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High aldehyde dehydrogenase and expression of cancer stem cell markers selects for breast cancer cells with enhanced malignant and metastatic ability

2008· article· en· W1997847812 on OpenAlexafffund
Alysha K. Croker, David Goodale, Jenny E. Chu, Carl O. Postenka, Benjamin D. Hedley, David A. Hess, Alison L. Allan

Bibliographic record

VenueJournal of Cellular and Molecular Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsRobarts Clinical TrialsWestern University
FundersCanadian Institutes of Health Research
KeywordsCD44Cancer stem cellMetastasisAldehyde dehydrogenaseCancer researchStem cellCD24Stem cell markerCancerCancer cellBiologyCellPathologyMedicineCell biologyBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Cancer stem cells (CSCs) have recently been identified in leukaemia and solid tumours; however, the role of CSCs in metastasis remains poorly understood. This dearth of knowledge about CSCs and metastasis is due largely to technical challenges associated with the use of primary human cancer cells in pre-clinical models of metastasis. Therefore, the objective of this study was to develop suitable pre-clinical model systems for studying stem-like cells in breast cancer metastasis, and to test the hypothesis that stem-like cells play a key role in metastatic behaviour. We assessed four different human breast cancer cell lines (MDA-MB-435, MDA-MB-231, MDA-MB-468, MCF-7) for expression of prospective CSC markers CD44/CD24 and CD133, and for functional activity of aldehyde dehydrogenase (ALDH), an enzyme involved in stem cell self-protection. We then used fluorescence-activated cell sorting and functional assays to characterize differences in malignant/metastatic behaviour in vitro (proliferation, colony-forming ability, adhesion, migration, invasion) and in vivo (tumorigenicity and metastasis). Sub-populations of cells demonstrating stem-cell-like characteristics (high expression of CSC markers and/or high ALDH) were identified in all cell lines except MCF-7. When isolated and compared to ALDH(low)CD44(low/-) cells, ALDH(hi)CD44(+)CD24(-) (MDA-MB-231) and ALDH(hi)CD44(+)CD133(+) (MDA-MB-468) cells demonstrated increased growth (P < 0.05), colony formation (P < 0.05), adhesion (P < 0.001), migration (P < 0.001) and invasion (P < 0.001). Furthermore, following tail vein or mammary fat pad injection of NOD/SCID/IL2gamma receptor null mice, ALDH(hi)CD44(+)CD24(-) and ALDH(hi)CD44(+)CD133(+) cells showed enhanced tumorigenicity and metastasis relative to ALDH(low)CD44(low/-) cells (P < 0.05). These novel results suggest that stem-like ALDH(hi)CD44(+)CD24(-) and ALDH(hi)CD44(+)CD133(+) cells may be important mediators of breast cancer 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.247
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations527
Published2008
Admission routes2
Has abstractyes

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