A combination of platelet features allows detection of early-stage cancer

Background: Detection of early-stage cancer significantly improves patient survival. As platelets play an important role in cancer progression, we aimed to investigate whether platelets can be used for the discovery of early-stage cancer.

Methods: Patients with lung (n = 86) or head of pancreas (n = 42) cancer were included, as were healthy sex-and age-matched controls (n = 92). Blood was collected before initiation of treatment. Platelet count, volume and activation status were quantified in whole blood. Next, concentrations of vascular endothelial growth factor, platelet-derived growth factor, platelet factor 4, thrombospondin-1 and connective tissue-activating peptide III were measured in both platelets and plasma. Using the results, two multivariable diagnostic models were developed and internally validated.

Findings: Multiple platelet features, including platelet count, volume and protein content, were significantly changed in lung and head of pancreas cancer patients. However, the pattern of changes differed between both groups. The diagnostic model developed for lung cancer discriminated very well between patients and controls (AUC = 88.7%). Addition of smoking as a variable significantly increased the AUC of the model to 94.5%. The diagnostic model for head of pancreas cancer also performed well (AUC = 82.7%). Both models were internally validated, resulting in optimism-corrected AUC's of 86.8% and 80.8%, respectively.

Interpretation: In patients with lung or head of pancreas cancer, several platelet characteristics are changed compared to healthy sex-and age-matched controls. A cancer type-specific combination of these platelet features can be used to discriminate between patients with early-stage cancer and healthy individuals. (C) 2017 Elsevier Ltd. All rights reserved.