Abstract LB-179: Integrated (epi)genomic analyses identify subgroup-specific therapeutic targets in CNS rhabdoid tumors
Bibliographic record
Abstract
Abstract Atypical Teratoid Rhabdoid Tumors (ATRTs) are the most common malignant embryonal brain tumors arising in younger children that are distinctly lethal cancers for which effective therapies are lacking. Although ATRTs exhibit substantial clinical heterogeneity, exome studies reveal a relatively bland coding genome with only recurrent alterations of SMARCB1. Despite apparent genomic/genetic homogeneity, we recently reported that ATRTs comprise at least two transcriptional subclasses that correlate with different clinical features and treatment outcomes. However, the biological mechanisms and basis for molecular and therapeutic heterogeneity in ATRTs remained unclear. In this study, we integrated whole genome, exome, RNAseq as well as genome wide methylation and nucleosomal profiling analyses to comprehensively define the genomic and epigenomic landscape of ATRT sub-groups and identify sub-group specific therapeutic targets. Integration of multiplatform genomic analyses revealed novel recurrent genetic alterations in upto 20% of ATRTs. We observed predominantly structural coding events that targeted genes with functions in neural development and epigenetic regulation including BCR, MKL1 and EP300, thus suggesting greater complexity to the ATRT genome than previously appreciated. Global methylation (162) and gene expression analyses (90) of primary tumors indicated further segregation of ATRTs into three epigenetic sub-groups (group 1, 2A and 2B) that correlated with distinct lineage enriched gene expression profiles, global and SMARCB1 specific genotypes and different anatomic tumor locations and age at diagnosis. Group 1 ATRT exhibited enrichment of neurogenic/NOTCH signaling loci (ASCL1, FABP7, MYCN, C1ORF61, HES5/6, DLL1) and were predominantly supra-tentorial tumors arising in children at a median age of 24 months. In contrast Group 2A tumors arose predominantly in infra-tentorial locations in the youngest patients, while group 2B tumors were characteristically spinal in location. BMP signaling and mesenchymal differentiation genes (BMP4, BAMBI, PDGFRB) were commonly enriched in group 2A and B tumors; Group 2B tumors were additionally characterized by enrichment of MYCC, HOXB & C gene clusters. Remarkably, ATAC-seq analyses revealed distinct chromatin landscape associated with each ATRT sub-group, that correlated strikingly with sub-group specific therapeutic response in ATRT cell lines to a panel of signaling (NOTCH, BMP, Dasatinib) and epigenetic (EZH2, G9a, BRD4) inhibitors. Significantly, we discovered that differential methylation of a novel, PDGFRβ associated enhancer element confers robust sensitivity to tyrosine kinase inhibitors Dasatinib and Nilotinib in group 2 ATRTs, and suggest these as novel agents for this highly lethal ATRT sub-type. Citation Format: Jonathon Torchia, Shengrui Feng, King Ching Ho, Louis Letourneau, Daniel Picard, Tiffany S. Chan, Alexandre Vasiljevic, Dong Anh Khuong Quang, Brian Golbourn, Dalia Barsyte-Lovejoy, Constanze Zeller, Patrick Sin-Chan, Natalia R. Agamez, Mei Lu, Lucie Lafay-Cousin, Joseph D. Norman, Maryam Fouladi, Lindsey M. Hoffman, Stefan Rutkowski, Torsten Pietsch, Alexander R. Judkins, Eric Bouffet, James T. Rutka, Cynthia E. Hawkins, Cheryl H. Arrowsmith, Daniel De Carvalho, Nada Jabado, Annie Huang. Integrated (epi)genomic analyses identify subgroup-specific therapeutic targets in CNS rhabdoid tumors. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-179.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.001 | 0.000 |
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 teacher head, 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".