Alternative splicing of NUMB correlates with tumor immune evasion and metabolic adaptation
Bibliographic record
Abstract
Abstract Alternative splicing of the NUMB gene at exon 9 generates protein isoforms linked to tumor growth and metastasis, but its impact on the tumor immune microenvironment remains unclear. Using RNA sequencing data from over 5,000 tumors across 16 cancer types, including breast cancer subtypes, we found that tumors with high NUMB exon 9 inclusion exhibit lower expression of immune-related genes, reduced immune cell infiltration, and decreased cytolytic activity, consistent with an immune “cold” phenotype. This pattern was consistent across multiple cancer types and breast cancer subtypes. Additionally, exon 9-high tumors showed evidence of increased oxidative phosphorylation, suggesting metabolic adaptations that support tumor progression. These findings identify NUMB exon 9 inclusion as a potential biomarker of immune evasion and highlight opportunities for patient stratification and targeted therapies based on NUMB exon 9 inclusion levels.
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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 | 0.001 |
| 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) | 0.002 | 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".