Abstract A45: Investigating the role of ASCL1 in regulating differentiation of gliobastoma precursor cells
Bibliographic record
Abstract
Abstract Glioblastoma (GBM), the most common and lethal adult primary brain tumour, exhibits cellular heterogeneity and a subpopulation of tumour cells exhibits the neural precursor phenotype and drives tumourigenesis. These findings suggest that tumours may represent aberrant organogenesis with growth caused by unlimited proliferation and failure of differentiation of malignant precursor cells. It has yet to be determined the relative importance of aberrant self-renewal versus blocked differentiation in the brain tumour phenotype. As GBM-initiating cells have precursor cell properties, promotion of differentiation represents a potential strategy for treatment. Forcing glioblastoma precursor cells (GPCs) to differentiate terminally would limit clonal expansion and attenuate tumour growth. Data generated in our lab suggests that differentiation potential varies between different patient-derived GPC cultures. This study aims to determine what defines a blocked differentiation phenotype in human glioblastoma and to determine whether differentiation therapy is a feasible strategy for glioblastoma treatment. A key regulator of neuronal differentiation is ASCL1 during normal development and adult neurogenesis. Microarray analysis of ASCL1 expression in GPCs (n = 33) revealed two subgroups of GPCs as having either high or low expression. Preliminary evidence suggests that GPCs with high expression of ASCL1 exhibit neuronal lineage commitment whereas GPCs with low expression of ASCL1 do not undergo lineage commitment. This was confirmed using immunocytochemistry, quantitative real-time PCR and Western blot analysis. Furthermore, an inverse correlation was observed between transcript levels of ASCL1 and DKK1, an antagonist of the Wnt signalling pathway, while a direct correlation was observed between ASCL1 and activated β-catenin (ABC). Treatment of GPCs with a GSK3β inhibitor resulted in the activation of Wnt signalling and concomitant increase in transcript levels of ASCL1 and neuronal lineage markers (i.e. TUJ1, MAP2). This study aims to further investigate the role of ASCL1 in glioblastoma and to determine whether neuronal lineage commitment in the context of ASCL1 activity is mediated in a Wnt-dependent manner. Gain- and loss-of-function studies are in progress to determine whether ASCL1 is sufficient and/or necessary for neuronal lineage commitment and consequent effects on tumour-initiating properties (i.e. proliferation and self-renewal) will be examined in vitro and in vivo. Citation Format: Nicole I. Park, Peter B. Dirks. Investigating the role of ASCL1 in regulating differentiation of gliobastoma precursor cells. [abstract]. In: Proceedings of the Third AACR International Conference on Frontiers in Basic Cancer Research; Sep 18-22, 2013; National Harbor, MD. Philadelphia (PA): AACR; Cancer Res 2013;73(19 Suppl):Abstract nr A45.
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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) | 0.002 | 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".