Refining the lens: Advancing KIT D816V testing in systemic mastocytosis
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
Introduction
Systemic mastocytosis (SM) is a rare but complex disorder driven by the accumulation of abnormal mast cells, caused by KIT D816V mutation in ~90% of cases.1,2 KIT is predominantly expressed in a few immune cell types only – mast cells, natural killer cells and dendritic cells – posing a challenge for detection. Yet, accurate identification of KIT D816V in SM is key, not only for diagnosis but also for prognosis and treatment decisions.1
As Cilloni et al. discuss in their review, how can we refine testing strategies to maximise sensitivity and minimise the number of undetected cases?
Choosing the right detection method
Detecting KIT D816V requires highly sensitive measurement techniques, as the mutant allele is often present at very low levels in both the blood and bone marrow.1 Current methodologies vary in sensitivity, with allele-specific oligonucleotide-quantitative PCR (ASO-qPCR) and droplet digital PCR (ddPCR) outperforming next-generation sequencing (NGS) in detecting low variant allele frequencies (VAFs) (see Figure 1).1,3
For example, a comparison of sensitivity shows that qPCR can detect mutations as low as 0.001% VAF, and the limit of detection (LoD) required for diagnosing SM is approximately 0.01% – standard techniques such as NGS, with LoD ranging between 1% and 5% VAF, can be inadequate for the challenge.1
Figure 1. Comparison of KIT detection methods: sensitivity vs LoD3
When the test is negative: What comes next?
In 5–10% of cases, the KIT D816V mutation may not be detected despite clinical suspicion. The EU-US Cooperative Group outlines three key scenarios to subsequently consider in Figure 2.1
Figure 2. Possible scenarios for negative KIT D816V results
Retesting with a more sensitive method is essential if the initial test used low-sensitivity techniques, to rule out false negatives. For instance, a negative result from peripheral blood (PB) does not altogether rule out SM as it may miss bone marrow (BM) involvement. Re-analysis using a high-quality BM sample – potentially with mast cell enrichment – can enhance detection. Additionally, borderline PB genomic DNA (gDNA) results often yield more reliable outcomes when higher DNA quantities are used, emphasising the importance of sample quality.1
If a patient is still experiencing signs of mast cell infiltration despite a negative KIT D816V result, Cilloni et al. recommended exploring beyond D816V to other KIT mutations. While reverse transcription (RT)-PCR and ddPCR detect only D816V, NGS can identify alternative mutations and assess VAF. This is particularly crucial in cases of co-existing myeloid disorders, such as myelodysplastic syndromes or myeloproliferative neoplasms, underscoring the need for comprehensive molecular testing.1
The prognostic power of KIT VAF
Beyond its diagnostic role, KIT D816V mutation burden has emerged as a powerful prognostic indicator. The extent of multilineage involvement, as reflected by KIT VAF, is significantly correlated with disease progression.1 For example, Naumann et al. (2021) demonstrated that patients with KIT VAF ≤2% had significantly better overall survival compared to those with KIT VAF >2% (P=0.005).4 Similarly, Navarro-Navarro et al. (2023) found that patients with KIT VAF >3.5% were associated with worse 10-year progression-free survival (P<0.0001).5
NGS: Unlocking a bigger picture
While challenging for the detection of KIT mutation, the aforementioned NGS can serve to uncover additional genetic and cytogenetic alterations that shape prognosis and treatment decisions in SM. Crucially, in advanced SM, mutations in SRSF2, ASXL1, and RUNX1 (S/A/R panel) signal worse clinical outcomes, including progression to mast cell leukaemia. NGS also detects cytogenetic abnormalities, such as monosomy 7 and complex karyotypes, linked to disease evolution. By integrating NGS into routine diagnostics, we gain a deeper understanding of SM heterogeneity—enhancing risk stratification.1
Conclusion: Towards a future of precision diagnosis and prognosis in SM
The interplay between mast cell infiltration, KIT D816V VAF, serum tryptase levels and S/A/R mutations provides a comprehensive framework for assessing SM severity and prognosis. KIT VAF correlates with mast cell burden and tryptase levels, while S/A/R mutations further refine prognosis, particularly in adverse outcomes. The distinction between low and high myeloid involvement highlights the heterogeneity of SM.1
As our understanding of KIT D816V testing deepens, so does our ability to refine SM diagnostics. Cilloni et al. highlight that while high-sensitivity PCR methods remain the gold standard, integrating broader genomic insights and biomarker analysis enhances diagnostic accuracy and predictive power for patients living with SM.1
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