Expanding clinical impact of liquid biopsy beyond genomics: exploration of novel epigenomic applications
Bibliographic record
Abstract
hematopoiesis (CH) alterations.Methods: Six diagnostic laboratories participating in a MSK-ACCESS powered with SOPHiA DDM set-up program were included.Across these sites, sequencing libraries were constructed from a common set of reference materials and sitespecific clinical materials using MSK-ACCESS powered with SOPHiA DDM and sequenced on Illumina NovaSeq 6000 or NextSeq 2000.Data was subjected to the SOPHiA DDM bioinformatics workflow for variant detection and annotation of germline and CH variants.Accuracy was determined through the concordance to the reference cfDNA and orthogonally detected variants in the clinical samples.Intra-and inter-laboratory variant allele frequency (VAF) variability was used to evaluate repeatability and reproducibility.WBC sequencing was employed to identify germline and CH variants.Results: Across sites, the average positive agreement for the 0.5% VAF commercial reference samples was 98.4%.The coefficient of variation of the 0.5% VAF samples had the same magnitude within (0.29, mean 0.48, SD 0.14) as for between (0.29, mean 0.49, SD 0.14) laboratory comparisons.In the clinical samples, 97.2% of reported variants with an expected VAF 0.5% were detected (101/104, PPA 94.1 -100%).Sensitivity was lower for < 0.5% VAF (39/55), reflecting stochastic sampling challenges.Across all VAFs, 39 externally reported variants in the clinical materials were observed at a similar abundance in cfDNA and WBC DNA and annotated as non-somatic.Conclusion: Real-world results of the MSK-ACCESS powered with SOPHiA DDM solution demonstrate high accuracy and precision while maintaining robustness of the assay across laboratories.In clinical samples, putative germline and CH alterations can be identified through WBC testing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".