical Devices; Clinical Chemistry and Clinical Toxicology Devices; Classification of Newborn Screening Test Systems for Amino Acids, Free Carnitine, and Acylcarnitines Using Tandem Mass Spectrometry.” Final Rule. Fed Regist 69, no. 226: 68254–68255. https://www.ncbi.nlm.nih.gov/pubmed/15562554.
Fredolini, C., K. V. Pathak, L. Paris, et al. 2020. “Shotgun Proteomics Coupled to Nanoparticle‐Based Biomarker Enrichment Reveals a Novel Panel of Extracellular Matrix Proteins as Candidate Serum Protein Biomarkers for Early‐Stage Breast Cancer Detection.” Breast Cancer Research: BCR 22, no. 1: 135. https://doi.org/10.1186/s13058-020-01373-9.
Freitag, C. E., P. Mei, L. Wei, A. V. Parwani, and Z. Li. 2020. “Genetic Alterations and Their Association With Clinicopathologic Characteristics in Advanced Breast Carcinomas: Focusing on Clinically Actionable Genetic Alterations.” Human Pathology 102: 94–103. https://doi.org/10.1016/j.humpath.2020.05.005.
Fung, E. T. 2010. “A Recipe for Proteomics Diagnostic Test Development: The OVA1 Test, From Biomarker Discovery to FDA Clearance.” Clinical Chemistry 56, no. 2: 327–329. https://doi.org/10.1373/clinchem.2009.140855.
Füzéry, A. K., J. Levin, M. M. Chan, and D. W. Chan. 2013. “Translation of Proteomic Biomarkers Into FDA Approved Cancer Diagnostics: Issues and Challenges.” Clinical Proteomics 10, no. 1: 13. https://doi.org/10.1186/1559-0275-10-13.
Gao, L., Y. Lin, P. Yue, et al. 2023. “Identification of a Novel Bile Marker Clusterin and a Public Online Prediction Platform Based on Deep Learning for Cholangiocarcinoma.” BMC Medicine 21, no. 1: 294. https://doi.org/10.1186/s12916-023-02990-9.
Gao, Q., H. Zhu, L. Dong, et al. 2019. “Integrated Proteogenomic Characterization of HBV‐Related Hepatocellular Carcinoma.” Cell 179, no. 2: 561–577.e22. https://doi.org/10.1016/j.cell.2019.08.052.
Gao, Y., J. Wang, Y. Zhou, S. Sheng, S. Y. Qian, and X. Huo. 2018. “Evaluation of Serum CEA, CA19‐9, CA72‐4, CA125 and Ferritin as Diagnostic Markers and Factors of Clinical Parameters for Colorectal Cancer.” Scientific Reports 8, no. 1: 2732. https://doi.org/10.1038/s41598-018-21048-y.
Gebreyesus, S. T., G. Muneer, C. C. Huang, et al. 2023. “Recent Advances in Microfluidics for Single‐Cell Functional Proteomics.” Lab on a Chip 23, no. 7: 1726–1751. https://doi.org/10.1039/d2lc01096h.
Gebreyesus, S. T., A. A. Siyal, R. B. Kitata, et al. 2022. “Streamlined Single‐Cell Proteomics by an Integrated Microfluidic Chip and Data‐Independent Acquisition Mass Spectrometry.” Nature Communications 13, no. 1: 37. https://doi.org/10.1038/s41467-021-27778-4.
Geffen, Y., S. Anand, Y. Akiyama, et al. 2023. “Pan‐Cancer Analysis of Post‐Translational Modifications Reveals Shared Patterns of Protein Regulation.” Cell 186, no. 18: 3945–3967. https://doi.org/10.1016/j.cell.2023.07.013.
Geyer, P. E., L. M. Holdt, D. Teupser, and M. Mann. 2017. “Revisiting Biomarker Discovery by Plasma Proteomics.” Molecular Systems Biology 13, no. 9: 942. https://doi.org/10.15252/msb.20156297.
Gillette, M. A., S. Satpathy, S. Cao, et al. 2020. “Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.” Cell 182, no. 1: 200–225.e35. https://doi.org/10.1016/j.cell.2020.06.013.
Ginsberg, R. J., and L. V. Rubinstein. 1995. “Randomized Trial of Lobectomy Versus Limited Resection for T1 N0 Non‐Small Cell Lung Cancer.” The Annals of Thoracic Surgery 60, no. 3: 615–622. https://doi.org/10.1016/0003-4975(95)00537-u.
Glasson, Y., L. A. Chépeaux, A. S. Dumé, et al. 2023. “Single‐Cell High‐Dimensional Imaging Mass Cytometry: One Step Beyond in Oncology.” Seminars in Immunopathology 45, no. 1: 17–28. https://doi.org/10.1007/s00281-022-00978-w.
Gray, S. W., B. Kim, L. Sholl, et al. 2017. “Medical Oncologists' Experiences in Using Genomic Testing for Lung and Colorectal Cancer Care.” Journal of Oncology Practice 13, no. 3: e185–e196. https://doi.org/10.1200/JOP.2016.016659.
Griesser, E., H. Wyatt, S. Ten Have, B. Stierstorfer, M. Lenter, and A. I. Lamond. 2020. “Quantitative Profiling of the Human Substantia Nigra Proteome From Laser‐Capture Microdissected FFPE Tissue.” Molecular & Cellular Proteomics 19, no. 5: 839–851. https://doi.org/10.1074/mcp.RA119.001889.
Gupta, A. R., G. A. Woodard, D. M. Jablons, M. J. Mann, and J. R. Kratz. 2021. “Improved Outcomes and Staging in Non‐Small‐Cell Lung Cancer Guided by a Molecular Assay.” Future Oncology 17, no. 34: 4785–4795. https://doi.org/10.2217/fon-2021-0517.
Gupta, K. K., V. K. Gupta, and R. W. Naumann. 2019. “Ovarian Cancer: Screening and Future Directions.” International Journal of Gynecological Cancer 29, no. 1: 195–200. https://doi.org/10.1136/ijgc-2018-000016.
Guzman, U. H., A. Martinez‐Val, Z. Ye, et al. 2024. “Ultra‐Fast Label‐Free Quantification and Comprehensive Proteome Coverage With Narrow‐Window Data‐Independent Acquisition.” Nature Biotechnology 42: 1855–1866. https://doi.org/10.1038/s41587-023-02099-7.
Haga, Y., Y. Minegishi, and K. Ueda. 2023. “Frontiers in Mass Spectrometry‐Based Clinical Proteomics for Cancer Diagnosis and Treatment.” Cancer Science 114, no. 5: 1783–1791. https://doi.org/10.1111/cas.15731.
Hamza, G. M., R. Raghunathan, S. Ashenden, B. Zhang, E. Miele, and A. F. Jarnuczak. 2024. “Proteomics of Prostate Cancer Serum and Plasma Using Low and High Throughput Approaches.” Clinical Proteomics 21, no. 1: 21. https://doi.org/10.1186/s12014-024-09461-0.
Han, C. L., C. T. Lai, A. J. Reyes, et al. 2024. “Lessons Learned: Establishing a CLIA‐Equivalent Laboratory for Targeted Mass Spectrometry Assays—Navigating the Transition From Research to Clinical Practice.” Clinical Proteomics 21, no. 1: 12. https://doi.org/10.1186/s12014-024-09455-y.
Han, S., X. Liu, S. Ju, et al. 2023. “New Mechanisms and Biomarkers of Lymph Node Metastasis in Cervical Cancer: Reflections From Plasma Proteomics.” Clinical Proteomics 20, no. 1: 35. https://doi.org/10.1186/s12014-023-09427-8.
Hartl, J., F. Kurth, K. Kappert, et al. 2023. “Quantitative Protein Biomarker Panels: A Path to Improved Clinical Practice Through Proteomics.” EMBO Molecular Medicine 15, no. 4: e16061. https://doi.org/10.15252/emmm.202216061.
He, F., R. Aebersold, M. S. Baker, et al. 2024. “π‐HuB: The Proteomic Navigator of the Human Body.” Nature 636, no. 8042: 322–331. https://doi.org/10.1038/s41586-024-08280-5.
He, X., X. Liu, F. Zuo, H. Shi, and J. Jing. 2023. “Artificial Intelligence‐Based Multi‐Omics Analysis Fuels Cancer Precision Medicine.” Seminars in Cancer Biology 88: 187–200. https://doi.org/10.1016/j.semcancer.2022.12.009.
He, Y., A. Mohamedali, C. Huang, M. S. Baker, and E. C. Nice. 2019. “Oncoproteomics: Current Status and Future Opportunities.” Clinica Chimica Acta 495: 611–624. https://doi.org/10.1016/j.cca.2019.06.006.
Hernandez‐Valladares, M., Ø. Bruserud, and F. Selheim. 2020. “The Implementation of Mass Spectrometry‐Based Proteomics Workflows in Clinical Routines of Acute Myeloid Leukemia: Applicability and Perspectives.” International Journal of Molecular Sciences 21, no. 18: 6830. https://doi.org/10.3390/ijms21186830.
