STEM-28. NANOPARTICLES ENCAPSULATING A CONNEXIN43 MIMETIC PEPTIDE LIMIT GLIOMA STEM CELL SURVIVAL AND GLIOBLASTOMA PROGRESSION
Bibliographic record
Abstract
Abstract Glioblastoma (GBM) is the most common and aggressive primary adult brain tumor in the US. The current treatment regimen for GBM still retains an alarmingly poor prognosis, with median survival of only 14.6 months. Failure to generate more effective treatment strategies is due to the infiltrative nature of GBM tumor cells, which hinders complete surgical resection, and cellular heterogeneity within GBM tumors, with a sub-population of glioma stem cells (GSCs) resistant to irradiation treatment and chemotherapeutic agents including temozolomide. As a result, all treated GBM patients will experience tumor recurrence, highlighting the need for novel approaches in targeting such refractory tumor cell populations to successfully treat GBM tumors and prevent recurrence. Using super resolution localization microscopy, we have identified that increased interaction of connexin43 (Cx43) with microtubules in GSCs confers tumorigenic behavior to these cells. We employed a Cx43 mimetic peptide named JM2 (juxtamembrane 2) that encompasses the microtubule binding sequence of the Cx43 carboxy-terminus. This peptide drug efficiently and specifically disrupts the interaction of Cx43 with microtubules and limits GSC survival, proliferation, and migration, without affecting normal human astrocytes. Next, we implemented the therapeutic strategy of JM2 encapsulation within biodegradable polymeric nanoparticles (NPs) to reduce administration frequency and patient discomfort, and increase peptide stability and activity. We confirmed sustained release of JM2 from these poly(lactic-co-glycolic) acid biodegradable NPs, and JM2 bioactivity through disruption of Cx43 interaction with microtubules. Administration of JM2-NPs inhibits GSC-derived neurosphere formation in vitro and patient GBM-derived organoid growth ex vivo. Finally, using an orthotopic xenograft brain tumor mouse model, we demonstrate in vivo that JM2-NPs significantly decrease the number of GSCs within brain tumors, and inhibit the formation of highly invasive GBM tumors. Our findings on generation of JM2-NPs to target GSC survival lays the foundation for future clinical trials in newly diagnosed GBM patients.
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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) | 0.001 | 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".