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- Gavriilidis, GI, et al.
(författare)
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Stem cell factor is implicated in microenvironmental interactions and cellular dynamics of chronic lymphocytic leukemia
- 2021
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Ingår i: Haematologica. - : Ferrata Storti Foundation (Haematologica). - 1592-8721 .- 0390-6078. ; 106:3, s. 692-700
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Tidskriftsartikel (refereegranskat)abstract
- The inflammatory cytokine Stem Cell Factor (SCF, ligand of c-kit receptor) has been implicated as a pro-oncogenic driver and an adverse prognosticator in several human cancers. Increased SCF levels have recently been reported in a small series of patients with chronic lymphocytic leukemia (CLL), however its precise role in CLL pathophysiology remains elusive. In this study, CLL cells were found to predominantly express the membrane isoform of SCF that is known to elicit a more robust activation of the c-kit receptor. SCF was significantly overexpressed in CLL cells compared to healthy tonsillar B cells whilst it correlated with adverse-prognostic biomarkers, shorter time-to-first treatment and shorter overall survival. Activation of immune receptors and long-term cell-cell interactions with the mesenchymal stroma led to an elevation of SCF primarily in adverse-prognostic CLL cases. On the contrary, suppression of oxidative stress and the BTK inhibitor Ibrutinib negated SCF levels. Interestingly, SCF significantly correlated with mitochondrial dynamics and HIF-1α which have previously been linked with clinical aggressiveness in CLL. SCF was able to elicit direct biological effects in CLL cells affecting redox homeostasis and cell proliferation. Overall, the aberrantly expressed SCF in CLL cells emerges as a key response regulator to microenvironmental stimuli whilst correlating with poor prognosis. On these grounds, specific targeting of this inflammatory molecule could serve as a novel therapeutic approach in CLL.
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- Leeksma, AC, et al.
(författare)
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Genomic arrays identify high-risk chronic lymphocytic leukemia with genomic complexity: a multi-center study
- 2021
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Ingår i: Haematologica. - : Ferrata Storti Foundation (Haematologica). - 1592-8721 .- 0390-6078. ; 106:1, s. 87-97
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Tidskriftsartikel (refereegranskat)abstract
- Complex karyotype (CK) identified by chromosome-banding analysis (CBA) has shown prognostic value in chronic lymphocytic leukemia (CLL). Genomic arrays offer high-resolution genome-wide detection of copy-number alterations (CNAs) and could therefore be well equipped to detect the presence of a CK. Current knowledge on genomic arrays in CLL is based on outcomes of single center studies, in which different cutoffs for CNA calling were used. To further determine the clinical utility of genomic arrays for CNA assessment in CLL diagnostics, we retrospectively analyzed 2293 arrays from 13 diagnostic laboratories according to established standards. CNAs were found outside regions captured by CLL FISH probes in 34% of patients, and several of them including gains of 8q, deletions of 9p and 18p (p<0.01) were linked to poor outcome after correction for multiple testing. Patients (n=972) could be divided in three distinct prognostic subgroups based on the number of CNAs. Only high genomic complexity (high-GC), defined as ≥5 CNAs emerged as an independent adverse prognosticator on multivariable analysis for time to first treatment (Hazard ratio: 2.15, 95% CI: 1.36-3.41; p=0.001) and overall survival (Hazard ratio: 2.54, 95% CI: 1.54-4.17; p<0.001; n=528). Lowering the size cutoff to 1 Mb in 647 patients did not significantly improve risk assessment. Genomic arrays detected more chromosomal abnormalities and performed at least as well in terms of risk stratification compared to simultaneous chromosome banding analysis as determined in 122 patients. Our findings highlight genomic array as an accurate tool for CLL risk stratification.
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- Wittek, Peter, et al.
(författare)
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Monitoring Term Drift Based on SemanticConsistency in an Evolving Vector Field
- 2015
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Ingår i: Proceedings of IJCNN-15.
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Konferensbidrag (refereegranskat)abstract
- Based on the Aristotelian concept of potentialityvs. actuality allowing for the study of energy and dynamics inlanguage, we propose a field approach to lexical analysis. Fallingback on the distributional hypothesis to statistically model wordmeaning, we used evolving fields as a metaphor to express timedependentchanges in a vector space model by a combinationof random indexing and evolving self-organizing maps (ESOM).To monitor semantic drifts within the observation period, anexperiment was carried out on the term space of a collection of12.8 million Amazon book reviews. For evaluation, the semanticconsistency of ESOM term clusters was compared with theirrespective neighbourhoods in WordNet, and contrasted withdistances among term vectors by random indexing. We found thatat 0.05 level of significance, the terms in the clusters showed a highlevel of semantic consistency. Tracking the drift of distributionalpatterns in the term space across time periods, we found thatconsistency decreased, but not at a statistically significant level.Our method is highly scalable, with interpretations in philosophy.
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