ACTR-02. DCC-2618, A NOVEL pan-KIT AND PDGFRa KINASE SWITCH CONTROL INHIBITOR, SHOWS ENCOURAGING SIGNAL IN A PATIENT (PT) WITH GLIOBLASTOMA (GBM)
Bibliographic record
Abstract
Non-clinical data suggest that PDGFRa plays an important role in the development and progression of human gliomas. To date, few PDGFRa inhibitors with CNS activity have been available. DCC-2618 was designed to potently inhibit the broadest range of mutations (mut) in KIT & PDGFRa kinases that emerge during tumor progession or on treatment. In a dose-escalation study (NCT# 02571036) of oral DCC-2618 (QD or BID q28 days), pts with advanced malignancies with a molecular rationale for activity were eligible. MRI scans were performed initially every 2 cycles then every 3 cycles. We enrolled 4 GBM pts and 1 anaplastic astrocytoma (AA) pt with PDGFRa muts/ amplifications who had progressed after standard temozolomide chemoradiation (GBM) or temozolomide only (AA) and had received 0 to 5 salvage therapies. Three pts (2 GBM and 1 AA) had a triple amplification of PDGFRa, KIT and KDR (4q12 amplicon). Two GBM pts had activating PDGFRa mutations. Pts were treated at 20 mg (1 pt), 50 mg BID (2 pts) or 100 mg QD (2 pts). The per-protocol population (N=48) received doses up to 200 mg BID and DCC-2618 was well tolerated. One GBM pt with mut PDGFRa progressed after 6 weeks and one stopped treatment due to a tumor-related hemaorrhage on C1D12. Two of the three pts with triple amplifications progressed after 2 cycles while the third pt (GBM, 20 mg BID) achieved a PR per RANO after 9 cycles. This pt is currently in cycle 20 with a remarkable 94% tumor reduction. The durable partial response of >18 months in a GBM patient (94% tumor reduction) warrants further evaluation of DCC-2618 in gliomas. An expansion cohort for pts with KIT- and PDGFRa driven tumors was initiated to be able to better select the patient population with a likely benefit.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".