Authors
Mritunjoy Dey, Piotr Remiszewski, Ewelina Perdas, Paweł Golik, Jakub Piątkowski, Anna M Czarnecka
Published in
Frontiers in genetics. Volume 17. Pages 1907450. Epub Oct 12, 2026.
Abstract
Sarcomas are rare, heterogeneous malignancies of mesenchymal origin whose diagnosis and molecular classification remain challenging. We introduced a oneclass anomaly detection framework to microRNA expression profiles to test whether sarcoma-associated miRNA features are distinguishable from those of epithelial, haematological, and neurological cancers and if these features carry any biological relevance.
Candidate miRNAs meeting cross-lineage significance criteria were further evaluated through differential expression analysis against subtype-matched normal mesenchymal reference tissue, pathway enrichment, and survival analysis. A five-miRNA index ("Index 5"), derived by Fisher's linear discriminant analysis with leave-one-out cross-validation in a TCGA-SARC training cohort, was applied without refitting to an independent external cohort (GSE36982).
The five-miRNA index ("Index 5") achieved an AUC of 0.93 and, applied without refitting to an independent external cohort (GSE36982), an AUC of 0.97. After Benjamini-Hochberg correction, one candidate miRNA (miR-1305) remained significantly associated with overall survival.
These findings identify a computationally derived, externally tested candidate miRNA signature associated with sarcoma. While this study lacks experimental and clinical validation, the broader aim of this study was to come up with a framework that would assist and speedup the exploratory candidate biomarker discovery process in rare malignancies.
PMID:
42928931
Bibliographic data and abstract were imported from PubMed on 26 Oct 2026.
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