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LIF-LIF-R and SDF-1-CXCR4 Axes Regulate Overlapping and Complementary Steps of Metastasis of Rhabdomyosarcoma - Implication for Developing Better Antimetastatic Therapies.

2005· article· en· W2594750141 on OpenAlexaff
Kasia Miekus, Marcin Wysoczynski, Ryan Reca, Jolanta Goździk, Bertolone J. Salvatore, Anna Janowska‐Wieczorek, Mariusz Z. Ratajczak

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLeukemia inhibitory factorRhabdomyosarcomaChemotaxisCancer researchCXCR4Cell cultureChemistryAlveolar rhabdomyosarcomaReceptorBiologyImmunologyMedicineChemokinePathologyCytokineSarcomaBiochemistry

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 Leukemia Inhibitory Factor (LIF)-LIF- receptor (LIF-R) axes play a pivotal role in RMS metastasis to BM. In this study performed on primary patient material (n=23) and human alveolar and embryonal RMS cell lines, we compared various prometastatic effects of both axes. First, we found that both motomorphogens (LIF and SDF-1) and their corresponding receptors (LIF-R and CXCR4) are upregulated in hypoxic conditions. Second, both functional receptors were expressed on RMS cells; however, the expression of LIF-R in contrast to CXCR4 was PAX3-FKHR-independent and did not correlate with the alveolar rhabdomyosarcoma (ARMS) phenotype. Both ligands stimulated similar signaling pathways (MAPKp42/44 and AKT) in RMS cells and similarly stimulated directional chemotaxis. However, SDF-1 affected the spontaneous motility of RMS cells to a higher degree than LIF and strongly upregulated the secretion of MMPs and VEGF. In contrast, LIF enhanced the resistance of RMS cells to cytostatics (e.g., etoposide). To compare the biological effects of both axes we focused on the ARMS cell line RH30 (highly responsive to SDF-1 and LIF) and selected cells that responded to SDF-1 but not LIF (RH30-S) and to LIF but not SDF-1 (RH30-L) by using repetitive chemotaxis to SDF-1 or LIF. We found that RH30-L cells, as compared to RH30-S cells, responded worse in chemotactic assay to BM-derived conditioned media; however, they adhered much better to BM stroma. When both cell populations (RH30-S and RH30-L), together with the parental RH30 cells, were tested in vivo for their seeding potential in various organs in RAG2 immunodeficient mice, we found that RH30-L cells seeded better to BM, liver and lymph nodes than RH30-S cells. More important, the metastatic potential of RH30 cells was significantly reduced only when the inhibitors of both receptors, (T140 for LIF-R and gp130 blocking antibody for CXCR4) were employed together. Hence, since RMS cells respond to more than one chemoattractant, strategies aimed at targeting a single factor-receptor axis would be ineffective. Targeting of the LIF-LIF-R axis, along with the SDF-1-CXCR4 axis, could thus become a new, more effective antimetastatic strategy to inhibit RMS 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 head0.030
GPT teacher head0.296
Teacher spread0.265 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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