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1000 Titel
  • Integrative statistical analyses of multiple liquid biopsy analytes in metastatic breast cancer
1000 Autor/in
  1. Keup, Corinna |
  2. Suryaprakash, Vinay |
  3. Hauch, Siegfried |
  4. Storbeck, Markus |
  5. Hahn, Peter |
  6. Sprenger-Haussels, Markus |
  7. Kolberg, Hans-Christian |
  8. Tewes, Mitra |
  9. Hoffmann, Oliver |
  10. Kimmig, Rainer |
  11. Kasimir-Bauer, Sabine |
1000 Erscheinungsjahr 2021
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-05-17
1000 Erschienen in
1000 Quellenangabe
  • 13(1):85
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s13073-021-00902-1 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8130163/ |
1000 Publikationsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Background!#!Single liquid biopsy analytes (LBAs) have been utilized for therapy selection in metastatic breast cancer (MBC). We performed integrative statistical analyses to examine the clinical relevance of using multiple LBAs: matched circulating tumor cell (CTC) mRNA, CTC genomic DNA (gDNA), extracellular vesicle (EV) mRNA, and cell-free DNA (cfDNA).!##!Methods!#!Blood was drawn from 26 hormone receptor-positive, HER2-negative MBC patients. CTC mRNA and EV mRNA were analyzed using a multi-marker qPCR. Plasma from CTC-depleted blood was utilized for cfDNA isolation. gDNA from CTCs was isolated from mRNA-depleted CTC lysates. CTC gDNA and cfDNA were analyzed by targeted sequencing. Hierarchical clustering was performed within each analyte, and its results were combined into a score termed Evaluation of multiple Liquid biopsy analytes In Metastatic breast cancer patients All from one blood sample (ELIMA.score), which calculates the contribution of each analyte to the overall survival prediction. Singular value decomposition (SVD), mutual information calculation, k-means clustering, and graph-theoretic analysis were conducted to elucidate the dependence between individual analytes.!##!Results!#!A combination of two/three/four LBAs increased the prevalence of patients with actionable signals. Aggregating the results of hierarchical clustering of individual LBAs into the ELIMA.score resulted in a highly significant correlation with overall survival, thereby bolstering evidence for the additive value of using multiple LBAs. Computation of mutual information indicated that none of the LBAs is independent of the others, but the ability of a single LBA to describe the others is rather limited-only CTC gDNA could partially describe the other three LBAs. SVD revealed that the strongest singular vectors originate from all four LBAs, but a majority originated from CTC gDNA. After k-means clustering of patients based on parameters of all four LBAs, the graph-theoretic analysis revealed CTC ERBB2 variants only in patients belonging to one particular cluster.!##!Conclusions!#!The additional benefits of using all four LBAs were objectively demonstrated in this pilot study, which also indicated a relative dominance of CTC gDNA over the other LBAs. Consequently, a multi-parametric liquid biopsy approach deconvolutes the genomic and transcriptomic complexity and should be considered in clinical practice.
1000 Sacherschließung
lokal Clinical Decision-Making [MeSH]
lokal Liquid biopsy
lokal Breast Neoplasms/epidemiology [MeSH]
lokal Disease Management [MeSH]
lokal Metastatic breast cancer patients
lokal Sensitivity and Specificity [MeSH]
lokal Multi-modal
lokal Circulating Tumor DNA [MeSH]
lokal Breast Neoplasms/diagnosis [MeSH]
lokal Sequence Analysis, DNA [MeSH]
lokal Biomarkers, Tumor [MeSH]
lokal Breast Neoplasms/etiology [MeSH]
lokal Female [MeSH]
lokal Neoplastic Cells, Circulating/pathology [MeSH]
lokal Humans [MeSH]
lokal Multi-parametric
lokal Breast Neoplasms/metabolism [MeSH]
lokal Multi-layer
lokal Disease Susceptibility [MeSH]
lokal Neoplastic Cells, Circulating/metabolism [MeSH]
lokal Liquid Biopsy/methods [MeSH]
lokal Multi-analyte
lokal Liquid Biopsy/statistics
lokal Research
lokal Prognosis [MeSH]
lokal Liquid Biopsy/standards [MeSH]
lokal Computational Biology/methods [MeSH]
lokal High-Throughput Nucleotide Sequencing [MeSH]
lokal Real-Time Polymerase Chain Reaction [MeSH]
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0003-3525-7511|https://frl.publisso.de/adhoc/uri/U3VyeWFwcmFrYXNoLCBWaW5heQ==|https://frl.publisso.de/adhoc/uri/SGF1Y2gsIFNpZWdmcmllZA==|https://frl.publisso.de/adhoc/uri/U3RvcmJlY2ssIE1hcmt1cw==|https://frl.publisso.de/adhoc/uri/SGFobiwgUGV0ZXI=|https://frl.publisso.de/adhoc/uri/U3ByZW5nZXItSGF1c3NlbHMsIE1hcmt1cw==|https://frl.publisso.de/adhoc/uri/S29sYmVyZywgSGFucy1DaHJpc3RpYW4=|https://frl.publisso.de/adhoc/uri/VGV3ZXMsIE1pdHJh|https://frl.publisso.de/adhoc/uri/SG9mZm1hbm4sIE9saXZlcg==|https://frl.publisso.de/adhoc/uri/S2ltbWlnLCBSYWluZXI=|https://frl.publisso.de/adhoc/uri/S2FzaW1pci1CYXVlciwgU2FiaW5l
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1000 Erstellt am 2023-11-16T17:32:58.675+0100
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