https://doi.org/10.4081/btvb.2024.120
Identifying novel biomarkers using proteomics to predict cancer-associated thrombosis
Submitted: 22 January 2024
Accepted: 8 April 2024
Published: 16 May 2024
Accepted: 8 April 2024
Abstract Views: 352
PDF: 141
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Comprehensive protein analyses of plasma are made possible by high-throughput proteomic screens, which may help find new therapeutic targets and diagnostic biomarkers. Patients with cancer are frequently affected by venous thromboembolism (VTE). The limited predictive accuracy of current VTE risk assessment tools highlights the need for new, more targeted biomarkers. Although coagulation biomarkers for the diagnosis, prognosis, and treatment of VTE have been investigated, none of them have the necessary clinical validation or diagnostic accuracy. Proteomics holds the potential to uncover new biomarkers and thrombotic pathways that impact the risk of thrombosis. This review explores the fundamental methods used in proteomics and focuses on particular biomarkers found in VTE and cancer-associated thrombosis.
Fernandes CJ, Morinaga LTK, Alves JL, et al. Cancer-associated thrombosis: the when, how and why. Eur Respir Rev 2019;28:180119.
DOI: https://doi.org/10.1183/16000617.0119-2018
Abdol Razak N, Jones G, Bhandari M, et al. Cancer-associated thrombosis: an overview of mechanisms, risk factors, and treatment. Cancers 2018;10:380.
DOI: https://doi.org/10.3390/cancers10100380
Khan F, Tritschler T, Kahn SR, Rodger MA. Venous thromboembolism. Lancet 2021;398:64-77.
DOI: https://doi.org/10.1016/S0140-6736(20)32658-1
Sikkens JJ, Beekman DG, Thijs A, et al. How much overtesting is needed to safely exclude a diagnosis? A different perspective on triage testing using bayes’ theorem. Arez AP, editor. PLOS ONE 2016;11:e0150891.
DOI: https://doi.org/10.1371/journal.pone.0150891
Jacobs B, Obi A, Wakefield T. Diagnostic biomarkers in venous thromboembolic disease. J Vasc Surg Venous Lymphat Disord 2016;4:508-17.
DOI: https://doi.org/10.1016/j.jvsv.2016.02.005
Yang P, Li H, Zhang J, Xu X. Research progress on biomarkers of pulmonary embolism. Clin Respir J.2021;15:1046-55.
DOI: https://doi.org/10.1111/crj.13414
Eichinger S. D-Dimer Levels and Risk of Recurrent Venous Thromboembolism. JAMA 2003;290:1071.
DOI: https://doi.org/10.1001/jama.290.8.1071
Palareti G, Legnani C, Cosmi B, V et al. Predictive value of D-Dimer Test for recurrent venous thromboembolism after anticoagulation withdrawal in subjects with a previous idiopathic event and in carriers of congenital thrombophilia. Circulation 2003;108:313-8.
DOI: https://doi.org/10.1161/01.CIR.0000079162.69615.0F
Avnery O, Martin M, Bura-Riviere A, et al. D-dimer levels and risk of recurrence following provoked venous thromboembolism: findings from the RIETE registry. J Intern Med 2020;287:32-41.
DOI: https://doi.org/10.1111/joim.12969
Di Minno MND, Calcaterra I, Papa A, et al. Diagnostic accuracy of D-Dimer testing for recurrent venous thromboembolism: A systematic review with meta-analysis. Eur J Intern Med 2021;89:39-47.
DOI: https://doi.org/10.1016/j.ejim.2021.04.004
Ay C, Vormittag R, Dunkler D, et al. D-Dimer and Prothrombin fragment 1 + 2 predict venous thromboembolism in patients with cancer: results from the vienna cancer and thrombosis study. J Clin Oncol 2009;27:4124-9.
DOI: https://doi.org/10.1200/JCO.2008.21.7752
Khorana AA, DeSancho MT, Liebman H, et al. Prediction and prevention of cancer-associated thromboembolism. The Oncologist 2021;26:e2-7.
DOI: https://doi.org/10.1002/onco.13569
Posch F, Riedl J, Reitter E, et al. Dynamic assessment of venous thromboembolism risk in patients with cancer by longitudinal D-Dimer analysis: A prospective study. J Thromb Haemost 2020;18:1348-56.
DOI: https://doi.org/10.1111/jth.14774
Riondino S, Ferroni P, Zanzotto F, et al. Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models. Cancers 2019;11:95.
