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Cited by 35Cancer Diagnosis and TreatmentEpigenetics and DNA MethylationCancer Genomics and Diagnostics

DNA methylation profiling to determine the primary sites of metastatic cancers using formalin-fixed paraffin-embedded tissues

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Zhang, Shirong, He, Shutao, Zhu, Xin, Wang, Yunfei, Xie, Qionghuan, Song, Xianrang, Xu, Chunwei, Wang, Wenxian +9 more·2023·Nature Communications
DOI 10.1038/s41467-023-41015-0PMC PMC10502058
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Abstract

Identifying the primary site of metastatic cancer is critical to guiding the subsequent treatment. Approximately 3–9% of metastatic patients are diagnosed with cancer of unknown primary sites (CUP) even after a comprehensive diagnostic workup. However, a widely accepted molecular test is still not available. Here, we report a method that applies formalin-fixed, paraffin-embedded tissues to construct reduced representation bisulfite sequencing libraries (FFPE-RRBS). We then generate and systematically evaluate 28 molecular classifiers, built on four DNA methylation scoring methods and seven machine learning approaches, using the RRBS library dataset of 498 fresh-frozen tumor tissues from primary cancer patients. Among these classifiers, the be ta value-based li near support ve ctor (BELIVE) performs the best, achieving overall accuracies of 81-93% for identifying the primary sites in 215 metastatic patients using top-k predictions (k = 1, 2, 3). Coincidentally, BELIVE also successfully predicts the tissue of origin in 81-93% of CUP patients (n = 68).

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Authors
Zhang, S., He, S., Zhu, X., Wang, Y., Xie, Q., Song, X., Xu, C., Wang, W., Xing, L., Xia, C., Wang, Q., Li, W., Zhang, X., Yu, J., Ma, S., Shi, J., & Gu, H.
Affiliations
  • Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)
  • Chinese Academy of Sciences (CN)
  • Zhejiang Cancer Hospital (CN)
  • Shandong Tumor Hospital (CN)
  • Nanjing General Hospital of Nanjing Military Command (CN)
  • Nanjing University of Chinese Medicine (CN)
  • First Affiliated Hospital of Wenzhou Medical University (CN)
  • First Affiliated Hospital Zhejiang University (CN)
Corresponding author
  • Ma, Shenglin
  • Shi, Jiantao
  • Gu, Hongcang
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2023-09-14
Volume
14
Issue
1
Pages
5686-5686
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-023-41015-0
PMC
PMC10502058
OpenAlex
W4386741438
Cited by
35
References
73
Citations by year
2026: 7 · 2025: 12 · 2024: 14 · 2023: 2
FWCI
4.27
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (81773242)
  • Natural Science Foundation of Zhejiang Province (32270691)
Topics
  • Health Sciences › Medicine › Oncology › Cancer Diagnosis and Treatment
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
Keywords
DNA methylation profiling, cancer of unknown primary, metastatic cancer, primary site identification, reduced representation bisulfite sequencing, formalin-fixed paraffin-embedded tissue, molecular classifier, tissue of origin prediction, machine learning classification
MeSH terms
Formaldehyde, Humans, Neoplasms, Unknown Primary, Neoplasms, Second Primary, Paraffin Embedding, DNA Methylation

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