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Record W2133428001 · doi:10.1093/carcin/bgu045

Cell adhesion molecules and their relation to (cancer) cell stemness

2014· review· en· W2133428001 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCarcinogenesis · 2014
Typereview
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsUniversity of ManitobaUniversity Health Network
Fundersnot available
KeywordsAnoikisCell adhesion moleculeReprogrammingCancer stem cellExtracellular matrixIntegrinCarcinogenesisCell adhesionCell biologyEpithelial–mesenchymal transitionCancer researchCadherinCancerBiologyCancer cellStem cellMetastasisCellBiochemistryGenetics

Abstract

fetched live from OpenAlex

Despite decades of search for anticancer drugs targeting solid tumors, this group of diseases remains largely incurable, especially if in advanced, metastatic stage. In this review, we draw comparison between reprogramming and carcinogenesis, as well as between stem cells (SCs) and cancer stem cells (CSCs), focusing on changing garniture of adhesion molecules. Furthermore, we elaborate on the role of adhesion molecules in the regulation of (cancer) SCs division (symmetric or asymmetric), and in evolving interactions between CSCs and extracellular matrix. Among other aspects, we analyze the role and changes of expression of key adhesion molecules as cancer progresses and metastases develop. Here, the role of cadherins, integrins, as well as selected transcription factors like Twist and Snail is highlighted, not only in the regulation of epithelial-to-mesenchymal transition but also in the avoidance of anoikis. Finally, we briefly discuss recent developments and new strategies targeting CSCs, which focus on adhesion molecules or targeting tumor vasculature.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
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 head0.047
GPT teacher head0.313
Teacher spread0.266 · 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