Abstract 4260: Clinical testing and implementation of the TruSight Myeloid Next Generation Sequencing (NGS) panel for identification of clinically relevant variants in hematological malignancies
Bibliographic record
Abstract
Abstract Recent cancer genome profiling studies have increased our understanding of the somatic mutation landscape of myeloid malignancies. A number of genes and variants are known to have prognostic/predictive utility in several myeloid malignancies, allowing for more accurate stratification, and enhanced patient management. This has led to consideration of NGS for detection of somatic mutations in myeloid malignancies in the clinical diagnostic setting, to supplant single-gene molecular testing assays in current use. Building on our prior work establishing a novel mass spectrometry-based high throughput mutation detection assay for hematologic malignancies, we investigated the application of NGS to myeloid malignancy diagnostics. To do this, we validated the Illumina TruSight Myeloid Sequencing Panel (54 genes, 568 amplicons) on 71 acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasm (MPN) patient samples, alongside relevant controls. NGS Libraries were prepared using standard protocols, and sequencing performed on the Illumina MiSeq platform. Concordance among NGS calls, single gene tests, and Sanger verification was tested as part of the clinical validation process. Analysis of 41 cases tested in our previously developed mass spectrometry assay indicated 100% concordance (70/70) for reportable variants mutually covered in both assays. Single nucleotide variations detectable in lab-standard single gene assays were all found by NGS (100% concordance). 58/71 (82%) cases had at least one additional potentially clinically relevant variant that would not have been identified in the existing assay (mean 1.95 additional variants/case; range 1-9). Additionally, we determined that AMLs carrying IDH1, IDH2 or TET2 mutations had a higher mutation burden (mean 4.6 mutations/case, range 2-7), compared to AMLs wild-type for these three genes (mean 3.1 mutations/case, range 2-4; p = 0.008). Clinically relevant insertions (up to 33 bp) and deletions (up to 52 bp) associated with AML and MPN, including FLT3 ITD and CALR deletions, were detected in known positive cases. In these cases, our analysis was supplemented with a custom bioinformatics algorithm allowing for alignment against an artificial reference sequence to detect larger indels. Due to low coverage of the clinically actionable CEBPA, we supplemented the NGS assay with Sanger sequencing for this locus. Therefore, we report the validation of an NGS panel for high throughput detection of mutations in myeloid malignancies, and the development of a wet-bench and informatics workflow enabling maximal information benefit in the diagnostic setting. This pipeline allows the detection of variants that impact diagnosis and patient management, with significantly improved information benefit over current tests. Citation Format: Mariam Thomas, Mahadeo Sukhai, Tong Zhang, Djamel Harbi, Justin De Souza, Katherine MacDonald, Trevor Pugh, Mark Minden, Andre Schuh, Tracy L. Stockley, Suzanne Kamel-Reid. Clinical testing and implementation of the TruSight Myeloid Next Generation Sequencing (NGS) panel for identification of clinically relevant variants in hematological malignancies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4260. doi:10.1158/1538-7445.AM2015-4260
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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 | 0.007 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".