Validation of the Role of Thrombin Generation Potential by a Fully Automated System in the Identification of Breast Cancer Patients at High Risk of Disease Recurrence

Patricia Gomez-Rosas, Marina Pesenti, Cristina Verzeroli, Cinzia Giaccherini, Laura Russo, Roberta Sarmiento, Giovanna Masci, Luigi Celio, Mauro Minelli, Sara Gamba, Carmen Julia Tartari, Carlo Tondini, Francesco Giuliani, Fausto Petrelli, Andrea D'Alessio, Giampietro Gasparini, Roberto Labianca, Armando Santoro, Filippo De Braud, Marina Marchetti, Anna Falanga, HYPERCAN Investigators, Patricia Gomez-Rosas, Marina Pesenti, Cristina Verzeroli, Cinzia Giaccherini, Laura Russo, Roberta Sarmiento, Giovanna Masci, Luigi Celio, Mauro Minelli, Sara Gamba, Carmen Julia Tartari, Carlo Tondini, Francesco Giuliani, Fausto Petrelli, Andrea D'Alessio, Giampietro Gasparini, Roberto Labianca, Armando Santoro, Filippo De Braud, Marina Marchetti, Anna Falanga, HYPERCAN Investigators

Abstract

Background The measurement of thrombin generation (TG) potential by the calibrated automated thrombogram (CAT) assay provides a strong contribution in identifying patients at high risk of early disease recurrence (E-DR). However, CAT assay still needs standardization and clinical validation. Objective In this study, we aimed to validate the role of TG for E-DR prediction by means of the fully automated ST Genesia system. Methods A prospective cohort of 522 patients from the HYPERCAN study with newly diagnosed resected high-risk breast cancer was included. Fifty-two healthy women acted as controls. Plasma samples were tested for protein C, free-protein S, and TG by ST Genesia by using the STG-ThromboScreen reagent with and without thrombomodulin (TM). Results In the absence of TM, patients showed significantly higher peak and ETP compared with controls. In the presence of TM, significantly lower inhibition of ETP and Peak were observed in patients compared with controls. E-DR occurred in 28 patients; these patients had significantly higher peak and endogenous thrombin potential (ETP) in the absence of TM compared with disease-free patients. Multivariable analysis identified mastectomy, luminal B HER2-neg, triple negative subtypes, and ETP as independent risk factors for E-DR. These variables were combined to generate a risk assessment score, able to stratify patients in three-risk categories. The E-DR rates were 0, 4.7, and 13.5% in the low-, intermediate-, and high-risk categories (hazard ratio = 8.7; p < 0.05, low vs. high risk). Conclusion Our data validate the ETP parameter with a fully automated standardized system and confirm its significant contribution in identifying high-risk early breast cancer at risk for E-DR during chemotherapy.

Keywords: breast cancer; disease recurrence; hypercoagulability; risk model; thrombin generation.

Conflict of interest statement

Conflict of Interest None declared.

The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. ( https://creativecommons.org/licenses/by/4.0/ ).

Figures

Fig. 1
Fig. 1
Endogenous thrombin generation potential inhibition and peak inhibition (A) in patients compared with controls and (B) in patients with E-DR compared with DF. E-DR, early disease recurrence; DF, disease free.
Fig. 2
Fig. 2
Thrombin generation parameters in the absence and presence of thrombomodulin according to early disease recurrence. ETP, endogenous thrombin potential; TM, thrombomodulina; E-DR, early disease recurrence; DF, disease free.
Fig. 3
Fig. 3
Receiver operating characteristic curve analysis for ETP-based score (A) and nETP-based score (B). ETP, endogenous thrombin potential.
Fig. 4
Fig. 4
Cumulative incidence of E-DR after curative surgery for breast cancer stratified by ETP-based score (A) and nETP-based score (B). (A) The E-DR rates by the ETP-based score were 0.8, 4.9, and 11.8% in the low-, intermediate-, and high-risk categories. Low versus high risk: HR = 14.7 (95% CI: 1.94–112;p = 0.009); Intermediate versus high risk: HR = 2.49 (95% CI: 1.15–5.39;p = 0.020. (B) The E-DR rates by the nETP-based score were 0, 4.7, and 13.5% in the low-, intermediate-, and high-risk categories. Low versus high risk: HR = 8.70 (95% CI: 1.08–70;p = 0.042); intermediate versus high risk: HR = 2.99 (95% CI: 1.40–6.41;p = 0.005). CI, confidence interval; E-DR, early disease recurrence; ETP, endogenous thrombin potential; HR, hazard ratio.

