CSIG-02. VAL-083 INHIBITS PROLIFERATION OF A PANEL OF EIGHT GLIOBLASTOMA STEM CELL LINES: DOWNREGULATION OF BDR4 AS A NOVEL ANTI-NEOPLASTIC MECHANISM
Bibliographic record
Abstract
VAL-083 (Dianhydrogalactitol) is a bi-functional DNA targeting agent that is currently being evaluated in a phase II trial in recurrent glioblastoma (GBM) patients. The goal of the present study was to further elucidate the anti-neoplastic effects and signaling pathways through which VAL-083 functions. We examined the efficacy of VAL-083 against a panel of eight GBM stem cells (GSCs) isolated from newly diagnosed GBM patients. The panel of GSCs were molecularly phenotyped based on the expression of several proteins including EGFR, EGFRvIII, and MGMT as well as several stem cell markers including SOX2, NESTIN, MST1, CD133, TFRC, and OLIG2. The effect of VAL-083 on GSC growth was measured using WST-1 reagent and the effect on GSC’s ability to form neurospheres was assessed by microscopy. Our results show that VAL-083 inhibits neurosphere formation in all eight GSCs. Further, VAL-083 inhibits the growth of GSCs with an IC50 of 200–2000 nM. To identify the molecular pathways affected by VAL-083, control and VAL-083-treated GSCs were subjected to proteomic analysis using reverse phase protein array (RPPA) technology. The RPPA examined the expression of a total of 297 proteins and phosphoproteins. It was found that VAL-083 affects the expression of several proteins and phosphoproteins central to GBM growth. A key protein significantly downregulated by VAL-083 was bromodomain protein 4 (BRD4). This is a salient important finding because BRD4 has been implicated in several cancers including GBM, and agents that target BRD4 are undergoing development as anti-neoplastic agents. In summary, we report that VAL-083 is effective in halting the growth of a panel of GSC isolated from newly diagnosed GBM patients and the underlying mechanism involves downregulation of BRD4.
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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 | 0.001 |
| 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".