Abstract LB-295: Detection of oncogenic kinase mutations in circulating plasma DNA and correlation with clinical benefit in the phase III GRID study of regorafenib <i>vs</i> placebo in TKI-refractory metastatic GIST.
Bibliographic record
Abstract
Abstract Background: GRID is a phase III study for patients with advanced gastrointestinal stromal tumors (GIST) following failure of imatinib (I) and sunitinib (S) who were randomized to receive either the multikinase inhibitor regorafenib (R) or placebo (P). R demonstrated a highly significant improvement in progression-free survival compared with P (HR 0.27, p<0.0001). A preplanned retrospective biomarker analysis was conducted to assess GIST genotypes in GRID patients and to explore the possible impact of different driver oncogene mutations on clinical outcomes. Methods: DNA was isolated from archival tumor tissue and analyzed for KIT mutations via Sanger sequencing. The expectation was that primary KIT mutations would be detectable in archival tissue but that secondary KIT mutations may be undetectable in tissues obtained before treatment with I or S. To overcome this potential limitation, plasma samples drawn at GRID study entry, post I and S failure, were used as a source of circulating DNA for evaluation of GIST oncogenic mutations (KIT, PDGFRA, BRAF) via BEAMing technology. Results: KIT mutations were detected in 83 of 138 (60%) plasma samples and 64 of 99 (65%) tumor tissue samples analyzed. Primary KIT exon 11 and 9 mutations were identified in approximately 42% and 18% of the tissue samples, respectively. The frequency of the canonical exon 9 mutations was similar for plasma and tissue samples, showing consistency between mutation-detection technologies. With limitations of tumor-based assays, a lower incidence of secondary KIT resistance mutations was detected in patient-matched archival tumor tissue compared with plasma samples: resistance mutations were detected in 12% of tissue samples vs 48% of plasma samples. Most (76%) secondary KIT mutations detected in plasma DNA were located in the KIT activation loop encoding structural alterations known to mediate resistance to I and S. Nearly half of the plasma samples in which secondary KIT mutations were identified harbored multiple secondary mutations, consistent with the results of previous studies on fresh tumor biopsies taken following resistance to both I and S. R was clinically active compared with P in all KIT mutational subgroups evaluated (HR 0.27 in patients with KIT exon 9 mutations; HR 0.25 in patients with secondary KIT mutations identified via plasma DNA). Conclusions: In GIST patients from the GRID trial, driver oncogenic mutations and secondary oncogenic mutations leading to I and S resistance are readily detectable via BEAMing of circulating DNA from plasma. BEAMing may provide a real-time assessment of tumor genotype in GIST and other cancers using blood-derived circulating DNA, that may be more comprehensive than tumor sampling. GIST patients with a wide spectrum of primary and secondary mutations in oncogenic kinases benefit from treatment with R. Citation Format: George D. Demetri, Michael Jeffers, Peter Reichardt, Yoon-Koo Kang, Jean-Yves Blay, Piotr Rutkowski, Hans Gelderblom, Peter Hohenberger, Michael Leahy, Margaret von Mehren, Heikki Joensuu, Giuseppe Badalamenti, Martin Blackstein, Axel Le Cesne, Patrick Schöffski, Robert G Maki, Sebastian Bauer, Binh Bui Nguyen, Jianming Xu, Toshirou Nishida, John Chung, Chetan D. Lathia, Christian Kappeler, Iris Kuss, Dirk Laurent, Paolo G Casali. Detection of oncogenic kinase mutations in circulating plasma DNA and correlation with clinical benefit in the phase III GRID study of regorafenib vs placebo in TKI-refractory metastatic GIST. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-295. doi:10.1158/1538-7445.AM2013-LB-295
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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 | 0.001 |
| 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) | 0.002 | 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".