ArticleNature communications2025
Enabling whole genome sequencing analysis from FFPE specimens in clinical oncology.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Enabling whole genome sequencing analysis from FFPE specimens in clinical oncology.Nature communications · 2025Article
Corrections and comments
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Authors and funding
23 authors.
Funding
Abstract
The adoption of whole genome sequencing (WGS) in clinical oncology is challenged by low data quality and increased artifacts in standard-of-care formalin-fixed paraffin-embedded (FFPE) samples. Analysis of 56 fresh frozen (FF) and FFPE matched pairs demonstrates that FFPE processing results in a median 20-fold enrichment in artifactual calls across mutation classes and impairs detection of clinically relevant biomarkers such as homologous recombination deficiency (HRD). We demonstrate that implementation of consensus calling reduces artifactual structural variant (SV) calls by 98% but is not sufficient in mitigating artifactual calls for single nucleotide variants (SNVs) and indels as compared to FF data. We develop FFPErase, a machine learning framework that filters SNV/indel artifacts and delivers clinical grade variant reporting allowing accurate quantification of clinically relevant biomarkers. Comparison of FFPErase WGS calls to clinical reporting by FDA-approved panel tests demonstrates 99% sensitivity and enables reporting of 24% more clinically relevant findings.
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Registered trials
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