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Record W2900461132

Anti-CD44 antibody, ARH460-16-2, binds to human AML CD34+CD38- cancer stem cells and demonstrates anti-tumor activity in an AML xenograft model

2008· article· en· W2900461132 on OpenAlexaff
Luis da Cruz, Fortunata McConkey, Ningping Feng, Daniel S. Pereira, Susan Hahn, Daniel Rubinstein, David Young

Bibliographic record

VenueCancer Research · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsArius3D (Canada)
Fundersnot available
KeywordsCD44CD38Cancer stem cellHaematopoiesisStem cellCD34Cancer researchMultiple myelomaLeukemiaMonoclonal antibodyBone marrowCancerMedicineAntibodyImmunologyBiologyInternal medicineCell
DOInot available

Abstract

fetched live from OpenAlex

3976 The CD44 glycoprotein was first identified in cells of hematopoietic origin. CD44 has been found expressed in several hematologic malignancies including AML, ALL, CLL and multiple myeloma. Further, CD44 has been shown to be expressed on the CD34+CD38- cancer stem cells in these malignancies. These findings suggest that targeting CD44 in leukemia may be an effective therapeutic strategy. Using Arius’ FunctionFIRST™ platform, ARH460-16-2, a monoclonal antibody targeting CD44, was discovered. This antibody has potent anti-tumor activity in solid tumor models of breast (CD44+CD24-/lo), liver and prostate cancer. Using flow cytometry, chimeric ARH460-16-2 (chARH460-16-2) was shown to bind to cancer cells from patients with AML, CLL, ALL (B and T), multiple myelomas and to cells from patients with Monoclonal Gammopathies of Undetermined Significance (MGUS), albeit at varying levels of binding. chARH460-16-2 also bound to various leukemia, lymphoma and multiple myeloma cell lines including KG-1, HL-60, CCRF-CEM and OPM, respectively. To determine whether ARH460-16-2 also recognizes CD44 on hemopoietic stem cells, flow cytometry was carried out on peripheral blood samples from patients with AML. The results showed that the antibody bound to all AML CD34+CD38- cancer stem cells. While ARH460-16-2 also bound normal hematopoietic CD34+CD38- stem cells, albeit to a lower degree, these data raise the possibility that ARH460-16-2 can target AML cancer stem cells in a therapeutic setting. Consistent with this notion, a non-GLP cynomolgus dose-ranging toxicology study using chARH460-16-2, did not detect abnormalities in the hematopoietic compartment even though chARH460-16-2 bound to variety of blood cell types. To assess the therapeutic potential in hematologic cancers chARH460-16-2 was tested in two established in vivo subcutaneous models of promyelocytic leukemia (HL-60) and AML (KG-1) in SCID mice. In these experiments, chARH460-16-2 had significant dose-responsive tumor growth inhibition in the KG-1 model (57% at 10 mg/kg) and an increase in the median survival of 62 days compared to 49 days in the control group. The antibody did not have anti-tumor activity in the HL-60 model. Because the maximum levels of binding to KG-1and HL-60, as determined by flow cytometry, were 100 and 4.5 fold above isotype respectively, it is possible that the therapeutic activity of the antibody may directly correlate with CD44 levels.
 ARH460-16-2 is being developed as a therapeutic monoclonal antibody for solid tumors and hematologic malignancies based on its effectiveness in pre-clinical models. Its target, CD44, is expressed in a variety of hematologic malignancies and CD34+CD38- cancer stem cells in AML and extends its therapeutic utility.

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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.412
Teacher spread0.328 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

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