DOI: https://doi.org/10.3390/cancers11010095
Helfer H, Skaff Y, Happe F, et al. Diagnostic approach for venous thromboembolism in cancer patients. Cancers 2023; 15:3031.
DOI: https://doi.org/10.3390/cancers15113031
Gotta J, Gruenewald LD, Eichler K, et al. Unveiling the diagnostic enigma of D-dimer testing in cancer patients: Current evidence and areas of application. Eur J Clin Invest 2023;53:e14060.
DOI: https://doi.org/10.1111/eci.14060
Niimi K, Nishida K, Lee C, et al. Optimal D-Dimer cutoff values for diagnosing deep vein thrombosis in patients with comorbid malignancies. Ann Vasc Surg 2024;98:293-300.
DOI: https://doi.org/10.1016/j.avsg.2023.06.033
Ay C, Dunkler D, Marosi C, et al. Prediction of venous thromboembolism in cancer patients. Blood 2010;116:5377-82.
DOI: https://doi.org/10.1182/blood-2010-02-270116
Verso M, Agnelli G, Barni S, et al. A modified Khorana risk assessment score for venous thromboembolism in cancer patients receiving chemotherapy: the Protecht score. Intern Emerg Med 2012;7:291-2.
DOI: https://doi.org/10.1007/s11739-012-0784-y
Bruinstroop E, Klok FA, Van De Ree MA, et al. Elevated d-dimer levels predict recurrence in patients with idiopathic venous thromboembolism: a meta-analysis. J Thromb Haemost 2009;7:611-8.
DOI: https://doi.org/10.1111/j.1538-7836.2009.03293.x
Eichinger S, Heinze G, Jandeck LM, Kyrle PA. Risk assessment of recurrence in patients with unprovoked deep vein thrombosis or pulmonary embolism: the Vienna Prediction model. Circulation 2010;121:1630-6.
DOI: https://doi.org/10.1161/CIRCULATIONAHA.109.925214
Martinelli I, De Stefano V, Mannucci PM. Inherited risk factors for venous thromboembolism. Nat Rev Cardiol 2014;11:140-56.
DOI: https://doi.org/10.1038/nrcardio.2013.211
Lindström S, Wang L, Smith EN, et al. Genomic and transcriptomic association studies identify 16 novel susceptibility loci for venous thromboembolism. Blood 2019;134:1645-57.
DOI: https://doi.org/10.1182/blood.2019000435
Crous-Bou M, Harrington L, Kabrhel C. Environmental and Genetic Risk Factors Associated with Venous Thromboembolism. Semin Thromb Hemost 2016;42:808-20.
DOI: https://doi.org/10.1055/s-0036-1592333
Letunica N, Van Den Helm S, McCafferty C, et al. Proteomics in Thrombosis and Hemostasis. Thromb Haemost 2022;122: 1076-84.
DOI: https://doi.org/10.1055/a-1690-8897
Zhang Z, Wu S, Stenoien DL, Paša-Tolić L. High-Throughput Proteomics. Annu Rev Anal Chem 2014;7:427-54.
DOI: https://doi.org/10.1146/annurev-anchem-071213-020216
Howes JM, Keen JN, Findlay JB, Carter AM. The application of proteomics technology to thrombosis research: the identification of potential therapeutic targets in cardiovascular disease. Diab Vasc Dis Res 2008;5:205-12.
DOI: https://doi.org/10.3132/dvdr.2008.033
Nanjappa V, Thomas JK, Marimuthu A, et al. Plasma Proteome Database as a resource for proteomics research: 2014 update. Nucleic Acids Res 2014;42:D959-65.
DOI: https://doi.org/10.1093/nar/gkt1251
Ronsein GE, Pamir N, Von Haller PD, et al. Parallel reaction monitoring (PRM) and selected reaction monitoring (SRM) exhibit comparable linearity, dynamic range and precision for targeted quantitative HDL proteomics. J Proteomics 2015;113:388-99.
DOI: https://doi.org/10.1016/j.jprot.2014.10.017
Edfors F, Iglesias MJ, Butler LM, Odeberg J. Proteomics in thrombosis research. Res Pract Thromb Haemost 2022;6: e12706.
DOI: https://doi.org/10.1002/rth2.12706
Aslam B, Basit M, Nisar MA, et al. Proteomics: Technologies and Their Applications. J Chromatogr Sci 2017;55:182-96.
DOI: https://doi.org/10.1093/chromsci/bmw167
Uzozie AC, Aebersold R. Advancing translational research and precision medicine with targeted proteomics. J Proteomics 2018;189:1-10.