Hoofnagle, A. N., and M. Y. Roth. 2013. “Improving the Measurement of Serum Thyroglobulin With Mass Spectrometry.” Journal of Clinical Endocrinology & Metabolism 98, no. 4: 1343–1352. https://doi.org/10.1210/jc.2012-4172.
Horak, P., and S. Fröhling. 2024. “Measuring Progress in Precision Oncology.” Cancer Discovery 14, no. 1: 18–19. https://doi.org/10.1158/2159-8290.CD-23-1237.
Huang, J., D. E. Lucero‐Prisno, 3rd, L. Zhang, et al. 2023. “Updated Epidemiology of Gastrointestinal Cancers in East Asia.” Nature Reviews Gastroenterology & Hepatology 20, no. 5: 271–287. https://doi.org/10.1038/s41575-022-00726-3.
Huang, P., Q. Kong, W. Gao, et al. 2020. “Spatial Proteome Profiling by Immunohistochemistry‐Based Laser Capture Microdissection and Data‐Independent Acquisition Proteomics.” Analytica Chimica Acta 1127: 140–148. https://doi.org/10.1016/j.aca.2020.06.049.
Huffman, R. G., A. Leduc, C. Wichmann, et al. 2023. “Prioritized Mass Spectrometry Increases the Depth, Sensitivity and Data Completeness of Single‐Cell Proteomics.” Nature Methods 20, no. 5: 714–722. https://doi.org/10.1038/s41592-023-01830-1.
Hughes, C. S., S. Foehr, D. A. Garfield, E. E. Furlong, L. M. Steinmetz, and J. Krijgsveld. 2014. “Ultrasensitive Proteome Analysis Using Paramagnetic Bead Technology.” Molecular Systems Biology 10, no. 10: 757. https://doi.org/10.15252/msb.20145625.
Hüttenhain, R., M. Choi, L. Martin de la Fuente, et al. 2019. “A Targeted Mass Spectrometry Strategy for Developing Proteomic Biomarkers: A Case Study of Epithelial Ovarian Cancer.” Molecular & Cellular Proteomics 18, no. 9: 1836–1850. https://doi.org/10.1074/mcp.RA118.001221.
Iyer, P., M. Moslim, J. M. Farma, and C. S. Denlinger. 2020. “Diffuse Gastric Cancer: Histologic, Molecular, and Genetic Basis of Disease.” Translational Gastroenterology and Hepatology 5: 52. https://doi.org/10.21037/tgh.2020.01.02.
Jia, B., X. Zhao, D. Wu, et al. 2021. “Identification of Serum Biomarkers to Predict Pemetrexed/Platinum Chemotherapy Efficacy for Advanced Lung Adenocarcinoma Patients by Data‐Independent Acquisition (DIA) Mass Spectrometry Analysis With Parallel Reaction Monitoring (PRM) Verification.” Translational Lung Cancer Research 10, no. 2: 981–994. https://doi.org/10.21037/tlcr-21-153.
Jiang, X., H. Zhao, O. L. Saldanha, et al. 2023. “An MRI Deep Learning Model Predicts Outcome in Rectal Cancer.” Radiology 307, no. 5: e222223. https://doi.org/10.1148/radiol.222223.
Jiang, Y., K. Zhou, Z. Sun, et al. 2023. “Non‐Invasive Tumor Microenvironment Evaluation and Treatment Response Prediction in Gastric Cancer Using Deep Learning Radiomics.” Cell reports. Medicine 4, no. 8: 101146. https://doi.org/10.1016/j.xcrm.2023.101146.
Jie, G. L., L. X. Peng, M. M. Zheng, et al. 2023. “Longitudinal Plasma Proteomics‐Derived Biomarkers Predict Response to MET Inhibitors for MET‐Dysregulated NSCLC.” Cancers 15, no. 1: 302. https://doi.org/10.3390/cancers15010302.
Joshi, S. K., P. Piehowski, T. Liu, et al. 2024. “Mass Spectrometry‐Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine.” Annual Review of Pharmacology and Toxicology 64: 455–479. https://doi.org/10.1146/annurev-pharmtox-022723-113921.
Kaur, G., A. Poljak, S. A. Ali, L. Zhong, M. J. Raftery, and P. Sachdev. 2021. “Extending the Depth of Human Plasma Proteome Coverage Using Simple Fractionation Techniques.” Journal of Proteome Research 20, no. 2: 1261–1279. https://doi.org/10.1021/acs.jproteome.0c00670.
Kennedy, J. J., J. R. Whiteaker, R. G. Ivey, et al. 2022. “Internal Standard Triggered‐Parallel Reaction Monitoring Mass Spectrometry Enables Multiplexed Quantification of Candidate Biomarkers in Plasma.” Analytical Chemistry 94, no. 27: 9540–9547. https://doi.org/10.1021/acs.analchem.1c04382.
Keyl, P., M. Bockmayr, D. Heim, et al. 2022. “Patient‐Level Proteomic Network Prediction by Explainable Artificial Intelligence.” NPJ Precision Oncology 6, no. 1: 35. https://doi.org/10.1038/s41698-022-00278-4.
Khurshid, Z., M. S. Zafar, R. S. Khan, S. Najeeb, P. D. Slowey, and I. U. Rehman. 2018. “Role of Salivary Biomarkers in Oral Cancer Detection.” Advances in Clinical Chemistry 86: 23–70. https://doi.org/10.1016/bs.acc.2018.05.002.
Kim, J., S.‐H. Park, and H. Lee. 2024. “PANCDR: Precise Medicine Prediction Using an Adversarial Network for Cancer Drug Response.” Briefings in Bioinformatics 25, no. 2: bbae088. https://doi.org/10.1093/bib/bbae088.
Kim, Y., U. B. Kang, S. Kim, et al. 2019. “A Validation Study of a Multiple Reaction Monitoring‐Based Proteomic Assay to Diagnose Breast Cancer.” Journal of Breast Cancer 22, no. 4: 579–586. https://doi.org/10.4048/jbc.2019.22.e57.
Kim, Y., I. Yeo, I. Huh, et al. 2021. “Development and Multiple Validation of the Protein Multi‐Marker Panel for Diagnosis of Pancreatic Cancer.” Clinical Cancer Research 27, no. 8: 2236–2245. https://doi.org/10.1158/1078-0432.CCR-20-3929.
Krug, K., E. J. Jaehnig, S. Satpathy, et al. 2020. “Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy.” Cell 183, no. 5: 1436–1456.e31. https://doi.org/10.1016/j.cell.2020.10.036.
Kubiniok, P., B. T. Finicle, F. Piffaretti, et al. 2019. “Dynamic Phosphoproteomics Uncovers Signaling Pathways Modulated by Anti‐Oncogenic Sphingolipid Analogs.” Molecular & Cellular Proteomics 18, no. 3: 408–422. https://doi.org/10.1074/mcp.RA118.001053.
Kulak, N. A., G. Pichler, I. Paron, N. Nagaraj, and M. Mann. 2014. “Minimal, Encapsulated Proteomic‐Sample Processing Applied to Copy‐Number Estimation in Eukaryotic Cells.” Nature Methods 11, no. 3: 319–324. https://doi.org/10.1038/nmeth.2834.
Kumar, V., S. Ray, S. Ghantasala, and S. Srivastava. 2020. “An Integrated Quantitative Proteomics Workflow for Cancer Biomarker Discovery and Validation in Plasma.” Frontiers in Oncology 10: 543997. https://doi.org/10.3389/fonc.2020.543997.
Kurian, M., J. J. Adashek, and H. J. West. 2024. “Cancer Care in the Era of Artificial Intelligence.” JAMA Oncology 10, no. 5: 683. https://doi.org/10.1001/jamaoncol.2023.7263.
Kwon, Y., P. D. Piehowski, R. Zhao, et al. 2022. “Hanging Drop Sample Preparation Improves Sensitivity of Spatial Proteomics.” Lab on a Chip 22, no. 15: 2869–2877. https://doi.org/10.1039/d2lc00384h.
Kwon, Y., J. Woo, F. Yu, et al. 2024. “Proteome‐Scale Tissue Mapping Using Mass Spectrometry Based on Label‐Free and Multiplexed Workflows.” Molecular & Cellular Proteomics 23, no. 11: 100841. https://doi.org/10.1016/j.mcpro.2024.100841.
Lathrop, J. T., D. A. Jeffery, Y. R. Shea, P. F. Scholl, and M. M. Chan. 2016. “US Food and Drug Administration Perspectives on Clinical Mass Spectrometry.” Clinical Chemistry 62, no. 1: 41–47. https://doi.org/10.1373/clinchem.2015.244731.
Lattmann, E., L. Räss, M. Tognetti, et al. 2024. “Size‐Exclusion Chromatography Combined With DIA‐MS Enables Deep Proteome Profiling of Extracellular Vesicles From Melanoma Plasma and Serum.” Cellular and Molecular Life Sciences 81, no. 1: 90. https://doi.org/10.1007/s00018-024-05137-y.
