Indolent systemic mastocytosis (ISM) patients have a normal life-expectancy, except for 5-10% cases that progress to more advanced SM (advSM) with a significantly poorer outcome. Mutations in genes other than KIT frequently found in myeloid neoplasms have been associated with a poorer outcome among advSM, while limited information exists about their frequency and prognostic impact in ISM. Here we investigated the frequency and prognostic impact of variants in 18 genes previously found to be altered in advSM, in 322 ISM patients (median follow-up of 5.7y) divided into a discovery (n=200) and a validation (n=122) cohort. Overall, 71 genetic variants were detected in 55/322 (17%) patients. Mutated ISM cases, particularly those carrying ASXL1, RUNX1 and/or DNMT3A pathogenic variant allele frequencies (VAF) {greater than or equal to}30%, displayed significantly shortened (p<.001) progression-free (PFS) and overall survival (OS) rates. Multivariate analysis showed that serum β2-microglobulin levels >2.5µg/mL (hazard ratio -HR-: 9.8; p=.001) together with a KIT D816V VAF {greater than or equal to}1% in bone marrow (HR: 10.1; p=.02) and pathogenic variants of ASXL1, RUNX1 and/or DNMT3A (A/R/D) VAF {greater than or equal to}30% (HR: 4.2; p=.02) were the best combination of independent predictors for PFS; In turn, A/R/D gene pathogenic VAF {greater than or equal to}30% was the only independent predictor for OS (HR: 51.8; p<.001). Based on these variables two scoring systems were built for risk-stratification of ISM at diagnosis with significantly different 10y PFS (100%, 91% and 0% for scores of 0, 1 and {greater than or equal to}2, respectively) and OS (100% vs 50% for scores of 0 and 1) rates. Key Points D816V KIT allele frequency in BM, higher sβ2M levels and ASXL1/RUNX1/DNMT3A pathogenic mutations identify ISM cases at risk of progression. Pathogenic mutations in the ASXL1/RUNX1/DNMT3A genes identify ISM cases with multilineal KIT and poorer prognosis.

During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors.

Systemic mastocytosis (SM) is a highly heterogeneous disease with indolent and aggressive forms, with the mechanisms leading to malignant transformation still remaining to be elucidated. Here, we investigated the presence and frequency of genetic variants in 34 SM patients with multilineal KIT D816V mutations. Initial screening was performed by targeted sequencing of 410 genes in DNA extracted from purified bone marrow cells and hair from 12 patients with nonadvanced SM and 8 patients with advanced SM, followed by whole-genome sequencing (WGS) in 4 cases. Somatic mutations were further investigated in another 14 patients with advanced SM. Despite the fact that no common mutation other than KIT D816V was found in WGS analyses, targeted next-generation sequencing identified 67 nonsynonymous genetic variants involving 39 genes. Half of the mutations were somatic (mostly multilineal), whereas the other half were germline variants. The presence of ≥1 multilineal somatic mutation involving genes other than KIT D816V, ≥3 germline variants, and ≥1 multilineal mutation in the SRSF2, ASXL1, RUNX1, and/or EZH2 genes (S/A/R/E genes), in addition to skin lesions, splenomegaly, thrombocytopenia, low hemoglobin levels, and increased alkaline phosphatase and β2-microglobulin serum levels, were associated with a poorer patient outcome. However, the presence of ≥1 multilineal mutation, particularly involving S/A/R/E genes, was the only independent predictor for progression-free survival and overall survival in our cohort. Key Points About half of the mutations other than KIT D816V identified in SM patients were germline in nature. Somatic EZH2 gene mutations provide prognostic information in addition to that of the well-established S/A/R gene panel. Visual Abstract

Microarrays constitute a new platform which allows the discovery and characterization of proteins. According to different features, such as content, surface or detection system, there are many types of protein microarrays which can be applied for the identification of disease biomarkers and the characterization of protein expression patterns. However, the analysis and interpretation of the amount of information generated by microarrays remain a challenge. Further data analysis strategies are essential to obtain representative and reproducible results. Therefore, the experimental design is key, since the number of samples and dyes, among others aspects, would define the appropriate analysis method to be used. In this sense, several algorithms have been proposed so far to overcome analytical difficulties derived from fluorescence overlapping and/or background noise. Each kind of microarray is developed to fulfill a specific purpose. Therefore, the selection of appropriate analytical and data analysis strategies is crucial to achieve successful biological conclusions. In the present review, we focus on current algorithms and main strategies for data interpretation.