Amyloidosis is a shared name for several rare, complex and serious diseases caused by extra-cellular deposits of different misfolded proteins. Accurate characterization of the amyloid protein is essential for patient care. Immunoelectron microscopy (IEM) and laser microdissection followed by tandem mass spectrometry (LMD-MS) are new gold standards for molecular subtyping. Both methods perform superiorly to immunohistochemistry, but their complementarities, strengths and weaknesses across amyloid subtypes and organ biopsy origin remain undefined. Therefore, we performed a retrospective study of 106 Congo Red positive biopsies from different involved organs; heart, kidney, lung, gut mucosa, skin and bone marrow. IEM, performed with gold-labelled antibodies against kappa light chains, lambda light chains, transthyretin and amyloid A, identified specific staining of amyloid fibrils in 91.6%; in six biopsies amyloid fibrils were not identified, and in two, the fibril subtype could not be established. LMD-MS identified amyloid protein signature in 98.1%, but in nine the amyloid protein could not be clearly identified. MS identified protein subtype in 89.6%. Corresponding specificities ranged at organ level from 94-100%. Concordance was 89.6-100% for different amyloid subtypes. Importantly, combined use of both methods increased the diagnostic classification to 100%. Some variety in performances at organ level was observed.
Chromosomal aberrations have significant prognostic importance in multiple myeloma (MM). However, proteasome inhibitors (PI) and IMiDs may partly overcome the poor prognostic impact of some of them. In this study, we investigated a population-based consecutive cohort newly diagnosed patients with MM admitted during a defined time period to hospitals in Denmark, Norway, and Sweden. The impact of treatment modality on the prognostic importance of specific chromosomal aberration was investigated, with special reference to gain 1q21. The median follow-up of patients still alive at analysis was 40 months for the high-dose (HDT)-treated ones and 29 months for the whole population. Three hundred forty-seven patients with a known 1q21 status were included in this study. The 347 patients were divided into three groups, that is, 119 patients with the 1q21 gain, 105 patients with other aberrations (OA), that is, del(13q), del(17p), t(4,14), and/or (14;16), and 123 patients with no aberrations (NA). The groups were compared in terms of overall survival (OS), time to progression (TTP), and response. The 3-yr OS for patients with gain 1q21 was 60% compared to patients with OA 74% and NO 82% (gain 1q21 vs. NO P < 0.001; gain 1q21 vs. OA P = 0.095). If treated with PI or IMiDs, the 3-yr OS was 58% for patients with gain 1q21 compared to patients with OA 78% and NO 78%, respectively (P = 0.041, P = 0.140). In HDT patients, the 3-yr OS was 69% for patients with gain 1q21 compared to patients with OA 84% and NO 88%, respectively (P < 0.008, P = 0.600). Thus, neither HDT nor using PI or IMiDs could overcome the poor prognostic impact of gain 1q21, while these drugs and HDT seemed to improve OS in patients with OA, approaching the survival in NO. Further, gain 1q21 appears to be one of the most important poor prognostic chromosomal aberrations in multiple myeloma with current treatments. Trials using new drugs or allogeneic transplantation are warranted.
Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically throughout the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril-forming protein, and its accurate identification is essential to the choice of treatment. Mass spectrometry-based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective interpretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model-assisted method for the unbiased identification of amyloid-containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid-containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid-containing biopsies and 78 Congo Red negative biopsies to identify novel “amyloid signature” proteins that included clusterin, fibulin-1, vitronectin complement component C9 and also three collagen proteins, as well as the well-known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid-negative control biopsies. The trained algorithm performed superior in the discrimination of amyloid-containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected amyloid-containing biopsies. Moreover, our method successfully classified amyloidosis patients according to the subtype in 102 out of 103 blinded cases. Collectively, our model-assisted approach identified novel amyloid-associated proteins and demonstrated the use of mass spectrometry-based data in clinical diagnostics of disease by the unbiased and reliable model-assisted classification of amyloid deposits and of the specific amyloid subtype.
Multiple myeloma (MM) is a common malignant hematological disease displaying considerable heterogeneity. Historical data indicate a prognostic significance of plasmablastic morphology, proliferation, and adverse cytogenetics, but there is little knowledge on the degree of interdependency of these parameters. The aim of this study was to study the degree of overlap between these variables. In a consecutive population-based cohort of 194 untreated MM patients, morphology, and proliferation index, using immunohistochemical double staining for Ki-67 and CD138, was analyzed. In addition, cytogenetic changes were studied by karyotyping and fluorescence in situ hybridization (FISH). Plasmablastic morphology correlated with unfavorable clinical features, high proliferation index, high percentage of plasma cell infiltration in the bone marrow, abnormal karyotype, and del(13q) detected by karyotyping, which indicates that plasmablastic morphology reflects advanced and highly proliferative disease. However, plasmablastic morphology did not correlate with established adverse prognostic cytogenetics identified by FISH, for example, t(4;14), t(14;16) and del(17p).
Our results indicate myc protein overexpression to be associated with advanced multiple myeloma and poor prognosis.
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