STEM-01. AN OSMR-CLIC1 CROSS TALK DRIVES KEY ONCOGENIC PATHWAYS IN GLIOBLASTOMA
Bibliographic record
Abstract
Abstract Glioblastoma (GB) is the most malignant genetically diverse brain tumour, with no cure. The most common genetic mutation in GB is a truncated active mutant of epidermal growth receptor (EGFR), the EGFRvIII. Oncostatin M Receptor (OSMR) orchestrates a feedforward signaling mechanism with EGFRvIII and the signal transducer and activator of transcription 3 (STAT3), to drive GB progression. Beyond EGFRvIII, OSMR promotes brain tumour stem cells (BTSCs) via upregulation of mitochondrial oxidative phosphorylation and contributes to therapy resistance. The molecular mechanisms underlying the multifaceted roles of OSMR in different contexts are largely unclear. Here, we systematically mapped the OSMR interactome using Mammalian Membrane Two-Hybrid High-Throughput Screening (MaMTH-HTS). This unbiased approach led to the identification of OSMR-specific and OSMR/EGFRvIII-specific binding proteins, revealing context-dependent OSMR functions. Among a subset of common interactors, we uncovered chloride intracellular channel 1 (CLIC1) as a critical regulator of both OSMR-STAT3 signaling and the OSMR/EGFRvIII complex in GB. CLIC1 physically associates with both OSMR and EGFRvIII and plays a key role in EGFRvIII packaging into extracellular vesicles (EVs). Genetic deletion of CLIC1 disrupts the OSMR/EGFRvIII interaction, impairs STAT3 activation, reduces EGFRvIII EV content, and slows GB progression. Using whole-cell patch-clamp recordings and a monoclonal antibody that selectively targets transmembrane CLIC1 (tmCLIC1omab), we establish a distinct pharmacologically and biophysically tmCLIC-mediated current in GB indispensable for sustaining EGFRvIII/STAT3 signaling. Importantly, we show that OSMR is required for maintaining CLIC1-mediated ionic balance at the plasma membrane (PM). Our study uncovers a bidirectional cross-talk between OSMR and tmCLIC1 in GB, which is essential for fueling its malignant growth.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".