Identification of pannexin 1-regulated genes, interactome, and pathways in rhabdomyosarcoma and its tumor inhibitory interaction with AHNAK
Bibliographic record
Abstract
Rhabdomyosarcoma (RMS), the most common soft tissue sarcoma in children, is an aggressive cancer with a poor prognosis. Despite current management, the 5-year survival rate for patients with metastatic RMS is ∼30%; underscoring the need to develop better treatment strategies. We have recently reported that pannexin 1 (PANX1) levels are downregulated in RMS and that restoring its expression inhibits RMS progression. Here, we have surveyed and characterized the molecular changes induced by PANX1 re-expression in RMS. We cataloged transcriptomic changes in this context by RNA sequencing. At the protein level, we unveiled PANX1 interactors using BioID, complemented by co-immunoprecipitation coupled to high-performance liquid chromatography/electrospray ionization tandem mass spectrometry performed in PANX1-enriched fractions. Using these data, we generated searchable public databases for the PANX1 interactome and changes to the RMS transcriptome occurring when PANX1 expression is restored. STRING network analyses revealed a PANX1 interactome involving plasma membrane and cytoskeleton-associated proteins including the previously undescribed interactor AHNAK. Indeed, AHNAK knockdown abrogated the PANX1-mediated reduction in RMS cell viability and migration. Using these unbiased approaches, we bring insight to the mechanisms by which PANX1 inhibits RMS progression, identifying the cell migration protein AHNAK as a key modifier of PANX1-mediated changes in RMS malignant properties.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".