Abstract IA15: Tissue-agnostic development of TRK inhibitors for pediatric cancer
Bibliographic record
Abstract
Abstract Fusions involving in the NTRK1, NTRK2, and NTRK3 genes that encode the TRKA, TRKB, and TRKC neurotrophin receptors (TRK fusions) occur across a wide range of cancers in children and adults. These fusions result in constitutive expression and ligand-independent activation of the TRK kinase. TRK fusions are pathognomonic for certain rare cancers, including infantile fibrosarcoma and cellular congenital mesoblastic nephroma, and occur at a lower frequency across a range of more common cancers in children including soft-tissue sarcomas, gliomas, and leukemias. Recently, larotrectinib was FDA approved for the treatment of TRK fusion solid tumors in children and adults, representing the first kinase inhibitor to receive FDA histology-agnostic approval for the treatment of cancer. This approval was based on a combined analysis of three clinical trials, including an ongoing pediatric phase 1/2 trial that demonstrated a 94% response rate in 34 children with TRK fusion-positive solid tumors. Remarkably, due to nearly concurrent development in pediatrics and adults, more than 30% of the patients with TRK fusion solid tumors treated with larotrectinib on clinical trials to date have been children. Other TRK inhibitors are also in pediatric development, including entrectinib and LOXO-195, and clinical trials of additional agents including repotrectinib are planned. Entrectinib, which also antagonizes ROS1 and ALK, was reported to induce responses in 11/11 children whose tumors harbored fusions of the TRK, ROS1 or ALK genes. LOXO-195 and repotrectinib have the potential to antagonize resistance mutations that can develop during treatment with first-generation TRK inhibitors, and we reported a 45% response rate to LOXO-195 among 20 patients enrolled to either single-patient treatment protocols or an ongoing pediatric and adult phase 1 study who harbored a TRK kinase resistance mutation. In this talk, I will review the data on the use of TRK inhibitors for TRK fusion cancers in children, discuss unanswered questions related to the use of TRK inhibitors in children and planned clinical trials designed to address these, and highlight the challenges and opportunities that arise when studying novel therapies for rare, molecularly defined diseases. Citation Format: Theodore W. Laetsch. Tissue-agnostic development of TRK inhibitors for pediatric cancer [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA15.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".