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Record W1212960208

The β-catenin target gene bFGF is expressed in a small fraction of tumor cells with characteristics of cancer stem cells in human colorectal cancer

2008· article· en· W1212960208 on OpenAlexaff
Silvio K. Scheel, Bikul Das, Micky Tsui, Thomas Brabletz, Angela Haynl, Herman Yeger, Thomas Kirchner, Andreas Jung

Bibliographic record

VenueCancer Research · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsWnt signaling pathwayCancer stem cellAdherens junctionBiologyCancer researchCateninStem cellBasic fibroblast growth factorEpithelial–mesenchymal transitionBeta-cateninCancerTumor progressionColorectal cancerCancer cellCell biologyCellCadherinMetastasisGrowth factorSignal transductionGenetics
DOInot available

Abstract

fetched live from OpenAlex

AACR Annual Meeting-- Apr 12-16, 2008; San Diego, CA 5002 Many human colorectal cancers (CRC) are characterized by the deregulation of the Wnt signalling pathway leading to the stabilization and accumulation of β-catenin in tumor cells. Depending on the subcellular localization, β-catenin exerts two functions: at the cell membrane in a complex with E-cadherin, it is an integral part of the zonula adherens, thus mediating epithelial organization. This phenotype is found in central areas of CRCs. At the invasive front β-catenin is expressed in the nucleus which is associated with a gain of mesenchymal characteristics and strong transcriptional activity of the Wnt/β-catenin pathway. Thus, in these cells Wnt/β-catenin target genes conferring migration, invasion and dissemination -hallmarks of malignant progression- are transcriptionally up-regulated. Therefore, nuclear β-catenin induces in the context of the invasive front an epithelio-mesenchymal transition (EMT). As the cancer stem cell marker CD133 is also a Wnt/β-catenin target gene, nuclear β-catenin expressing tumor cells might thus be migrating cancer stem cells (MCSC). Finally, in cell culture, the maintenance of dedifferentiated, as spheroids growing colorectal tumor cells with the capability of initiating tumor growth in mice strictly depends on bFGF (basic fibroblast growth factor), indicating bFGF as an essential stemness supporting growth factor. Therefore, we hypothesized that bFGF might be another Wnt/β-catenin target gene which is produced in an autocrine manner as part of an inherent stemness maintenance program of mesenchymally transformed MCSCs at the invasive front of human colorectal carcinomas. In a first set of experiments we show evidence that bFGF is indeed a Wnt/β-catenin target gene employing electromobillity shift assays (EMSA) and chromatin immunoprecipitations (ChIP), luciferase-gene reporter assays, expression analysis in cultivated colorectal tumor cell lines using RT-PCR and Western blotting as well as β-catenin specific RNA interference (RNAi). In a second line of experiments we demonstrate that the cultivated human colorectal cancer cell line CaCo2 contains at least two different types of cells with respect to Hoechst 33342 dye exclusion. A tiny (0.1 %) Hoechst 33342 low or negative side population (SP) of cells initiated tumor growth in a xenograft mouse model at low cell numbers in contrast when cells were taken from the bulk culture or Hoechst 33342 positive population. Interestingly, the SP cells expressed high amounts of bFGF as well as CD133 compared to non-SP CaCo2 cells. Taken together we demonstrate that β-catenin regulates bFGF expression and that tumor initiating cells are characterized by high expression of bFGF and CD133. This is in support with the model that tumor cells at the invasive front resemble MCSC which is strengthened by the immunohistochemically detectable expression of bFGF in these cells.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

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)0.0040.002

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 head0.031
GPT teacher head0.315
Teacher spread0.284 · 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 designObservational
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
Published2008
Admission routes1
Has abstractyes

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