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Record W4300606952

Systematic in-vitro evaluation of the NCI/NIH Developmental Therapeutics Program Approved Oncology Drug Set for the identification of a candidate drug repertoire for MLL-rearranged leukemia

2011· article· en· W4300606952 on OpenAlexaboutno aff
Hoeksema KA, Aarthi Jayanthan, T Cooper, Lia Gore, T Trippett, Jessica Boklan, Arceci RJ, Aru Narendran

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2011
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsDrugMedicineIdentification (biology)LeukemiaPharmacologyOncologyComputational biologyInternal medicineBiology
DOInot available

Abstract

fetched live from OpenAlex

Kimberley A Hoeksema1, Aarthi Jayanthan1, Todd Cooper2, Lia Gore3, Tanya Trippett4, Jessica Boklan6, Robert J Arceci5, Aru Narendran11Division of Pediatric Oncology, Alberta Children's Hospital, Calgary, AB, Canada; 2Aflac Cancer Center and Blood Disorders Service, Children's Healthcare of Atlanta, Emory University, Atlanta, GA, USA; 3Center for Cancer and Blood Disorders, Children's Hospital, University of Colorado Denver, Aurora, CO, USA; 4Memorial Sloan-Kettering Cancer Center, New York, NY, USA; 5Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA; 6Center for Cancer and Blood Disorders, Phoenix Children's Hospital, Phoenix, AZ, USAAbstract: Despite significant progress made in the overall cure rate, the prognosis for relapsed and refractory malignancies in children remains extremely poor. Hence, there is an urgent need for studies that enable the timely selection of appropriate agents for Phase I clinical studies. The Pediatric Oncology Experimental Therapeutics Investigators' Consortium (POETIC) is systematically evaluating libraries of known and novel compounds for activity against subsets of high-risk pediatric malignancies with defined molecular aberrations for future clinical development. In this report, we describe the in-vitro activity of a diverse panel of approved oncology drugs against MLL-rearranged pediatric leukemia cell lines. Agents in the Approved Oncology Drug Set II (National Cancer Institute/National Institutes of Health Developmental Therapeutics Program) were evaluated by in-vitro cytotoxicity assays in pediatric acute lymphoblastic leukemia and acute myeloid leukemia cell lines with MLL gene rearrangements. Validation studies were carried out with patient leukemia cells in culture. Comparative analysis for toxicity against nonmalignant cells was evaluated in normal bone marrow stromal cells and normal human lymphocytes. Results from this study show that 42 of the 89 agents tested have measurable cytotoxicity against leukemia cells, and among these, 12 were effective against all five MLL-rearranged cell lines (IC50 [half maximal inhibitory concentration] < 1 µM). These 12 agents include cladribine, dactinomycin, daunorubicin, docetaxel, etoposide, gemcitabine, mitomycin C, mitoxantrone, teniposide, topotecan, triethylenemelamine, and vinblastine. We show that the Approved Oncology Drug Set II contains a number of agents with potent antileukemic activity in the tested cell lines. As approved drugs, these agents have been used in clinical settings for many years for other malignancies, thus their toxicity profile, pharmacokinetics, and other properties are readily available. Further evaluation of their use in future clinical trials for pediatric leukemia with MLL abnormalities should be considered.Keywords: drug screening, therapeutic repertoire

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)0.001
metaresearch head score (Gemma)0.002
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.399
GPT teacher head0.574
Teacher spread0.174 · 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
Published2011
Admission routes1
Has abstractyes

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