27 Characterization of the molecular consequences of CIC-knockout and neomorphic IDH1 R132H mutation on transcriptomic and epigenomic landscapes
Bibliographic record
Abstract
CIC, or Capicua, encodes a transcriptional repressor that is itself repressed by RAS/MAPK signalling. CIC is a recurrent target of somatic mutation in type 1 low grade gliomas (LGG), with at least half of the alterations predicted to be deleterious. Type 1 LGGs are a cohort of tumours that are molecularly defined by the loss of heterozygosity of chromosome arms 1p and 19q and the presence of neomorphic IDH1/2 mutations. Despite the high frequency of mutations in CIC within this tumour type, CIC’s putative tumour suppressive role remains to be elucidated. It is also unclear how CIC may cooperate with neomorphic IDH1/2 to promote gliomagenesis. To comprehensively characterize the molecular consequences of CIC loss, we performed RNA-seq, Whole Genome Bisulfite Sequencing, and ChIP-seq on 6 different histone modifications on isogenic CIC-wildtype (WT) and CIC-knockout (KO) normal human astrocytes. To also investigate the collective effects of CIC deficiency and neomorphic IDH1 on the transcriptome and epigenome, we generated the same dataset in isogenic CIC-WT and CIC-KO astrocytes possessing the IDH1 R132H mutation. Analysis of differentially expressed genes illustrates the enrichment of oncogenic pathways in specifically the CIC-KO, IDH1-R132H cells, supporting a synergistic relationship between CIC loss and IDH1-R132H in driving tumour progression. Integrative analyses are ongoing to unveil the epigenetic mechanisms underpinning the regulatory changes in these isogenic cell line models.
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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) | 0.001 | 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 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".