Acute lymphoblastic leukemias carrying a chromosomal translocation involving the mixed-lineage leukemia gene (MLL, ALL1, HRX) have a particularly poor prognosis. Here we show that they have a characteristic, highly distinct gene expression profile that is consistent with an early hematopoietic progenitor expressing select multilineage markers and individual HOX genes. Clustering algorithms reveal that lymphoblastic leukemias with MLL translocations can clearly be separated from conventional acute lymphoblastic and acute myelogenous leukemias. We propose that they constitute a distinct disease, denoted here as MLL, and show that the differences in gene expression are robust enough to classify leukemias correctly as MLL, acute lymphoblastic leukemia or acute myelogenous leukemia. Establishing that MLL is a unique entity is critical, as it mandates the examination of selectively expressed genes for urgently needed molecular targets.

Differential expression of a relatively small number of genes is associated with drug resistance and treatment outcome in childhood ALL.

Drug resistance remains a major obstacle to successful cancer treatment. A database of drug-associated gene expression profiles was screened for molecules whose profile overlapped with a gene expression signature of glucocorticoid (GC) sensitivity/resistance in acute lymphoblastic leukemia (ALL) cells. The screen indicated that the mTOR inhibitor rapamycin profile matched the signature of GC sensitivity. We tested the hypothesis that rapamycin would induce GC sensitivity in lymphoid malignancy cells and found that it sensitized to GC-induced apoptosis via modulation of antiapoptotic MCL1. These data indicate that MCL1 is an important regulator of GC-induced apoptosis and that the combination of rapamycin and glucocorticoids has potential utility in lymphoid malignancies. Furthermore, this approach represents a strategy for identification of promising combination therapies for cancer.

SUMMARYBackground-In childhood acute lymphoblastic leukemia (ALL) genetic subtypes are recognized that determine the risk-group for further treatment. However, 25% of precursor BALL are currently genetically unclassified and have an intermediate prognosis. The present study used genome-wide strategies to reveal new biological insights and advance the prognostic classification of childhood ALL.

Key Points• BCR-ABL1-like signature and IKZF1 deletions are clinically important to identify high-risk acute lymphoblastic patients.Most relapses in childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL) are not predicted using current prognostic features. Here, we determined the cooccurrence and independent prognostic relevance of 3 recently identified prognostic features: BCR-ABL1-like gene signature, deletions in IKZF1, and high CRLF2 messenger RNA expression (CRLF2-high). These features were determined in 4 trials representing 1128 children with ALL: DCOG ALL-8, ALL9, ALL10, and Cooperative ALL (COALL)-97/03. BCR-ABL1-like, IKZF1-deleted, and CRLF2-high cases constitute 33.7% of BCR-ABL1-negative, MLL wild-type BCP-ALL cases, of which BCR-ABL1-like and IKZF1 deletion (co)occurred most frequently. Higher cumulative incidence of relapse was found for BCR-ABL1-like and IKZF1-deleted, but not CRLF2-high, cases relative to remaining BCP-ALL cases, reflecting the observations in each of the cohorts analyzed separately. No relapses occurred among cases with CRLF2-high as single feature, whereas 62.9% of all relapses in BCR-ABL1-negative, MLL wild-type BCP-ALL occurred in cases with BCR-ABL1-like signature and/or IKZF1 deletion. Both the BCR-ABL1-like signature and IKZF1 deletions were prognostic features independent of conventional prognostic markers in a multivariate model, and both remained prognostic among cases with intermediate minimal residual disease. The BCR-ABL1-like signature and an IKZF1 deletion, but not CRLF2-high, are prognostic factors and are clinically of importance to identify high-risk patients who require more intensive and/or alternative therapies. (Blood. 2013;122(15):2622-2629