Leal, T. A., A. C. Argento, K. Bhadra, et al. 2020. “Prognostic Performance of Proteomic Testing in Advanced Non‐Small Cell Lung Cancer: A Systematic Literature Review and Meta‐Analysis.” Current Medical Research and Opinion 36, no. 9: 1497–1505. https://doi.org/10.1080/03007995.2020.1790346.
Leduc, A., L. Khoury, J. Cantlon, S. Khan, and N. Slavov. 2024. “Massively Parallel Sample Preparation for Multiplexed Single‐Cell Proteomics Using nPOP.” Nature Protocols 19, no. 12: 3750–3776. https://doi.org/10.1038/s41596-024-01033-8.
Lee, J. Y., and N. Kim. 2015. “Diagnosis of Helicobacter Pylori by Invasive Test: Histology.” Annals of Translational Medicine 3, no. 1: 10. https://doi.org/10.3978/j.issn.2305-5839.2014.11.03.
Lee, M. S., and S. Pant. 2021. “Personalizing Medicine With Germline and Somatic Sequencing in Advanced Pancreatic Cancer: Current Treatments and Novel Opportunities.” American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting 41: 1–13. https://doi.org/10.1200/EDBK_321255.
Leipert, J., and A. Tholey. 2019. “Miniaturized Sample Preparation on a Digital Microfluidics Device for Sensitive Bottom‐Up Microproteomics of Mammalian Cells Using Magnetic Beads and Mass Spectrometry‐Compatible Surfactants.” Lab on a Chip 19, no. 20: 3490–3498. https://doi.org/10.1039/c9lc00715f.
Lengfeld, J., H. Zhang, S. Stoesz, et al. 2021. “Challenges in Detection of Serum Oncoprotein: Relevance to Breast Cancer Diagnostics.” Breast Cancer (Dove Medical Press) 13: 575–593. https://doi.org/10.2147/BCTT.S331844.
Li, J., M. Che, B. Zhang, K. Zhao, C. Wan, and K. Yang. 2023. “The Association Between the Neuroendocrine System and the Tumor Immune Microenvironment: Emerging Directions for Cancer Immunotherapy.” Biochimica et Biophysica Acta, Reviews on Cancer 1878, no. 6: 189007. https://doi.org/10.1016/j.bbcan.2023.189007.
Li, J., L. S. Smith, and H. J. Zhu. 2021. “Data‐Independent Acquisition (DIA): An Emerging Proteomics Technology for Analysis of Drug‐Metabolizing Enzymes and Transporters.” Drug Discovery Today: Technologies 39: 49–56. https://doi.org/10.1016/j.ddtec.2021.06.006.
Li, L., L. Bai, H. Lin, et al. 2021. “Multiomics Analysis of Tumor Mutational Burden Across Cancer Types.” Computational and Structural Biotechnology Journal 19: 5637–5646. https://doi.org/10.1016/j.csbj.2021.10.013.
Li, N., J. Huang, S. He, et al. 2024. “The Development of a Novel Zeolite‐Based Assay for Efficient and Deep Plasma Proteomic Profiling.” Journal of Nanobiotechnology 22, no. 1: 164. https://doi.org/10.1186/s12951-024-02404-9.
Li, P., J. Chen, Y. Chen, et al. 2023. “Construction of Exosome SORL1 Detection Platform Based on 3D Porous Microfluidic Chip and Its Application in Early Diagnosis of Colorectal Cancer.” Small 19, no. 20: e2207381. https://doi.org/10.1002/smll.202207381.
Li, S., Y. Qu, L. Liu, et al. 2023. “Comparative Proteomic Profiling of Plasma Exosomes in Lung Cancer Cases of Liver and Brain Metastasis.” Cell & Bioscience 13, no. 1: 180. https://doi.org/10.1186/s13578-023-01112-5.
Li, W., F. Li, X. Zhang, H. K. Lin, and C. Xu. 2021. “Insights into the Post‐Translational Modification and Its Emerging Role in Shaping the Tumor Microenvironment.” Signal Transduction and Targeted Therapy 6, no. 1: 422. https://doi.org/10.1038/s41392-021-00825-8.
Li, Y., B. Wang, F. Ma, et al. 2023. “Proteomic Characterization of the Colorectal Cancer Response to Chemoradiation and Targeted Therapies Reveals Potential Therapeutic Strategies.” Cell Rep Med 4, no. 12: 101311. https://doi.org/10.1016/j.xcrm.2023.101311.
Li, Z. Y., M. Huang, X. K. Wang, et al. 2018. “Nanoliter‐Scale Oil‐Air‐Droplet Chip‐Based Single Cell Proteomic Analysis.” Analytical Chemistry 90, no. 8: 5430–5438. https://doi.org/10.1021/acs.analchem.8b00661.
Liang, T., L. M. Leung, B. Opene, et al. 2019. “Rapid Microbial Identification and Antibiotic Resistance Detection by Mass Spectrometric Analysis of Membrane Lipids.” Analytical Chemistry 91, no. 2: 1286–1294. https://doi.org/10.1021/acs.analchem.8b02611.
Liberto, J. M., S. Y. Chen, I. M. Shih, T. H. Wang, T. L. Wang, and T. R. Pisanic, 2nd. 2022. “Current and Emerging Methods for Ovarian Cancer Screening and Diagnostics: A Comprehensive Review.” Cancers 14, no. 12: 2885. https://doi.org/10.3390/cancers14122885.
Lin, A., H. Zhang, H. Meng, et al. 2021. “TNF‐Alpha Pathway Alternation Predicts Survival of Immune Checkpoint Inhibitors in Non‐Small Cell Lung Cancer.” Frontiers in Immunology 12: 667875. https://doi.org/10.3389/fimmu.2021.667875.
Lin, Y., and S. N. Thomas. 2023. “Impact of Valid Act Implementation on Mass Spectrometry‐Based Clinical Proteomic Laboratory Developed Tests.” Journal of Mass Spectrometry and Advances in the Clinical Lab 28: 30–34. https://doi.org/10.1016/j.jmsacl.2023.02.001.
Liu, L., L. Liu, Y. Wang, et al. 2024. “Robust Glycoproteomics Platform Reveals a Tetra‐Antennary Site‐Specific Glycan Capping With Sialyl‐Lewis Antigen for Early Detection of Gastric Cancer.” Advanced Science (Weinheim, Baden‐Wurttemberg, Germany) 11, no. 9: e2306955. https://doi.org/10.1002/advs.202306955.
Liu, R., X. Zhao, W. Guo, et al. 2020. “Dynamic Monitoring of HER2 Amplification In Circulating DNA of Patients With Metastatic Colorectal Cancer Treated With Cetuximab.” Clinical & Translational Oncology: Official Publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico 22, no. 6: 928–934. https://doi.org/10.1007/s12094-019-02215-7.
Liu, W., L. Xie, Y. H. He, et al. 2021. “Large‐Scale and High‐Resolution Mass Spectrometry‐Based Proteomics Profiling Defines Molecular Subtypes of Esophageal Cancer for Therapeutic Targeting.” Nature Communications 12, no. 1: 4961. https://doi.org/10.1038/s41467-021-25202-5.
Liu, Y., A. Elmas, and K.‐l. Huang. 2025. “Mutation Impact on mRNA Versus Protein Expression Across Human Cancers.” GigaScience 14: giae113. https://doi.org/10.1093/gigascience/giae113.
Liu, Z., H. Huang, J. Ren, et al. 2024. “Plasma Exosomes Contain Protein Biomarkers Valuable for the Diagnosis of Lung Cancer.” Discover Oncology 15, no. 1: 194. https://doi.org/10.1007/s12672-024-01022-z.
Llovet, J. M., R. K. Kelley, A. Villanueva, et al. 2021. “Hepatocellular Carcinoma.” Nature Reviews Disease Primers 7, no. 1: 6. https://doi.org/10.1038/s41572-020-00240-3.
Lobo, M. D. P., F. B. M. B. Moreno, G. H. M. F. Souza, S. M. M. L. Verde, R. A. Moreira, and A. C. O. Monteiro‐Moreira. 2017. “Label‐Free Proteome Analysis of Plasma Fom Patients With Breast Cancer: Stage‐Specific Protein Expression.” Frontiers in Oncology 7: 14. https://doi.org/10.3389/fonc.2017.00014.
Lombard‐Banek, C., S. A. Moody, and P. Nemes. 2016. “Single‐Cell Mass Spectrometry for Discovery Proteomics: Quantifying Translational Cell Heterogeneity in the 16‐Cell Frog (Xenopus) Embryo.” Angewandte Chemie International Edition 55, no. 7: 2454–2458. https://doi.org/10.1002/anie.201510411.
Longuespée, R., D. Alberts, C. Pottier, et al. 2016. “A Laser Microdissection‐Based Workflow for FFPE Tissue Microproteomics: Important Considerations for Small Sample Processing.” Methods 104: 154–162. https://doi.org/10.1016/j.ymeth.2015.12.008.