DOI: https://doi.org/10.1016/j.jprot.2018.02.021
Fu Q, Kowalski MP, Mastali M, et al. Highly Reproducible Automated Proteomics Sample Preparation Workflow for Quantitative Mass Spectrometry. J Proteome Res 2018; 17:420-8.
DOI: https://doi.org/10.1021/acs.jproteome.7b00623
Smith JG, Gerszten RE. Emerging Affinity-Based Proteomic Technologies for Large-Scale Plasma Profiling in Cardiovascular Disease. Circulation 2017;135:1651-64.
DOI: https://doi.org/10.1161/CIRCULATIONAHA.116.025446
Lubec G, Afjehi-Sadat L. Limitations and Pitfalls in Protein Identification by Mass Spectrometry. Chem Rev 2007;107: 3568-84.
DOI: https://doi.org/10.1021/cr068213f
Deutsch EW, Omenn GS, Sun Z, M et al. Advances and Utility of the Human Plasma Proteome. J Proteome Res 2021;20: 5241-63.
DOI: https://doi.org/10.1021/acs.jproteome.1c00657
Zhang YX, Li JF, Yang YH, et al. Identification of haptoglobin as a potential diagnostic biomarker of acute pulmonary embolism. Blood Coagul Fibrinolysis 2018;29:275-81.
DOI: https://doi.org/10.1097/MBC.0000000000000715
Vormittag R, Vukovich T, Mannhalter C, et al. Haptoglobin phenotype 2-2 as a potentially new risk factor for spontaneous venous thromboembolism. Haematologica 2005;90:1557-61.
Insenser M, Montes-Nieto R, Martínez-García MÁ, et al. Identification of reduced circulating haptoglobin concentration as a biomarker of the severity of pulmonary embolism: a nontargeted proteomic study. PloS One 2014;9.
DOI: https://doi.org/10.1371/journal.pone.0100902
Han B, Li C, Li H, et al. Discovery of plasma biomarkers with data-independent acquisition mass spectrometry and antibody microarray for diagnosis and risk stratification of pulmonary embolism. J Thromb Haemost 2021;19:1738-51.
DOI: https://doi.org/10.1111/jth.15324
Jensen SB, Hindberg K, Solomon T, et al. Discovery of novel plasma biomarkers for future incident venous thromboembolism by untargeted synchronous precursor selection mass spectrometry proteomics. J Thromb Haemost 2018;16:1763-74.
DOI: https://doi.org/10.1111/jth.14220
Lundberg M, Eriksson A, Tran B, et al. Homogeneous antibody-based proximity extension assays provide sensitive and specific detection of low-abundant proteins in human blood. Nucleic Acids Res 2011;39:e102-e102.
DOI: https://doi.org/10.1093/nar/gkr424
Brody E, Willis M, Smith J, et al. The use of aptamers in large arrays for molecular diagnostics. Mol Diagn 1999;4:381-8.
DOI: https://doi.org/10.1016/S1084-8592(99)80014-9
Joshi A, Mayr M. In Aptamers They Trust: Caveats of the SOMAscan Biomarker Discovery Platform From SomaLogic. Circulation 2018;138:2482-5.
DOI: https://doi.org/10.1161/CIRCULATIONAHA.118.036823
Drobin K, Nilsson P, Schwenk JM. Highly Multiplexed antibody suspension bead arrays for plasma protein profiling. In: Bäckvall H, Lehtiö J (eds.). The low molecular weight proteome. New York, NY: Springer 2013:137-45.
DOI: https://doi.org/10.1007/978-1-4614-7209-4_8
Pietzner M, Wheeler E, Carrasco-Zanini J, et al. Synergistic insights into human health from aptamer- and antibody-based proteomic profiling. Nat Commun 2021;12:6822.
DOI: https://doi.org/10.1038/s41467-021-27164-0
Bendes A, Dale M, Mattsson C, et al. Bead-Based assays for validating proteomic profiles in body fluids. In: Barderas R, LaBaer J, Srivastava S, editors. Protein Microarrays for Disease Analysis. New York, NY: Springer US 2021:65-78.
DOI: https://doi.org/10.1007/978-1-0716-1562-1_5
Wik L, Nordberg N, Broberg J, et al. Proximity extension assay in combination with next-generation sequencing for high-throughput proteome-wide analysis. Mol Cell Proteomics 2021;20:100168.
DOI: https://doi.org/10.1016/j.mcpro.2021.100168
Ten Cate V, Prochaska JH, Schulz A, et al. Protein expression profiling suggests relevance of noncanonical pathways in isolated pulmonary embolism. Blood 2021;137:2681-93.
