Mutational heterogeneity of imatinib resistance and efficacy of ripretinib vs sunitinib in patients with gastrointestinal stromal tumor: ctDNA analysis from INTRIGUE.
Bibliographic record
Abstract
397784 Background: Ripretinib, a switch-control tyrosine kinase inhibitor (TKI), is indicated for patients (pts) with gastrointestinal stromal tumor (GIST) who received prior treatment with ≥3 TKIs, including imatinib. Sunitinib is approved for advanced GIST after imatinib failure. Circulating tumor DNA (ctDNA) analysis may provide insight into the efficacy of these agents in second-line advanced GIST. Here, we present exploratory baseline ctDNA results from INTRIGUE. Methods: INTRIGUE is an open-label, phase 3 study that enrolled adult pts with advanced GIST who progressed on or had intolerance to imatinib (NCT03673501). Randomization was 1:1 to ripretinib 150 mg once daily (QD) or sunitinib 50 mg QD (4 wks on/2 wks off). Baseline peripheral whole blood was analyzed by Guardant360, a 74-gene ctDNA next-generation sequencing (NGS)-based assay. Only KIT mutations are reported here. Results: Of 453 pts in the overall intent-to-treat (ITT) population, 362 (80%) samples were analyzed. ctDNA was detected in 280/362 (77%), with KIT mutations detected in 213/280 (76%). Common resistance mutations were in the KIT activation loop (AL; exons 17/18; 89/213, 42%) and ATP-binding pocket (ATP-BP; exons 13/14; 81/213, 38%). Efficacy in pts with detectable ctDNA in the KIT exon 11 and overall ITT populations was consistent with the primary analysis based on tumor data used for randomization. Pts with KIT exon 11 + 17/18 (−9/13/14) mutations had superior progression-free survival (PFS), objective response rate (ORR), and overall survival (OS) with ripretinib vs sunitinib, whereas pts with exon 11 + 13/14 (−9/17/18) mutations had better PFS, ORR, and OS with sunitinib vs ripretinib (Table). Subgroup safety profiles were consistent with the primary analysis. Conclusions: While KIT ATP-BP mutations predicted clinical benefit from sunitinib vs ripretinib, pts harboring resistance mutations in the KIT AL derived meaningful clinical benefit from ripretinib but not sunitinib. This study demonstrates the value of ctDNA NGS-based sequencing of the complex landscape of KIT mutations to predict the clinical benefit of ripretinib or sunitinib as second-line therapy in pts with advanced GIST. Clinical trial information: NCT03673501 . [Table: see text]
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".