Luchini, C., A. Pea, and A. Scarpa. 2022. “Artificial Intelligence in Oncology: Current Applications and Future Perspectives.” British Journal of Cancer 126, no. 1: 4–9. https://doi.org/10.1038/s41416-021-01633-1.
Ma, C., Y. Li, J. Li, et al. 2023. “Comprehensive and Deep Profiling of the Plasma Proteome With Protein Corona on Zeolite Nay.” Journal of Pharmaceutical Analysis 13, no. 5: 503–513. https://doi.org/10.1016/j.jpha.2023.04.002.
Ma, L., H. Guo, Y. Zhao, et al. 2024. “Liquid Biopsy in Cancer Current: Status, Challenges and Future Prospects.” Signal Transduction and Targeted Therapy 9, no. 1: 336. https://doi.org/10.1038/s41392-024-02021-w.
Makhmut, A., D. Qin, S. Fritzsche, J. Nimo, J. König, and F. Coscia. 2023. “A Framework for Ultra‐Low‐Input Spatial Tissue Proteomics.” Cell Systems 14, no. 11: 1002–1014.e5. https://doi.org/10.1016/j.cels.2023.10.003.
Malone, E. R., M. Oliva, P. J. B. Sabatini, T. L. Stockley, and L. L. Siu. 2020. “Molecular Profiling for Precision Cancer Therapies.” Genome Medicine 12, no. 1: 8. https://doi.org/10.1186/s13073-019-0703-1.
Man, J., J. Millican, A. Mulvey, V. Gebski, and R. Hui. 2021. “Response Rate and Survival at Key Timepoints With PD‐1 Blockade vs Chemotherapy in PD‐L1 Subgroups: Meta‐Analysis of Metastatic NSCLC Trials.” JNCI Cancer Spectrum 5, no. 3: pkab012. https://doi.org/10.1093/jncics/pkab012.
Mann, M., C. Kumar, W. F. Zeng, and M. T. Strauss. 2021. “Artificial Intelligence for Proteomics and Biomarker Discovery.” Cell Systems 12, no. 8: 759–770. https://doi.org/10.1016/j.cels.2021.06.006.
Mansuri, M. S., K. Williams, and A. C. Nairn. 2023. “Uncovering Biology by Single‐Cell Proteomics.” Communications Biology 6, no. 1: 381. https://doi.org/10.1038/s42003-023-04635-2.
Mariam, A., S. Kamath, K. Schveder, H. L. McLeod, and D. M. Rotroff. 2023. “Biomarkers for Response to Anti‐PD‐1/Anti‐PD‐L1 Immune Checkpoint Inhibitors: A Large Meta‐Analysis.” Oncology (Williston Park, N.Y.) 37, no. 5: 210–219. https://doi.org/10.46883/2023.25920995.
Martínez‐Val, A., K. Fort, C. Koenig, et al. 2023. “Hybrid‐Dia: Intelligent Data Acquisition Integrates Targeted and Discovery Proteomics to Analyze Phospho‐Signaling In Single Spheroids.” Nature Communications 14, no. 1: 3599. https://doi.org/10.1038/s41467-023-39347-y.
Matzinger, M., E. Müller, G. Dürnberger, P. Pichler, and K. Mechtler. 2023. “Robust and Easy‐to‐Use One‐Pot Workflow for Label‐Free Single‐Cell Proteomics.” Analytical Chemistry 95, no. 9: 4435–4445. https://doi.org/10.1021/acs.analchem.2c05022.
McGrail, D. J., P. G. Pilié, N. U. Rashid, et al. 2021. “High Tumor Mutation Burden Fails to Predict Immune Checkpoint Blockade Response Across All Cancer Types.” Annals of Oncology 32, no. 5: 661–672. https://doi.org/10.1016/j.annonc.2021.02.006.
Megger, D. A., T. Bracht, H. E. Meyer, and B. Sitek. 2013. “Label‐Free Quantification in Clinical Proteomics.” Biochimica et Biophysica Acta (BBA) ‐ Proteins and Proteomics 1834, no. 8: 1581–1590. https://doi.org/10.1016/j.bbapap.2013.04.001.
Meissner, F., J. Geddes‐McAlister, M. Mann, and M. Bantscheff. 2022. “The Emerging Role of Mass Spectrometry‐Based Proteomics in Drug Discovery.” Nature Reviews Drug Discovery 21, no. 9: 637–654. https://doi.org/10.1038/s41573-022-00409-3.
Mendes, M. L., and G. Dittmar. 2022. “Targeted Proteomics on Its Way to Discovery.” Proteomics 22, no. 15–16: e2100330. https://doi.org/10.1002/pmic.202100330.
Di Meo, A., E. P. Diamandis, H. Rodriguez, A. N. Hoofnagle, J. Ioannidis, and M. Lopez. 2014. “What Is Wrong With Clinical Proteomics?.” Clinical Chemistry 60, no. 10: 1258–1266. https://doi.org/10.1373/clinchem.2014.225185.
Mertins, P., D. R. Mani, K. V. Ruggles, et al. 2016. “Proteogenomics Connects Somatic Mutations to Signalling In Breast Cancer.” Nature 534, no. 7605: 55–62. https://doi.org/10.1038/nature18003.
Milbury, C. A., J. Creeden, W. K. Yip, et al. 2022. “Clinical and Analytical Validation of FoundationoneCDx, a Comprehensive Genomic Profiling Assay for Solid Tumors.” PLoS One 17, no. 3: e0264138. https://doi.org/10.1371/journal.pone.0264138.
Morshed, N., W. T. Ralvenius, A. Nott, et al. 2020. “Phosphoproteomics Identifies Microglial Siglec‐F Inflammatory Response During Neurodegeneration.” Molecular Systems Biology 16, no. 12: e9819. https://doi.org/10.15252/msb.20209819.
Mosele, F., J. Remon, J. Mateo, et al. 2020. “Recommendations for the Use of Next‐Generation Sequencing (NGS) for Patients With Metastatic Cancers: A Report From the ESMO Precision Medicine Working Group.” Annals of oncology: official journal of the European Society for Medical Oncology 31, no. 11: 1491–1505. https://doi.org/10.1016/j.annonc.2020.07.014.
Moulder, R., S. D. Bhosale, D. R. Goodlett, and R. Lahesmaa. 2018. “Analysis of the Plasma Proteome Using iTRAQ and TMT‐Based Isobaric Labeling.” Mass Spectrometry Reviews 37, no. 5: 583–606. https://doi.org/10.1002/mas.21550.
Mun, D. G., J. Bhin, S. Kim, et al. 2019. “Proteogenomic Characterization of Human Early‐Onset Gastric Cancer.” Cancer Cell 35, no. 1: 111–124.e10. https://doi.org/10.1016/j.ccell.2018.12.003.
Mund, A., F. Coscia, A. Kriston, et al. 2022. “Deep Visual Proteomics Defines Single‐Cell Identity and Heterogeneity.” Nature Biotechnology 40, no. 8: 1231–1240. https://doi.org/10.1038/s41587-022-01302-5.
Muneer, G., C. S. Chen, and Y. J. Chen. 2025. “Advancements in Global Phosphoproteomics Profiling: Overcoming Challenges in Sensitivity and Quantification.” Proteomics 25, no. 1–2: e202400087. https://doi.org/10.1002/pmic.202400087.
Muneer, G., C. S. Chen, T. T. Lee, B. Y. Chen, and Y. J. Chen. 2024. “A Rapid One‐Pot Workflow for Sensitive Microscale Phosphoproteomics.” Journal of Proteome Research 23, no. 8: 3294–3309. https://doi.org/10.1021/acs.jproteome.3c00862.
Muneer, G., S. T. Gebreyesus, C. S. Chen, et al. 2025. “Mapping Nanoscale‐To‐Single‐Cell Phosphoproteomic Landscape by Chip‐DIA.” Advanced Science (Weinheim, Baden‐Wurttemberg, Germany) 12, no. 1: e2402421. https://doi.org/10.1002/advs.202402421.
Muntel, J., J. Kirkpatrick, R. Bruderer, et al. 2019. “Comparison of Protein Quantification in a Complex Background by DIA and TMT Workflows With Fixed Instrument Time.” Journal of Proteome Research 18, no. 3: 1340–1351. https://doi.org/10.1021/acs.jproteome.8b00898.
Murciano‐Goroff, Y. R., S. P. Suehnholz, A. Drilon, and D. Chakravarty. 2023. “Precision Oncology: 2023 in Review.” Cancer Discovery 13, no. 12: 2525–2531. https://doi.org/10.1158/2159-8290.CD-23-1194.
Nahnsen, S., C. Bielow, K. Reinert, and O. Kohlbacher. 2013. “Tools for Label‐Free Peptide Quantification.” Molecular & Cellular Proteomics 12, no. 3: 549–556. https://doi.org/10.1074/mcp.R112.025163.
