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Record W3043397081 · doi:10.1042/bst20190992

The evolution of multicellularity and cancer: views and paradigms

2020· review· en· W3043397081 on OpenAlexaff
Aurora M. Nedelcu

Bibliographic record

VenueBiochemical Society Transactions · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMulticellular organismBiologySomatic cellEvolutionary biologySomatic evolution in cancerSelection (genetic algorithm)CancerDiseaseCancer cellGeneticsCellGeneComputer science

Abstract

fetched live from OpenAlex

Conceptually and mechanistically, the evolution of multicellularity required the integration of single cells into new functionally, reproductively and evolutionary stable multicellular individuals. As part of this process, a change in levels of selection occurred, with selection at the multicellular level overriding selection at the cell level. The stability of multicellular individuals is dependent on a combination of mechanisms that supress within-group evolution, by both reducing the occurrence of somatic mutations as well as supressing somatic selection. Nevertheless, mutations that, in a particular microenvironment, confer mutant lineages a fitness advantage relative to normal somatic cells do occur, and can result in cancer. This minireview highlights several views and paradigms that relate the evolution of multicellularity to cancer. As a phenomenon, cancer is generally understood as a failure of multicellular systems to suppress somatic evolution. However, as a disease, cancer is interpreted in different frameworks: (i) a breakdown of cooperative behaviors underlying the evolution of multicellularity, (ii) a disruption of molecular networks established during the emergence of multicellularity to impose constraints on single-celled units, or (iii) an atavistic state resulting from reactivating primitive programs that originated in the earliest unicellular species. A number of assumptions are common in all the views relating cancer as a disease to the evolution of multicellularity. For instance, cancer is considered a reversal to unicellularity, and cancer cells are thought to both resemble unicellular organisms and benefit from ancestral-like traits. Nevertheless, potential limitations of current paradigms should be acknowledged as different perspectives can provide novel insights with potential therapeutic implications.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.029
GPT teacher head0.287
Teacher spread0.258 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations42
Published2020
Admission routes1
Has abstractyes

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