Abstract 4126: Identifying novel tumor modifier genes involved in gliomagenesis using retroviral gene-trapping mutagenesis screens
Bibliographic record
Abstract
Abstract Glioblastoma multiforme (GBMs) are the most common and lethal of all gliomas, with an average survival of ∼ 12-16 months. Several gain- and loss-of-function genetic alterations have been implicated in gliomagenesis leading to GBM formation, however many more genetic alterations exist, as evidenced by recent reports from The Cancer Genome Atlas (TCGA) project on human GBMs. Well-characterized mouse models, especially those that progressively develop gliomas, also, offer an opportunity to discover novel glioma relevant genetic alterations, using viral and non-viral random mutagenesis strategies. Using gene-trap strategies in our spontaneous transgenic mouse RasB8 glioma model, which expresses V12H-Ras under the control of the astrocyte tissue specific human promoter GFAP, we identified GATA6, a member of the GATA family of transcription factors, as a novel tumour suppressor gene (TSG) involved in progression of human GBMs and GATA4, a close family member of GATA6, to also function as a TSG involved in initiation of gliomagenesis. We now generated novel gain of function and loss of function gene-traps and transduced non-transformed but genetically susceptible primary murine astrocytes harboring either activated V12H-Ras, or loss of the tumour suppressors, p53, Ink4a/Arf, Pten−/− and over-expression of the human EGFRvIII mutant. Pending verification in our mouse models and human specimens we hypothesized that that trapped clones from V12H-Ras, p53 null and Ink4a/ARF null astrocytes would reveal progression factors, as these genetic alterations are associated with human low grade gliomas and occur early on in GBM formation. In contrast, trapped clones from astrocytes with EGFRvIII or Pten−/−, already demonstrated to promote progression, would likely lead to the discovery of initiation factors. Several gene-trapped clones led to transformation as measured by soft agar assays in initial screens using astrocytes with activated V12H-Ras. By means of inverse PCR we identified gene-trap insertion sites in introns of RapGap1, Ikkβ, Socs6, and Pink1 leading to loss of function. Of great interest was PTEN induced Kinase 1, PINK1, a mitochondrial serine/threonine kinase that is frequently mutated in patients in Parkinson disease while its link to cancer and GBM is poorly characterized. Initial screening in GBMs reveals reduced expression of PINK1 protein compared to normal human astrocyte controls. Pink1 gene-trap clones also exhibited increased proliferation and increased transformation compared to empty vector controls providing initial evidence that mouse and human PINK1 may have tumour suppressive properties, with current validation in progress. Gene-trapping strategies in robust animal models provide an invaluable tool that complement large scale cancer genome sequencing projects in identification of relevant driver GBM modifier genes in random non-biased manner. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4126.
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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) | 0.001 | 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) | 0.002 | 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".