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Record W2096788030 · doi:10.1158/0008-5472.can-09-2153

Characterization of Melanoma Cells Capable of Propagating Tumors from a Single Cell

2010· article· en· W2096788030 on OpenAlexaff
Matthew A. Held, David P. Curley, David Dankort, Martin McMahon, Viswanathan Muthusamy, Marcus Bosenberg

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldMedicine
TopicCancer Cells and Metastasis
Canadian institutionsMcGill University
FundersNational Institute of Environmental Health SciencesNational Cancer Institute
KeywordsMelanomaCD34Cancer researchIn vitroCancerBiologyCellCancer cellImmunologyStem cellCell biologyGenetics

Abstract

fetched live from OpenAlex

Questions persist about the nature and number of cells with tumor-propagating capability in different types of cancer, including melanoma. In part, this is because identification and characterization of purified tumorigenic subsets of cancer cells has not been achieved to date. Here, we report tumor formation after injection of single purified melanoma cells derived from three novel mouse models. Tumor formation occurred after every injection of individual CD34+p75- melanoma cells, with intermediate rates using CD34-p75- cells, and rarely with CD34-p75+ cells. These findings suggest that tumorigenic melanoma cells may be more common than previously thought and establish that multiple distinct populations of melanoma-propagating cells (MPC) can exist within a single tumor. Interestingly, individual CD34-p75- MPCs could regenerate cellular heterogeneity after tumor formation in mice or multiple passages in vitro, whereas CD34+p75- MPCs underwent self-renewal only, showing that reestablishment of tumor heterogeneity is not always a characteristic of individual cells capable of forming tumors. Functionally, single purified MPCs were more resistant to chemotherapy than non-MPCs. We anticipate that purification of these MPCs may allow a more comprehensive evaluation of the molecular features that define tumor-forming capability and chemotherapeutic resistance in melanoma.

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 categoriesInsufficient payload (model declined to judge)
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 score0.007
Threshold uncertainty score1.000

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)0.0010.000

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 head0.055
GPT teacher head0.342
Teacher spread0.287 · 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.

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

Citations106
Published2010
Admission routes1
Has abstractyes

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