Neuronal ALKAL2 and its ALK receptor contribute to the development of colitis-associated colorectal cancer
Bibliographic record
Abstract
Tumor-infiltrating nerves play a critical role in cancer progression and treatment resistance. Our recent work identified ALKAL2, a ligand for the Anaplastic Lymphoma Kinase (ALK) receptor, as a key mediator of inflammatory pain, with its expression significantly elevated in TRPV1+ sensory neurons during inflammation. Here, we explored the regulation of neuronal ALKAL2 in a colitis-associated colorectal cancer (CAC) model. We found that neuronal ALKAL2 is upregulated at early stages of CAC, which in turn activates ALK signaling in the colonic mucosa. Notably, treating mouse colonic organoids with exogenous ALKAL2 triggered ALK activation. In vivo, mice treated with the ALK inhibitor lorlatinib at the onset of colitis exhibited a remarkable 90% reduction in tumor burden without significantly affecting overall inflammation. Moreover, activating TRPV1+ neurons using DREADD technology exacerbated tumor growth, whereas silencing these neurons significantly reduced it. These findings reveal that TRPV1+ nociceptors drive CAC progression via the ALKAL2/ALK pathway.
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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) | 0.002 | 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".