Cell-to-cell communication is essential for the organization, coordination, and development of cellular networks and multi-cellular systems. Intercellular communication is mediated by soluble factors (including growth factors, neurotransmitters, and cytokines/chemokines), gap junctions, exosomes and recently described tunneling nanotubes (TNTs). It is unknown whether a combination of these communication mechanisms such as TNTs and gap junctions may be important, but further research is required. TNTs are long cytoplasmic bridges that enable long-range, directed communication between connected cells. The proposed functions of TNTs are diverse and not well understood but have been shown to include the cell-to-cell transfer of vesicles, organelles, electrical stimuli and small molecules. However, the exact role of TNTs and gap junctions for intercellular communication and their impact on disease is still uncertain and thus, the subject of much debate. The combined data from numerous laboratories indicate that some TNT mediate a long-range gap junctional communication to coordinate metabolism and signaling, in relation to infectious, genetic, metabolic, cancer, and age-related diseases. This review aims to describe the current knowledge, challenges and future perspectives to characterize and explore this new intercellular communication system and to design TNT-based therapeutic strategies.

The online version of this article has a Supplementary Appendix. BackgroundMicroRNA regulate the activity of protein-coding genes including those involved in hematopoietic cancers. The aim of the current study was to explore which microRNA are unique for seven different subtypes of pediatric acute lymphoblastic leukemia. Design and MethodsExpression levels of 397 microRNA (including novel microRNA) were measured by quantitative real-time polymerase chain reaction in 81 cases of pediatric leukemia and 17 normal hematopoietic control cases. ResultsAll major subtypes of acute lymphoblastic leukemia, i.e. T-cell, MLL-rearranged, TEL-AML1-positive, E2A-PBX1-positive and hyperdiploid acute lymphoblastic leukemia, with the exception of BCR-ABL-positive and 'B-other' acute lymphoblastic leukemias (defined as precursor Bcell acute lymphoblastic leukemia not carrying the foregoing cytogenetic aberrations), were found to have unique microRNA-signatures that differed from each other and from those of healthy hematopoietic cells. Strikingly, the microRNA signature of TEL-AML1-positive and hyperdiploid cases partly overlapped, which may suggest a common underlying biology. Moreover, aberrant down-regulation of let-7b (~70-fold) in MLL-rearranged acute lymphoblastic leukemia was linked to up-regulation of oncoprotein c-Myc (PFDR<0.0001). Resistance to vincristine and daunorubicin was characterized by an approximately 20-fold up-regulation of miR125b, miR-99a and miR-100 (PFDR≤0.002). No discriminative microRNA were found for prednisolone response and only one microRNA was linked to resistance to L-asparaginase. A combined expression profile based on 14 microRNA that were individually associated with prognosis, was highly predictive of clinical outcome in pediatric acute lymphoblastic leukemia (5-year disease-free survival of 89.4%±7% versus 60.8±12%, P=0.001). ConclusionsGenetic subtypes and drug-resistant leukemic cells display characteristic microRNA signatures in pediatric acute lymphoblastic leukemia. Functional studies of discriminative and prognostically important microRNA may provide new insights into the biology of pediatric acute lymphoblastic leukemia.

Kinases are dysregulated in most cancer but the frequency of specific kinase mutations is low, indicating a complex etiology in kinase dysregulation. Here we report a strategy to rapidly identify functionally important kinase targets, irrespective of the etiology of kinase pathway dysregulation, ultimately enabling a correlation of patient genetic profiles to clinically effective kinase inhibitors. Our methodology assessed the sensitivity of primary leukemia patient samples to a panel of 66 small-molecule kinase inhibitors over 3 days. Screening of 151 leukemia patient samples revealed a wide diversity of drug sensitivities, with 70% of the clinical specimens exhibiting hypersensitivity to one or more drugs. From this data set, we developed an algorithm to predict kinase pathway dependence based on analysis of inhibitor sensitivity patterns. Applying this algorithm correctly identified pathway dependence in proof-of-principle specimens with known oncogenes, including a rare FLT3 mutation outside regions covered by standard molecular diagnostic tests. Interrogation of all 151 patient specimens with this algorithm identified a diversity of gene targets and signaling pathways that could aid prioritization of deep sequencing data sets, permitting a cumulative analysis to understand kinase pathway dependence within leukemia subsets. In a proof-of-principle case, we showed that in vitro drug sensitivity could predict both a clinical response and the development of drug resistance. Taken together, our results suggested that drug target scores derived from a comprehensive kinase inhibitor panel could predict pathway dependence in cancer cells while simultaneously identifying potential therapeutic options.