Combined RNAi-Mediated Suppression of Rictor and EGFR Resulted in Complete Tumor Regression in an Orthotopic Glioblastoma Tumor Model
Bibliographic record
Abstract
The PI3K/AKT/mTOR pathway is commonly over activated in glioblastoma (GBM), and Rictor was shown to be an important regulator downstream of this pathway. EGFR overexpression is also frequently found in GBM tumors, and both EGFR and Rictor are associated with increased proliferation, invasion, metastasis and poor prognosis. This research evaluated in vitro and in vivo whether the combined silencing of EGFR and Rictor would result in therapeutic benefits. The therapeutic potential of targeting these proteins in combination with conventional agents with proven activity in GBM patients was also assessed. In vitro validation studies were carried out using siRNA-based gene silencing methods in a panel of three commercially available human GBM cell lines, including two PTEN mutant lines (U251MG and U118MG) and one PTEN-wild type line (LN229). The impact of EGFR and/or Rictor silencing on cell migration and sensitivity to chemotherapeutic drugs in vitro was determined. In vivo validation of these studies was focused on EGFR and/or Rictor silencing achieved using doxycycline-inducible shRNA-expressing U251MG cells implanted orthotopically in Rag2M mice brains. Target silencing, tumor size and tumor cell proliferation were assessed by quantification of immunohistofluorescence-stained markers. siRNA-mediated silencing of EGFR and Rictor reduced U251MG cell migration and increased sensitivity of the cells to irinotecan, temozolomide and vincristine. In LN229, co-silencing of EGFR and Rictor resulted in reduced cell migration, and increased sensitivity to vincristine and temozolomide. In U118MG, silencing of Rictor alone was sufficient to increase this line's sensitivity to vincristine and temozolomide. In vivo, while the silencing of EGFR or Rictor alone had no significant effect on U251MG tumor growth, silencing of EGFR and Rictor together resulted in a complete eradication of tumors. These data suggest that the combined silencing of EGFR and Rictor should be an effective means of treating GBM.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".