Abstract 7179: Streamlined Glioma diagnosis from formalin-fixed paraffin-embedded (FFPE) tissue: One assay, a fraction of the cost and turnaround time
Bibliographic record
Abstract
Abstract We developed a single diagnostic assay to detect Glioma biomarkers including whole chromosomal and gene copy number variations (CNVs), and single nucleotide variations (SNVs). CNVs and SNVs are traditionally detected using different large/high-throughput platforms that can only exist in big genomic facilities. This leads to very high molecular costs and long turnaround times. The current complex diagnostic algorithm creates delays in patient management while increasing inequity in healthcare as smaller non-centralized labs are unable to conduct glioma molecular testing. To streamline glioma diagnosis and address these challenges, we aimed to use a third-generation sequencing platform called nanopore sequencing. It can simultaneously detect both CNVs and SNVs using small inexpensive tools, but is not yet compatible with formalin-fixed paraffin-embedded (FFPE) DNA. Therefore, we developed a PCR based assay to create clean nanopore compatible FFPE DNA copies to detect CNVs and SNVs. We established a single nucleotide polymorphism (SNP) microarray-based approach to detect the CNVs. Approximately 300 amplicons were included in the assay design including unique SNP-rich areas to detect the chromosomal heterozygosity. We included all glioma markers required by World Health Organization's (WHO) guidelines including chromosomal CNVs on chr 1, 7, 10, 19; gene CNVs on CDKN2A, CDKN2B, EGFR; and SNVs on IDH1, IDH2, TERT promoter, TP53, ATRX, H3-3A and H3C2. We optimized the testing conditions, and reduced cost and turn-around including streamlining the data analysis using a custom shell script. Lastly, we conducted a mini validation as well as a cost and turn-around time analysis using 40 Glioma FFPE samples. All our samples had a concordant molecular classification status with the reference results. The concordance, sensitivity and specificity (total accuracy) of the assay were all at 100%. A loss status of chr 1p, chr 19q and chr 10 were determined via a loss of heterozygosity (LOH), and gain status of chr 7 was observed as an allele gain 2:1 SNP pattern. Our total turnaround time (from DNA extraction to data analysis) is 3 business days for an entire batch of samples, which is at least 1/3rd the turnaround time of conventional methods. Our material cost is $150 CAD/sample (including DNA extraction, library preparation and sequencing) which is ∼10% of the existing assay costs. This is the first single streamlined diagnostic test to detect CNVs and SNVs in Gliomas using FFPE DNA. Our assay will increase healthcare equity by allowing smaller labs to adopt molecular testing due to its low assay/capital cost, shorter testing time, and streamlined workflow, helping to overcome many of the existing cancer diagnostic challenges. Citation Format: Mashiat Lamia Mimosa, Jared T. Simpson, Shreya Patel, Karel Boissinot, Mora Tiab, Ramzi Fattouh, Rola M. Saleeb. Streamlined Glioma diagnosis from formalin-fixed paraffin-embedded (FFPE) tissue: One assay, a fraction of the cost and turnaround time [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7179.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".