Multicellular cooperation and the hallmarks of cancer: A new foundation
Bibliographic record
Abstract
Abstract Multicellularity evolved independently several times across the tree of life. In all cases, these events were dependent on various types of cellular cooperation. We previously identified five universal foundations of cellular cooperation that are required in all complex multicellular lineages to allow the collection of cells to function and reproduce as a whole (i.e. a multicellular individual). These include: proliferation inhibition, controlled cell death, resource allocation, division of labor, and maintenance of the extracellular environment. We propose that there is a sixth universal foundation of multicellularity that breaks down in cancer: proximity maintenance. By staying in close proximity, cells can more easily provide benefits for one another, communicate, coordinate their behavior, and evolve increased size and complexity. Here, we revisit and further develop the five original foundations of multicellular cooperation in the context of the evolution of multicellularity from unicellular ancestors and their implications for cancer progression. In our previous work, we suggested that the breakdown of all these cooperative behaviors is reflected in the universal hallmarks of cancer. Similarly, the breakdown of proximity maintenance maps to another hallmark of cancer—activating invasion and metastasis.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".