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1000 Titel
  • Decoding cell-type contributions to the cfRNA transcriptomic landscape of liver cancer
1000 Autor/in
  1. Safrastyan, Aram |
  2. zu Siederdissen, Christian Höner |
  3. Wollny, Damian |
1000 Erscheinungsjahr 2023
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2023-10-05
1000 Erschienen in
1000 Quellenangabe
  • 17(1):90
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2023
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s40246-023-00537-w |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10552294/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Background!#!Liquid biopsy, particularly cell-free RNA (cfRNA), has emerged as a promising non-invasive diagnostic tool for various diseases, including cancer, due to its accessibility and the wealth of information it provides. A key area of interest is the composition and cellular origin of cfRNA in the blood and the alterations in the cfRNA transcriptomic landscape during carcinogenesis. Investigating these changes can offer insights into the manifestations of tissue alterations in the blood, potentially leading to more effective diagnostic strategies. However, the consistency of these findings across different studies and their clinical utility remains to be fully elucidated, highlighting the need for further research in this area.!##!Results!#!In this study, we analyzed over 350 blood samples from four distinct studies, investigating the cell type contributions to the cfRNA transcriptomic landscape in liver cancer. We found that an increase in hepatocyte proportions in the blood is a consistent feature across most studies and can be effectively utilized for classifying cancer and healthy samples. Moreover, our analysis revealed that in addition to hepatocytes, liver endothelial cell signatures are also prominent in the observed changes. By comparing the classification performance of cellular proportions to established markers, we demonstrated that cellular proportions could distinguish cancer from healthy samples as effectively as existing markers and can even enhance classification when used in combination with these markers.!##!Conclusions!#!Our comprehensive analysis of liver cell-type composition changes in blood revealed robust effects that help classify cancer from healthy samples. This is especially noteworthy, considering the heterogeneous nature of datasets and the etiological distinctions of samples. Furthermore, the observed differences in results across studies underscore the importance of integrative and comparative approaches in the future research to determine the consistency and robustness of findings. This study contributes to the understanding of cfRNA composition in liver cancer and highlights the potential of cellular deconvolution in liquid biopsy.
1000 Sacherschließung
lokal Humans
lokal Liquid Biopsy
lokal Liver Neoplasms/genetics
lokal Transcriptome/genetics [MeSH]
lokal Gene Expression Profiling
lokal Humans [MeSH]
lokal Liquid Biopsy [MeSH]
lokal Transcriptome/genetics
lokal Cell-Free Nucleic Acids [MeSH]
lokal Cell-Free Nucleic Acids
lokal Gene Expression Profiling [MeSH]
lokal Liver Neoplasms/genetics [MeSH]
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/U2FmcmFzdHlhbiwgQXJhbQ==|https://frl.publisso.de/adhoc/uri/enUgU2llZGVyZGlzc2VuLCBDaHJpc3RpYW4gSMO2bmVy|https://frl.publisso.de/adhoc/uri/V29sbG55LCBEYW1pYW4=
1000 Label
1000 Förderer
  1. Projekt DEAL |
  2. Ministry for Economics, Sciences and Digital Society of Thuringia |
  3. German DFG Collaborative Research Centre AquaDiva |
1000 Fördernummer
  1. -
  2. DigLeben-5575/10-9
  3. CRC 1076/3-A06 AquaDiva
1000 Förderprogramm
  1. Open Access funding
  2. -
  3. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Projekt DEAL |
    1000 Förderprogramm Open Access funding
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Ministry for Economics, Sciences and Digital Society of Thuringia |
    1000 Förderprogramm -
    1000 Fördernummer DigLeben-5575/10-9
  3. 1000 joinedFunding-child
    1000 Förderer German DFG Collaborative Research Centre AquaDiva |
    1000 Förderprogramm -
    1000 Fördernummer CRC 1076/3-A06 AquaDiva
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6475558.rdf
1000 Erstellt am 2024-05-08T08:18:50.373+0200
1000 Erstellt von 336
1000 beschreibt frl:6475558
1000 Bearbeitet von 317
1000 Zuletzt bearbeitet 2024-05-14T08:26:28.725+0200
1000 Objekt bearb. Tue May 14 08:26:14 CEST 2024
1000 Vgl. frl:6475558
1000 Oai Id
  1. oai:frl.publisso.de:frl:6475558 |
1000 Sichtbarkeit Metadaten public
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