Bibliographic record
Abstract
Gliomas account for 80% of malignant central nervous system cancers and current therapies have shown limited success in treating this disease1. Characterization of the mutational landscape of these tumours has led to the identification genetic low grade glioma (LGG) subtypes within adults2 ,3,4. These are largely defined by neomorphic mutation in the genes coding for isocitrate dehydrogenase (IDH1 or IDH2), presenting in both IDH mutant astrocytoma and IDH mutant oligodendroglioma. However, these subtypes differ with respect to their mutational landscapes and clinical manifestations, with IDH mutant astrocytoma having a worse prognosis and limited therapeutic options2,3. IDH mutant oligodendroglioma harbor truncal mutations in IDH and the TERT promoter as well as co-deletion of chromosomal arms 1p and 19q. IDH mutant astrocytoma is associated with truncal mutations in IDH, TP53, and ATRX2. In addition to these canonical LGG mutations, the rs55705857 single nucleotide polymorphism (SNP) has been shown to increase the risk of IDH-mutant LGG by an odds ratio of 6 and 9 within IDH mutant astrocytoma and IDH mutant oligodendroglioma respectively1-4, however the mechanism through which this SNP confers increased LGG risk has been elusive.I have generated mouse models for IDH mutant astrocytoma using a strategy combining CRISPR gene-editing with Cre-recombinase technologies to precisely model the mutations believed to initiate LGG pathogenesis, as well as bred two rs55705857 mutant alleles into these models. Our IDH mutant astrocytoma model develops LGG-like tumours in brain tissue with a penetrance of 30% at a latency of 463 days, while the addition of mutant rs55705857 elevates tumour penetrance to ~75% while decreasing latency to 172 days. In collaboration with the Jenkins Lab at the Mayo Clinic, I have uncovered one of the mechanisms through which the rs55705857 risk allele enhances gliomagenesis. We demonstrated that rs55705857 resides within a brain-specific enhancer, where the risk allele disrupts OCT2/4 binding and thus prevents OCT2/4 mediated repression of the MYC promoter, inducing increased MYC expression. Lastly, I’ve developed and executed an in-vivo CRISPR and ORF screens to identify the genes such as Notch1 and Pten that drive malignant progression of LGG into deadly glioblastoma (GBM).
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".