References

    1. Eichinger S. Cancer associated thrombosis: risk factors and outcomes. Thromb Res. 2016;140 01:S12–S17.
    1. Mahajan A, Brunson A, White R, Wun T. The epidemiology of cancer-associated venous thromboembolism: an update. Semin Thromb Hemost. 2019;45(04):321–325.
    1. Falanga A, Russo L, Milesi V. The coagulopathy of cancer. Curr Opin Hematol. 2014;21(05):423–429.
    1. Falanga A. Thrombophilia in cancer. Semin Thromb Hemost. 2005;31(01):104–110.
    1. Abdol Razak N B, Jones G, Bhandari M, Berndt M C, Metharom P. Cancer-associated thrombosis: an overview of mechanisms, risk factors, and treatment. Cancers (Basel) 2018;10(10):E380.
    1. Remiker A S, Palumbo J S. Mechanisms coupling thrombin to metastasis and tumorigenesis. Thromb Res. 2018;164 01:S29–S33.
    1. Falanga A, Marchetti M, Vignoli A, Balducci D. Clotting mechanisms and cancer: implications in thrombus formation and tumor progression. Clin Adv Hematol Oncol. 2003;1(11):673–678.
    1. Rickles F R, Falanga A. Activation of clotting factors in cancer. Cancer Treat Res. 2009;148:31–41.
    1. Pabinger I, van Es N, Heinze G. A clinical prediction model for cancer-associated venous thromboembolism: a development and validation study in two independent prospective cohorts. Lancet Haematol. 2018;5(07):e289–e298.
    1. COMPASS–CAT Working Group . Gerotziafas G T, Taher A, Abdel-Razeq H. A predictive score for thrombosis associated with breast, colorectal, lung, or ovarian cancer: the prospective COMPASS-cancer-associated thrombosis study. Oncologist. 2017;22(10):1222–1231.
    1. Zwicker J I, Furie B C, Furie B. Cancer-associated thrombosis. Crit Rev Oncol Hematol. 2007;62(02):126–136.
    1. Giaccherini C, Marchetti M, Masci G.Thrombotic biomarkers for risk prediction of malignant disease recurrence in patients with early stage breast cancerHaematologica2019
    1. Falanga A, Marchetti M. Hemostatic biomarkers in cancer progression. Thromb Res. 2018;164 01:S54–S61.
    1. Falanga A, Marchetti M, Massi D.Thrombophilic status may predict prognosis in patients with metastatic BRAFV600-mutated melanoma who are receiving BRAF inhibitors J Am Acad Dermatol 201674061254–1.256E7., e4
    1. HYPERCAN Study Group . Falanga A, Santoro A, Labianca R. Hypercoagulation screening as an innovative tool for risk assessment, early diagnosis and prognosis in cancer: the HYPERCAN study. Thromb Res. 2016;140 01:S55–S59.
    1. HYPERCAN Investigators . Marchetti M, Giaccherini C, Masci G. Thrombin generation predicts early recurrence in breast cancer patients. J Thromb Haemost. 2020;18(09):2220–2231.
    1. Tripodi A. Thrombin generation assay and its application in the clinical laboratory. Clin Chem. 2016;62(05):699–707.
    1. De Smedt E, Hemker H C. Thrombin generation is extremely sensitive to preheating conditions. J Thromb Haemost. 2011;9(01):233–234.
    1. Subcommittee on Factor VIII, Factor IX, and Rare Coagulation Disorders . Dargaud Y, Wolberg A S, Gray E, Negrier C, Hemker H C. Proposal for standardized preanalytical and analytical conditions for measuring thrombin generation in hemophilia: communication from the SSC of the ISTH. J Thromb Haemost. 2017;15(08):1704–1707.
    1. Duarte R CF, Rios D RA, Rezende S M, Jardim L L, Ferreira C N, Carvalho M DG. Standardization and evaluation of the performance of the thrombin generation test under hypo- and hypercoagulability conditions. Hematol Transfus Cell Ther. 2019;41(03):244–252.
    1. Dargaud Y, Luddington R, Gray E. Standardisation of thrombin generation test--which reference plasma for TGT? An international multicentre study. Thromb Res. 2010;125(04):353–356.
    1. Dargaud Y, Wolberg A S, Luddington R. Evaluation of a standardized protocol for thrombin generation measurement using the calibrated automated thrombogram: an international multicentre study. Thromb Res. 2012;130(06):929–934.
