Plasma proteome screen of individuals with elevated blood counts to identify diagnostic signatures and biomarkers inherent to patients with myeloproliferative neoplasms

The study identifies TFRC as a promising biomarker for diagnosing polycythemia vera, especially when combined with serum erythropoietin.

Summary and findings

This study measured the plasma proteome of 87 patients with elevated blood counts, comparing 55 diagnosed with myeloproliferative neoplasms (MPN) to 32 non-MPN controls. The study identified 189 differentially expressed proteins, with specific biomarkers for MPN subtypes. Diagnostic accuracy for identifying polycythemia vera (PV) increased from 89.3% with TFRC alone to 99.3% when combined with serum erythropoietin.

Abstract

Background The Philadelphia negative myeloproliferative neoplasms (MPN), including essential thrombocythemia (ET), polycythemia vera (PV) and primary myelofibrosis (PMF), are characterized by myeloid cell proliferation, thrombosis and inflammation. Suspicion of MPN arises from increased blood count in one or more lineages; however, knowledge on the MPN plasma proteome including biomarkers measurable in blood, are lacking. Comparing the plasma proteome of MPN patients to subjects with elevated blood counts but without MPN diagnosis, may provide an increased understanding of the MPN disease biology as well as diagnostic biomarkers measurable in blood. Patients and methods We performed plasma proteome profiling in 87 patients referred to the Department of Hematology due to elevated blood counts. Of these, 55 were diagnosed with MPN and 32 did not fulfill MPN diagnostic criteria and thus constituted the non-MPN control group. Results The frequency of thrombosis was equal between the groups. We found 189 differentially expressed proteins between MPN and non-MPN, enriched for Hemostasis and Platelet activation proteins. Using Lasso multiple regression, we identified SORT1, GP1BA, PSPN, MMP1 and BAG6 separating MPN from non-MPN individuals, and TFRC and SEMA7A specific for MPN subtype PV. Interestingly, TFRC alone had a diagnostic accuracy for identifying PV of 89.3%, and when combined with serum erythropoietin it increased to 99.3%. Only two proteins, IL-6 and GH1, were increased in JAK2 mutant MPN compared to JAK2 wildtype MPN. The same trend was seen for JAK2 mutant ET compared to JAK2 wildtype ET, indicating that IL-6 is induced by JAK STAT activation. However, IL-6 levels did not differ between MPN and non-MPN patients. Discussion/conclusion In conclusion, hemostasis and platelet activation are inherent to MPN disease whereas little difference was found in proinflammatory cytokines between MPN and non-MPN groups. We demonstrate novel potential blood biomarkers for MPN and MPN subtypes, in particular TFRC for identifying PV patients.

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