Nakayasu, E. S., M. Gritsenko, P. D. Piehowski, et al. 2021. “Tutorial: Best Practices and Considerations for Mass‐Spectrometry‐Based Protein Biomarker Discovery and Validation.” Nature Protocols 16, no. 8: 3737–3760. https://doi.org/10.1038/s41596-021-00566-6.
Nastase, A., S. O. Dima, A. Lupo, et al. 2022. “Molecular Markers for Long‐Term Survival in Stage IIIA (N2) NSCLC Patients.” Cancer Genomics ‐ Proteomics 19, no. 1: 94–104. https://doi.org/10.21873/cgp.20306.
Necula, L., L. Matei, D. Dragu, et al. 2019. “Recent Advances in Gastric Cancer Early Diagnosis.” World Journal of Gastroenterology 25, no. 17: 2029–2044. https://doi.org/10.3748/wjg.v25.i17.2029.
Nelson, H. D., E. S. O'Meara, K. Kerlikowske, S. Balch, and D. Miglioretti. 2016. “Factors Associated With Rates of False‐Positive and False‐Negative Results From Digital Mammography Screening: An Analysis of Registry Data.” Annals of Internal Medicine 164, no. 4: 226–235. https://doi.org/10.7326/M15-0971.
Nice, E. C. 2022. “The Status of Proteomics as We Enter the 2020 S: Towards Personalised/Precision Medicine.” Analytical Biochemistry 644: 113840. https://doi.org/10.1016/j.ab.2020.113840.
Nishiwada, S., M. Sho, Y. Cui, et al. 2021. “A Gene Expression Signature for Predicting Response to Neoadjuvant Chemoradiotherapy in Pancreatic Ductal Adenocarcinoma.” International Journal of Cancer 148, no. 3: 769–779. https://doi.org/10.1002/ijc.33284.
Nolen, B. M., and A. E. Lokshin. 2013. “Biomarker Testing for Ovarian Cancer: Clinical Utility of Multiplex Assays.” Molecular Diagnosis & Therapy 17, no. 3: 139–146. https://doi.org/10.1007/s40291-013-0027-6.
Nwosu, A. J., S. A. Misal, T. Truong, et al. 2022. “In‐Depth Mass Spectrometry‐Based Proteomics of Formalin‐Fixed, Paraffin‐Embedded Tissues With a Spatial Resolution of 50–200 μm.” Journal of Proteome Research 21, no. 9: 2237–2245. https://doi.org/10.1021/acs.jproteome.2c00409.
Olmos, D., D. Lorente, D. Alameda, et al. 2024. “Treatment Patterns and Outcomes In Metastatic Castration‐Resistant Prostate Cancer Patients With and Without Somatic or Germline Alterations in Homologous Recombination Repair Genes.” Annals of Oncology 35, no. 5: 458–472. https://doi.org/10.1016/j.annonc.2024.01.011.
Orsburn, B. C. 2023. “Metabolomic, Proteomic, and Single‐Cell Proteomic Analysis of Cancer Cells Treated With the KRAS(G12D) Inhibitor MRTX1133.” Journal of Proteome Research 22, no. 12: 3703–3713. https://doi.org/10.1021/acs.jproteome.3c00212.
Orsburn, B. C., Y. Yuan, and N. N. Bumpus. 2022. “Insights into Protein Post‐Translational Modification Landscapes of Individual Human Cells by Trapped Ion Mobility Timeof‐Flight Mass Spectrometry.” Nature Communications 13, no. 1: 7246. https://doi.org/10.1038/s41467-022-34919-w.
Osipov, A., O. Nikolic, A. Gertych, et al. 2024. “The Molecular Twin Artificial‐Intelligence Platform Integrates Multi‐Omic Data to Predict Outcomes for Pancreatic Adenocarcinoma Patients.” Nature Cancer 5, no. 2: 299–314. https://doi.org/10.1038/s43018-023-00697-7.
Park, J., H. J. Oh, D. Han, et al. 2020. “Parallel Reaction Monitoring‐Mass Spectrometry (PRM‐MS)‐Based Targeted Proteomic Surrogates for Intrinsic Subtypes in Breast Cancer: Comparative Analysis With Immunohistochemical Phenotypes.” Journal of Proteome Research 19, no. 7: 2643–2653. https://doi.org/10.1021/acs.jproteome.9b00490.
Patterson, K. L., A. B. Arul, M. J. Choi, et al. 2023. “Establishing Quality Control Procedures for Large‐Scale Plasma Proteomics Analyses.” Journal of the American Society for Mass Spectrometry 34, no. 6: 1105–1116. https://doi.org/10.1021/jasms.3c00050.
Penault‐Llorca, F., K. M. Kerr, P. Garrido, et al. 2022. “Expert Opinion on NSCLC Small Specimen Biomarker Testing—Part 2: Analysis, Reporting, and Quality Assessment.” Virchows Archiv 481, no. 3: 351–366. https://doi.org/10.1007/s00428-022-03344-1.
Petrera, A., C. von Toerne, J. Behler, et al. 2021. “Multiplatform Approach for Plasma Proteomics: Complementarity of Olink Proximity Extension Assay Technology to Mass Spectrometry‐Based Protein Profiling.” Journal of Proteome Research 20, no. 1: 751–762. https://doi.org/10.1021/acs.jproteome.0c00641.
Pickering, C., P. Aiyetan, G. Xu, et al. 2023. “Plasma Glycoproteomic Biomarkers Identify Metastatic Melanoma Patients With Reduced Clinical Benefit From Immune Checkpoint Inhibitor Therapy.” Frontiers in Immunology 14: 1187332. https://doi.org/10.3389/fimmu.2023.1187332.
Piehowski, P. D., Y. Zhu, L. M. Bramer, et al. 2020. “Automated Mass Spectrometry Imaging of Over 2000 Proteins From Tissue Sections at 100‐μm Spatial Resolution.” Nature Communications 11, no. 1: 8. https://doi.org/10.1038/s41467-019-13858-z.
Pontillo, C., and H. Mischak. 2017. “Urinary Peptide‐Based Classifier CKD273: Towards Clinical Application in Chronic Kidney Disease.” Clinical Kidney Journal 10, no. 2: 192–201. https://doi.org/10.1093/ckj/sfx002.
Porcaro, F., S. Voccola, G. Cardinale, P. Porcaro, and P. Vito. 2024. “DNA Methylation Biomarkers in Stool Samples: Enhancing Colorectal Cancer Screening Strategies.” Oncology Reviews 18: 1408529. https://doi.org/10.3389/or.2024.1408529.
Prasad, V., and A. Addeo. 2020. “The Fda Approval of Pembrolizumab for Patients With TMB >10 mut/Mb: Was it a Wise Decision? No.” Annals of Oncology 31, no. 9: 1112–1114. https://doi.org/10.1016/j.annonc.2020.07.001.
Qiu, T., X. Zhi, and S. Ren. 2023. “Recent Advance of Next‐Generation Sequencing In Patients With Lung Cancer.” Expert Review of Molecular Diagnostics 23, no. 11: 959–970. https://doi.org/10.1080/14737159.2023.2260755.
Ragupathi, A., M. Singh, A. M. Perez, and D. Zhang. 2023. “Targeting the BRCA1/2 Deficient Cancer With Parp Inhibitors: Clinical Outcomes and Mechanistic Insights.” Frontiers in Cell and Developmental Biology 11: 1133472. https://doi.org/10.3389/fcell.2023.1133472.
Rebouissou, S., and J. C. Nault. 2020. “Advances in Molecular Classification and Precision Oncology in Hepatocellular Carcinoma.” Journal of Hepatology 72, no. 2: 215–229. https://doi.org/10.1016/j.jhep.2019.08.017.
van Renterghem, A. W. J., J. van de Haar, and E. E. Voest. 2023. “Functional Precision Oncology Using Patient‐Derived Assays: Bridging Genotype and Phenotype.” Nature Reviews Clinical Oncology 20, no. 5: 305–317. https://doi.org/10.1038/s41571-023-00745-2.
Rizk, E. M., R. D. Gartrell, L. W. Barker, et al. 2019. “Prognostic and Predictive Immunohistochemistry‐Based Biomarkers in Cancer and Immunotherapy.” Hematology/Oncology Clinics of North America 33, no. 2: 291–299. https://doi.org/10.1016/j.hoc.2018.12.005.
Rodriguez, H., J. C. Zenklusen, L. M. Staudt, J. H. Doroshow, and D. R. Lowy. 2021. “The Next Horizon in Precision Oncology: Proteogenomics to Inform Cancer Diagnosis and Treatment.” Cell 184, no. 7: 1661–1670. https://doi.org/10.1016/j.cell.2021.02.055.
Rosenberger, F. A., M. Thielert, M. T. Strauss, et al. 2023. “Spatial Single‐Cell Mass Spectrometry Defines Zonation of the Hepatocyte Proteome.” Nature Methods 20, no. 10: 1530–1536. https://doi.org/10.1038/s41592-023-02007-6.
