Larotrectinib resistance in TRK fusion cancers: Analysis of a tumor-agnostic, global clinical trial dataset.
Bibliographic record
Abstract
3066 Background: Larotrectinib (laro) is the first-in-class, highly selective, TRK inhibitor approved for tumor- and age-agnostic use in TRK fusion cancers. This is the seminal report of primary and secondary laro resistance based on an analysis of the regulatory dataset that supported drug approval across multiple countries. Methods: Genomic data from patients (pts) with non-primary CNS TRK fusion cancer enrolled in a global, prospective, multicenter database of three laro clinical trials including adult and pediatric pts were analyzed. Tumor DNA (Illumina TruSight Oncology [TSO] Comprehensive, TSO 500, or FoundationOne CDx) or circulating tumor DNA (Guardant360 or GuardantOMNI) NGS was performed pre-laro (baseline; BL) and post-laro initiation. On-target NTRK (solvent front [SF], gatekeeper [GK], xDFG) mutations and COSMIC-classified tier 1/2 off-target alterations were identified. Primary laro resistance analysis set included pts with no meaningful clinical benefit (PD/SD < 4 months). Secondary (acquired) laro resistance analysis set included pts who developed resistance after meaningful clinical benefit (CR/PR/SD ≥4 months). Data cutoff: July 20, 2024. Results: Of 304 adult and pediatric pts enrolled, 216 had BL genomic data. Primary laro resistance was observed in 24 pts. Only 1 pt had an on-target mutation ( NTRK3 G623R), likely attributable to prior crizotinib; 9 pts (38%) had off-target alterations involving AKT, BRAF, FGFR1, GNAS, KRAS, NRAS, and PIK3CA . Secondary laro resistance was observed in 55 pts with valid post-BL ctDNA (the most common of these TRK fusion cancers were infantile fibrosarcoma [22%], other soft tissue sarcoma [18%], thyroid [11%], lung and salivary gland [9% each]); acquired alterations were identified in 16 of these pts. On-target resistance alone was observed in 5 of 16 pts (31%) and were mainly SF or GK single or double mutation-mediated ( NTRK1 F589L, NTRK1 G595R, NTRK3 G623R [n = 2], NTRK3 G623R/G696A). One xDFG mutation was identified. Off-target resistance alone was observed in 7 of 16 pts (44%) and included hotspot KRAS G12D/A/S/V or G13D, PIK3CA E545K or E542A, BRAF V600E, and GNAS R844H/C mutations. Complex, combined on-target and off-target resistance was observed in 4 of 16 pts (25%): on-target SF or GK alterations ( NTRK1 G595R, NTRK1 F589L/G595R, NTRK3 G623R, NTRK3 G623R/F617L) co-occurred with KRAS G12D or G12D/G13D, and NRAS G12D or Q61H. An analysis of resistance profiles by cancer type and age will be presented. Conclusions: In this analysis, on-target resistance to laro, including potential double NTRK resistance mutations, was commonly observed. Off-target, largely MAPK or PI3K/AKT pathway reactivating resistance, also occurred. In select cases, complex and likely polyclonal resistance including both on-target and off-target alterations were identified. These observations impact novel therapy development for TRK fusion cancers. Clinical trial information: NCT02637687 , NCT02576431 , NCT02122913 .
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".