ENMD-981693 Is an Orally-Active Kinase Inhibitor with Activity towards Human Hematologic Cancers In Vitro and In Vivo.
Bibliographic record
Abstract
Abstract The clinical success of Gleevec (imatinib) for chronic myelogenous leukemia has demonstrated that small-molecule inhibitors of specific kinases can be developed into effective oncology therapies. However, the rapid development of resistance in leukemic cells to drugs such as Gleevec and the limited therapeutic indications addressed with these molecules suggests that considerable opportunity exists for new inhibitors with a distinctive spectrum of activities against multiple kinase targets. ENMD-981693 is a novel, orally-active molecule that was discovered through a screening effort directed towards Aurora kinases, a family of serine/threonine kinases that are essential for mitotic progression. ENMD-981693 is selective for the Aurora A isoform, with an IC50 value of 25 nM, compared to an IC50 value of ~700 nM for Aurora B. The activity of ENMD-981693 was evaluated against a panel of 100 recombinant kinases, and the compound was shown to inhibit a broad range of tyrosine kinase targets including Flt3, CSF1R, Lck, JAK2, and c-Kit. ENMD-981693 inhibited the in vitro growth of human hematopoietic cancer lines including MV4;11, K562, THP-1, Jurkat, TF-1, U937, and HL-60 with IC50 values ranging from 0.04 – 21 μM. ENMD-981693 was shown to induce G2/M cell cycle arrest followed by apoptosis in U937 cells, without induction of the endo-reduplication phenotype (≥4N DNA content) associated with Aurora B-acting inhibitors such as MK-0457 (VX-680) and AZD1152. Primary cells derived from AML patients were sensitive to treatment with ENMD-981693 in vitro, resulting in IC50 values from 0.2 – 6.0 μM. Sensitivity of primary CML samples was more variable in in vitro cytotoxicity assays, with IC50s in the range of 0.1 – 40 μM. ENMD-981693 shows significant antitumor activity and is well tolerated in xenograft studies, with no weight loss or morbidity observed in administration schedules of up to 100 mg/kg bid or 200 mg/kg qd, given continuously for more than 30 days. Results from in vivo efficacy studies with ENMD-981693 using the MV4;11 xenograft model will be described. In conclusion, ENMD-981693 is a novel kinase inhibitor with potent activity towards a number of targets important in hematologic cancers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".