Broad Activity of Apto-253 in AML and Other Hematologic Malignancies Correlates with KLF4 Expression Level
Notice bibliographique
Résumé
Abstract Introduction: Aberrant expression of the homeodomain transcription factor CDX2 has recently been reported in a large proportion of AML cases. One consequence of CDX2 deregulation appears to be repressed expression of the transcription factor KLF4. Repression of KLF4 was shown to be critical for CDX2-mediated tumorigenesis, and forced genetic de-repression of KLF4 led to apoptosis of AML cells. APTO-253 is a novel small molecule that induces the expression of KLF4 and is cytotoxic to AML cell lines at low-nanomolar concentrations. We evaluated the activity of APTO-253 against a broad panel of primary specimens from patients with acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), and myelodysplastic syndromes/myeloproliferative neoplasms (MDS/MPN). APTO-253 was tested both as a single agent and in combinations with 2 other emerging targeted therapies, the BET bromodomain inhibitor JQ1 and the FLT3 inhibitor quizartinib. Methods: We used an ex vivo drug sensitivity assay to determine the activity of APTO-253, JQ1, and quizartinib across increasing concentrations of each agent up to 10 μM. Combinations were tested at fixed, equimolar ratios over the same concentration range. After a 3-day ex vivo culture, cell viability was assessed using a colorimetric tetrazolium-based MTS assay, and IC50 values were calculated. RNA-Seq was performed on AML specimens to permit investigation of correlations of drug sensitivity with gene expression levels. Results: We evaluated specimens from 177 patients with a variety of hematologic malignancy diagnoses (80 AML, 72 CLL, 25 MDS/MPN). The highest frequency of APTO-253 sensitivity occurred in AML, with 43/80 (54%) samples exhibiting an IC50 <1 μM. At this cutoff, 25/72 (35%) CLL samples and 3/25 (12%) MDS/MPN samples were sensitive to APTO-253. The average expression of KLF4 mRNA was 2-fold lower among AML samples with an IC50 <1 µM compared to those with IC50 >1 µM (p=0.07). Approximately 65% (56/87) of cases tested with a combination of APTO-253 and JQ1 showed the combination IC50 to be at least 2-fold lower than the IC50 of either agent alone. This enhanced efficacy of APTO-253 with JQ1 was observed across all 3 hematologic malignancies tested, whereas quizartinib enhancement of APTO-253 sensitivity was confined to AML (14/38, or 37% showed reduced IC50). Conclusions: These results support the potential of KLF4 as an important and frequently dysregulated master transcription factor in AML and suggest that the KLF4 inducer APTO-253 is effective at killing tumor cells in a majority of AML samples. The data also indicate activity of APTO-253 in other hematologic malignancies, namely CLL. Expression level of KLF4 may be one component of a biomarker for prediction of APTO-253 efficacy; a more extensive global gene expression signature analysis is under way. Finally, these data have identified prominent interaction of APTO-253 with the BET bromodomain inhibitor JQ1, as well as AML-restricted interaction of APTO-253 with the FLT3 inhibitor quizartinib, suggesting these classes of drugs as potential combination partners for APTO-253. Disclosures Rice: Aptose Biosciences: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. 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. Vellanki:Aptose Biosciences: Employment, Equity Ownership. Druker:Oncotide Pharmaceuticals: Research Funding; Sage Bionetworks: Research Funding; Fred Hutchinson Cancer Research Center: Research Funding; Bristol-Myers Squibb: Research Funding; Novartis Pharmaceuticals: Research Funding; Henry Stewart Talks: Patents & Royalties; McGraw Hill: Patents & Royalties; Leukemia & Lymphoma Society: Membership on an entity's Board of Directors or advisory committees, Research Funding; Blueprint Medicines: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Oregon Health & Science University: Patents & Royalties; MolecularMD: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Gilead Sciences: Consultancy, Membership on an entity's Board of Directors or advisory committees; ARIAD: Research Funding; AstraZeneca: Consultancy; Aptose Therapeutics, Inc (formerly Lorus): Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; CTI Biosciences: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees; Millipore: Patents & Royalties; Roche TCRC, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cylene Pharmaceuticals: Consultancy, Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Tyner:Incyte: Research Funding; Janssen Pharmaceuticals: Research Funding; Constellation Pharmaceuticals: Research Funding; Array Biopharma: Research Funding; Aptose Biosciences: Research Funding.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».