Rujchanarong, D., J. Lefler, J. E. Saunders, et al. 2021. “Defining the Tumor Microenvironment by Integration of Immunohistochemistry and Extracellular Matrix Targeted Imaging Mass Spectrometry.” Cancers 13, no. 17: 4419. https://doi.org/10.3390/cancers13174419.
Ryu, J., and S. N. Thomas. 2021. “Quantitative Mass Spectrometry‐Based Proteomics for Biomarker Development in Ovarian Cancer.” Molecules 26, no. 9: 2674. https://doi.org/10.3390/molecules26092674.
Saad, M. B., L. Hong, M. Aminu, et al. 2023. “Predicting Benefit From Immune Checkpoint Inhibitors in Patients With Non‐Small‐Cell Lung Cancer by CT‐Based Ensemble Deep Learning: A Retrospective Study.” Lancet Digital Health 5, no. 7: e404–e420. https://doi.org/10.1016/S2589-7500(23)00082-1.
Sadee, W., D. Wang, K. Hartmann, and A. E. Toland. 2023. “Pharmacogenomics: Driving Personalized Medicine.” Pharmacological Reviews 75, no. 4: 789–814. https://doi.org/10.1124/pharmrev.122.000810.
Saillard, C., F. Delecourt, B. Schmauch, et al. 2023. “Pacpaint: a Histology‐Based Deep Learning Model Uncovers the Extensive Intratumor Molecular Heterogeneity of Pancreatic Adenocarcinoma.” Nature Communications 14, no. 1: 3459. https://doi.org/10.1038/s41467-023-39026-y.
Sakai, K., T. Takahama, M. Shimokawa, et al. 2021. “Predicting Osimertinib‐Treatment Outcomes Through EGFR Mutant‐Fraction Monitoring in the Circulating Tumor DNA of EGFR T790M‐Positive Patients With Non‐Small Cell Lung Cancer (Wjog8815l).” Molecular Oncology 15, no. 1: 126–137. https://doi.org/10.1002/1878-0261.12841.
Samstein, R. M., C. H. Lee, A. N. Shoushtari, et al. 2019. “Tumor Mutational Load Predicts Survival After Immunotherapy Across Multiple Cancer Types.” Nature Genetics 51, no. 2: 202–206. https://doi.org/10.1038/s41588-018-0312-8.
Satpathy, S., E. J. Jaehnig, K. Krug, et al. 2020. “Microscaled Proteogenomic Methods for Precision Oncology.” Nature Communications 11, no. 1: 532. https://doi.org/10.1038/s41467-020-14381-2.
Savage, S. R., X. Yi, J. T. Lei, et al. 2024. “Pan‐Cancer Proteogenomics Expands the Landscape of Therapeutic Targets.” Cell 187, no. 16: 4389–4407.e15. https://doi.org/10.1016/j.cell.2024.05.039.
Schoof, E. M., B. Furtwängler, N. Üresin, et al. 2021. “Quantitative Single‐Cell Proteomics as a Tool to Characterize Cellular Hierarchies.” Nature Communications 12, no. 1: 3341. https://doi.org/10.1038/s41467-021-23667-y.
Sella, T., S. I. Gelber, P. D. Poorvu, et al. 2021. “Response to Neoadjuvant Chemotherapy and the 21‐Gene Breast Recurrence Score Test in Young Women With Estrogen Receptor‐Positive Early Breast Cancer.” Breast Cancer Research and Treatment 186, no. 1: 157–165. https://doi.org/10.1007/s10549-020-05989-5.
Shapiro, J. P., H. M. Komar, B. Hancioglu, et al. 2017. “Laser Capture Microdissection of Pancreatic Acinar Cells to Identify Proteomic Alterations in a Murine Model of Caerulein‐Induced Pancreatitis.” Clinical and Translational Gastroenterology 8, no. 4: e89. https://doi.org/10.1038/ctg.2017.15.
Shen, B., X. Yi, Y. Sun, et al. 2020. “Proteomic and Metabolomic Characterization of COVID‐19 Patient Sera.” Cell 182, no. 1: 59–72.e15. https://doi.org/10.1016/j.cell.2020.05.032.
Shi, J., W. S. Phipps, B. Y. Owusu, et al. 2022. “A Distributable LC‐MS/MS Method for the Measurement of Serum Thyroglobulin.” Journal of Mass Spectrometry and Advances in the Clinical Lab 26: 28–33. https://doi.org/10.1016/j.jmsacl.2022.09.005.
Shi, J., X. Wang, H. Zhu, et al. 2018. “Determining Allele‐Specific Protein Expression (ASPE) Using a Novel Quantitative Concatamer Based Proteomics Method.” Journal of Proteome Research 17, no. 10: 3606–3612. https://doi.org/10.1021/acs.jproteome.8b00620.
Shi, Q., J. Xuhong, T. Luo, et al. 2023. “PIK3CA Mutations Are Associated With Pathologic Complete Response Rate to Neoadjuvant Pyrotinib and Trastuzumab Plus Chemotherapy for HER2‐Positive Breast Cancer.” British Journal of Cancer 128, no. 1: 121–129. https://doi.org/10.1038/s41416-022-02021-z.
Shi, W., Y. Wang, C. Xu, et al. 2023. “Multilevel Proteomic Analyses Reveal Molecular Diversity Between Diffuse‐Type and Intestinal‐Type Gastric Cancer.” Nature Communications 14, no. 1: 835. https://doi.org/10.1038/s41467-023-35797-6.
Shimura, T., D. Dayde, H. Wang, et al. 2020. “Novel Urinary Protein Biomarker Panel for Early Diagnosis of Gastric Cancer.” British Journal of Cancer 123, no. 11: 1656–1664. https://doi.org/10.1038/s41416-020-01063-5.
Shin, D., Y. Kim, J. Park, and Y. Kim. 2025. “High‐Throughput Proteomics‐Guided Biomarker Discovery of Hepatocellular Carcinoma.” Biomedical Journal 48, no. 1: 100752. https://doi.org/10.1016/j.bj.2024.100752.
Siegel, R. L., K. D. Miller, S. A. Fedewa, et al. 2017. “Colorectal Cancer Statistics, 2017.” CA: A Cancer Journal for Clinicians 67, no. 3: 177–193. https://doi.org/10.3322/caac.21395.
Sogawa, K., S. Takano, F. Iida, et al. 2016. “Identification of a Novel Serum Biomarker for Pancreatic Cancer, C4b‐Binding Protein α‐Chain (C4BPA) by Quantitative Proteomic Analysis Using Tandem Mass Tags.” British Journal of Cancer 115, no. 8: 949–956. https://doi.org/10.1038/bjc.2016.295.
Soltis, A. R., N. W. Bateman, J. Liu, et al. 2022. “Proteogenomic Analysis of Lung Adenocarcinoma Reveals Tumor Heterogeneity, Survival Determinants, and Therapeutically Relevant Pathways.” Cell reports. Medicine 3, no. 11: 100819. https://doi.org/10.1016/j.xcrm.2022.100819.
Specht, H., E. Emmott, A. A. Petelski, et al. 2021. “Single‐Cell Proteomic and Transcriptomic Analysis of Macrophage Heterogeneity Using Scope2.” Genome Biology 22, no. 1: 50. https://doi.org/10.1186/s13059-021-02267-5.
Steiner, C., P. Lescuyer, P. Cutler, J. C. Tille, and A. Ducret. 2022. “Relative Quantification of Proteins in Formalin‐Fixed Paraffin‐Embedded Breast Cancer Tissue Using Multiplexed Mass Spectrometry Assays.” Molecular & Cellular Proteomics 21, no. 11: 100416. https://doi.org/10.1016/j.mcpro.2022.100416.
Straubhaar, J., A. D'Souza, Z. Niziolek, and B. Budnik. 2024. “Single Cell Proteomics Analysis of Drug Response Shows Its Potential as a Drug Discovery Platform.” Molecular Omics 20, no. 1: 6–18. https://doi.org/10.1039/d3mo00124e.
Su, M., Z. Zhang, L. Zhou, C. Han, C. Huang, and E. C. Nice. 2021. “Proteomics, Personalized Medicine and Cancer.” Cancers 13, no. 11: 2512. https://doi.org/10.3390/cancers13112512.
Sun, H., S. Poudel, D. Vanderwall, D. G. Lee, Y. Li, and J. Peng. 2022. “29‐Plex Tandem Mass Tag Mass Spectrometry Enabling Accurate Quantification by Interference Correction.” Proteomics 22, no. 19–20: e2100243. https://doi.org/10.1002/pmic.202100243.
Sun, Y., Z. Guo, X. Liu, et al. 2022. “Noninvasive Urinary Protein Signatures Associated With Colorectal Cancer Diagnosis and Metastasis.” Nature Communications 13, no. 1: 2757. https://doi.org/10.1038/s41467-022-30391-8.
