Abstract 3847: Cytoplasmic ECT2: Implications for invasion and migration and RAS-RAC cross-talk in glioma
Bibliographic record
Abstract
Abstract Gliomas are a highly malignant primary brain tumour characterized by their adept ability to invade normal brain parenchyma. We have previously identified the cytoplasmic and normally nuclear sequestered pro-cytokinetic, small cytoskeletal GTPase ECT2 to be involved in the invasive process of malignant glioma. ECT2 shows dysregulated spatial regulation in malignant gliomas with increased cytoplasmic expression, in particular at the leading edge of invading primary glioma cells. This aberrant ECT2 plays a role in RAC1 and CDC42 activation, as shRNA mediated loss of ECT2 leads to no effect on cell cycle, but a less invasive phenotype and diminished RAC1 and CDC42 levels. Using immunoprecipitation and mass spectrometry we identified the novel RAS-GAP, RASAL2 as a significant cytoplasmic interactor with ECT2 in gliomas. We show this interaction represents a mechanism by which RAS (which is aberrantly activated in gliomas) can cross-talk with the RAC/RHO pathway and coordinate growth and invasion of gliomas. Over-expression of ECT2 leads to mesenchymal-amoeboid transition (MAT) in glioma cells. Cells expressing GFP-ECT2 show hyperactive cortical dynamics with the formation of membrane blebs, similar to an amoeboid phenotype. ECT2 localized to the cortical blebs during retraction in a similar manner to active RHOA in amoeboid cells. It is known that MAT relies on an antagonistic relationship between RHOA (pro-amoeboid) and RAC1 (promesenchymal). We tested whether our phenotype was mediated by RHOA or RAC1 by administration of the RHOA downstream inhibitor of ROCK, Y27632 and RAC1 NSC23766. RHOA pathway inhibition by Y27632 at 25uM was able to reverse this hypercortical activity and resulted in formation of lamellipodia, as seen with RAC1 activation. NSC23766 was unable to abolish the amoeboid phenotype in concentrations of up to 100uM. A proportion of GFP-ECT2 amoeboid cells were capable of migrating at velocities of up to 10 um/sec. Interestingly, although loss of ECT2 has no phenotypic changes in cells plated in a 2D context, loss of ECT2 by shRNA in cells plated within a collagen matrix show marked reduction in amoeboid phenotype. The ability of glioma cells to undergo MAT is a relatively new concept, however well documented in other cancer subtypes such as melanoma. The molecular switches involved in MAT remain elusive, however our data reveals a potential role for ECT2 in migratory phenotype switching. Importantly, when a stably expressing ECT2 shRNA glioma line is orthotopically injected into mouse brains, these ECT2 knockdown xenografts exhibit enhanced survival and diminished tumour engraftment as compared to controls. Taken together, this suggests that ECT2 is a viable target for malignant gliomas. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3847. doi:10.1158/1538-7445.AM2011-3847
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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) | 0.003 | 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".