T-cell lymphoblastic lymphoma (T-LBL) is a heterogeneous malignancy of lymphoblasts committed to T-cell lineage. Dismal outcomes (15-30%) in case of T-LBL relapses warrants for establishing risk-based treatment in future. This is a first comprehensive, systematic, integrated genome-wide analysis including relapse cases aimed towards identifying molecular markers of prognostic relevance for T-LBL. NOTCH1 was identified as putative driver for T-LBL. Activated NOTCH/PI3K-AKT signaling axis and alterations in cell cycle regulators constitutes the core oncogenic program for T-LBL. Mutated KMT2D was identified as a prognostic marker. The cumulative incidence of relapse was 47±17% in patients with KMT2D mutations compared with 14±3% in KMT2D wildtype. Structural analysis of the mutated domains of KMT2D revealed plausible impact on the structure and functional consequences. These findings provide new insights into the pathogenesis of T-LBL including high translational potential. The ongoing trial LBL 2018 (NCT04043494) allows prospective validation and subsequent fine-tuning of the stratification criteria for T-LBL risk groups to improve survival of the pediatric patients.

The main challenges in the treatment of T-cell lymphoblastic lymphoma (T-LBL) in children and adolescents are twofold: to increase survival rates in concert with reduction of acute and long-term toxicities including the rate of secondary malignancies. The need for molecular and prognostic markers in T-LBL is crucial to allow for systematic treatment optimization and may serve as targets for new treatment approaches.

Despite poor survival, controversies remain in the treatment for refractory or relapsed pediatric non-Hodgkin lymphoma (r/r NHL). The current project aimed to collect international experience on the re-induction treatment of r/r NHL, hematopoietic stem cell transplantation (HSCT), risk factors associated with outcome, and to suggest treatment recommendations. Inclusion criteria were (i) refractory disease, disease progression or relapse of any NHL subtype except anaplastic large cell lymphoma, (ii) age < 18 years at initial diagnosis, (iii) diagnosis in/after January 2000. Data from 639 eligible patients were evaluable. The eight-year probability of overall survival was 34 ± 2% with highly significant differences according to NHL subtypes: 28 ± 3% for 254 Burkitt lymphoma/leukemia, 50 ± 6% for 98 diffuse large B-cell lymphomas, 57 ± 8% for 41 primary mediastinal large B-cell lymphomas, 27 ± 3% for 177 T-lymphoblastic lymphomas, 52 ± 10% for 34 precursor-B-cell lymphoblastic lymphomas and 30 ± 9% for 35 patients with rare NHL subtypes. Subtype-specific factors associated with survival and treatment recommendations are suggested. There were no survivors without HSCT, except in few very small subgroups. Conclusions: There is an urgent need to further improve survival in r/r NHL. The current study provides the largest real-world series, which underlines the role of HSCT and suggests treatment recommendations.

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While survival has improved for Burkitt lymphoma patients, potential differences in outcome between pediatric and adult patients remain unclear. In both age groups, survival remains poor at relapse. Therefore, we conducted a comparative study in a large pediatric cohort, including 191 cases and 97 samples from adults. While TP53 and CCND3 mutation frequencies are not age related, samples from pediatric patients showed a higher frequency of mutations in ID3, DDX3X, ARID1A and SMARCA4, while several genes such as BCL2 and YY1AP1 are almost exclusively mutated in adult patients. An unbiased analysis reveals a transition of the mutational profile between 25 and 40 years of age. Survival analysis in the pediatric cohort confirms that TP53 mutations are significantly associated with higher incidence of relapse (25 ± 4% versus 6 ± 2%, p-value 0.0002). This identifies a promising molecular marker for relapse incidence in pediatric BL which will be used in future clinical trials.

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Genome wide association studies have identified numerous single nucleotide polymorphisms (SNPs) associated with obesity, yet effect sizes of individual SNPs are small. Therefore, the aim of our study was to investigate whether a genetic risk score (GRS) comprising risk alleles of SNPs identified in the GIANT consortium meta-analyses shows association with body mass index (BMI) and other BMI related metabolic alterations in a cohort with an extreme phenotype. Genotyping of 93 SNPs was performed in 314 obese individuals (mean BMI 40.5 ± 7.8 kg/m², aged 45 ± 12 years), participating in a standardized weight reduction program, and in 74 lean controls (mean BMI 24.6 ± 3.3 kg/m², aged 41.7 ± 13.4 years). Allele numbers of all 93 SNPs were added to a GRS. Anthropometric parameters, parameters of glucose/insulin and lipid metabolism were assessed standardized after a 12 hours fast. GRS was significantly different between controls and obese individuals (unweighted GRS: 86.6 vs 89.0, P = .002; weighted GRS: 84.9 vs 88.3, P = .005). Furthermore, linear regression analysis showed significant associations of GRS with BMI (P < .0001), weight (P = .0005), waist circumference (P = .0039), fat mass (P < .0001) and epicardial fat thickness (P = .0032), yet with small effect sizes (r² < 0.06). In conclusion, in our study GRS could differentiate between extreme obese and lean individuals, and was associated with BMI and its related traits, yet with small effect sizes.