TRAF6 is an amplified oncogene bridging the RAS and NF-κB pathways in human lung cancer
Bibliographic record
Abstract
Somatic mutations and copy number alterations (as a result of deletion or amplification of large portions of a chromosome) are major drivers of human lung cancers. Detailed analysis of lung cancer-associated chromosomal amplifications could identify novel oncogenes. By performing an integrative cytogenetic and gene expression analysis of non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC) cell lines and tumors, we report here the identification of a frequently recurring amplification at chromosome 11 band p13. Within this region, only TNF receptor-associated factor 6 (TRAF6) exhibited concomitant mRNA overexpression and gene amplification in lung cancers. Inhibition of TRAF6 in human lung cancer cell lines suppressed NF-κB activation, anchorage-independent growth, and tumor formation. In these lung cancer cell lines, RAS required TRAF6 for its oncogenic capabilities. Furthermore, TRAF6 overexpression in NIH3T3 cells resulted in NF-κB activation, anchorage-independent growth, and tumor formation. Our findings show that TRAF6 is an oncogene that is important for RAS-mediated oncogenesis and provide a mechanistic explanation for the previously apparent importance of constitutive NF-κB activation in RAS-driven lung 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 | 0.000 | 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) | 0.001 | 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".