Hemostasis and cancer: Impact of haemostatic biomarkers for the prediction of clinical outcomes in patients with cancer. (27th September 2022)

• Record Type: Journal Article
• Authors: Moik, Florian; Ay, Cihan
• Is Part Of: Journal of thrombosis and haemostasis. Volume 20:Number 12(2022)
• Page Start: 2733
• Page End: 2745
• Publication Date: 2022-09-27
• Subjects: biomarkers -- cancer -- clinical decision‐making -- hemostasis -- prognosis; Thrombosis -- Periodicals; Hemostasis -- Periodicals; Blood coagulation disorders -- Periodicals; 616.1
• DOI: 10.1111/jth.15880
• Languages: English
• ISSNs: 1538-7933

Abstract

Abstract: Patients with cancer are characterized by a dysregulation of the hemostatic system and systemic hypercoagulability. Different components of the hemostatic system are involved in tumor‐promoting mechanisms including primary tumor growth, cancer cell invasion, immune evasion, angiogenesis, and the metastatic process. Therefore, different degrees of systemic hemostatic activation in patients with cancer can reflect distinct underlying biological phenotypes of cancer and seem to correlate with cancer aggressiveness. Peripheral blood levels of hemostatic biomarkers, indicating the activation status of different parts of the hemostatic system including the coagulation cascade, fibrinolytic activity, platelet activation, or endothelial activation, can be used to reflect cancer‐associated systemic hypercoagulability. Thereby, hemostatic biomarkers represent promising candidates to investigate as surrogate markers for underlying cancer activity and progression dynamics and therefore as biomarkers for the prediction of clinical outcomes in cancer patients. In the present review, we provide an up‐to‐date summary of available data on hemostatic biomarkers for prognostication of overall survival and prediction of therapy response in patients with cancer, including specific oncologic treatment settings for potential clinical application. We provide a thorough discussion on potential clinical implementation and current limitations and highlight the most promising emerging biomarkers that might be used to contribute to risk‐stratified, personalized oncologic decision making in the future.