OS5.1 Molecular subgroups of low- and high-grade gliomas diagnosed in the first year of life
Bibliographic record
Abstract
CNS tumours are the most common malignancies in infants. The majority of tumours diagnosed in the first year of life are gliomas. Though considered benign, low-grade gliomas (LGG) diagnosed in infancy have a worse outcome, whereas high-grade gliomas (HGG) have a better outcome than their counterparts in older children. We sought to determine the genetic drivers and clinical factors that impact outcome of this understudied patient population. Multi-institutional retrospective study of patients diagnosed with gliomas (WHO I-IV) in the first year of life. Clinical information and samples were collected for 171 patients diagnosed between 1985 and 2017. Histopathology was centrally reviewed and whenever sufficient tissue was available DNA and RNA extracted for molecular studies. Tier 1 of molecular studies consisted of clinically available tools, including a Nanostring panel detecting known glioma-associated fusions and ddPCR for BRAFV600E and H3K27M. Selected negative cases were then further profiled in tier 2 by RNA sequencing, SNP array and/or methylation array. Novel oncofusions were further validated. Ten-year overall survival for LGG and HGG in the entire cohort was 77% and 35%, respectively. Midline diencephalic tumours were predominantly low-grade (optic pathway gliomas, OPG), comprising 98% of all diencephalic tumours and 47% of all LGG. Molecular analysis of OPG revealed high frequency of BRAF alterations, with 44% carrying a BRAFV600E mutation and 36% a BRAF-KIAA1549 fusion. OPG were associated with a markedly worse outcome when compared with LGGs at other locations (10-year overall survival of 63% vs 92%), suggesting that these patients respond poorly to conventional treatment and should be prioritized for targeted therapies. Strikingly, hemispheric tumours (35% of all LGG and 82.4% of all LGG and HGG, respectively) were found to have recurrent alterations shared between LGG and HGG, most notably novel gene fusions involving the ALK oncogene. Additionally, NTRK, FGFR, MET and novel fusions involving ROS1 were found predominantly in hemispheric tumours, particularly in HGG. iNHA cells transduced with CCDC88A-ALK fusion and implanted intracranially in NSG mice were tumorigenic in vivo with a short latency and 100% penetrance. Gliomas in infants have a distinct molecular profile and clinical course. Whereas diencephalic tumours are predominantly low-grade and driven by BRAF alterations, recurrent alterations involving NTRK/ALK/ROS1, FGFR and MET are found in HGG and a subset of these alterations are shared with LGG hemispheric tumours. Our study characterizes a critically understudied patient population and reveals a high frequency of targetable alterations, supporting routine molecular studies and the use of targeted inhibitors in future clinical trials.
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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 | 0.000 | 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) | 0.000 | 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".