Purpose To review the impact of collaborative studies on advances in the biology and treatment of acute lymphoblastic leukemia (ALL) in children and adolescents. Methods A review of English literature on childhood ALL focusing on collaborative studies was performed. The resulting article was reviewed and revised by the committee chairs of the major ALL study groups. Results With long-term survival rates for ALL approaching 90% and the advent of high-resolution genome-wide analyses, several international study groups or consortia were established to conduct collaborative research to further improve outcome. As a result, treatment strategies have been improved for several subtypes of ALL, such as infant, MLL-rearranged, Philadelphia chromosome–positive, and Philadelphia chromosome–like ALL. Many recurrent genetic abnormalities that respond to tyrosine kinase inhibitors and multiple genetic determinants of drug resistance and toxicities have been identified to help develop targeted therapy. Several genetic polymorphisms have been recognized that show susceptibility to developing ALL and that help explain the racial/ethnic differences in the incidence of ALL. Conclusion The information gained from collaborative studies has helped decipher the heterogeneity of ALL to help improve personalized treatment, which will further advance the current high cure rate and the quality of life for children and adolescents with ALL.

Contemporary treatment of pediatric acute myeloid leukemia (AML) requires the assignment of patients to specific risk groups. To explore whether expression profiling of leukemic blasts could accurately distinguish between the known risk groups of AML, we analyzed 130 pediatric and 20 adult AML diagnostic bone marrow or peripheral blood samples using the Affymetrix U133A microarray. Class discriminating genes were identified for each of the major prognostic subtypes of pediatric AML, including t(15;17) [ PML-RAR␣], t(8;21)[AML1-ETO], inv 16 [CBF␤-MYH11], MLL chimeric fusion genes, and cases classified as FAB-M7. When subsets of these genes were used in supervised learning algorithms, an overall classification accuracy of more than 93% was achieved. Moreover, we were able to use the expression signatures generated from the pediatric samples to accurately classify adult de novo AMLs with the same genetic lesions. The class discriminating genes also provided novel insights into the molecular pathobiology of these leukemias. Finally, using a combined pediatric data set of 130 AMLs and 137 acute lymphoblastic leukemias, we identified an expression signature for cases with MLL chimeric fusion genes irrespective of lineage. Surprisingly, AMLs containing partial tandem duplications of MLL failed to cluster with MLL chimeric fusion gene cases, suggesting a significant difference in their underlying mechanism of transformation. IntroductionAcute myeloid leukemia (AML) is a relatively rare malignancy in the pediatric population, comprising only 15% to 20% of the acute leukemias diagnosed in this age group. 1 Nevertheless, it remains a challenging disease with an inferior treatment outcome compared with pediatric acute lymphoblastic leukemia (ALL). Despite the introduction of new drugs, the aggressive use of allogeneic and autologous bone marrow transplantation, and improvements in supportive care, overall cure rates of AML in most contemporary treatment protocols remain below 60%. [2][3][4][5] Further improvements in cure rates are likely to come from a better understanding of both the molecular abnormalities responsible for the formation and growth of the leukemic cells, and the mechanisms underlying drug resistance.Increasingly, contemporary treatment protocols are incorporating methods for both accurate diagnosis and subsequent risk stratification. To achieve this requires not only distinguishing myeloblasts from lymphoblasts, but also assessing the extent of lineage commitment and differentiation, as well as the presence of specific molecular lesions or chromosomal abnormalities. Efforts over the last several decades have revealed AML to be a heterogeneous disease, with marked differences in cure rates between various genetic subtypes. [6][7][8][9] Acute promyelocytic leukemia was the first clear example of a clinically distinct AML subtype, being characterized by FAB-M3 morphology and expression of the t(15;17)-encoded promyelocytic leukemia-retinoic acid receptor alpha (PML-RAR␣) fusion protein. [10][11][12][13][14] ...

SUMMARY To define the mutation spectrum in non-Down syndrome acute megkaryoblastic leukemia (non-DS-AMKL), we performed transcriptome sequencing on diagnostic blasts from 14 pediatric patients and validated our findings in a recurrency/validation cohort consisting of 34 pediatric and 28 adult AMKL leukemia samples. Our analysis identified a cryptic chromosome 16 inversion [inv(16)(p13.3q24.3)] in 27% of pediatric cases, which encodes a CBFA2T3-GLIS2 fusion protein. Expression of CBFA2T3-GLIS2 in Drosophila and murine hematopoietic cells induced bone morphogenic protein (BMP) signaling, and resulted in a marked increase in the self-renewal capacity of hematopoietic progenitors. These data suggest that expression of CBFA2T3-GLIS2 directly contributes to leukemogenesis.

Acute Megakaryoblastic Leukemia (AMKL) is a subtype of acute myeloid leukemia (AML) in which cells morphologically resemble abnormal megakaryoblasts. While rare in adults, AMKL accounts for 4–15% of newly diagnosed childhood AML1–3. AMKL in patients without Down syndrome (non-DS-AMKL) is frequently associated with poor outcomes. Previous efforts have identified chimeric oncogenes in a significant number of cases, including RBM15-MKL1, CBFA2T3-GLIS2, KMT2A gene rearrangements and NUP98-KDM5A4–6. The etiology of 30–40% of cases, however, remains unknown. To better understand the genomic landscape of non-DS-AMKL, we performed RNA and exome sequencing on specimens from 99 patients (75 pediatric and 24 adult). We demonstrate that pediatric non-DS-AMKL is a heterogeneous malignancy that can be divided into seven subgroups with varying outcomes. These subgroups are characterized by chimeric oncogenes with cooperating mutations in epigenetic and kinase signaling genes. Overall, these data shed light on the etiology of AMKL and provide useful information for treatment tailoring.

Although there are high survival rates for children with acute lymphoblastic leukaemia, their outcome is often counterbalanced by the burden of toxic eff ects. This is because reported frequencies vary widely across studies, partly because of diverse defi nitions of toxic eff ects. Using the Delphi method, 15 international childhood acute lymphoblastic leukaemia study groups assessed acute lymphoblastic leukaemia protocols to address toxic eff ects that were to be considered by the Ponte di Legno working group. 14 acute toxic eff ects (hypersensitivity to asparaginase, hyperlipidaemia, osteonecrosis, asparaginase-associated pancreatitis, arterial hypertension, posterior reversible encephalopathy syndrome, seizures, depressed level of consciousness, methotrexate-related stroke-like syndrome, peripheral neuropathy, high-dose methotrexate-related nephrotoxicity, sinusoidal obstructive syndrome, thrombo embolism, and Pneumocystis jirovecii pneumonia) that are serious but too rare to be addressed comprehensively within any single group, or are deemed to need consensus defi nitions for reliable incidence comparisons, were selected for assessment. Our results showed that none of the protocols addressed all 14 toxic eff ects, that no two protocols shared identical defi nitions of all toxic eff ects, and that no toxic eff ect defi nition was shared by all protocols. Using the Delphi method over three face-to-face plenary meetings, consensus defi nitions were obtained for all 14 toxic eff ects. In the overall assessment of outcome of acute lymphoblastic leukaemia treatment, these expert opinion-based defi nitions will allow reliable comparisons of frequencies and severities of acute toxic eff ects across treatment protocols, and facilitate international research on cause, guidelines for treatment adaptation, preventive strategies, and development of consensus algorithms for reporting on acute lymphoblastic leukaemia treatment.