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The contribution of the most common reciprocal translocation in childhood B-cell precursor leukemia t(12;21)(p13;q22) to leukemia development is still under debate. Direct as well as secondary indirect effects of the TEL-AML1 fusion protein are commonly recorded by using cell lines and patient samples, often bearing the TEL-AML1 fusion protein for decades. To identify direct targets of the fusion protein a short-term induction of TEL-AML1 is needed. We here describe in detail the experimental procedure, quality controls and contents of the ChIP, mRNA expression and SILAC datasets associated with the study published by Linka and colleagues in the Blood Cancer Journal [1] utilizing a short term induction of TEL-AML1 in an inducible precursor B-cell line model.
Grid Infrastrukturen sind heute in der Lage, auch große Datenmengen verteilt zu verarbeiten. Ein Anwendungsgebiet, das davon profitiert, ist das Textmining. Es zeichnet sich vor allem durch die große Anzahl voneinander unabhängiger Teiljobs aus, in die eine Aufgabe zerlegt werden kann. Um die Gesamtlaufzeit bis zur Fertigstellung eines Textmininglaufes für einen großen Datenbestand zu optimieren, ist Load-Balancing unerlässlich. Dafür muss abgeschätzt werden, wie lange eine Ressource für die Lösung eines Teilproblems benötigt. Diese Abschätzungen beruhen auf den Aufzeichnungen vorangegangener Textminingverarbeitungen. Sind darüber noch keine Daten vorhanden, muss die Laufzeitvorhersage anhand der Leistungsfähigkeit der Hardware einer Ressource prognostiziert werden. Wir stellen in dieser Arbeit Methoden vor, mit denen die Laufzeit für Textmining-Applikationen mittels historischer Daten und Hardwareeigenschaften vorhergesagt werden kann. Dabei nutzen wir Methoden der Statistik und des maschinellen Lernens, um eine Prognose zu berechnen. Anschließend wird ein Dienst vorgestellt, der eine Laufzeitvorhersage im Grid anbietet. Er kann auch für andere Anwendungsgebiete als das Textmining eingesetzt werden und ist in der Lage, Informationen über die Laufzeiten von Jobs auf den Ressourcen abzurufen. Dazu nutzt er bereits vorhandene Dienste der Grid-Middleware und kann sich so dynamisch in bestehende Strukturen eingliedern.
Preleukemic clones carrying BCR-ABLp190 oncogenic lesions are found in neonatal cord blood, where the majority of preleukemic carriers do not convert into precursor B-cell acute lymphoblastic leukemia (pB-ALL). However, the critical question of how these preleukemic cells transform into pB-ALL remains undefined. Here we model a BCR-ABLp190 preleukemic state and show that limiting BCR-ABLp190 expression to hematopoietic stem/progenitor cells (HS/PC) in mice (Sca1-BCR-ABLp190) causes pB-ALL at low penetrance, which resembles the human disease. pB-ALL blast cells were BCR-ABL-negative and transcriptionally similar to pro-B/pre-B cells, suggesting disease onset upon reduced Pax5 functionality. Consistent with this, double Sca1-BCR-ABLp190+Pax5+/- mice developed pB-ALL with shorter latencies, 90% incidence, and accumulation of genomic alterations in the remaining wild-type Pax5 allele. Mechanistically, the Pax5-deficient leukemic pro-B cells exhibited a metabolic switch towards increased glucose utilization and energy metabolism. Transcriptome analysis revealed that metabolic genes (IDH1, G6PC3, GAPDH, PGK1, MYC, ENO1, ACO1) were upregulated in Pax5-deficient leukemic cells, and a similar metabolic signature could be observed in human leukemia. Our studies unveil the first in vivo evidence that the combination between Sca1-BCR-ABLp190 and metabolic reprogramming imposed by reduced Pax5 expression is sufficient for pB-ALL development. These findings might help to prevent conversion of BCR-ABLp190 preleukemic cells.
Survival of patients with pediatric acute lymphoblastic leukemia (ALL) after allogeneic hematopoietic stem cell transplantation (allo-SCT) is mainly compromised by leukemia relapse, carrying dismal prognosis. As novel individualized therapeutic approaches are urgently needed, we performed whole-exome sequencing of leukemic blasts of 10 children with post–allo-SCT relapses with the aim of thoroughly characterizing the mutational landscape and identifying druggable mutations. We found that post–allo-SCT ALL relapses display highly diverse and mostly patient-individual genetic lesions. Moreover, mutational cluster analysis showed substantial clonal dynamics during leukemia progression from initial diagnosis to relapse after allo-SCT. Only very few alterations stayed constant over time. This dynamic clonality was exemplified by the detection of thiopurine resistance-mediating mutations in the nucleotidase NT5C2 in 3 patients’ first relapses, which disappeared in the post–allo-SCT relapses on relief of selective pressure of maintenance chemotherapy. Moreover, we identified TP53 mutations in 4 of 10 patients after allo-SCT, reflecting acquired chemoresistance associated with selective pressure of prior antineoplastic treatment. Finally, in 9 of 10 children’s post–allo-SCT relapse, we found alterations in genes for which targeted therapies with novel agents are readily available. We could show efficient targeting of leukemic blasts by APR-246 in 2 patients carrying TP53 mutations. Our findings shed light on the genetic basis of post–allo-SCT relapse and may pave the way for unraveling novel therapeutic strategies in this challenging situation.