Uncovering the role of mutant RAC1 in cutaneous melanoma
Bibliographic record
Abstract
RAC1 is a member of the Rho family of small GTPases.Next-generation sequencing studies discovered that 5-10% of cutaneous melanoma possess an activating hotspot p.P29S mutation [1,2].Previous studies have shown that RAC1-P29S promotes proliferation of melanocytes and modulates response to mitogen-activated protein kinase (MAPK)-targeted therapy [3,4].However, the mechanism of action of RAC1-P29S remains unknown.To gain a better understanding of the role of RAC1-P29S in melanoma, we performed unbiased transcriptomic and proteomic analyses to elucidate signaling pathways affected by the p.P29S mutation.We performed RNA-sequencing (RNA-seq) on melanocytes engineered to overexpress RAC1-P29S.We integrated our analysis with human melanoma data available from The Cancer Genome Atlas (TCGA).Gene set enrichment analysis (GSEA) revealed that the most significant pathways deregulated in RAC1-P29S mutant melanomas were related to immune response and mitochondrial respiration.In addition, to gain insight into signaling mechanisms responsible for expression signatures and oncogenic functions of the P29S mutant, we identified several interacting proteins with RAC1-P29S in human melanocytes by utilizing proximity-dependent biotin identification (BioID) and complex purification assays.From our preliminary analysis, we identified a scaffolding protein, IQGAP1, as a preferential interactor of RAC1-P29S.In future works, we will perform more in-depth mechanistic studies from our unbiased proteomic and transcriptomic analyses presented here with the goal to devise novel therapeutic strategies to treat RAC1-mutant cancers.
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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 | 0.001 | 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 | 0.000 |
| 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".