Characterization of immune response against Mycobacterium marinum infection in the main hematopoietic organ of adult zebrafish (Danio rerio)

Abstract Tuberculosis remains a major global health challenge. To gain information about genes important for defense against tuberculosis, we used a well-established tuberculosis model; Mycobacterium marinum infection in adult zebrafish. To characterize the immunological response to mycobacterial infection at 14 days post infection, we performed a whole-genome level transcriptome analysis using cells from kidney, the main hematopoietic organ of adult zebrafish. Among the upregulated genes, those associated with immune signaling and regulation formed the largest category, whereas the largest group of downregulated genes had a metabolic role. We also performed a forward genetic screen in adult zebrafish and identified a fish line with severely impaired survival during chronic mycobacterial infection. Based on transcriptome analysis, these fish have decreased expression of several immunological genes. Taken together, these results give new information about the genes involved in the defense against mycobacterial infection in zebrafish

Multimodal classification of molecular subtypes in pediatric acute lymphoblastic leukemia

Abstract Genomic analyses have redefined the molecular subgrouping of pediatric acute lymphoblastic leukemia (ALL). Molecular subgroups guide risk-stratification and targeted therapies, but outcomes of recently identified subtypes are often unclear, owing to limited cases with comprehensive profiling and cross-protocol studies. We developed a machine learning tool (ALLIUM) for the molecular subclassification of ALL in retrospective cohorts as well as for up-front diagnostics. ALLIUM uses DNA methylation and gene expression data from 1131 Nordic ALL patients to predict 17 ALL subtypes with high accuracy. ALLIUM was used to revise and verify the molecular subtype of 281 B-cell precursor ALL (BCP-ALL) cases with previously undefined molecular phenotype, resulting in a single revised subtype for 81.5% of these cases. Our study shows the power of combining DNA methylation and gene expression data for resolving ALL subtypes and provides a comprehensive population-based retrospective cohort study of molecular subtype frequencies in the Nordic countries

The pediatric precision oncology INFORM registry: clinical outcome and benefit for patients with very high-evidence targets

INFORM is a prospective, multinational registry gathering clinical and molecular data of relapsed, progressive, or high-risk pediatric patients with cancer. This report describes long-term follow-up of 519 patients in whom molecular alterations were evaluated according to a predefined seven-scale target prioritization algorithm. Mean turnaround time from sample receipt to report was 25.4 days. The highest target priority level was observed in 42 patients (8.1%). Of these, 20 patients received matched targeted treatment with a median progression-free survival of 204 days [95% confidence interval (CI), 99-not applicable], compared with 117 days (95% CI, 106-143;P= 0.011) in all other patients. The respective molecular targets were shown to be predictive for matched treatment response and not prognostic surrogates for improved outcome. Hereditary cancer predisposition syndromes were identified in 7.5% of patients, half of which were newly identified through the study. Integrated molecular analyses resulted in a change or refinement of diagnoses in 8.2% of cases. SIGNIFICANCE: The pediatric precision oncology INFORM registry prospectively tested a target prioritization algorithm in a real-world, multinational setting and identified subgroups of patients benefiting from matched targeted treatment with improved progression-free survival, refinement of diagnosis, and identification of hereditary cancer predisposition syndromes