Identifying novel biomarkers using proteomics to predict cancer-associated thrombosis

Submitted: 22 January 2024
Accepted: 8 April 2024
Published: 16 May 2024
Abstract Views: 210
PDF: 102
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.


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.



PlumX Metrics


Download data is not yet available.



Fernandes CJ, Morinaga LTK, Alves JL, et al. Cancer-associated thrombosis: the when, how and why. Eur Respir Rev 2019;28:180119. DOI:
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:
Khan F, Tritschler T, Kahn SR, Rodger MA. Venous thromboembolism. Lancet 2021;398:64-77. DOI:
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:
Jacobs B, Obi A, Wakefield T. Diagnostic biomarkers in venous thromboembolic disease. J Vasc Surg Venous Lymphat Disord 2016;4:508-17. DOI:
Yang P, Li H, Zhang J, Xu X. Research progress on biomarkers of pulmonary embolism. Clin Respir J.2021;15:1046-55. DOI:
Eichinger S. D-Dimer Levels and Risk of Recurrent Venous Thromboembolism. JAMA 2003;290:1071. DOI:
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:
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:
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:
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:
Khorana AA, DeSancho MT, Liebman H, et al. Prediction and prevention of cancer-associated thromboembolism. The Oncologist 2021;26:e2-7. DOI:
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:
Riondino S, Ferroni P, Zanzotto F, et al. Predicting VTE in Cancer Patients: Candidate Biomarkers and Risk Assessment Models. Cancers 2019;11:95. DOI:
Helfer H, Skaff Y, Happe F, et al. Diagnostic approach for venous thromboembolism in cancer patients. Cancers 2023; 15:3031. DOI:
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:
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:
Ay C, Dunkler D, Marosi C, et al. Prediction of venous thromboembolism in cancer patients. Blood 2010;116:5377-82. DOI:
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:
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:
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:
Martinelli I, De Stefano V, Mannucci PM. Inherited risk factors for venous thromboembolism. Nat Rev Cardiol 2014;11:140-56. DOI:
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:
Crous-Bou M, Harrington L, Kabrhel C. Environmental and Genetic Risk Factors Associated with Venous Thromboembolism. Semin Thromb Hemost 2016;42:808-20. DOI:
Letunica N, Van Den Helm S, McCafferty C, et al. Proteomics in Thrombosis and Hemostasis. Thromb Haemost 2022;122: 1076-84. DOI:
Zhang Z, Wu S, Stenoien DL, Paša-Tolić L. High-Throughput Proteomics. Annu Rev Anal Chem 2014;7:427-54. DOI:
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:
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:
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:
Edfors F, Iglesias MJ, Butler LM, Odeberg J. Proteomics in thrombosis research. Res Pract Thromb Haemost 2022;6: e12706. DOI:
Aslam B, Basit M, Nisar MA, et al. Proteomics: Technologies and Their Applications. J Chromatogr Sci 2017;55:182-96. DOI:
Uzozie AC, Aebersold R. Advancing translational research and precision medicine with targeted proteomics. J Proteomics 2018;189:1-10. DOI:
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:
Smith JG, Gerszten RE. Emerging Affinity-Based Proteomic Technologies for Large-Scale Plasma Profiling in Cardiovascular Disease. Circulation 2017;135:1651-64. DOI:
Lubec G, Afjehi-Sadat L. Limitations and Pitfalls in Protein Identification by Mass Spectrometry. Chem Rev 2007;107: 3568-84. DOI:
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:
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:
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:
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:
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:
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:
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:
Joshi A, Mayr M. In Aptamers They Trust: Caveats of the SOMAscan Biomarker Discovery Platform From SomaLogic. Circulation 2018;138:2482-5. DOI:
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:
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:
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:
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:
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:
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:
Guo L, Liu M, Huang J, et al Role of interleukin-15 in cardiovascular diseases. J Cell Mol Med 2020;24:7094-101. DOI:
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:
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:
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:
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:
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:
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:
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:
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:
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:
Bussolino F, Valdembri D, Caccavari F, Serini G. Semaphoring vascular morphogenesis. Endothelium 2006;13:81-91. DOI:
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:
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:
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:
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: (accessed on September 27th, 2023) DOI:
Lakhin AV, Tarantul VZ, Gening LV. Aptamers: problems, solutions and prospects. Acta Naturae 2013;5:34-43. DOI:
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:
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:
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:
Raffield LM, Dang H, Pratte KA, et al. Comparison of Proteomic Assessment Methods in Multiple Cohort Studies. PROTEOMICS 2020;20:1900278. DOI:
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:
Eldjarn GH, Ferkingstad E, Lund SH, et al. Large-scale plasma proteomics comparisons through genetics and disease associations. Nature 2023;622:348-58. DOI:
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:
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:
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:
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:
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:
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:
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:
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:
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:

Supporting Agencies

NIH/NCI Cancer Center Support Grant P30 CA008748, Conquer Cancer Foundation, Career Development Award

How 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).