Swensen, A. C., D. Veličković, S. M. Williams, et al. 2022. “Proteomic Profiling of Intra‐Islet Features Reveals Substructure‐Specific Protein Signatures.” Molecular & Cellular Proteomics: MCP 21, no. 12: 100426. https://doi.org/10.1016/j.mcpro.2022.100426.
Taguchi, F., B. Solomon, V. Gregorc, et al. 2007. “Mass Spectrometry to Classify Non‐Small‐Cell Lung Cancer Patients for Clinical Outcome After Treatment With Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors: A Multicohort Cross‐Institutional Study.” Journal of the National Cancer Institute 99, no. 11: 838–846. https://doi.org/10.1093/jnci/djk195.
Tan, Y. C., T. Y. Low, P. Y. Lee, and L. C. Lim. 2024. “Single‐Cell Proteomics by Mass Spectrometry: Advances and Implications In Cancer Research.” Proteomics 24, no. 12–13: e2300210. https://doi.org/10.1002/pmic.202300210.
Theodosiou, A. A., and R. C. Read. 2023. “Artificial Intelligence, Machine Learning and Deep Learning: Potential Resources for the Infection Clinician.” Journal of Infection 87, no. 4: 287–294. https://doi.org/10.1016/j.jinf.2023.07.006.
Thielert, M., E. C. Itang, C. Ammar, et al. 2023. “Robust Dimethyl‐Based Multiplex‐DIA Doubles Single‐Cell Proteome Depth via a Reference Channel.” Molecular Systems Biology 19, no. 9: e11503. https://doi.org/10.15252/msb.202211503.
Thomas, S. N., D. French, P. J. Jannetto, B. A. Rappold, and W. A. Clarke. 2022. “Liquid Chromatography‐Tandem Mass Spectrometry for Clinical Diagnostics.” Nature Reviews Methods Primers 2, no. 1: 96. https://doi.org/10.1038/s43586-022-00175-x.
Tognetti, M., K. Sklodowski, S. Müller, et al. 2022. “Biomarker Candidates for Tumors Identified From Deep‐Profiled Plasma Stem Predominantly From the Low Abundant Area.” Journal of Proteome Research 21, no. 7: 1718–1735. https://doi.org/10.1021/acs.jproteome.2c00122.
Trapani, D., O. Ginsburg, T. Fadelu, et al. 2022. “Global Challenges and Policy Solutions In Breast Cancer Control.” Cancer Treatment Reviews 104: 102339. https://doi.org/10.1016/j.ctrv.2022.102339.
Truong, T., K. G. I. Webber, S. Madisyn Johnston, et al. 2023. “Data‐Dependent Acquisition With Precursor Coisolation Improves Proteome Coverage and Measurement Throughput for Label‐Free Single‐Cell Proteomics.” Angewandte Chemie International Edition 62, no. 34: e202303415. https://doi.org/10.1002/anie.202303415.
Tsai, I. J., E. C. Y. Su, I. L. Tsai, and C. Y. Lin. 2021. “Clinical Assay for the Early Detection of Colorectal Cancer Using Mass Spectrometric Wheat Germ Agglutinin Multiple Reaction Monitoring.” Cancers 13, no. 9: 2190. https://doi.org/10.3390/cancers13092190.
Tuffaha, H., K. Edmunds, D. Fairbairn, et al. 2024. “Guidelines for Genetic Testing In Prostate Cancer: A Scoping Review.” Prostate Cancer and Prostatic Diseases 27: 594–603. https://doi.org/10.1038/s41391-023-00676-0.
Tung, N., C. Ricker, H. Messersmith, et al. 2024. “Selection of Germline Genetic Testing Panels in Patients With Cancer: ASCO Guideline.” Journal of Clinical Oncology 42, no. 21: 2599–2615. https://doi.org/10.1200/JCO.24.00662.
Twomey, J. D., and B. Zhang. 2021. “Cancer Immunotherapy Update: FDA‐Approved Checkpoint Inhibitors and Companion Diagnostics.” AAPS Journal 23, no. 2: 39. https://doi.org/10.1208/s12248-021-00574-0.
Uramoto, H., and F. Tanaka. 2014. “Recurrence After Surgery in Patients With NSCLC.” Translational Lung Cancer Research 3, no. 4: 242–249. https://doi.org/10.3978/j.issn.2218-6751.2013.12.05.
Vandereyken, K., A. Sifrim, B. Thienpont, and T. Voet. 2023. “Methods and Applications for Single‐Cell and Spatial Multi‐Omics.” Nature Reviews Genetics 24, no. 8: 494–515. https://doi.org/10.1038/s41576-023-00580-2.
Vasaikar, S., C. Huang, X. Wang, et al. 2019. “Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities.” Cell 177, no. 4: 1035–1049.e19. https://doi.org/10.1016/j.cell.2019.03.030.
Végvári, Á., J. E. Rodriguez, and R. A. Zubarev. 2022. “Single‐Cell Chemical Proteomics (SCCP) Interrogates the Timing and Heterogeneity of Cancer Cell Commitment to Death.” Analytical Chemistry 94, no. 26: 9261–9269. https://doi.org/10.1021/acs.analchem.2c00413.
Wagner, S. J., D. Reisenbüchler, N. P. West, et al. 2023. “Transformer‐Based Biomarker Prediction From Colorectal Cancer Histology: A Large‐Scale Multicentric Study.” Cancer Cell 41, no. 9: 1650–1661.e4. https://doi.org/10.1016/j.ccell.2023.08.002.
Wang, Q., R. Chaerkady, J. Wu, et al. 2011. “Mutant Proteins as Cancer‐Specific Biomarkers.” Proceedings of the National Academy of Sciences 108, no. 6: 2444–2449. https://doi.org/10.1073/pnas.1019203108.
Wang, W., H. Xie, B. Xia, L. Zhang, Y. Hou, and K. Li. 2021. “Identifying Potential Markers for Monitoring Progression to Ovarian Cancer Using Plasma Label‐Free Proteomics.” Journal of Cancer 12, no. 6: 1651–1659. https://doi.org/10.7150/jca.50733.
Wang, Y., Z. Y. Guan, S. W. Shi, et al. 2024. “Pick‐Up Single‐Cell Proteomic Analysis for Quantifying up to 3000 Proteins in a Mammalian Cell.” Nature Communications 15, no. 1: 1279. https://doi.org/10.1038/s41467-024-45659-4.
Wang, Y., B. Meng, X. Wang, et al. 2023. “Noninvasive Urinary Protein Signatures Combined Clinical Information Associated With Microvascular Invasion Risk in HCC Patients.” BMC Medicine 21, no. 1: 481. https://doi.org/10.1186/s12916-023-03137-6.
Wang, Z., K. Yu, H. Tan, et al. 2020. “27‐Plex Tandem Mass Tag Mass Spectrometry for Profiling Brain Proteome in Alzheimer's Disease.” Analytical Chemistry 92, no. 10: 7162–7170. https://doi.org/10.1021/acs.analchem.0c00655.
Webber, K. G. I., T. Truong, S. M. Johnston, et al. 2022. “Label‐Free Profiling of up to 200 Single‐Cell Proteomes Per Day Using a Dual‐Column Nanoflow Liquid Chromatography Platform.” Analytical Chemistry 94, no. 15: 6017–6025. https://doi.org/10.1021/acs.analchem.2c00646.
Wei, B., Y. Shan, Z. Du, et al. 2022. “Identifying Circulating Tumor DNA Mutations Associated With Neoadjuvant Chemotherapy Efficacy in Local Advanced Breast Cancer.” Applied Biochemistry and Biotechnology 194, no. 9: 3961–3973. https://doi.org/10.1007/s12010-022-03946-0.
Wenk, D., C. Zuo, T. Kislinger, and L. Sepiashvili. 2024. “Recent Developments in Mass‐Spectrometry‐Based Targeted Proteomics of Clinical Cancer Biomarkers.” Clinical Proteomics 21, no. 1: 6. https://doi.org/10.1186/s12014-024-09452-1.
Werner, T., M. Fahrner, and O. Schilling. 2023. “Using Proteomics for Stratification and Risk Prediction in Patients With Solid Tumors.” Supplememt, Die Pathologie 44, no. S3: 176–182. https://doi.org/10.1007/s00292-023-01261-x.
Wisniewski, J. R. 2018. “Filter‐Aided Sample Preparation for Proteome Analysis.” Methods in Molecular Biology 1841: 3–10. https://doi.org/10.1007/978-1-4939-8695-8_1.
Wu, C. C., K. A. Tsantilas, J. Park, et al. 2024. “Mag‐Net: Rapid Enrichment of Membrane‐Bound Particles Enables High Coverage Quantitative Analysis of the Plasma Proteome.” Preprint, bioRxiv. https://doi.org/10.1101/2023.06.10.544439.
Wu, E., K. Wu, R. Daneshjou, D. Ouyang, D. E. Ho, and J. Zou. 2021. “How Medical AI Devices Are Evaluated: Limitations and Recommendations From an Analysis of FDA Approvals.” Nature Medicine 27, no. 4: 582–584. https://doi.org/10.1038/s41591-021-01312-x.
