Netrin-1 and UNC5B Cooperate with Integrins to Mediate YAP-Driven Cytostasis
Bibliographic record
Abstract
Opposite expression and pro- or anti-cancer function of YAP and its paralog TAZ/WWTR1 stratify cancers into binary YAPon and YAPoff classes. These transcriptional coactivators are oncogenic in YAPon cancers. In contrast, YAP/TAZ are silenced epigenetically along with their integrin and extracellular matrix adhesion target genes in neural and neuroendocrine YAPoff cancers (e.g., small cell lung cancer, retinoblastoma). Forced YAP/TAZ expression induces these targets, causing cytostasis in part through Integrin-αV/β5, independent of the integrin-binding RGD ligand. Other effectors of this anticancer YAP function are unknown. Here, using clustered regularly interspaced short palindromic repeats (CRISPR) screens, we link the Netrin receptor UNC5B to YAP-induced cytostasis in YAPoff cancers. Forced YAP expression induces UNC5B through TEAD DNA-binding partners, as either TEAD1/4-loss or a YAP mutation that disrupts TEAD-binding (S94A) blocks, whereas a TEAD-activator fusion (TEAD(DBD)-VP64) promotes UNC5B induction. Ectopic YAP expression also upregulates UNC5B relatives and their netrin ligands in YAPoff cancers. Netrins are considered protumorigenic, but knockout and peptide/decoy receptor blocking assays reveal that in YAPoff cancers, UNC5B and Netrin-1 can cooperate with integrin-αV/β5 to mediate YAP-induced cytostasis. These data pinpoint an unsuspected Netrin-1/UNC5B/integrin-αV/β5 axis as a critical effector of YAP tumor suppressor activity. SIGNIFICANCE: Netrins are widely perceived as procancer proteins; however, we uncover an anticancer function for Netrin-1 and its receptor UNC5B.
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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".