A Phase II Study of Neoadjuvant Opnurasib KRAS G12C Inhibitor in Patients With Surgically Resectable Non-Small Cell Lung Cancer (CCTG IND.242A): A Substudy of the IND.242 Platform Master Protocol
Bibliographic record
Abstract
Molecularly targeted agents are increasingly being studied in the treatment of early-stage non-small cell lung cancer (NSCLC) to try and improve cure. However, phase 3 data on neoadjuvant therapy have largely been conducted in a biomarker agnostic manner with inconsistent exclusion of EGFR and ALK alterations. Our objective was to develop IND.242 as a large-scale neoadjuvant platform trial to introduce novel agents into the preoperative window for molecularly-defined NSCLC patient populations. Given that KRAS G12C mutations are common in the overall NSCLC patient population, ranging from 9.4% to 13% of cases across different cohorts, and may be associated to worse prognosis, the initial IND.242A Substudy was designed to test neoadjuvant JDQ443 (opnurasib), a selective KRAS G12C inhibitor. This current trial report describes the multicenter, Canadian Cancer Trials Group (CCTG)-led IND.242 neoadjuvant phase 2 platform master protocol and its first Substudy (IND.242A) of neoadjuvant opnurasib KRAS G12C inhibitor for patients with surgically resectable NSCLC (AJCC 8th edition stage IA2 to IIIA). In IND.242A, a maximum of 27 patients will be accrued in participating Canadian sites. The primary objective is the rate of major pathological response (MPR) following neoadjuvant opnurasib. Secondary objectives include safety and tolerability of the treatment regimen, objective response rate (ORR) by RECIST 1.1 for the neoadjuvant treatment period, pathological complete response (pCR) rate, event-free survival (EFS) at 2 years, and surgical outcomes. Exploratory objectives are to explore patient related outcomes (PROs) and identify potential predictive biomarkers of response and mechanisms of resistance on tissue and peripheral blood samples.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".