Wu, H. Y., Y. Y. Pan, A. T. Kopylov, et al. 2020. “Assessment of Serological Early Biomarker Candidates for Lung Adenocarcinoma by Using Multiple Reaction Monitoring‐Mass Spectrometry.” PROTEOMICS – Clinical Applications 14, no. 4: e1900095. https://doi.org/10.1002/prca.201900095.
Wu, M., Q. Huang, Y. Xie, et al. 2022. “Improvement of the Anticancer Efficacy of PD‐1/PD‐L1 Blockade via Combination Therapy and Pd‐L1 Regulation.” Journal of Hematology & Oncology 15, no. 1: 24. https://doi.org/10.1186/s13045-022-01242-2.
Xiang, P., A. Liyu, Y. Kwon, et al. 2023. “Spatial Proteomics Toward Subcellular Resolution by Coupling Deep Ultraviolet Laser Ablation With Nanodroplet Sample Preparation.” ACS Measurement Science Au 3, no. 6: 459–468. https://doi.org/10.1021/acsmeasuresciau.3c00033.
Xiao, Z., K. Nie, T. Han, et al. 2021. “Development and Validation of a TNF Family‐Based Signature for Predicting Prognosis, Tumor Immune Characteristics, and Immunotherapy Response in Colorectal Cancer Patients.” Journal of Immunology Research 2021: 6439975. https://doi.org/10.1155/2021/6439975.
Xing, X., L. Cai, J. Ouyang, et al. 2023. “Proteomics‐Driven Noninvasive Screening of Circulating Serum Protein Panels for the Early Diagnosis of Hepatocellular Carcinoma.” Nature Communications 14, no. 1: 8392. https://doi.org/10.1038/s41467-023-44255-2.
Xu, K., J. Bayani, E. Mallon, et al. 2022. “Discordance between Immunohistochemistry and Erb‐B2 Receptor Tyrosine Kinase 2 mRNA to Determine Human Epidermal Growth Factor Receptor 2 Low Status for Breast Cancer.” Journal of Molecular Diagnostics 24, no. 7: 775–783. https://doi.org/10.1016/j.jmoldx.2022.04.002.
Xu, R., J. Tang, Q. Deng, et al. 2018. “Spatial‐Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology.” Analytical Chemistry 90, no. 9: 5879–5886. https://doi.org/10.1021/acs.analchem.8b00596.
Xu, X., Q. Peng, X. Jiang, et al. 2024. “Altered Glycosylation in Cancer: Molecular Functions and Therapeutic Potential.” Cancer Communications 44, no. 11: 1316–1336. https://doi.org/10.1002/cac2.12610.
Yang, K. L., F. Yu, G. C. Teo, et al. 2023. “MSBooster: Improving Peptide Identification Rates Using Deep Learning‐Based Features.” Nature Communications 14, no. 1: 4539. https://doi.org/10.1038/s41467-023-40129-9.
Yang, T., W. Li, T. Huang, and J. Zhou. 2023. “Genetic Testing Enhances the Precision Diagnosis and Treatment of Breast Cancer.” International Journal of Molecular Sciences 24, no. 23: 16607. https://doi.org/10.3390/ijms242316607.
Ye, Z., P. Sabatier, J. Martin‐Gonzalez, et al. 2024. “One‐Tip Enables Comprehensive Proteome Coverage in Minimal Cells and Single Zygotes.” Nature Communications 15, no. 1: 2474. https://doi.org/10.1038/s41467-024-46777-9.
Yi, X., B. Wen, S. Ji, et al. 2024. “Deep Learning Prediction Boosts Phosphoproteomics‐Based Discoveries Through Improved Phosphopeptide Identification.” Molecular & Cellular Proteomics 23, no. 2: 100707. https://doi.org/10.1016/j.mcpro.2023.100707.
Yoneyama, T., S. Ohtsuki, K. Honda, et al. 2016. “Identification of IGFBP2 and IGFBP3 As Compensatory Biomarkers for CA19‐9 in Early‐Stage Pancreatic Cancer Using a Combination of Antibody‐Based and LC‐MS/MS‐Based Proteomics.” PLoS One 11, no. 8: e0161009. https://doi.org/10.1371/journal.pone.0161009.
Yoon, K. A., S. M. Woo, Y. H. Kim, et al. 2019. “Comprehensive Cancer Panel Sequencing Defines Genetic Diversity and Changes in the Mutational Characteristics of Pancreatic Cancer Patients Receiving Neoadjuvant Treatment.” Gut and Liver 13, no. 6: 683–689. https://doi.org/10.5009/gnl18355.
Yoshimura, R., W. Shigeeda, Y. Fujita, et al. 2024. “Diagnostic Method of Mass Spectrometry for Detecting Lymph Node Metastasis of Non‐Small Cell Lung Cancer.” Thoracic Cancer 15, no. 3: 209–214. https://doi.org/10.1111/1759-7714.15179.
Zhang, H., T. Liu, Z. Zhang, et al. 2016. “Integrated Proteogenomic Characterization of Human High‐Grade Serous Ovarian Cancer.” Cell 166, no. 3: 755–765. https://doi.org/10.1016/j.cell.2016.05.069.
Zhang, Q., Y. Lou, J. Yang, et al. 2019. “Integrated Multiomic Analysis Reveals Comprehensive Tumour Heterogeneity and Novel Immunophenotypic Classification in Hepatocellular Carcinomas.” Gut 68, no. 11: 2019–2031. https://doi.org/10.1136/gutjnl-2019-318912.
Zhang, Q., Y. Ma, Y. Yan, L. Zhang, and Y. Zhang. 2024. “CYB5R1 is a Potential Biomarker That Correlates With Stemness and Drug Resistance in Gastric Cancer.” Translational Oncology 39: 101766. https://doi.org/10.1016/j.tranon.2023.101766.
Zhang, T., L. I. Karsh, M. J. Nissenblatt, and S. E. Canfield. 2020. “Androgen Receptor Splice Variant, AR‐V7, as a Biomarker of Resistance to Androgen Axis‐Targeted Therapies in Advanced Prostate Cancer.” Clinical Genitourinary Cancer 18, no. 1: 1–10. https://doi.org/10.1016/j.clgc.2019.09.015.
Zhang, Z., and D. W. Chan. 2010. “The Road From Discovery to Clinical Diagnostics: Lessons Learned From the First FDA‐Cleared In Vitro Diagnostic Multivariate Index Assay of Proteomic Biomarkers.” Cancer Epidemiology, Biomarkers & Prevention 19, no. 12: 2995–2999. https://doi.org/10.1158/1055-9965.EPI-10-0580.
Zhang, Z., and X. Wei. 2023. “Artificial Intelligence‐Assisted Selection and Efficacy Prediction of Antineoplastic Strategies for Precision Cancer Therapy.” Seminars in Cancer Biology 90: 57–72. https://doi.org/10.1016/j.semcancer.2023.02.005.
Zhao, Y., Q. Xue, M. Wang, et al. 2023. “Evolution of Mass Spectrometry Instruments and Techniques for Blood Proteomics.” Journal of Proteome Research 22, no. 4: 1009–1023. https://doi.org/10.1021/acs.jproteome.3c00102.
Zhou, B., Z. Zhou, Y. Chen, et al. 2020. “Plasma Proteomics‐Based Identification of Novel Biomarkers in Early Gastric Cancer.” Clinical Biochemistry 76: 5–10. https://doi.org/10.1016/j.clinbiochem.2019.11.001.
Zhou, J., W. Yang, Y. Hu, et al. 2017. “Site‐Specific Fucosylation Analysis Identifying Glycoproteins Associated With Aggressive Prostate Cancer Cell Lines Using Tandem Affinity Enrichments of Intact Glycopeptides Followed by Mass Spectrometry.” Analytical Chemistry 89, no. 14: 7623–7630. https://doi.org/10.1021/acs.analchem.7b01493.
Zhu, Y., M. Dou, P. D. Piehowski, et al. 2018. “Spatially Resolved Proteome Mapping of Laser Capture Microdissected Tissue With Automated Sample Transfer to Nanodroplets.” Molecular & Cellular Proteomics 17, no. 9: 1864–1874. https://doi.org/10.1074/mcp.TIR118.000686.
Zhu, Y., P. D. Piehowski, R. Zhao, et al. 2018. “Nanodroplet Processing Platform for Deep and Quantitative Proteome Profiling of 10–100 Mammalian Cells.” Nature Communications 9, no. 1: 882. https://doi.org/10.1038/s41467-018-03367-w.

Grants

  1. /This study was supported and funded by the Next-Generation Pathway of Taiwan Cancer Precision Medicine Program (AS-KPQ-107-TCPMP), National Science and Technology Council (Grant: MOST 110-2113-M-001-020-MY3, NSTC 113-2113-M-001-020-MY3 and NSTC 113-2634-F-039-001) and Academia Sinica (AS-GC-111-M03) in Taiwan.
Journal Article Review

Word Cloud

Similar Articles

Cited By