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An In Vitro and In Vivo Evidence That Downregulation of Leukemia Inhibitory Factor (LIF) Receptor (LIF-R) Decreases the Metastatic Potential of Human Rhabdomyosarcoma (RMS) Cells.

2006· article· en· W2586464258 on OpenAlexaff
Marcin Wysoczynski, Katarzyna Miękus, Anna Marcinkowska, Anna Janowska‐Wieczorek, Mariusz Z. Ratajczak

Bibliographic record

VenueBlood · 2006
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLeukemia inhibitory factorHepatocyte growth factorRhabdomyosarcomaCancer researchCell cultureIn vivoBiologyBone marrowInternal medicineReceptorMolecular biologyChemistryMedicinePathologyImmunologySarcomaCytokineInterleukin 6

Abstract

fetched live from OpenAlex

Abstract Rhabdomyosarcoma (RMS) and skeletal muscle-derived tumors frequently infiltrate bone marrow (BM). We have demonstrated that the stromal-derived factor (SDF)-1-CXCR4 receptor (Blood2002;100:2597) and hepatocyte growth factor (HGF)-c-Met receptor (Cancer Res. 2003;63:7926) play an important role in RMS metastasis to BM. Leukemia inhibitory factor (LIF) is a well known factor that plays an important role in skeletal muscle development/regeneration and similarly as SDF-1 and HGF is secreted by BM stroma. This prompted us to examine whether the LIF-LIF receptor (LIF-R) axis affects the biology/metastasis of RMS cells. We employed in our studies, human established RMS cell lines, as well as RMS samples isolated from patients and noticed that LIF-R was expressed not only on established human RMS cell lines (7/7) but more importantly, it was also detectable in patient samples (23/23). We also found that in RMS cells LIF stimulatesphosphorylation of MAPKp42/44, AKT and STAT3,chemotaxis and adhesion andincreases resistance to cytostatics (e.g., etoposide). These LIF-mediated effects were inhibited after downregulating the LIF-R by siRNA. To learn more on the biological significance of the LIF-LIF-R axis in vivo we employed two models. First, human RMS cells (RH-30) were exposed or not exposed to LIF-R siRNA and subsequently injected into SCID™-Beige immunodeficient mice. To estimate the number of RMS cells that seed to BM and liver in these animals, we isolated DNA and using real- time RT-PCR, amplified human a-satellite sequences and murine b-actin. The number of human cells present in murine organs was subsequently calculated from a standard curve derived from mixing varying numbers of human cells with a constant number of murine cells. We noticed that downregulation of LIF-R by siRNA significantly decreased the number of human RMS cells in murine BM and liver (x4 and x2 respectively). In a second model, the RH30 cell line was selected by repetitive chemotaxis for cells that are highly responsive to LIF (RH-30 L) and subsequently the cells from parental RH-30 cell line and RH-30 L cells were injected intramuscularly. Six weeks after tumour inoculation, we detected more metastasis in bone marrow and lungs in mice injected with RH-30L cells as compared to parental RH-30 clone (x6 and x3 respectively). In conclusion, we present evidence for the first time that the inhibition of LIF-LIF-R axis may decrease the invasive potential of human RMS both in vitro and in vivo. Hence, molecular targeting of LIF-LIF-R axis could possibly become a more effective new strategy to control the progression and metastasis of RMS.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.399

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 head0.024
GPT teacher head0.274
Teacher spread0.250 · 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 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

Citations0
Published2006
Admission routes1
Has abstractyes

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