Abstract 2226: Validation of a liquid biopsy tool to identify point mutations in pediatric brain tumor patients
Bibliographic record
Abstract
Abstract The use of liquid biopsies to diagnose and monitor tumors has been widely explored especially in adult cancers. In pediatric cancers, the feasibility of this method as a clinical tool is still to be established. Pediatric low grade gliomas (PLGG) are characterized by mutations in the MAPK pathway, and 20% harbour BRAFV600E mutation, which can also be found in paediatric patients with Langerhans cell histiocytoma (LCH), thyroid carcinoma and melanomas. Specific histone mutations have been described in pediatric high grade gliomas(HGG) and diffuse midline pontine gliomas(DIPG). Midline gliomas are not amenable to a gross total resection; however, a biopsy is needed for pathological and molecular diagnosis. In this scenario, liquid biopsy is of utmost importance and has the potential to spare the risk of morbidity with surgical procedures, determine diagnosis and prognosis, as well as serve as a tool to guide and monitor response to therapy with targeted agents. The objective of this study is to evaluate the use of droplet digital PCR (ddPCR) for identification of point mutations in cerebro-spinal fluid (CSF) or plasma of BRAF V600E or H3K27M positive pediatric patients. CSF was collected from a total of 51 patients, and plasma from 55 patients. ctDNA was extracted from 3 ml of plasma or 2 ml of CSF, and pre-amplified prior to ddPCR, which was conducted on the RainDance system. For BRAFV600E: Forty-five patients had CSF samples available for analysis, 8 had known positive brain tumors, 32 negative brain tumors, 5 normal controls; 5/8 positive cases had BRAFV600E mutation in ctDNA from CSF, one of the patients with negative CSF and positive tumor was on treatment with BRAF inhibitors. Plasma was analysed in 17 patients with known positive brain tumors and additionally 10 patients negative for BRAFV600E, all of the plasma samples were negative for the mutation. For H3K27M: Thirty patients had CSF samples for analysis 1 was a known positive tumor, 27 negative and 2 unknown status (radiological diagnosis of DIPG). Of the 3 DIPG samples 2 were positive, one with unknown status of the primary tumor. Plasma was also analysed for H3K27M mutation in 7 patients with known positive brain tumors, one DIPG with unknown status and 7 negative samples. All plasma samples tested negative for the mutation. Sensitivity and Specificity for this assay was respectively 62% and 97% for BRAF and 66% and 98 % for H3K27M in CSF. The sensitivity in plasma for brain tumors is poor, however seems better for non-CNS lesions. In summary, we show that liquid biopsy with analysis of CSF ctDNA is feasible with high specificity, important in the context of a diagnoses tool. Moving forward larger cohorts need to be validated towards the goal of implementing ddPCR as a clinical tool for diagnosis of specific point mutations in pediatric patients with CNS tumors. Citation Format: Liana Nobre, Michal Zapotocky, Monique Johnson, Jonathan Wasserman, Oussama Abla, Jim Whitlock, Uri Tabori, Cynthia Hawkins. Validation of a liquid biopsy tool to identify point mutations in pediatric brain tumor patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2226.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".