DOI: https://doi.org/10.1182/blood.2019004571
Nosaka M, Ishida Y, Kimura A, et al. Absence of IFN-γ accelerates thrombus resolution through enhanced MMP-9 and VEGF expression in mice. J Clin Invest 2011;121:2911-20.
DOI: https://doi.org/10.1172/JCI40782
Guo L, Liu M, Huang J, et al Role of interleukin-15 in cardiovascular diseases. J Cell Mol Med 2020;24:7094-101.
DOI: https://doi.org/10.1111/jcmm.15296
Memon AA, Sundquist K, PirouziFard M, et al. Identification of novel diagnostic biomarkers for deep venous thrombosis. Br J Haematol 2018;181:378-85.
DOI: https://doi.org/10.1111/bjh.15206
Purdy M, Obi A, Myers D, Wakefield T. P- and E- selectin in venous thrombosis and non-venous pathologies. J Thromb Haemost 2022;20:1056-66.
DOI: https://doi.org/10.1111/jth.15689
Tang X, Zhang Z, Fang M, et al. Transferrin plays a central role in coagulation balance by interacting with clotting factors. Cell Res 2020;30:119-32.
DOI: https://doi.org/10.1038/s41422-019-0260-6
Kölmel S, Hobohm L, Käberich A, et al. Potential involvement of osteopontin in inflammatory and fibrotic processes in pulmonary embolism and chronic thromboembolic pulmonary hypertension. Thromb Haemost 2019;119:1332-46.
DOI: https://doi.org/10.1055/s-0039-1692174
Khorana AA, Barnard J, Wun T, et al. Biomarker signatures in cancer patients with and without venous thromboembolism events: a substudy of CASSINI. Blood Adv 2022;6: 1212-21.
DOI: https://doi.org/10.1182/bloodadvances.2021005710
Bruzelius M, Iglesias MJ, Hong MG, et al. PDGFB, a new candidate plasma biomarker for venous thromboembolism: results from the VEREMA affinity proteomics study. Blood 2016;128:e59-66.
DOI: https://doi.org/10.1182/blood-2016-05-711846
Tannenberg P, Chang YT, Muhl L, et al. Extracellular retention of PDGF-B directs vascular remodeling in mouse hypoxia-induced pulmonary hypertension. Am J Physiol-Lung Cell Mol Physiol 2018;314:L593-605.
DOI: https://doi.org/10.1152/ajplung.00054.2017
Razzaq M, Iglesias MJ, Ibrahim-Kosta M, et al. An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism. Sci Rep 2021;11:14015.
DOI: https://doi.org/10.1038/s41598-021-93390-7
Greliche N, Germain M, Lambert JC, et al. A genome-wide search for common SNP x SNP interactions on the risk of venous thrombosis. BMC Med Genet 2013;14:36.
DOI: https://doi.org/10.1186/1471-2350-14-36
Bussolino F, Valdembri D, Caccavari F, Serini G. Semaphoring vascular morphogenesis. Endothelium 2006;13:81-91.
DOI: https://doi.org/10.1080/10623320600698003
Kashiwagi H, Shiraga M, Kato H, et al. Negative regulation of platelet function by a secreted cell repulsive protein, semaphorin 3A. Blood 2005;106:913-21.
DOI: https://doi.org/10.1182/blood-2004-10-4092
Hardin M, Cho MH, McDonald ML, et al. A genome-wide analysis of the response to inhaled β2-agonists in chronic obstructive pulmonary disease. Pharmacogenomics J 2016;16: 326-35.
DOI: https://doi.org/10.1038/tpj.2015.65
Iglesias MJ, Sanchez-Rivera L, Ibrahim-Kosta M, et al. Elevated plasma complement factor H related 5 protein is associated with venous thromboembolism. Nat Commun 2023;14:3280.
DOI: https://doi.org/10.1038/s41467-023-43764-4
Sanchez-Rivera L, Iglesias MJ, Ibrahim-Kosta M, et al. Elevated plasma Complement Factor H Regulating Protein 5 is associated with venous thromboembolism and COVID-19 severity. Cardiovasc Med 2022. Available from: http://medrxiv.org/lookup/doi/10.1101/2022.04.20.22274046 (accessed on September 27th, 2023)
DOI: https://doi.org/10.1101/2022.04.20.22274046
Lakhin AV, Tarantul VZ, Gening LV. Aptamers: problems, solutions and prospects. Acta Naturae 2013;5:34-43.
