Abstract A39: Molecular characterization of ETMRs reveals role for R-loop mediated genomic instability and new treatment options
Bibliographic record
Abstract
Abstract Introduction: Embryonal tumors with multilayered rosettes (ETMRs) are aggressive brain tumors that occur mainly in infants. Patients face a very poor prognosis with a median overall survival of ~12 months after diagnosis. The tumors harbor in ~90% of all cases amplification of a miRNA cluster on chromosome 19 (C19MC) that is thought to be the driver of the disease. However, current treatment options are lacking as (a) the mechanisms downstream of C19MC are poorly understood and (b) the drivers in cases lacking the C19MC aberration are unknown. To develop better treatment protocols for ETMR patients, more insight is needed in what is driving these tumors and how that can be targeted. Materials and Methods: To investigate the genomic and epigenomic landscape of ETMR in depth, we collected 193 ETMR samples and 23 matched relapses and performed DNA methylation profiling on all and DNA (whole genome, whole exome, and panel) sequencing and mRNA and miRNA transcriptome analysis on a subset of them. The BT183 ETMR cell line was used for drug treatments. Results: Among the 22 tumors without C19MC amplification, we identified 8 cases with truncating DICER1 germline mutations in one allele and somatic missense mutations in the RNASE III domain in the other allele. No DICER1 mutations were identified in C19MC amplified cases. In addition, structural variations (SVs) affecting C19MC were found in 3 other C19MC nonamplified cases and amplification of another miRNA cluster, miR-17-92, in 2 other cases. However, despite the presence of different genetic aberrations, based on DNA methylation and transcriptome profiling no molecular subgrouping was observed within our cohort. Whole-genome sequencing revealed an overall low recurrence and conservation of SNVs but strong conservation of SVs from primary tumors to relapses, especially surrounding C19MC. Moreover, many newly acquired SNVs in the relapses are associated to a new cisplatin treatment-related mutational signature. SVs detected in ETMRs significantly colocalized with R-loops, structures that form upon a collision of replication and transcription and are associated to increased levels of chromosomal instability, which is frequently observed in ETMRs. Using a DICER1 KO model, we found that global deregulation of miRNAs led to increased levels of R-loops and R-loop associated chromosomal instability. Finally, we show that a combination of topoisomerase and PARP inhibitors is highly synergistic and strongly increased the levels of both R-loops and DNA damage in ETMR cells and effectively killed the cells. Conclusions: Our results show that genomically instable ETMR cells are vulnerable to further increases in chromosomal instability, knowledge that may lead to new treatment strategies for ETMR patients and possibly other cancers with high levels of R-loops. Citation Format: Sander Lambo, Susanne Grübner, Tobias Rausch, Sebastian Waszak, Christin Schmidt, Sonja Krausert, Loreen Weichert, Aparna Gorthi, Carolina Romero, Annie Huang, Julia Schueler, Jan Korbel, Alexander Bishop, Stefan Pfister, Andrey Korshunov, Marcel Kool. Molecular characterization of ETMRs reveals role for R-loop mediated genomic instability and new treatment options [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr A39.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".