CSIG-22. A CD133-Akt-Wnt SIGNALING AXIS PROVIDES FUNCTIONAL INSIGHT INTO THE ROLE OF CD133 IN GLIOBLASTOMA BRAIN TUMOR-INITIATING CELLS
Bibliographic record
Abstract
Current transcriptional profiles of adult glioblastoma (GBM) recognize the activation of distinct signaling programs. Single-cell sequencing efforts have provided greater resolution of core developmental pathways implicated in disease progression and relapse. Of note, the Wnt pathway is activated in a subset of patients, despite the lack of recurrent activating mutations in human GBM. Given the description of CD133 as a marker of tumor-initiating cells in a number of human cancers associated with activated Wnt signaling, we investigated the role of CD133 in human GBM as a novel Wnt regulator. CD133high GBM lines were found to have greater Wnt levels when compared to CD133low lines. To establish a signaling axis between CD133 and Wnt we investigated the CD133-dependent activation of Akt and the subsequent downstream inhibition of GSK leading to beta-catenin activation. Ectopic expression of CD133 resulted in increased pAKT, pGSK (Ser 9), and beta-catenin. To further describe the context-dependent role for Akt activation of Wnt through GSK inhibition, CD133high lines were treated with the Akt inhibitor, MK-2006, which decreased pAKT, pGSK (Ser 9), and beta-catenin. In order to validate the tumorigenic potential of Wnt-activated cells, a Wnt reporter was used to isolate cells with endogenous Wnt signaling. Wnt-active cells maintained an increased self-renewal and tumor-initiating capacity when compared to Wnt-inactive cells. Xenografts generated from Wnt active cells had a reduced survival advantage as these contained an enhanced expression of stemness genes when compared to Wnt-inactive xenografts. To develop a rationale clinical therapeutic, we used RWO3, a novel humanized antibody directed at CD133. In vivo treatment with RW03 showed a significant reduction in activated Wnt signaling, highlighting the role of CD133 in modulating the Wnt pathway. Our work establishes a CD133-Akt-Wnt signaling axis in GBM through the functional characterization of CD133 and subsequent context-specific Akt-dependent regulation of the canonical Wnt pathway.
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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 | 0.001 | 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 | 0.001 |
| 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".