DOI: https://doi.org/10.32607/20758251-2013-5-4-34-43
Tala JA, Polikoff LA, Pinto MG, et al. Protein biomarkers for incident deep venous thrombosis in critically ill adolescents: An exploratory study. Pediatr Blood Cancer 2020;67:e28159.
DOI: https://doi.org/10.1002/pbc.28159
Petrera A, Von Toerne C, Behler J, et al. Multiplatform approach for plasma proteomics: complementarity of olink proximity extension assay technology to mass spectrometry-based protein profiling. J Proteome Res 2021;20:751-62.
DOI: https://doi.org/10.1021/acs.jproteome.0c00641
Katz DH, Robbins JM, Deng S, et al. Proteomic profiling platforms head to head: Leveraging genetics and clinical traits to compare aptamer- and antibody-based methods. Sci Adv 2022;8:eabm5164.
DOI: https://doi.org/10.1126/sciadv.abm5164
Raffield LM, Dang H, Pratte KA, et al. Comparison of Proteomic Assessment Methods in Multiple Cohort Studies. PROTEOMICS 2020;20:1900278.
DOI: https://doi.org/10.1002/pmic.201900278
Faquih T, Mook-Kanamori DO, Rosendaal FR, et al. Agreement of aptamer proteomics with standard methods for measuring venous thrombosis biomarkers. Res Pract Thromb Haemost 2021;5:e12526.
DOI: https://doi.org/10.1002/rth2.12526
Eldjarn GH, Ferkingstad E, Lund SH, et al. Large-scale plasma proteomics comparisons through genetics and disease associations. Nature 2023;622:348-58.
DOI: https://doi.org/10.1038/s41586-023-06563-x
Khorana AA, Ahrendt SA, Ryan CK, et al. Tissue factor expression, angiogenesis, and thrombosis in pancreatic cancer. Clin Cancer Res 2007;13:2870-5.
DOI: https://doi.org/10.1158/1078-0432.CCR-06-2351
Zwicker JI, Liebman HA, Neuberg D, et al. Tumor-derived tissue factorbearing microparticles are associated with venous thromboembolic events in malignancy. Clin Cancer Res 2009;15:6830-40.
DOI: https://doi.org/10.1158/1078-0432.CCR-09-0371
Khorana AA, Connolly GC, Hagen F, et al. A proteomics-based approach to identifying mechanisms of cancer-associated thrombosis: potential role for immunoglobulins. Blood 2013;122:1127.
DOI: https://doi.org/10.1182/blood.V122.21.1127.1127
Cui M, Huang J, Zhang S, et al. Immunoglobulin expression in cancer cells and its critical roles in tumorigenesis. Front Immunol. 2021;12:613530.
DOI: https://doi.org/10.3389/fimmu.2021.613530
Liu Y, Gao L, Fan Y, et al. Discovery of protein biomarkers for venous thromboembolism in non-small cell lung cancer patients through data-independent acquisition mass spectrometry. Front Oncol 2023;13:1079719.
DOI: https://doi.org/10.3389/fonc.2023.1079719
Ercan H, Mauracher LM, Grilz E, H et al. Alterations of the platelet proteome in lung cancer: accelerated F13A1 and ER processing as new actors in hypercoagulability. Cancers 2021;13:2260.
DOI: https://doi.org/10.3390/cancers13092260
Walraven M, Sabrkhany S, Knol J, et al. Effects of cancer presence and therapy on the platelet proteome. Int J Mol Sci 2021;22:8236.
DOI: https://doi.org/10.3390/ijms22158236
McNamee N, De La Fuente LR, Santos-Martinez MJ, O’Driscoll L. Proteomics profiling identifies extracellular vesicles’ cargo associated with tumour cell induced platelet aggregation. BMC Cancer 2022;22:1023.
DOI: https://doi.org/10.1186/s12885-022-10068-7
Mohammed Y, Van Vlijmen BJ, Yang J, et al. Multiplexed targeted proteomic assay to assess coagulation factor concentrations and thrombosis-associated cancer. Blood Adv 2017; 1:1080-7.
DOI: https://doi.org/10.1182/bloodadvances.2017007955
Supporting Agencies
NIH/NCI Cancer Center Support Grant P30 CA008748, Conquer Cancer Foundation, Career Development AwardHow to Cite
Fernandez Turizo, M. J., Patell, R., & Zwicker, J. I. (2024). Identifying novel biomarkers using proteomics to predict cancer-associated thrombosis. Bleeding, Thrombosis and Vascular Biology, 3(s1). https://doi.org/10.4081/btvb.2024.120
Copyright (c) 2024 The Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.
