DNA Methylation–Based Classification of Soft Tissue and Bone Sarcomas: Systematic Review of Diagnostic Performance, Copy Number Insights, and Clinical Integration

Soft tissue and bone sarcomas are diagnostically challenging due to their morphological overlap. Genome-wide DNA methylation profiling has emerged as an ancillary tool for classification, providing both a supervised diagnostic call and inferred copy-number alterations (CNAs) from a single assay. This systematic review synthesizes the evidence on its diagnostic performance, clinical utility, and integration into practice. Following PRISMA 2020 guidelines, a systematic literature search of PubMed and Google Scholar was conducted for studies published between 2010 and 2025. Eligible studies reported on the use of methylation-based classifiers for sarcoma diagnosis against an integrated histomolecular reference standard. Nine studies were included. In validation cohorts, methylation classifiers provided high-confidence predictions (calibrated score ≥0.9) in 55-75% of cases. When a high-confidence prediction was made, concordance with the reference diagnosis was high (83-88%). Discrepant high-confidence calls prompted diagnostic re-evaluation, leading to revised diagnoses in a significant proportion of cases. Methylation-derived CNAs provided critical diagnostic information for key differentials, such as MDM2 amplification in liposarcoma and 22q loss in SMARCB1-deficient tumors. Performance was robust in fusion-driven sarcomas but lower in selected benign entities. Technical success was influenced by tumor purity and specimen type (FFPE vs. frozen). Evidence for nanopore-based methods remains preliminary. DNA methylation-based classification is a clinically validated tool that augments the diagnosis of sarcomas, offering high diagnostic concordance and valuable copy-number insights. Its integration requires careful interpretation within a multidisciplinary framework. Further prospective validation and standardization of emerging sequencing technologies are warranted.

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Publication Details

Journal
Studies in Multidisciplinary Medical Research
Published
2025-08-18
DOI
https://doi.org/10.61882/smmr.202501.07.04
Primary Topic
Sarcoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
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article

DNA Methylation–Based Classification of Soft Tissue and Bone Sarcomas: Systematic Review of Diagnostic Performance, Copy Number Insights, and Clinical Integration

S.C. Bagheri, Hamidreza Mousazadeh Meibodi, Mashalah Babashahi, Parisa Keyhanpajooh
Studies in Multidisciplinary Medical Research
Sarcoma Diagnosis and Treatment
article

DNA Methylation–Based Classification of Soft Tissue and Bone Sarcomas: Systematic Review of Diagnostic Performance, Copy Number Insights, and Clinical Integration

S.C. Bagheri, Hamidreza Mousazadeh Meibodi, Mashalah Babashahi, Parisa Keyhanpajooh
article en

Abstract

Soft tissue and bone sarcomas are diagnostically challenging due to their morphological overlap. Genome-wide DNA methylation profiling has emerged as an ancillary tool for classification, providing both a supervised diagnostic call and inferred copy-number alterations (CNAs) from a single assay. This systematic review synthesizes the evidence on its diagnostic performance, clinical utility, and integration into practice. Following PRISMA 2020 guidelines, a systematic literature search of PubMed and Google Scholar was conducted for studies published between 2010 and 2025. Eligible studies reported on the use of methylation-based classifiers for sarcoma diagnosis against an integrated histomolecular reference standard. Nine studies were included. In validation cohorts, methylation classifiers provided high-confidence predictions (calibrated score ≥0.9) in 55-75% of cases. When a high-confidence prediction was made, concordance with the reference diagnosis was high (83-88%). Discrepant high-confidence calls prompted diagnostic re-evaluation, leading to revised diagnoses in a significant proportion of cases. Methylation-derived CNAs provided critical diagnostic information for key differentials, such as MDM2 amplification in liposarcoma and 22q loss in SMARCB1-deficient tumors. Performance was robust in fusion-driven sarcomas but lower in selected benign entities. Technical success was influenced by tumor purity and specimen type (FFPE vs. frozen). Evidence for nanopore-based methods remains preliminary. DNA methylation-based classification is a clinically validated tool that augments the diagnosis of sarcomas, offering high diagnostic concordance and valuable copy-number insights. Its integration requires careful interpretation within a multidisciplinary framework. Further prospective validation and standardization of emerging sequencing technologies are warranted.

Studies in Multidisciplinary Medical ResearchVol. 1(7)
Shahrekord University of Medical Sciences (IR), Shiraz University of Medical Sciences (IR), Medical University of Ilam (IR), Ilam University (IR), Fasa University of Medical Sciences (IR)
Openalex Percentile: Top 59%
Sarcoma Diagnosis and Treatment
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