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Record W2592957633 · doi:10.3324/haematol.2016.159053

Targeted therapy for a subset of acute myeloid leukemias that lack expression of aldehyde dehydrogenase 1A1

2017· article· en· W2592957633 on OpenAlexaff
Maura Gasparetto, Shanshan Pei, Mohammad Minhajuddin, Nabilah Khan, Daniel A. Pollyea, Jason R. Myers, John M. Ashton, Michael W. Becker, Vasilis Vasiliou, R. Keith Humphries, Craig T. Jordan, Clayton A. Smith

Bibliographic record

VenueHaematologica · 2017
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsArsenic trioxideAldehyde dehydrogenaseCancer researchHaematopoiesisMyelodysplastic syndromesStem cellMyeloid leukemiaCyclophosphamideLeukemiaMyeloidBiologyImmunologyChemistryMedicineChemotherapyInternal medicineApoptosisBone marrowBiochemistryCell biologyEnzyme

Abstract

fetched live from OpenAlex

Aldehyde dehydrogenase 1A1 (ALDH1A1) activity is high in hematopoietic stem cells and functions in part to protect stem cells from reactive aldehydes and other toxic compounds. In contrast, we found that approximately 25% of all acute myeloid leukemias expressed low or undetectable levels of ALDH1A1 and that this ALDH1A1− subset of leukemias correlates with good prognosis cytogenetics. ALDH1A1− cell lines as well as primary leukemia cells were found to be sensitive to treatment with compounds that directly and indirectly generate toxic ALDH substrates including 4-hydroxynonenal and the clinically relevant compounds arsenic trioxide and 4-hydroperoxycyclophosphamide. In contrast, normal hematopoietic stem cells were relatively resistant to these compounds. Using a murine xenotransplant model to emulate a clinical treatment strategy, established ALDH1A1− leukemias were also sensitive to in vivo treatment with cyclophosphamide combined with arsenic trioxide. These results demonstrate that targeting ALDH1A1− leukemic cells with toxic ALDH1A1 substrates such as arsenic and cyclophosphamide may be a novel targeted therapeutic strategy for this subset of acute myeloid leukemias.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.039
Threshold uncertainty score0.845

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.090
GPT teacher head0.365
Teacher spread0.275 · 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

Citations30
Published2017
Admission routes1
Has abstractyes

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