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Record W4414370442 · doi:10.1093/emph/eoaf026

Multicellular cooperation and the hallmarks of cancer: A new foundation

2025· article· en· W4414370442 on OpenAlexaff
Carlo C. Maley, Amy M. Boddy, Aurora M. Nedelcu, Athena Aktipis

Bibliographic record

VenueEvolution Medicine and Public Health · 2025
Typearticle
Languageen
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsUniversity of New Brunswick
FundersNational Institutes of Health
KeywordsMulticellular organismContext (archaeology)Function (biology)Foundation (evidence)Resource (disambiguation)Cell division

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.789
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.408
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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