Biology subjects

Brueggemann, M.

Publications and source records attributed to Brueggemann, M..

3 recordsLinked to original sources

bioRxiv2024

Long-read transcriptome sequencing of CLL and MDS patients uncovers molecular effects of SF3B1 mutations

BackgroundMutations in splicing factor 3B subunit 1 (SF3B1) frequently occur in patients with chronic lymphocytic leukemia (CLL) and myelodysplastic syndromes (MDS). These mutations have a different effect on the disease prognosis with beneficial effect in MDS and worse prognosis in CLL patients. A full-length transcriptome approach can expand our knowledge on SF3B1 mutation effects on RNA splicing and its contribution to patient survival and treatment options. ResultsWe applied long-read transcriptome sequencing to 44 MDS and CLL patients with and without SF3B1 mutations and found > 60% of novel isoforms. Splicing alterations were largely shared between cancer types and specifically affected the usage of introns and 3 splice sites. Our data highlighted a constrained window at canonical 3 splice sites in which dynamic splice site switches occurred in SF3B1-mutated patients. Using transcriptome-wide RNA binding maps and molecular dynamics simulations, we showed multimodal SF3B1 binding at 3 splice sites and predicted reduced RNA binding at the second binding pocket of SF3B1K700E. ConclusionsOur work presents the hitherto most complete long-read transcriptome sequencing study in CLL and MDS and provides a resource to study aberrant splicing in cancer. Moreover, we showed that different disease prognosis results most likely from the different cell types expanded during cancerogenesis rather than different mechanism of action of the mutated SF3B1. These results have important implications for understanding the role of SF3B1 mutations in hematological malignancies and other related diseases. HighlightsO_LILong-read transcriptome sequencing data enables the identification of > 60% of novel isoforms in the transcriptomes of CLL and MDS patients and isogenic cell lines. C_LIO_LISF3B1 mutations trigger common splicing alterations upon SF3B1 mutations across patient cohorts, most frequently decreased intron retention and increased alternative 3 splice site usage. C_LIO_LIMutation effect depends on alternative 3 splice site and branch point positioning that coincide with bimodal SF3B1 binding at these sites C_LIO_LIMolecular dynamics simulations predict reduced binding of SF3B1K700E to mRNA at the second binding pocket harboring the polypyrimidine tract. C_LI

cancer biology↗

bioRxiv2023

Mutational and transcriptional landscape of pediatric B-cell precursor lymphoblastic lymphoma

Pediatric B-cell precursor (BCP) lymphoblastic malignancies are neoplasms with manifestation either in bone marrow/blood (BCP acute lymphoblastic leukemia, BCP-ALL) or less common in extramedullary tissue (BCP lymphoblastic lymphoma, BCP-LBL). Although both presentations are similar in morphology and immunophenotype molecular studies are virtually restricted to BCP-ALL so far. The lack of molecular studies on BCP-LBL is probably due to its rarity and the restriction to tiny, mostly formalin-fixed paraffin embedded (FFPE) tissues. Here we present the first comprehensive mutational and transcriptional analysis of what we consider the largest BCP-LBL cohort described to date (n=97). Whole exome sequencing indicates a mutational spectrum of BCP-LBL strikingly similar to that found in BCP-ALL. However, epigenetic modifiers were more frequently mutated in BCP-LBL, whereas BCP-ALL was more frequently affected by mutation in genes involved in B-cell development. Integrating copy number alterations, somatic mutations and gene expression by RNA-sequencing revealed virtually all molecular subtypes originally defined in BCP-ALL to be present in BCP-LBL too, with only 7% of lymphomas that were not assigned to a subtype. Therefore, the results here described may pave the way for molecular risk adapted treatment protocols for BCP-LBL patients. KeypointsComprehensive molecular characterization of B-cell precursor lymphoblastic lymphoma allows molecular subtyping analogous to leukemias Compared to leukemias, lymphomas show more alterations in epigenetic modifiers and less in B-cell development genes

cancer biology↗

bioRxiv2023

The gene expression classifier ALLCatchR identifies B-precursor ALL subtypes and underlying developmental trajectories across age

Current classifications (WHO-HAEM5 / ICC) define up to 26 molecular B-cell precursor acute lymphoblastic leukemia (BCP-ALL) disease subtypes, which are defined by genomic driver aberrations and corresponding gene expression signatures. Identification of driver aberrations by RNA-Seq is well established, while systematic approaches for gene expression analysis are less advanced. Therefore, we developed ALLCatchR, a machine learning based classifier using RNA-Seq expression data to allocate BCP-ALL samples to 21 defined molecular subtypes. Trained on n=1,869 transcriptome profiles with established subtype definitions (4 cohorts; 55% pediatric / 45% adult), ALLCatchR allowed subtype allocation in 3 independent hold-out cohorts (n=1,018; 75% pediatric / 25% adult) with 95.7% accuracy (averaged sensitivity across subtypes: 91.1% / specificity: 99.8%). High confidence predictions were achieved in 84.6% of samples with 99.7% accuracy. Only 1.2% of samples remained unclassified. ALLCatchR outperformed existing tools and identified novel candidates in previously unassigned samples. We established a novel RNA-Seq reference of human B-lymphopoiesis. Implementation in ALLCatchR enabled projection of BCP-ALL samples to this trajectory, which identified shared patterns of proximity of BCP-ALL subtypes to normal lymphopoiesis stages. ALLCatchR sustains RNA-Seq routine application in BCP-ALL diagnostics with systematic gene expression analysis for accurate subtype allocations and novel insights into underlying developmental trajectories.

cancer biology↗