<i>De novo</i> evolution of transmissible tumors in Hydra
Bibliographic record
Abstract
Abstract While most cancers are not transmissible, there are rare cases where cancer cells have acquired the ability to spread vertically or horizontally to other individuals, and sometimes species, causing epidemics in their hosts. However, as these transmissible cancers are usually detected once they are relatively well disseminated in host populations, the conditions associated with their origin remain poorly understood. Using the freshwater cnidarian Hydra oligactis , which exhibits spontaneous tumor development that in some strains became vertically transmitted, this study presents the first experimental observation of the evolution of a transmissible tumor. Specifically, we assessed the initial vertical transmission rate of spontaneous tumors and explored the potential for optimizing this rate through artificial selection. One of the hydra strains, which evolved transmissible tumors over five generations, was characterized by analysis of cell type and microbiome, as well as assessment of life-history traits. Our findings indicate that tumor transmission can be immediate for some strains and can be enhanced by selection. The resulting tumors are characterized by overproliferation of large interstitial stem cells and, in contrast with other transmissible tumors on Hydra, are not associated with a specific microbiome. Furthermore, although tumor transmission has only been established over 5 generations, it was sufficient to alter life-history traits in the host, suggesting a compensatory response. This work, therefore, makes the first contribution to understanding the conditions of transmissible cancer emergence and their short-term consequences for the host.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".