Expression of high amounts of the CD117 molecule in a case of B-cell non-Hodgkin's lymphoma carrying the t(14:18) translocation.

The c-kit proto-oncogen (CD117) has been described to be present in normal and neoplastic hemopoietic cells including both myeloid and lymphoid lineages. Among the normal lymphoid cells CD117 expression would be restricted to a small subset of NK-cells, and to early T-cell precursors and it is not expressed by normal B-cells. Regarding chronic lymphoproliferative disorders the only data provided up to now suggests that CD117 expression is restricted to cases of Hodgkin's disease and anaplastic large-cell lymphoma. In the present paper we describe a case of a B-cell chronic lymphoproliferative disorder carrying the t(14:18) translocation as demonstrated by molecular studies, in which the flow cytometric immunophenotypic analysis of both peripheral blood and bone marrow samples revealed the expression of high amounts of the CD117 antigen in the surface of the clonal B-cell population. Further studies are necessary to explore both the functional role of c-kit expression in the neoplastic B-cells from this patient and its potential utility for the diagnosis and follow-up of patients with B-cell non-Hodgkin's lymphoma.

Multivariate analysis of regional-scale geochemical data for environmental monitoring

A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.