Abstract A41: TRICEPS: A feasibility study of personalized targeted therapy in relapsed/refractory childhood cancers
Bibliographic record
Abstract
Abstract In Canada, about 1500 pediatric cancers are diagnosed each year. Despite improvements in risk-stratified treatments, around 20% of childhood cancer patients do not respond to current therapies and ultimately succumb to their disease, urging the need for new and more effective therapeutic approaches. Personalized targeted therapy (PTT) based on next generation sequencing (NGS) may be a key component to increase cure rates and decrease treatment-related morbidity and mortality. To assess the feasibility of performing PTT clinical trials in the context of childhood cancers, a pilot study is currently underway at the Sainte-Justine UHC, Montreal, where 30 relapsed or refractory cancer patients (aged 0-21 years) are being recruited over a 2 year period and offered in-depth genomic and transcriptomic investigation to identify patient-specific alterations. This pilot study will allow us to determine the number of children with cancer who are suitable candidates for targeted therapy, to determine the number and type of driver mutation(s) found in the recurrent or refractory childhood cancers, to determine the number of cancer patients who harbor actionable driver mutation(s) that can be targeted with a Health Canada/FDA approved targeted drug and to assess the feasibility of going from biopsy to a detailed tumour analysis report within a clinically-relevant timeframe. Thus far, sixteen patients have been recruited in this study between April 2014 and July 2015. Study subject accrual has been successful with 100% compliance. Eight patients have undergone extensive genomic investigation in a real-time manner. We identified clinically relevant genomic alterations (singe nucleotide variants or structural variations) that can be used to inform clinical management for 8/8 of these patients. Patient screen failures occurred due to benign tumor biopsies, necrotic tumor tissue or low tumor purity, resulting in suboptimal DNA/RNA quantity or quality for NGS. Identified relapse-specific mutations allowed follow up of minimal residual disease, particularly post-transplant for relapsed leukemia cases, influenced patient management and revealed alternative therapeutic options for future personalized targeted therapy. This feasibility study shows that PTT based on NGS technology is a useful approach that could be implemented in the clinic within a foreseeable future to guide treatment of relapsed or refractory childhood cancer patients. The following step toward translating our results into novel personalized therapeutic approaches will be the development of phase II clinical trials to evaluate the efficacy of these targeted therapies in terms of therapeutic response, survival, and overall quality of life. Our overreaching goal is to be able to offer personalized targeted therapy options to all patients upon primary diagnosis of their cancer. Citation Format: Sylvie Langlois, Jasmine Healy, Mathieu Lajoie, Sophie Dumoucel, Fida Khater, Thomas Sontag, Pascal St-Onge, Patrick Beaulieu, Henrique Bittencourt, Dorothée Dal Soglio, Anne-Sophie Carret, Sonia Cellot, Josette Champagne, Michel Duval, Maja Krajinovic, Jean-Marie Leclerc, Natalie Patey, Nelson Piché, Yvan Samson, Pierre Teira, Monia Marzouki, Daniel Sinnett. TRICEPS: A feasibility study of personalized targeted therapy in relapsed/refractory childhood cancers. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Pediatric Cancer Research: From Mechanisms and Models to Treatment and Survivorship; 2015 Nov 9-12; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(5 Suppl):Abstract nr A41.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".