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Record W2792106554 · doi:10.1016/j.bbmt.2017.12.413

Rabbit Anti-Thymocyte Globulin Induces Greater Killing of Leukemic Stem Cells Than the Healthy Hematopoietic Stem Cells

2018· article· en· W2792106554 on OpenAlexaff
Rosy Dabas, Poonam Dharmani Khan, Monica Modi, Tiffany Van Slyke, Joanne Luider, Joseph Brandwein, Don Morris, Andrew Daly, Faisal Khan, Jan Storek

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsFoothills Medical CentreAlberta HealthCalgary Laboratory ServicesAlberta Health ServicesUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsStem cellMedicineHaematopoiesisImmunologyCD34LeukemiaBone marrowMyeloid leukemiaPeripheral blood mononuclear cellCancer researchBiologyIn vitro

Abstract

fetched live from OpenAlex

Background: Rabbit anti-thymocyte globulin (ATG) is given with hematopoietic cell transplant (HCT) conditioning to prevent graft-versus-host disease (GvHD). Recently we showed that in vitro ATG at clinically relevant concentrations kills not only T cells but also leukemic blasts (Dabas et al., BBMT 2016). This might explain the non-increase in relapse incidence in patients given ATG versus no ATG (Walker et al., Lancet Oncol 2016). However, leukemia relapse is still the most frequent cause of HCT failure. A high number of leukemic stem cells (LSCs) remaining after therapy is indicative of poor prognosis or relapse. We have shown that ATG kills LSCs, however, at a high concentration of 50 mg/L. We next studied whether at that high concentration ATG kills also healthy hematopoietic stem cell (HSCs), as attempts to achieve the high concentration clinically would be indicated only if ATG killed LSCs but not HSCs. Study design: To study the cytotoxic effect of ATG on LSCs and HSCs, we used cryopreserved blood mononuclear cells (MNCs) from 25 newly diagnosed acute myeloid leukemia (AML) patients as a source of LSCs. Healthy volunteers' cryopreserved blood MNCs (n = 10) or cryopreserved filgrastim-mobilized apheresed blood MNC grafts from healthy donors (n = 15) were used as the source of HSCs. By flow cytometry, we measured stem cell killing induced by ATG (50 mg/L) in presence of active complement (human serum). The LSCs and HSCs were phenotypically defined as CD45dim/−, side scatterlow, CD34+, CD38− and negative for the lineage markers (CD14, CD16, CD19, CD56, CD3, CD235a and CD41a). Dead cells were identified as 7-amino-actinomycin D positive (7AAD+). Results: Treatment of LSCs with ATG resulted in median 36.6% dead (7AAD+) cells. In contrast, treatment of blood HSCs and graft HSCs resulted in 2% and 15% 7AAD+ cells, respectively. Conclusion: Here we show that in vitro LSCs are more sensitive to ATG mediated killing than healthy HSCs. However, the killing of LSCs occurs only at a relatively high ATG concentration (50 mg/L) which is ~5-fold higher than the maximum serum concentration achieved with a typical ATG dose (4.5 mg/kg). If ATG had the anti-LSCs activity also in vivo, using high dose ATG (leading to serum concentration of 50 mg/L) in patients could result in simultaneous decrease of both GVHD and relapse. Given the minimal effect on HSCs, the high dose ATG might not jeopardize engraftment.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.022
GPT teacher head0.255
Teacher spread0.232 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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