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Abstract LB-091: Inhibition of Siglec-15 prevents bone loss in a mouse model of multiple myeloma

2016· article· en· W2506579659 on OpenAlexaff
Gilles B. Tremblay, Anna N. Moraitis, Karin Vanderkerken, Mario Filion

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsAlethia Biotherapeutics (Canada)
Fundersnot available
KeywordsBortezomibMultiple myelomaBone marrowMedicineFemurTibiaBone diseaseOsteoporosisInternal medicinePathologyAnatomySurgery

Abstract

fetched live from OpenAlex

Abstract Multiple myeloma (MM) is a B-cell malignancy associated with infiltration and growth of plasma cells in the bone marrow resulting in end-organ damage including devastating osteolytic bone disease. We examined the ability of 25B2, an antibody targeting Siglec-15, to prevent bone loss in the 5T2MM syngeneic model of MM. C57BlKaLwRij male mice (n = 10/group) were injected with 5T2MM cells and 24h later treated for 12 weeks with the PBS, 25B2 (10 mg/kg, q3d), bortezomib (0.7 mg/kg, q3d) or a combination of 25B2 and bortezomib. 25B2 treatment caused a 3.7-, 5.4- and 1.2-fold increase in bone volume (%BV/TV) compared to PBS-treated mice in the tibia, femur and lumbar vertebra (LV), respectively. Increases in bone volume were also seen with bortezomib with 3.1-, 4.1- and 1.4-fold increases in the tibia, femur and LV, respectively. Combination of the two agents further increased%BV/TV by 6.9-, 10.5- and 1.5-fold in the tibia, femur and LV, respectively, when compared to the PBS treated mice. All of the changes were statistically significant with the exception of those in the LV. Unlike bortezomib treatment, which inhibits the growth of 5T2MM cells in this model, there was no direct effect of 25B2 on tumor burden in 5T2MM mice when the percentage of plasmacytosis and the serum paraprotein levels were measured. However, 25B2 caused a significant decrease in the number of bone lesions by 49.5%. The number of lesions in the bortezomib group decreased by 71.7%, but there was no significant difference between the 25B2 and bortezomib groups. The number of lesions decreased by 89.4% in the combination group. Consistent with the mechanism of action of Siglec-15 antibodies, osteoclasts were rendered inactive, however cross-talk with bone-forming osteoblasts was likely maintained. This unique mechanism of action would be particularly appropriate for MM, where osteolytic disease is not only the result of increased osteoclast activity but also decreased osteoblast-mediated bone formation. The 5T2MM model is one of the most representative of the human pathology and therefore, the effect observed in response to the Siglec-15 antibody holds the promise that such a treatment in MM patients could provide benefit and further delay skeletal related events. Citation Format: Gilles B. Tremblay, Anna Moraitis, Karin Vanderkerken, Mario Filion. Inhibition of Siglec-15 prevents bone loss in a mouse model of multiple myeloma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-091.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.103
GPT teacher head0.403
Teacher spread0.300 · 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
Published2016
Admission routes1
Has abstractyes

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