Abstract PR006: Liquid biopsy enables identification of mechanisms of tumor evolution in patients with newly diagnosed high-risk neuroblastoma: A report from the Children’s Oncology Group
Bibliographic record
Abstract
Abstract Background: Neuroblastoma is the most common extracranial solid tumor diagnosed in children. Outcomes for high-risk neuroblastoma (HR-NB) have improved but causes of treatment-refractory disease and relapse are poorly understood. ANBL1531 is a Children’s Oncology Group phase 3 study that enrolled over 700 patients with HR-NB. Longitudinal liquid biopsy samples were collected to identify prognostic biomarkers and study patterns of tumor evolution that contribute to treatment resistance. Assessment of circulating tumor DNA (ctDNA) allows for non-invasive serial sequencing of the tumor genome using peripheral blood samples. We describe sequencing approaches and the progress of this ongoing work. Methods: Serial plasma samples were submitted to the Crompton lab for cell-free DNA sequencing by ultra-low passage whole genome sequencing (ULP-WGS) to estimate ctDNA content. To date, the Crompton lab has received 2,184 serial plasma samples. Samples with detectable ctDNA were also sequenced by whole-exome sequencing and a pan-cancer panel targeting 400 genes. We have performed deep pan-cancer panel sequencing on 188 longitudinal blood samples collected from 71 patients. Matched germline and primary tumor sequencing data are available for 56 and 49 of these patients, respectively. Paired baseline and relapse plasma samples with ctDNA > 20% were also sequenced by whole genome sequencing to detect relapse-specific changes in nucleosome positioning. Results: ULP-WGS showed that 332/335 patients (99.1%) with a pre-treatment blood sample had detectable ctDNA ranging between 3-99% of total cell-free DNA. ctDNA remained detectable in 84%, 37%, 27%, 3.1%, 2.9% and 0.7% of cases at pre-induction and pre-cycle 2, 3, 4, end-induction, prior to post-consolidation therapy, and end post-consolidation respectively. Paired analysis of sequencing data revealed heterogeneity in the somatic variants detected between primary tumor and ctDNA samples. Five out of 47 patients assigned to a treatment arm for patients with ALK wild-type HR-NB with available tumor and pre-treatment ctDNA sequencing data had somatic mutations in the ALK gene, however, 3 of these mutations were only detectable in ctDNA. We also detected recurrent mutations in RAS/RAF pathway, DNA damage repair pathway, and NOTCH pathway genes. Signature analysis of pre-treatment and relapse samples revealed presence of mismatch repair deficiency and reactive oxygen species signatures. Using nucleosome positioning we detected recurrent changes in the activity of specific transcription factor programs in relapse samples. Functional validation of prioritized relapse-specific ctDNA variants is ongoing and will also be reported. Conclusions: In summary, this research project bridges critical gaps in understanding the primary resistance mechanisms of HR-NB by employing a non-invasive methodology and comprehensive analysis of genomic and translational contributors to tumor evolution. These data provide an opportunity for the discovery of new therapeutic targets that could improve the outcome for patients with HR-NB. Citation Format: Gabriela Virdzekova, Kelly Klega, Kristopher Boss, Patrick Reynolds, Arlene Naranjo, Elaine Mardis, Trevor Pugh, Mark Applebaum, Rochelle Bagatell, Gad Getz, Steven DuBoi, Brian Cromtpon. Liquid biopsy enables identification of mechanisms of tumor evolution in patients with newly diagnosed high-risk neuroblastoma: A report from the Children’s Oncology Group [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr PR006.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".