    1. Spronk H M, Dielis A W, De Smedt E. Assessment of thrombin generation II: validation of the calibrated automated thrombogram in platelet-poor plasma in a clinical laboratory. Thromb Haemost. 2008;100(02):362–364.
    1. Ljungkvist M, Strandberg K, Berntorp E. Evaluation of a standardized protocol for thrombin generation using the calibrated automated thrombogram: a Nordic study. Haemophilia. 2019;25(02):334–342.
    1. Calzavarini S, Brodard J, Quarroz C. Thrombin generation measurement using the ST Genesia Thrombin Generation System in a cohort of healthy adults: normal values and variability. Res Pract Thromb Haemost. 2019;3(04):758–768.
    1. Douxfils J, Morimont L, Bouvy C. Assessment of the analytical performances and sample stability on ST Genesia system using the STG-DrugScreen application. J Thromb Haemost. 2019;17(08):1273–1287.
    1. Siguret V, Abdoul J, Delavenne X. Rivaroxaban pharmacodynamics in healthy volunteers evaluated with thrombin generation and the active protein C system: modeling and assessing interindividual variability. J Thromb Haemost. 2019;17(10):1670–1682.
    1. Pfrepper C, Metze M, Siegemund A, Klöter T, Siegemund T, Petros S. Direct oral anticoagulant plasma levels and thrombin generation on ST Genesia system. Res Pract Thromb Haemost. 2020;4(04):619–627.
    1. Roullet S, Labrouche S, Freyburger G. Comparison of two thrombin generation methods, CAT and ST-genesia, in liver transplant patients. Thromb Haemost. 2019;119(06):899–905.
    1. Talon L, Sinegre T, Lecompte T. Hypercoagulability (thrombin generation) in patients with cirrhosis is detected with ST-Genesia. J Thromb Haemost. 2020;18(09):2177–2190.
    1. Morrow G B, Beavis J, Harper S. Coagulation status of critically ill patients with and without liver disease assessed using a novel thrombin generation analyzer. J Thromb Haemost. 2020;18(07):1576–1585.
    1. Zermatten M G, Fraga M, Calderara D B, Aliotta A, Moradpour D, Alberio L. Biomarkers of liver dysfunction correlate with a prothrombotic and not with a prohaemorrhagic profile in patients with cirrhosis. JHEP Rep. 2020;2(04):100120.
    1. Mantovani A, Danese E, Salvagno G L.Association between lower plasma adiponectin levels and higher plasma thrombin generation parameters in men with type 2 diabetes: role of plasma triglyceridesJ Endocrinol Invest2020
    1. American Society of Clinical Oncology ; College of American Pathologists . Wolff A C, Hammond M E, Hicks D G. Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. Arch Pathol Lab Med. 2014;138(02):241–256.
    1. Loeffen R, Kleinegris M C, Loubele S T. Preanalytic variables of thrombin generation: towards a standard procedure and validation of the method. J Thromb Haemost. 2012;10(12):2544–2554.
    1. Colleoni M, Sun Z, Price K N. Annual hazard rates of recurrence for breast cancer during 24 years of follow-up: results from the international breast cancer study group trials I to V. J Clin Oncol. 2016;34(09):927–935.
    1. Bouwens E A, Stavenuiter F, Mosnier L O. Mechanisms of anticoagulant and cytoprotective actions of the protein C pathway. J Thromb Haemost. 2013;11 01:242–253.
    1. Nijziel M R, van Oerle R, Christella M. Acquired resistance to activated protein C in breast cancer patients. Br J Haematol. 2003;120(01):117–122.
    1. Tinholt M, Viken M K, Dahm A E. Increased coagulation activity and genetic polymorphisms in the F5, F10 and EPCR genes are associated with breast cancer: a case-control study. BMC Cancer. 2014;14:845.
    1. Chaari M, Ayadi I, Rousseau A. Impact of breast cancer stage, time from diagnosis and chemotherapy on plasma and cellular biomarkers of hypercoagulability. BMC Cancer. 2014;14:991.
    1. Tinholt M, Sandset P M, Mowinckel M C. Determinants of acquired activated protein C resistance and D-dimer in breast cancer. Thromb Res. 2016;145:78–83.
    1. Falanga A, Schieppati F, Russo D. Cancer tissue procoagulant mechanisms and the hypercoagulable state of patients with cancer. Semin Thromb Hemost. 2015;41(07):756–764.

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