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Clinical Pharmacokinetics of Apto-253 Support Its Use As a Novel Agent for the Treatment of Relapsed or Refractory Hematologic Malignancies

2015· article· en· W2558903074 on OpenAlexaff
William G. Rice, Jeff Lightfoot, Hongying Zhang, Tiffany Cheng, Avanish Vellanki, Robert Peralta, Stephen B. Howell, Andrea Local, Fannie Chau, Luis Esquivies

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicKruppel-like factors research
Canadian institutionsAptose Biosciences (Canada)
Fundersnot available
KeywordsKLF4MedicineCancer researchLeukemiaInternal medicineChemistryTranscription factorBiochemistryGene

Abstract

fetched live from OpenAlex

Abstract APTO-253 is a novel anticancer small molecule currently in a multicenter open-label, Phase I dose escalation study in patients with relapsed or refractory hematologic malignancies. APTO-253 has potent cytotoxic activity against leukemia, lymphoma and myeloma cell lines IC50s of 6.9 - 305 nM. APTO-253 produces significant tumor growth inhibition in the KG-1, THP-1 and Kasumi-1 xenograft models of human acute myeloid leukemia (AML). The anticancer activity of APTO-253 is mediated through induction of Krüppel-like factor 4 (KLF4), a tumor suppressor that is epigenetically silenced in many solid tumors and hematologic cancers. KLF4 expression is often downregulated in AML due to repressive binding of CDX2 to the KLF4 promoter. Increased levels of CDX2 are found in the majority of patients with AML and ALL, as well as in 40% of MDS patients, whereas CDX2 is not expressed in normal hematopoietic cells. Treatment of cultured AML cells with APTO-253 reverses the KLF4 silencing, resulting in induction of p21 and cell death by apoptosis. KG-1 AML cells treated with APTO-253 showed time- and concentration-dependent induction of KLF4 and a concentration-dependent increase in p21 mRNA levels following induction of KLF4. APTO-253 treatment of KG-1 cells for 24 h induced a 14-fold increase in KLF4 mRNA and 16-fold increase in p21 mRNA over basal levels. Following washout of APTO-253, the level of KLF4 mRNA decayed to approximately 50% of maximum induction level over a 24 h period. The potential for APTO-253 as a therapeutic option in AML was further supported by safety and pharmacokinetics data from an earlier Phase I trial of APTO-253 in patients with advanced or metastatic solid tumors during which APTO-253 was administered at doses of 20 - 387 mg/m2 using a dosing schedule of days 1 and 2, and 15 and 16 of a 28 day cycle. APTO-253 showed a dose-dependent increase in Cmax and AUC, and as the dose was escalated from 80 to 176 mg/m2 the Cmax ranged from 1,800 - 4,960 nM on day 1 and 1,600 - 6,100 nM on day 2. These results suggest that exposure levels from these doses of APTO-253 should be sufficient for single agent activity in patients with AML and other hematologic malignancies. APTO-253 demonstrated a favorable safety profile when tested against 5 major cytochrome P450 enzymes (1A2, 2C19, 2C9, 2D6 and 3A4), against a panel of proteins and receptors, and in the hERG tail current density assay. Metabolic profiling of APTO-253 at 50 μM in human liver microsomes showed no glutathione or glucuronide conjugation and only a minor hydroxylated metabolite. Finally, 1 μM APTO-253 did not inhibit kinases in a safety panel (40 kinases) or in a broad oncology panel (98 kinases), demonstrating that APTO-253 activity is not driven by kinase inhibition. Taken together, our results demonstrate that APTO-253 has substantial potential for the treatment of AML and other hematologic malignancies and is of particular interest due to its ability to modulate the expression of the KLF4 master transcription factor that plays a central role in restraining the growth of leukemic cells. Disclosures Howell: Aptose Biosciences: Consultancy, Equity Ownership; Angstrom: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Abeoda: Equity Ownership, Membership on an entity's Board of Directors or advisory committees; InhibRx: Equity Ownership.

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)0.000
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 score0.116
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.175
GPT teacher head0.409
Teacher spread0.234 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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