Publication Summaries

Building on our previous summary of ‘Blood and Bone’, where we examined how sample sources affect KIT D816V test sensitivity, we now sharpen our focus on test sensitivity, molecular data interpretation and prognostic insights in SM. How do different detection methods align, and what can mutational burden reveal about disease progression? A recent review by Cilloni et al. sheds light on the recommended methods for diagnosis and follow-up.¹

Powerful -omics tools are unlocking new insights in systemic mastocytosis (SM). This summary highlights the latest proteomics data from Iribarren et al., which aim to identify biomarkers that differentiate SM subtypes with varying prognoses. By comparing SM with another myeloproliferative  disorder, the study also identifies SM-specific biomarkers and delves into their cellular origins.¹

In recent years, several tools have improved systemic mastocytosis (SM) assessment, but there is still a critical need for more precise serum biomarkers to improve diagnosis, subvariant classification and risk stratification. Lübke et al. rigorously evaluated key serum chemistry parameters for diagnosis, prognosis and organ damage in SM, drawing on newly available patient registries.¹

This summary delves into new genetic data that have shaped the updated mastocytosis WHO classification system, and which also shed light on the trajectory of future guidelines.¹

Another key tool in the haematological assessment toolkit is testing for KIT D816V. The presence of this somatic mutation in clonal cells is common in SM. However, the question of which tissue type should be tested for KIT D816V to yield the highest sensitivity result is only just now being answered. Navarro-Navarro et al. recently employed several elegant assays to explore whether different sets of blood or bone marrow samples produce more accurate results for KIT D816V positivity in SM, with the aim of optimising the test’s sensitivity as well as exploring its potential for prognostics.¹

Tryptase measurements have become part of the haematological assessment toolkit for physicians, but their interpretation is only one part of the complex mast cell biology puzzle.¹ So how can we utilise the potential of tryptase levels to home in on the correct diagnosis for patients? Beyens et al. set out a useful algorithm and considerations for the interpretation of tryptase levels in patients.